The study of quantum vortex dynamics in HeII offers great potential for advancing quantum-fluid models. Bose-Einstein condensates, neutron stars, and even superconductors exhibit quantum vortices, whose interactions are crucial for dissipation in these systems. These vortices have quantized velocity circulation around their cores, which, in HeII, are of atomic size. They have been observed indirectly, through methods such as second sound attenuation or electron bubble imprints on photosensitive materials. Over the past twenty years, decorating cryogenic flows with particles has become a powerful approach to studying these vortices. However, recent particle visualization experiments often face challenges with stability, initial conditions, stationarity, and reproducibility. Moreover, most dynamical analyses are performed in 2D, even though many flows are inherently 3D. We constructed a rotating cryostat with optical ports on an elongated square cupola to enable 2D2C, 2D3C, and 3D3C Lagrangian and Eulerian studies of rotating HeII flow. Using this setup, individual quantum vortices have been tracked with micron-sized particles, as demonstrated by Peretti et al., Sci. Adv. 9, eadh2899 (2023). The cryostat and associated equipment -- laser, cameras, sensors, and electronics -- float on a 50 $\mu$m air cushion, allowing for precise control of the experiment's physical parameters. The performance during rotation is discussed, along with details on particle injection.

Two-dimensional (2d) electronic systems on a lattice at fractional filling $\nu = p/q$ exhibit a competition between charge ordered insulators, called Wigner-Mott insulators (WMIs), at large Coulomb repulsion and Fermi-liquid metals at large electronic kinetic energy. When those two energy scales are roughly equal, insulating states that restore the lattice translation symmetry, which we call quantum charge liquids (QCLs), may emerge. When gapped, these QCLs must exhibit topological order. In this work, we show that the allowed topological ordered phases that are proximate to the WMI strongly depend on the charge ordering in the WMI. In particular, we show that when $q$ is even, no direct transition exists between a WMI with the smallest allowed unit cell size from filling constraints, i.e., the "minimal" WMI, and the topological order with the smallest ground state degeneracy on a torus allowed by filling constraints, i.e., the "minimal" TO. Furthermore, we describe the quantum melting transition of the WMIs to the proximate QCLs in terms of the proliferation of the topological defects of the WMIs. The field theory of this transition in terms of the topological defects reveals their role as precursors to the anyon excitations in the QCLs.

We formulate a continuum quantum mechanics for non-relativistic, dipole-conserving fractons. Imposing symmetries and locality results in novel phenomena absent in ordinary quantum mechanical systems. A single fracton has a vanishing Hamiltonian, and thus its spectrum is entirely composed of zero modes. For the two-body problem, the Hamiltonian is perfectly described by Sturm--Liouville (SL) theory. The effective two-body Hamiltonian is an SL operator on $(-1,1)$ whose spectral type is set by the edge behavior of the pair inertia function $K(x)\sim \lvert x -x_\mathrm{edge} \rvert^{\theta}$. We identify a sharp transition at $\theta=2$: for $\theta<2$ the spectrum is discrete and wavepackets reflect from the edges, whereas for $\theta>2$ the spectrum is continuous and wavepackets slow down and, dominantly, squeeze into asymptotically narrow regions at the edges. For three particles, the differential operator corresponding to the Hamiltonian is piecewise defined, requiring several "matching conditions" which cannot be analyzed as easily. We proceed with a lattice regularization that preserves dipole conservation, and implicitly selects a particular continuum Hamiltonian that we analyze numerically. We find a spectral transition in the three-body spectrum, and find evidence for quantum analogs of fracton attractors in both eigenstates and in the time evolution of wavepackets. We provide intuition for these results which suggests that the lack of ergodicity of classical continuum fractons will survive their quantization for large systems.

The AM2Pn2 Zintl compounds are a large class of semiconductor materials that have a wide range of bandgaps and are mostly stable in the same crystal structure. Representative compounds BaCd2P2 and CaZn2P2 have recently been found to exhibit high visible light absorption and long carrier lifetime. Here we use high throughput first-principles calculations to study AM2Pn2 alloys for applications as tandem top cell absorbers (i.e., bandgaps around 1.8 eV) and far infrared detector materials (i.e., bandgaps lower than 0.5 eV). Using a first-principles computational screening workflow for assessing stability and electronic structure of alloys, we identify several promising candidates. These include Ca(Cd0.8Mg0.2)2P2 with a suitable direct bandgap for use in tandem top cells on silicon bottom cells and SrCd2(Sb1-xBix)2 for far infrared detectors. We demonstrate that alloys of AM2Pn2 materials can be realized by experimentally synthesizing Ca(Zn0.8Mg0.2)2P2.

The pairing symmetry and underlying mechanism for superconducting state of AV${}_3$Sb${}_5$ (A=K, Rb, Cs) kagome metal has been a topic of intense investigation. In this work, we consider an 8-band minimal model, which includes V, and the two types of Sb, both within and above/below the kagome plane. This model captures the Fermi surface pocket with significant in-plane Sb contribution near the zone center, and also has the two types of van Hove singularities (VHS), one of which has a strong out of plane Sb weight. By including V-V and V-planar Sb nearest-neighbor Coulomb interactions, we obtain the susceptibilities for fluctuating bond-order and loop-current in both charge and spin channels, and examine the resulting superconducting instabilities. In particular, we find that the time-reversal odd (even) charge-loop-current (charge bond-order) fluctuations favor unconventional (conventional) pairing symmetry such as $s_{+-}$ and $d+id$ ($s_{++}$). Recent experimental works have highlighted the presence of $s$-wave pairing with two distinct gaps, one isotropic and one anisotropic. We discuss how this scenario may be compatible with either $s_{++}$ or $s_{+-}$ pairing, with an isotropic gap on the pocket dominated by in-plane Sb, but a highly anisotropic gap on V-dominated bands.

We show that multichannel quantum systems with uncorrelated but asymmetric Anderson-type disorder can exhibit anomalous diffusion, even in the absence of heavy-tailed disorder. Using a minimal two-channel model with channel asymmetry, we demonstrate a crossover from normal to anomalous transport tuned by interchannel coupling. Applied to quasi-one-dimensional lattices with edge disorder, this leads to long-tailed transmission statistics characterized by ballistic segments interspersed with localized ones, reminiscent of Lévy flights. This channel-asymmetric anomalous diffusion (CAAD) emerges from quantum interference between channels with differing disorder strengths. While CAAD governs transport at intermediate lengths, conventional localization prevails asymptotically, violating the Thouless relation. These results highlight a distinct quantum mechanism for anomalous diffusion beyond classical paradigms.

We present a Kokkos-accelerated implementation of the Moment Tensor Potential (MTP) for LAMMPS, designed to improve both computational performance and portability across CPUs and GPUs. This package introduces an optimized CPU variant--achieving up to 2x speedups over existing implementations--and two new GPU variants: a thread-parallel version for large-scale simulations and a block-parallel version optimized for smaller systems. It supports three core functionalities: standard inference, configuration-mode active learning, and neighborhood-mode active learning. Benchmarks and case studies demonstrate efficient scaling to million-atom systems, substantially extending accessible length and time scales while preserving the MTP's near-quantum accuracy and native support for uncertainty quantification.

Scalable and cost-effective methods for processing transparent electrodes at the microscale are transversal for advancing in electrochemistry, optoelectronics, microfluidics, and energy harvesting. In these fields, the precise fabrication of micrometric circuits plays a critical role in determining device performance and integration with added-value substrates. In this context, Laser Subtractive Manufacturing stands out among microfabrication techniques for its adaptability to diverse materials and complex configurations, as well as its straightforward scalability and affordability nature. However, a challenge in micromachining metals and metal oxides is the inherent formation of LIPSS, which can significantly impair electrical conductivity, particularly when circuit dimensions fall within the micrometer range. Herein, we investigate the micromachining of TCOs using ultrashort pulse laser systems applied to ITO thin films. We analyze the formation of LIPSS at the edges of the micromachined regions associated with the Gaussian distribution of the energy within the laser spot and their impact on the electrical properties depending on the circuit characteristics. Thus, we evaluate the influence of LIPSS orientation and periodicity by fabricating various circuit patterns using femtosecond lasers at green (515 nm) and ultraviolet (343 nm) wavelengths. A correlation between electrical resistivity measurements and structural analysis reveals distinct effects of nanostructure formation depending on the laser source. For green wavelength, the regions where LIPSS are oriented perpendicular to the ITO track exhibit higher resistance, by a factor just above two, compared to those where LIPSS are parallel. Additionally, UV laser processing results in a pronounced reduction of ITO thickness at the boundary between the LIPSS region and the substrate.

The intricate competition between coexisting charge density waves (CDWs) can lead to rich phenomena, offering unique opportunities for phase manipulation through electromagnetic stimuli. Leveraging time-resolved X-ray diffraction, we demonstrate ultrafast control of a CDW in EuTe$_4$ upon optical excitation. At low excitation intensities, the amplitude of one of the coexisting CDW orders increases at the expense of the competing CDW, whereas at high intensities, it exhibits a nonmonotonic temporal evolution characterized by both enhancement and reduction. This transient bidirectional controllability, tunable by adjusting photo-excitation intensity, arises from the interplay between optical quenching and phase-competition-induced enhancement. Our findings, supported by phenomenological time-dependent Ginzburg-Landau theory simulations, not only clarify the relationship between the two CDWs in EuTe$_4$, but also highlight the versatility of optical control over order parameters enabled by phase competition.

Interlayer sliding degrees of freedom often determine the physical properties of two-dimensional (2D) materials. In graphene, for instance, the metastable rhombohedral stacking arrangement hosts correlated and topological electronic phases, which are absent in conventional Bernal stacking. Here, we demonstrate a sliding-induced first-order structural phase transition between Bernal and rhombohedral tetralayer graphene driven by gate voltages. Through transport measurement, we observe bistable switching between a Bernal-dominant state and a rhombohedral-Bernal mixed state across a wide space of the gate-voltage phase diagram. The structural phase transition results in nonvolatile switching between a paramagnet and a ferromagnet accompanied by the anomalous Hall effect. The sign reversal of the anomalous Hall effect under opposite displacement fields suggests that it may originate from domain boundaries between the Bernal and rhombohedral regions. Our discovery paves the way for on-demand toggling of quantum phases based on the sliding phase transition of 2D materials and offers a playground to explore unconventional physics at the stacking domain boundaries.

The position of mobile active and inactive ions, specifically ion insertion sites, within organic crystals, significantly affects the properties of organic materials used for energy storage and ionic transport. Identifying the positions of these atom (and ion) sites in an organic crystal is difficult, especially when the element has a low X-ray scattering power, such as lithium (Li) and hydrogen, which are difficult to detect with powder X-ray diffraction (XRD) methods. First-principles calculations, exemplified by density functional theory (DFT), are very effective for confirming the relative stability of ion positions in materials. However, the lack of effective strategies to identify ion sites in these organic crystalline frameworks renders this task extremely challenging. This work presents two algorithms: (i) Efficient Location of Ion Insertion Sites from Extrema in electrostatic local potential and charge density (ELIISE), and (ii) ElectRostatic InsertioN (ERIN), which leverage charge density and electrostatic potential fields accessed from first-principles calculations, combined with the Simultaneous Ion Insertion and Evaluation (SIIE) workflow -- that inserts all ions simultaneously -- to determine ion positions in organic crystals. We demonstrate that these methods accurately reproduce known ion positions in 16 organic materials and also identify previously overlooked low-energy sites in tetralithium 2,6-naphthalenedicarboxylate (Li$_4$NDC), an organic electrode material, highlighting the importance of inserting all ions simultaneously as done in the SIIE workflow.

We study SU(4)-symmetric Heisenberg model on the cubic lattice with spatially anisotropic magnetic couplings. We utilize several approaches based on the tensor-network representation of the many-body wave functions, which enable accurate analysis of ground-state properties of the model in different regimes of spatial anisotropy including fully isotropic three-dimensional case. Our results point to the persistence of the dimerized color-ordered phase throughout whole range of magnetic couplings excluding only the limit of completely decoupled one-dimensional chains.

Superconductor-semiconductor hybrid materials have been extensively used for experiments on electrically tunable quantum devices. Notably, Josephson junctions utilizing nanowire weak links have enabled a number of new gate-tunable qubits, including gatemons, Andreev level qubits and spin qubits. Conversely, superconducting parametric amplifiers based on Josephson junctions have not yet been implemented using nanowires, even though such nearly quantum limited amplifiers are key elements in experiments on quantum circuits. Here we present Josephson parametric amplifiers based on arrays of parallel InAs nanowires that feature a large critical current as required for linear amplification. The resonance frequency of the devices is gate-tunable by almost 1 GHz, with a gain exceeding 20 dB in multiple frequencies and noise approaching the quantum-limit. This new platform enables on-chip integration of gate-tunable qubits with quantum limited amplifiers using the same hybrid materials and on any substrate.

Thermal diode is a growing technology and important for active thermal flow control. Since the theoretical designing of thermal diode in 2004, various kinds of solid-state thermal diodes have been theoretically and experimentally investigated. Here, we report on the observation of thermal rectification in bulk-size superconductor-normal metal junctions. High-purity (5N) wires of Pb and Al are soldered, and thermal conductivity (\k{appa}) of the junctions is measured in two different directions of the heat flow, forward (\k{appa}F) and reverse (\k{appa}R) directions. Thermal rectification ratio (\k{appa}F / \k{appa}R) of 1.75 is obtained at T ~ 5.2 K with H = 400 Oe. The merit of the Pb-Al junction is a large difference of \k{appa} in an order of several hundred W m-1 K-1 and magneto-tunability of the working temperature.

The theory of circular dichroism in single-wall carbon nanotubes derived within the tight-binding method by a complicated approach in previous work is rederived in a straightforward way using the multipolar expansion of the light-matter interaction.

Biphilic microdome arrays are ubiquitous in nature, but their synthetic counterparts have been scarce. To bridge that gap, we leverage condensed droplet polymerization (CDP) to enable their template-free synthesis. During CDP, monomer droplets serve as microreactors for free-radical polymerization. The droplet diameter is monitored in real time. To enable the precise prediction of the convex geometric parameters, we develop a theoretical framework that integrates geometric arguments, scaling analysis, and kinetic theories. The model accurately predicts the dimensions of the as-synthesized microdome arrays, pointing to unprecedented precision in the synthesis of such topography. To illustrate its impact, the methodology is used to enable biphilic microdomes with targeted dimensions, for the reduction of surface colonization by a biofilm-forming pathogen, Pseudomonas aeruginosa. Importantly, the reduction is achieved with a moderately hydrophobic surface that has been considered prone to fouling, pointing to a fresh material design strategy and broadened palette of synthetic surfaces.

Fe$_3$Ga$_4$ possesses a helical spin spiral with a complex competition between ferromagnetic and antiferromagnetic ground states. This competition generates multiple metamagnetic transitions that are governed by both applied magnetic field and temperature. At intermediate temperatures between T$_1$ (68 K) and T$_2$ (360 K), the ferromagnetically aligned spins transition to an antiferromagnetic spin spiral. In this study, magnetoresistance (MR) measurements are performed on an aligned single crystal and compared to magnetization properties in order to gain insight on the unique alignment of the spins. The high-field MR is positive at low temperatures indicating cyclotronic behavior and negative at high temperature from electron-magnon scattering. Of particular significance is a large anomalous positive MR at low fields, possibly due to emergent spin fluctuations thus prompting further exploration of this multifaceted material.

Oxides exhibiting metallic conduction are crucial for various applications, including fuel cells, battery electrodes, resistive and magnetoresistive materials, electrocatalysts, transparent conductors, and high-temperature superconductors. Oxides that approach metallicity also play significant roles in switching applications, where the metal-insulator transition phenomenon is utilized across a range of technologies. This perspective, motivated by the question of when oxides are metallic, employs electronic structure calculations on metallic oxides to identify the typical feature in the electronic structures that promote metallic behavior. The critical factor of the bandwidth of the electronic energy bands near the Fermi energy is emphasized since it has been somewhat overlooked in the literature. For example, bandwidth considerations would suggest that the recently proposed phosphate "LK-99" would never be a suitable target for superconductivity. From the analysis performed here, we learn that if the width of the conduction band as obtained from density functional theory-based electronic structure calculations is less than 1 eV, then the likelihood of obtaining a metallic compound is vanishingly small. This survey of representative oxide metals highlights the essential elements of extended covalency that lead to wide bands. A key takeaway is that oxyanion compounds such as borates, carbonates, silicates, sulfates, nitrates, and phosphates are unlikely to exhibit metallic conduction at ambient pressure. While the focus here is on oxides, the general findings should apply across various material families, extending to organic crystals, polymers, and framework materials.

The two-dimensional layered ferromagnet Fe3GaTe2, composed of a Te-FeI-FeII/Ga-FeI-Te stacking sequence, hosts two inequivalent Fe sites and exhibits a high Curie temperature and strong out-of-plane magneticanisotropy, making it a promising platform for spintronic applications. Recent experiments have observed a pressure-induced switching of the magnetic easy axis from out-of-plane to in-plane near 10 GPa, though its microscopic origin remains unclear. Here, we employ first-principles calculations to investigate the pressure dependence of the magnetocrystalline anisotropy energy in Fe3GaTe2. Our results reveal a clear easy-axis switching at a critical pressure of approximately 10 GPa, accompanied by a sharp decrease in the magnetic moments arising from FeI and FeII atoms. As pressure increases, spin-up and spin-down bands broaden and shift oppositely due to band dispersion effects, leading to a reduction in net magnetization. Simultaneously, the SOC contribution from FeI, which initially favors an out-of-plane easy axis, diminishes and ultimately changes sign, thereby promoting in-plane anisotropy. The SOC contribution from the outer-layer Te atoms also decreases steadily with pressure, although it retains its original sign; this additional reduction further reinforces the in-plane magnetic easy axis. In contrast, FeII atoms continue to favor an out-of-plane orientation, but their contribution is insufficient to counterbalance the dominant in-plane preference at high pressure. These findings elucidate the origin of magnetic easy-axis switching in Fe3GaTe2 and provide insights for tuning magnetic anisotropy in layered materials for spintronic applications.

Localized $5d^2$ electrons in a cubic crystal field possess multipoles such as electric quadrupoles and magnetic octupoles. We studied the cubic double perovskite Ba$_2$CaOsO$_6$ containing the Os$^{6+}$ ($5d^2$) ions, which exhibits a phase transition to a `hidden order' below $T^* \sim$ 50 K, by X-ray absorption spectroscopy (XAS) and X-ray magnetic circular dichroism (XMCD) at the Os $L_{2,3}$ edge. The cubic ligand-field splitting between the $t_{2g}$ and $e_g$ levels of Os $5d$ was deduced by XAS to be $\sim$4 eV. The temperature dependence of the XMCD spectra was consistent with a $\sim$18 meV residual cubic splitting of the lowest $J_{\rm eff} =$ 2 multiplet state into the non-Kramers $E_g$ doublet ground state and the $T_{2g}$ triplet excited state. Ligand-field (LF) multiplet calculation under fictitious strong magnetic fields indicated that the exchange interaction between nearest-neighbor octupoles should be as strong as $\sim$1.5 meV if a ferro-octupole order is stabilized in the `hidden-ordered' state, consistent with the exchange interaction of $\sim$1 meV previously predicted theoretically using model and density functional theory calculations.

The exploration of transverse electromagnetic responses in solids with broken spatial-inversion (I) and/or time-reversal (T) symmetries has unveiled numerous captivating phenomena, including the (anomalous) Hall effect, Faraday rotations, non-reciprocal directional dichroism, and off-diagonal linear magnetoelectricity, all within the framework of magnetotoroidicity. Here, we introduce a novel class of transverse electromagnetic responses originating from electrotoroidicity in ferro-rotational (FR) systems with preserved I and T symmetries, distinct from magnetotoroidicity. We discover a high-order off-diagonal magnetic susceptibility of FR domains and a reduced linear diagonal magnetic susceptibility at FR domain walls in doped ilmenite FeTiO3. The non-trivial "Hall-like" effect of the former corresponds to an anomalous transverse susceptibility in the presence of spontaneous electrotoroidal moments in FR materials. Our findings unveil an emergent type of transverse electromagnetic responses even in I and T symmetry-conserved conditions and illustrate new functionalities of abundant FR materials.

Oxygen-deficient amorphous tellurium oxides ($a$-TeO$_x$) have recently challenged the intrinsic hole mobility limits of amorphous oxides, with thin-film transistors reaching mobilities up to 15 cm$^{2}$V$^{-1}$s$^{-1}$ upon Se doping. However, the atomistic origins of this behavior, and its seeming contradiction with established semiconductor physics, have remained unresolved. Here, we combine machine-learning-accelerated ab initio molecular dynamics with hybrid-functional defect calculations to establish a new microscopic picture. We show that substantial oxygen loss drives spontaneous segregation into interpenetrating $a$-Te and $a$-TeO$_2$ domains, rather than forming dispersed oxygen vacancies. The diffuse Te-$5p$ states from the $a$-Te network supply percolative pathways for holes, so mobility rises monotonically with oxygen deficiency, enabling mobilities that exceed current records. Doped Se incorporates into the $a$-Te domain, enhancing the connectivity of conductive pathways, thereby increasing hole mobility. Similar behavior in amorphous SeO$_x$ suggests domain percolation as a general route to high-mobility p-type transport in amorphous oxides.

We introduce the concept of \emph{orbital altermagnetism}, a symmetry-protected magnetic order of pure orbital degrees of freedom. It is characterized with ordered anti-parallel orbital magnetic moments in real space but momentum-dependent orbital band splittings, analogous to spin altermagnetism. Using a minimal tight-binding model with complex hoppings in a square-kagome lattice, we show that such order inherently arises from staggered loop currents, producing a $d$-wave-like orbital-momentum locking. First-principles calculations show that orbital altermagnetism emerges independent of spin ordering in in-plane ferromagnets of CuBr$_2$ and VS$_2$, so that it can be unambiguously identified experimentally. On the other hand, it may also coexist with spin altermagnetism, such as in monolayer MoO and CrO. The orbital altermagnetism offers an alternative platform for symmetry-driven magnetotransport and orbital-based spintronics, as exemplified by large nonlinear current-induced orbital magnetization.

Recent advances in materials informatics have expanded the number of synthesizable materials. However, screening promising candidates, such as semiconductors, based on defect properties remains challenging. This is primarily due to the lack of a general framework for predicting defect formation energies in multiple charge states from structural data. In this Letter, we present a protocol, namely data normalization, Fermi level alignment, and treatment of perturbed host states, and validate it by accurately predicting oxygen vacancy formation energies in three charge states using a single model. We also introduce a joint machine-learning model that integrates defect formation energies and band-edge predictions for virtual screening. Using this framework, we identify 89 hole-dopable oxides, including BaGaSbO, a potential ambipolar photovoltaic material. Our protocol is expected to become a standard approach for machine-learning studies on point defect formation energies.

Accurately predicting phonon scattering is crucial for understanding thermal transport properties. However, the computational cost of such calculations, especially for four-phonon scattering, can often be more prohibitive when large number of phonon branches and scattering processes are involved. In this work, we present FourPhonon_GPU, a GPU-accelerated framework for three-phonon and four-phonon scattering rate calculations based on the FourPhonon package. By leveraging OpenACC and adopting a heterogeneous CPU-GPU computing strategy, we efficiently offload massive, parallelizable tasks to the GPU while using the CPU for process enumeration and control-heavy operations. Our approach achieves over 25x acceleration for the scattering rate computation step and over 10x total runtime speedup without sacrificing accuracy. Benchmarking on various GPU architectures confirms the method's scalability and highlights the importance of aligning parallelization strategies with hardware capabilities. This work provides an efficient and accurate computational tool for phonon transport modeling and opens pathways for accelerated materials discovery.

The origin of the charge density wave (CDW) phase in TiSe$_2$ is a highly debated topic, with lattice and excitonic correlations proposed as the main driving mechanisms. One of the proposed scenarios is the excitonic insulator (EI) mechanism, where soft electronic mode drives the phase transition. However, the existence of this purely electronic mode is controversial. Here, we perform fully ab-initio calculations of the electron excitation spectra in TiSe$_2$ with electron-hole excitonic effects included via Bethe-Salpeter equations. In the normal high-temperature phase the excitation spectra is dominated by the exciton mode at 1.6 eV, while no well-defined soft electronic modes that could support the EI phase are present. In the CDW phase, the structural distortions induce a CDW band-gap opening between Ti-$d$ and Se-$p$ states, which supports the formation of the two low-energy excitonic modes in the optical spectrum at 0.4 eV and 80 meV. Close to the transition temperature $T_{\rm CDW}$, these two excitonic modes are softened and approach zero energy. These results suggest that the EI mechanism is not a main driving force in the formation of the CDW phase in TiSe$_2$, but there is a region in the phase diagram near $T_{\rm CDW}$ where EI fluctuations could be relevant.

Harnessing the quantum coherence and tunability of molecular-scale structures, we theoretically explore thermoelectric transport in ring-shaped molecular junctions featuring dimerized hopping integrals. By engineering alternating strong and weak bonds in both staggered and non-staggered configurations, we reveal a marked transmission asymmetry that drives a substantial enhancement in the thermoelectric figure of merit, ZT. To further steer transport behavior, we introduce controlled aperiodicity via site-energy modulations in unit cell format governed by the Aubry-André-Harper (AAH) potential, a quasiperiodic landscape that enables tunable localization-delocalization transitions. This interplay between hopping dimerization and AAH-type disorder gives rise to energy filtering effects and a rich spectrum where extended and critical states coexist, amplifying the Seebeck coefficient while preserving finite electrical conductance. Through a comprehensive non-equilibrium Green's function analysis, we uncover how key device parameters, including disorder strength, dimerization amplitude, and lead-ring connectivity, collectively shape transport characteristics. Notably, asymmetric lead couplings are shown to enhance performance by leveraging quantum interference pathways. Our findings highlight a robust design strategy for optimizing nanoscale thermoelectric functionality, providing actionable insights for experimental realization in molecular electronic platforms.

The superconducting diode effect (SDE) - the asymmetry of critical currents with respect to current direction - is a pivotal advancement in non-reciprocal superconductivity. While SDE has been realized in diverse systems, a fundamental challenge remains achieving field-free operation in iron-based superconductors with simple device geometries. Here, we report a non-volatile, field-free SDE in thin crystalline FeTe$_{0.55}$Se$_{0.45}$(FTS), showing asymmetric critical currents with a rectification coefficient of 1.9% and operating temperatures up to 9 K. Intriguingly, a pronounced non-zero second harmonic resistance emerges at the superconducting transition, exhibiting a sign reversal under varying current and temperature. The SDE persists at zero magnetic field and the rectification coefficient($\eta$) exhibits an even symmetric dependence on the magnetic field, distinguishing it from magnetic chirality anisotropy mechanisms. In addition to this, we systematically ruled out influences from dynamic superconducting domains, thermal gradients, and sample geometry, while establishing that localized stress amplifies the rectification coefficient, likely constituting one of the principal contributing factors. These results establish FTS as a robust platform for realizing field-free superconducting diodes in a structurally simple platform.

Manifolds with nontrivial topology play an essential role in the study of topological phases of matter. In this paper, we study the nontrivial symmetry response of the $2+1$D $Z_2$ symmetry-protected topological (SPT) phase when the system is put on a non-orientable manifold -- the Klein bottle. In particular, we find that when a symmetry defect is inserted along the orientation-reserving cycle of the Klein bottle, the ground state of the system gets an extra charge. This response remains well defined at transition points into the trivial SPT phase, resulting in an exact two-fold degeneracy in the ground state independent of the system size. We demonstrate the symmetry response using exactly solvable lattice models of the SPT phase, as well as numerical work across the transition. We explore the connection of this result to the modular transformation of the $3+1$D $Z_2$ gauge theory and the emergent nature of the parity symmetry in the $Z_2$ SPT phase.

The superconducting diode effect (SDE)-the unidirectional, dissipationless flow of supercurrent-is a critical element for future superconducting electronics. Achieving high efficiency under zero magnetic field is a key requirement. The Josephson junction constitutes a versatile SDE platform for exploiting quantum materials that exhibit ferromagnetism, topology, or unconventional superconductivity. However, a single two-dimensional material system that inherently offers these properties and allows for precise interface engineering, such as twisting, remains elusive. Here we report a record-high, field-free diode efficiency of ~30% in twist van der Waals Josephson heterostructures of the sign-change iron-chalcogenide superconductor FeTe0.55Se0.45 and the conventional transition-metal dichalcogenide superconductor 2H-NbSe2. The diode response shows a striking twist-angle dependence: the efficiency peaks at crystallographic alignment and collapses with a small misorientation of ~7 deg. Importantly, the twist-angle evolution of superconducting interference measurements reveals that efficient nonreciprocity arises from asymmetric edge supercurrents, whereas bulk transport suppresses the effect. These findings establish edge states as the driving mechanism of the unconventional SDE, linking it to exotic pairing and topology in multiband iron-based superconductors. Our findings reveal intricate physics involving novel pairing symmetry, magnetism, and topology in the multiband iron-based superconductor, and offer a new route to high-performance superconducting diodes.

We study a binary Bose gas in a symmetric dual-core, pancake-shaped trap, modelled by two linearly coupled two-dimensional Gross-Pitaevskii equations with Lee-Huang-Yang corrections. Two different cases are considered. First, we consider a spatially uniform condensate, where we identify the domains of parameters for macroscopic quantum tunnelling, self-trapping and localisation revivals. The analytical formulas for the Josephson frequencies in the zero- and $\pi$-phase modes are derived. As the total atom number varies, the system displays a rich bifurcation structure. In the zero-phase, two successive pitchfork bifurcations generate bistability and hysteresis, while the $\pi$-phase exhibits a single pitchfork bifurcation. The second case is when the quantum droplets are in a dual-core trap. Analytical predictions for the oscillation frequencies are derived via a variational approach for the coupled dynamics of quantum droplets, and direct numerical simulations validate the results. We identify critical values of the linear coupling that separate Josephson and self-trapped regimes as the particle number changes. We also found the Andreev-Bashkin superfluid drag effect in numerical simulations of the droplet-droplet interactions in the two-core geometry.

Strong-field terahertz (THz) excitations enable dynamic control over electronic, lattice and symmetry degrees of freedom in quantum materials. Here, we uncover pronounced terahertz-induced symmetry modulations and coherent phonon dynamics in the van der Waals antiferromagnet MnPS3, in which inversion symmetry is broken by its antiferromagnetic spin configuration. Time-resolved second harmonic generation measurements reveal long-lived giant oscillations in the antiferromagnetic phase, with amplitudes comparable to the equilibrium signal, driven by phonons involving percent-level atomic displacements relative to the equilibrium bond lengths. The temporal evolution of the rotational anisotropy patterns indicate a dynamic breaking of mirror symmetry, modulated by two vibrational modes at 1.7 THz and 4.5 THz, with the former corresponding to a hidden mode not observed in equilibrium spectroscopy. We show that these effects arise in part from a field-induced charge rearrangement mechanism that lowers the local crystal symmetry, and couples to the phonon modes. A long-lived field-driven response was uncovered with a complex THz polarization dependence which, in comparison to theory, indicates evidence for an antiferromagnetic-to-ferrimagnetic transition. Our results establish an effective field-tunable pathway for driving excitations otherwise weak in equilibrium, and for manipulating magnetism in low-dimensional materials via dynamical modulation of symmetry.

Classical and multiscale non-equilibrium thermodynamics have different histories and different objectives. In this Note we explain the differences and review some topics in which the multiscale viewpoint of mesoscopic time evolution of macroscopic systems helped to advance the classical non-equilibrium thermodynamics. Eventually, we illustrate the Braun-Le Chatelier principle in dissipative thermodynamics.

The Stoner criterion for ferromagnetism arises from interaction-driven asymmetric filling of spin bands, requiring that the spin susceptibility: (i) peaks dominantly at $\mathbf{Q}=\bm{0}$; and (ii) diverges at a critical interaction strength. Here, we demonstrate that this Stoner mechanism breaks down due to competition with altermagnetic orders, even when both conditions are met. Altermagnetism in solids is characterized by collinear antiparallel spin alignment that preserves translational symmetry, and inherently fulfills these requirements. As a proof of concept, we study a two-orbital Hubbard model with electron filling near Van Hove singularities at high-symmetry momenta. Our results reveal that orbital-resolved spin fluctuations, amplified by strong inter-orbital hopping, stabilize intrinsic altermagnetic order. A quantum phase transition from altermagnetism to ferromagnetism occurs at critical Hund's coupling $J_H$. We further propose directional spin conductivity anisotropy as a detectable signature of this transition via non-local spin transport. This work establishes the pivotal role of altermagnetism in correlated systems.

Controlling nonequilibrium dynamics in quantum materials requires ultrafast probes with spectral selectivity. We report femtosecond reflectivity measurements on the cuprate superconductor Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$ using free-electron laser extreme-ultraviolet (23.5--177~eV) and near-infrared (1.5~eV) pump pulses. EUV pulses access deep electronic states, while NIR light excites valence-band transitions. Despite these distinct channels, both schemes produce nearly identical dynamics: above $T_c$, excitations relax through fast (100--300~fs) and slower (1--5~ps) channels; below $T_c$, a delayed component signals quasiparticle recombination and condensate recovery. We find that when electronic excitations are involved, the ultrafast response is governed mainly by absorbed energy rather than by the microscopic nature of the excitation. In contrast, bosonic driving in the THz or mid-infrared produces qualitatively different dynamics. By demonstrating that EUV excitation of a correlated superconductor yields macroscopic dynamics converging with those from optical pumping, this work defines a new experimental paradigm: FEL pulses at core-level energies provide a powerful means to probe and control nonequilibrium electronic states in quantum materials on their intrinsic femtosecond timescales. This establishes FEL-based EUV pumping as a new capability for ultrafast materials science, opening routes toward soft X-ray and attosecond studies of correlated dynamics.

The melting transitions of a colloidal lattice confined to a two-dimensional ($2D$) periodic substrate of square symmetry are studied using Monte Carlo simulations. When the strengths of interparticle and particle-substrate interactions are comparable, the incommensurate nature of square and triangular ordering leads to the formation of a partially pinned solid with only one of the smallest {\bf G} vectors of the substrate present. This low-temperature phase has true long-range order. By varying the lattice parameter of the substrate while keeping the filling fraction constant, it is seen that the transition from this low-temperature solid to a high-temperature modulated liquid phase can happen via either a single crossover transition or by a two-stage melting process. The transitions are found to be second-order in nature when the lattice parameter is $d \lesssim 9 \lambda$, as confirmed by the finite-size scaling behavior of the specific heat. For the two-stage melting scenario, the intermediate phase is found to be hexatic. The transitions observed in this work are different from the predictions of the KTHNY theory. The study reveals how constraints from substrate periodicity can fundamentally alter melting dynamics, offering insights into the design of tunable colloidal systems and advancing the understanding of phase transitions in two-dimensional particle systems.

Hydrogen-like systems in ultra-high magnetic fields are of significant interest in interdisciplinary research. Previous studies have focused on the exciton wavefunction shrinkage under magnetic fields down to artificial crystal lattices (e.g., quantum wells, superlattices), where the effective mass approximation remains valid. However, further compression toward the natural crystal lattice scale remains experimentally challenging. In this study, we report magneto-absorption measurements on the yellow-exciton series in Cu2O using pulsed magnetic fields of up to 500 T. The strong low energy absorption features are assigned to the spin Zeeman split 2p0 and 3p0 exciton states. The high field data provides a value for the reduced effective mass of the exciton u* = 0.415 \pm 0.01me. Intriguingly, the broadening of the 2p0 ground state transition exhibits a sudden increase for ultrahigh magnetic fields above 300 T, providing possible evidence for Harper broadening - an indication of the breakdown of the effective mass approximation when the magnetic length becomes comparable to the lattice constant of the crystal.

This study investigates the potential impact of intramolecular excitations on the active regions of biomolecular chains, which may play a role in physiological processes within living cells. We assumed that an excitation localized in a specific chain segment can modify its physical properties (e.g., local charge distribution or electric dipole moments), thereby altering its role in biochemical processes. As a consequence, the biochemical functionality of the molecular chain may be altered, or even disrupted. Moreover, quantum resonance effects may cause an excitation induced at one structural element to delocalize and appear at a distant site, potentially affecting the functionality of regions located far from the site where the excitation was initially induced. To investigate this phenomenon, we developed and analyzed a theoretical model in which a single excitation is induced in a particular structural element of a finite molecular chain in thermal equilibrium with its environment. The interaction between the excitation and the thermal oscillations of the chain was taken into account. Differential equations for the correlation functions were derived and solved analytically using integral transformations, providing information on the probability of finding the excitation at each site of the chain. The results show that both the probability of finding the excitation at distant sites and its residence time depend on the chain's physical characteristics, temperature, and initial excitation location.

Active particles affect their environment as much as the environment affects their active motion. Here, we present an experimental system where both can be simultaneously adjusted in situ using an external AC electric field. The environment consists in a two-dimensional bath of colloidal silica particles, whereas the active particles are gold-coated Janus spheres. As the electric field orthogonal to the planar layer increases, the former become stiffer and the latter become faster. The active motion evolves from a viscous like to a viscoelastic like behavior, with the reorientation frequency increasing with the particle speed. This effect culminates in the spontaneous chiralization of particle trajectories. We demonstrate that self-sustained reorientations arise from local compressions and interaction asymmetries, revealing a general particle-level mechanism where changes in the mechanical properties of the environment reshape active trajectories.

We review and obtain some new results on the temperature dependence of spatially nonlocal response functions of graphene and their applications to calculation of both the equilibrium and nonequilibrium Casimir and Casimir-Polder forces. After a brief summary of the properties of the polarization tensor of graphene obtained within Dirac model in the framework of quantum field theory, we derive the expressions for the longitudinal and transverse dielectric functions. The behavior of these functions at different temperatures is investigated in the regions below and above the threshold. Special attention is paid to the double pole at zero frequency which is present in the transverse response function of graphene. An application of the response functions of graphene to calculation of the equilibrium Casimir force between two graphene sheets and Casimir-Polder forces between an atom (nanoparticle) and a graphene sheet is considered with due attention to the role of a nonzero energy gap, chemical potential and a material substrate underlying the graphene sheet. The same subject is discussed for out-of-thermal-equilibrium Casimir and Casimir-Polder forces. The role of the obtained and presented results for fundamental science and nanotechnology is outlined.

Polarization in ferroelectric domains arises from atomic-scale structural variations that govern macroscopic functionalities. The interfaces between these domains known as domain walls host distinct physical responses, making their identification and control critical. Four dimensional scanning transmission electron microscopy (4DSTEM) enables simultaneous acquisition of real and reciprocal-space information at the atomic scale, offering a powerful platform for domain mapping. However, conventional analyses rely on computationally intensive processing and manual interpretation, which are time consuming and prone to misalignment and diffraction artefacts. Here, we present a convolutional neural network that, with minimal training, classifies polarization directions from diffraction data and segments domains in real space. We further introduce an adaptive sampling strategy that prioritizes images from domain wall regions, reducing the number of training images required while improving accuracy and interpretability. We demonstrate this approach for domain mapping in ferroelectric boracite, Cu3B7O13Cl.

We present a novel semiconductor-superconductor hybrid material based on a molecular beam epitaxially grown InAsSb surface quantum well with an in-situ deposited Nb top layer. Relative to conventional Al-InAs based systems, the InAsSb surface quantum well offers a lower effective mass and stronger spin-orbit interaction, while the Nb layer has a higher critical temperature and a larger critical magnetic field. The in-situ deposition of the Nb results in a high-quality interface that enables strong coupling to the InAsSb quantum well. Transport measurements on Josephson junctions reveal an induced superconducting gap of 1.3 meV. Furthermore, a planar asymmetric SQUID is realized, exhibiting gate-tunable superimposed oscillations originating from both the individual Josephson junction and the full SQUID loop. The large induced superconducting gap combined with strong spin-orbit interaction position this material as an attractive platform for experiments exploring gate-tunable superconductivity and topological superconducting devices.

To simultaneously achieve high hardness and high toughness in protective coatings remains a fundamental challenge. Here, we harness the superlattice architecture to combine Koehler hardening while the coherent interfaces reduce the crack driving force and improve toughness, enabling coatings that are both hard and damage tolerant. We design and fabricate epitaxial HfN$_{1.33}$/Hf$_{0.76}$Al$_{0.24}$N$_{1.15}$ superlattices, deposited on MgO(001) substrates using low-energy, high-flux ion-assisted reactive magnetron sputtering. These superlattices with bilayer periods ranging from 6 to 20 nm, exhibit a unique three-fold superstructure, confirmed by X-ray diffraction and reciprocal space mapping (RSM). Each constituent forms distinct 3D checkerboard superstructures, with a period of 7.5 Å for HfN and 12.5 A for HfAlN. RSMs further reveal low mosaicity, high crystalline quality, and in-plane compressive strains, indicating well preserved coherence across interfaces. Mechanical testing shows that the superlattices maintain the high hardness of HfAlN (\~36 GPa) independent of bilayer period, while surpassing the softer HfN (~27 GPa), consistent with interface-driven Koehler strengthening. Micropillar compression shows brittle fracture on the {110}<110> system, yet with distributed cracking and faster mechanical recovery compared to monolithic films, suggesting improved toughness. Cube-corner indentation further corroborate this behavior, with pile-up and suppressed fracture events. These results demonstrate that epitaxial HfN/HfAlN superlattices uniquely combine high hardness with improved toughness, enabled by their three-fold superstructured architecture. Leveraging the intrinsic high-temperature stability of HfN-based materials, this design offers a robust pathway toward next-generation protective coatings capable of maintaining performance under extreme conditions.

We show theoretically that an imposed uniaxial anisotropy leads to new universality classes for the dynamics of active particles suspended in a viscous fluid. In the homogeneous state, their concentration relaxes superdiffusively, stirred by the long-ranged flows generated by its own fluctuations, as confirmed by our numerical simulations. Increasing activity leads to an anisotropic diffusive instability, driven by an active contribution to the particle current proportional to the local curvature of the suspension velocity profile.

We develop a unified viscous hydrodynamics for charge and valley transport in gapped graphene in the quantum Hall regime. We redefine Hall viscosity as a response to static electric-field gradients instead of strain, establishing a derivative hierarchy that fundamentally links it to nonlocal Hall conductivity. The theory predicts quantized Hall viscosity for charge and valley, including a ground-state contribution. Crucially, the valley current is unaffected by the Lorentz force and is directly accessible via the local pressure, namely the electrostatic potential that tracks fluid vorticity.

We report an experimental study of a Si/SiGe double quantum dot (DQD) directly coupled to a niobium superconducting coplanar stripline (CPS) microwave resonator. This hybrid architecture enables high-bandwidth dispersive readout suitable for real-time feedback and error-correction protocols. Fast and sensitive readout is achieved primarily by optimizing the DQD gate lever arm, guided by MaSQE quantum dot simulations, which enhances the dispersive signal without requiring high-impedance resonators. We demonstrate a signal-to-noise ratio (SNR) of unity with an integration time of 34.54 nanoseconds, corresponding to a system bandwidth of 14.48 MHz and a charge sensitivity of 0.000186 e per square root hertz. Analysis of the voltage power spectral density (PSD) of the in-phase (I) and quadrature (Q) baseband signals characterizes the system's readout noise, with the PSD's dependence on integration time providing insight into distinct physical regimes.

Two-dimensional (2D) materials have shown broad application prospects in fields such as energy, environment, and aerospace owing to their unique electrical, mechanical, thermal and other properties. With the development of artificial intelligence (AI), the discovery and design of novel 2D materials have been significantly accelerated. However, due to the lack of basic theories of material synthesis, identifying reliable synthesis processes for theoretically designed materials is a challenge. The emergence of large language model offers new approaches for the reliability prediction of material synthesis processes. However, its development is limited by the lack of publicly available datasets of material synthesis processes. To address this, we present the Material Synthesis 2025 (MatSyn25), a large-scale open dataset of 2D material synthesis processes. MatSyn25 contains 163,240 pieces of synthesis process information extracted from 85,160 high-quality research articles, each including basic material information and detailed synthesis process steps. Based on MatSyn25, we developed MatSyn AI which specializes in material synthesis, and provided an interactive web platform that enables multifaceted exploration of the dataset (this https URL). MatSyn25 is publicly available, allowing the research community to build upon our work and further advance AI-assisted materials science.

When combined into van der Waals heterostructures, transition metal dichalcogenide monolayers enable the exploration of novel physics beyond their unique individual properties. However, for interesting phenomena such as interlayer charge transfer and interlayer excitons to occur, precise control of the interface and ensuring high-quality interlayer contact is crucial. Here, we investigate bilayer heterostructures fabricated by combining chemical-vapor-deposition-grown MoS$_2$ and exfoliated WS$_2$ monolayers, allowing us to form several heterostructures with various twist angles within one preparation step. In case of sufficiently good interfacial contact, evaluated by photoluminescence quenching, we observe a twist-angle-dependent enhancement of the WS$_2$ A$_{1g}$ Raman mode. In contrast, other WS$_2$ and MoS$_2$ Raman modes (in particular, the MoS$_2$ A$_{1g}$ mode) do not show a clear enhancement under the same experimental conditions. We present a systematic study of this mode-selective effect using nonresonant Raman measurements that are complemented with ab-initio calculations of Raman spectra. We find that the selective enhancement of the WS$_2$ A$_{1g}$ mode exhibits a strong dependence on interlayer distance. We show that this selectivity is related to the A$_{1g}$ eigenvectors in the heterolayer: the eigenvectors are predominantly localized on one of the two layers; yet, the intensity of the MoS$_2$ mode is attenuated because the WS$_2$ layer is vibrating (albeit with much lower amplitude) out of phase, while the WS$_2$ mode is amplified because the atoms on the MoS$_2$ layer are vibrating in phase. To separate this eigenmode effect from resonant Raman enhancement, our study is extended with near-resonant Raman measurements.

In density functional theory (DFT), the ground state charge density is the fundamental variable which determines all other ground state properties. Many machine learning charge density models are developed by prior efforts, which have been proven useful to accelerate DFT calculations. Yet they all use the total charge density (TCD) as the training target. In this work, we advocate predicting difference charge density (DCD) instead. We term this simple technique by $\Delta$-SAED, which leverages the prior physical information of superposition of atomic electron densities (SAED). The robustness of $\Delta$-SAED is demonstrated through evaluations over diverse benchmark datasets, showing an extra accuracy gain for more than 90% structures in the test sets. Using a Si allotropy dataset, $\Delta$-SAED is demonstrated to advance model's transferability to chemical accuracy for non-self-consistent calculations. By incorporating physical priors to compensate for the limited expressive power of machine learning models, $\Delta$-SAED offers a cost-free yet robust approach to improving charge density prediction and enhancing non-self-consistent performance.

Controlling the size of droplets, for example in biological cells, is challenging because large droplets typically outcompete smaller droplets due to surface tension. This coarsening is generally accelerated by hydrodynamic effects, but active chemical reactions can suppress it. We show that the interplay of these processes leads to three different dynamical regimes: (i) Advection dominates the coalescence of small droplets, (ii) diffusion leads to Ostwald ripening for intermediate sizes, and (iii) reactions finally suppress coarsening. Interestingly, a range of final droplet sizes is stable, of which one is selected depending on initial conditions. Our analysis demonstrates that hydrodynamic effects control initial droplet sizes, but they do not affect the later dynamics, in contrast to passive emulsions.

Rare-earth-doped nitride phosphors are promising materials for solid-state lighting and photonic applications due to their thermal stability, sharp emission lines, and strong UV-blue absorption. In this work, we present a first-principles density functional theory (DFT) study, using the GGA+U approach, of pristine and Eu3+-doped CaAlSiN3 at doping levels of 8.5% and 17%. Electronic structure calculations show that Eu incorporation introduces localized 4f states within the band gap, leading to band-gap narrowing and enabling red photoluminescence through the 5D0 -> 7F2 transition. Spin-polarized density of states and spin density mapping confirm the magnetic nature of Eu3+, while charge density, Bader analysis, and electron localization function (ELF) indicate mixed ionic-covalent bonding and charge transfer from Eu to neighboring N and Al atoms, stabilizing the doped lattice. Optical spectra, including dielectric function, absorption, refractive index, and reflectivity, reveal red-shifted absorption edges and enhanced visible-range light-matter interactions, consistent with experimental red to near-infrared emission. Formation energy analysis confirms the thermodynamic feasibility of Eu substitution, while elastic constants and Pugh's ratio indicate mechanical robustness and ductility. Thermoelectric transport properties, obtained using WIEN2k and BoltzTraP, suggest that moderate Eu3+ doping improves the power factor and reduces lattice thermal conductivity through disorder scattering. These results establish Eu-doped CaAlSiN3 as a stable and efficient red-emitting phosphor for white light-emitting diodes (WLEDs) and provide theoretical insights for crystal site engineering in advanced optoelectronic materials.

Accurate determination of electronic states with low density in the bandgap (in-gap states) is crucial for understanding and optimizing the performance of organic optoelectronic devices. In the device research field, photoelectron yield spectroscopy (PYS) has been widely used to evaluate such states, and its derivative is commonly employed to estimate the density of states (DOS). However, low-energy photons in PYS can generate excitons and anions in organic semiconductors, raising questions about whether derivative PYS spectra truly represent the DOS. Here, we applied hv-dependent high-sensitivity ultraviolet photoelectron spectroscopy with low-energy photons to probe the origin of photoelectrons in organic semiconductors. We show that PYS signals arise from the single-quantum external photoelectron effect (SQEPE) of in-gap states, from SQEPE of the singly occupied molecular orbital (SOMO) in anions, and biphotonic electron emission (BEE) effect via exciton fusions. Because the BEE signal masks the DOS, derivative PYS can misestimate the DOS of in-gap states. In contrast, constant final state yield spectroscopy (CFS-YS) can reliably determine the DOS. For example, in Tris(8-hydroxyquinoline) aluminum (Alq3), we observed BEE, and CFS-YS revealed the DOS of in-gap states and SOMO over six orders of magnitude. The direct determination of the SOMO DOS allowed us to clarify the role of Alq3 in the electron injection layer in organic light-emitting diodes. Moreover, the BEE process can act as both a carrier-generation and degradation pathway in organic optoelectronic devices. These findings demonstrate that CFS-YS provides a reliable method to determine the DOS of in-gap states and to probe exciton and/or anion interactions. We establish practical guidelines for determining the DOS of in-gap states for low-energy photon measurements, such as examining photon-flux dependence.

Rhombohedral or ABC stacked multilayer graphene hosts a correlated magnetic ground state at charge neutrality, making it one of the simplest systems to investigate strong electronic correlations. We investigate this ground state in multilayer graphene structures using the Hubbard model in a distance dependent Slater-Koster tight binding framework. We show that by using a universal Hubbard-$U$ term, we can accurately capture the spin polarization predicted by hybrid density functional theory calculations for both hexagonal (ABA) and rhombohedral (ABC) stackings. Using this $U$ value, we calculate the magnetic moments of 3-8 layers of ABC and ABA graphene multilayers. We demonstrate that the structure and magnitude of these magnetic moments are robust when heterostructures are built from varying numbers of ABC and ABA multilayers. By applying different types of mechanical distortions, we study the behaviour of the magnetism in graphene systems under uniaxial strain and pressure. Our results establish a computationally efficient framework to investigate correlation-driven magnetism across arbitrary stacking configurations of graphite polytypes.

Temperature dependent magnetic properties of superconductor-ferromagnet-superconductor (SC/FM/SC) trilayers are studied both experimentally and theoretically, with a focus on ferromagnetic resonance (FMR). The influence of the SC and FM layer thicknesses on the FMR field is examined. To differentiate the mechanisms involved, we additionally investigate structures containing nonmagnetic metallic (M) or insulating (I) spacers (SC/FM/M/SC or SC/FM/I/SC). All the studied multilayers show large reductions in the FMR field below the critical temperature of the SC, except the system containing an insulating spacer (SC/FM/I/SC). This SC-induced FMR-shift (resonance field/frequency) is larger for thicker SC as well as FM layers, reaching a saturation value for very large thicknesses. To explain the measured results, an analytical model is developed, in which the FM-magnetization precession modulates the magnetic flux in the system, thereby inducing an alternating supercurrent in the SC, which in turn produces a dynamic back-action magnetic field on the FM that shifts its resonance frequency. The model considers closed current loops, where the FM layer conductively links the supercurrents flowing in the opposite directions in the two outer SC layers. Our results provide a practical route for increasing the operating frequency of magnonic devices.

Open quantum systems governed by non-Hermitian effective Hamiltonians exhibit unique phenomena, such as the non-Hermitian skin effect, where eigenstates localize at system boundaries. We investigate this effect in a Rashba nanowire coupled to a ferromagnetic lead and demonstrate that it can be detected via non-local transport spectroscopy: while local conductance remains symmetric, the non-local conductance becomes non-reciprocal. We account for this behavior using both conventional transport arguments and the framework of non-Hermitian physics. Furthermore, we explain that exceptional points shift in parameter space when transitioning from periodic to open boundary conditions, a phenomenon observed in other non-Hermitian systems but so far not explained. Our results establish transport spectroscopy as a tool to probe non-Hermitian effects in open electronic systems.

This work investigates the magneto-transport properties of exfoliated NiTe2 nano-flakes with varying thicknesses and disorder levels, unveiling two distinct physical mechanisms governing the observed anisotropic linear magnetoresistance (MR). For the perpendicular magnetic field configuration, the well-defined linear MR in high fields is unambiguously attributed to a classical origin. This conclusion is supported by the proportionality between the MR slope and the carrier mobility, and between the crossover field and the inverse of mobility. In stark contrast, the linear MR under parallel magnetic fields exhibits a non-classical character. It shows a pronounced enhancement with decreasing flake thickness, which correlates with an increasing hole-to-electron concentration ratio. This distinctive thickness dependence suggests an origin in the nonlinear band effects near the Dirac point, likely driven by the shift of the Fermi level. Furthermore, the strengthening of MR anisotropic with enhanced inter-layer transport contradicts the prediction of the guiding-center diffusion model for three-dimensional systems. Our findings highlight the critical roles of band topology and structural dimensional in the anomalous magneto-transport of Dirac semi-metals.

We present a first-principles density functional theory study of the structural, electronic, optical, and thermoelectric properties of Sc2BeX4 (X = S, Se) chalcogenides for energy applications. Both compounds are dynamically and thermodynamically stable, exhibiting negative formation energies of -2.6 eV (Sc2BeS4) and -2.2 eV (Sc2BeSe4). They feature direct band gaps of 1.8 eV and 1.2 eV, respectively, within the TB-mBJ approximation, indicating strong visible-light absorption. Optical analysis reveals high static dielectric constants (9.0 for S and 16.5 for Se), absorption peaks near 13.5 eV, and reflectivity below 30 percent. Thermoelectric calculations predict p-type conduction with Seebeck coefficients reaching 2.5e-4 V/K and electrical conductivities of 2.45e18 and 1.91e18 (Ohm m s)^-1 at 300 K. Power factors approach 1.25e11 W/K^2 m s, with a maximum dimensionless figure of merit (ZT) of 0.80 at 800 K. Calculated Debye temperatures (420 K for Sc2BeS4 and 360 K for Sc2BeSe4) imply low lattice thermal conductivity. These findings establish Sc2BeX4 chalcogenides as promising materials for photovoltaic and thermoelectric applications.

We consider a multi-walker generalization of the true self-avoiding walk, the bricklayer model. We perform stochastic simulations and solve the continuum partial differential equations that describe the collective evolution of $N$ bricklayers/walkers. These equations were previously derived from hydrodynamic considerations. In the large-$N$ limit, the results from simulation agree with the solutions of the partial differential equations.

Altermagnets exhibit momentum-dependent spin splitting without net magnetization, combining characteristics of both ferromagnets and antiferromagnets, making them highly interesting for spintronics applications. CrSb is a prime candidate with a high Néel temperature ($\sim700$~K) and a large exchange-driven splitting of $\sim0.6$--1~eV. Using ab-initio calculations, we consider slabs of various orientations in the ultrathin limit. We find that (100) oriented slabs have spin-degenerate bands. In (0001) oriented slabs, the exchange-driven altermagnetic spin splitting collapses, but including spin-orbit coupling restores a residual anisotropic splitting of $\sim70$~meV. In contrast, the (110) oriented slabs show an altermagnetic spin splitting of $\sim400$~meV, and emerges as a robust candidate for realizing large, exchange-driven altermagnetism

Single ion implantation using focused ion beam systems enables high spatial resolution and maskless doping for rapid and scalable engineering of materials for quantum technologies, particularly qubits and colour centres in solid-state hosts. In such applications, the confidence with which a single ion can be deterministically implanted is crucial, and so the efficiency of the detection mechanism is a vital parameter. Here, we present a study of the single-ion detection efficiency for a variety of ion species (Si, P, Mn, Co, Ge, Sb, Au and Bi) into various hosts (Si, SiO2, Al2O3, GaAs, diamond and SiC). The effect of varying ion mass, charge and kinetic energy are studied, in addition to the cluster implantation of Sb, Au and Bi. We demonstrate that it is possible to achieve detection efficiencies >90% for a wide range of ion species and substrate combination through selection of the implantation parameters. Furthermore, detection efficiencies of 100% are found for the doping of Sb clusters which is of direct relevance for the future fabrication of quantum devices.

We present a unified description of attractive and repulsive polarons, formed in a one-dimensional Bose gas hosting an impurity particle, by obtaining all ground and excited state solutions to the Gross-Pitaevskii equation. Modeling the impurity with an attractive square-well potential, we characterize the excited-state energy branches as a function of interaction strength. As the impurity-bath coupling increases, the excited states change from distinct soliton configurations to hybridized soliton-polaron states, eventually crossing over from repulsive to attractive polarons at unitarity. We identify a universal regime near this crossover where the polaron properties are accurately characterized by the zero-energy scattering length.

Unveiling the interplay between spin density wave (SDW) and charge density wave (CDW) orders in correlated electron materials is important to obtain a comprehensive understanding of their electronic, structural, and magnetic properties. Kagome lattice materials are interesting because their flat electronic bands, Dirac points, and van Hove singularities can enable a variety of exotic electronic and magnetic phenomena. The kagome metal FeGe, which exhibits a CDW order deep within an A-type antiferromagnetic (AFM) phase, was found to respond dramatically to post-growth annealing - with the ability to tune the CDW repeatedly from long-range order to no (or extremely weak) order. Additionally, neutron scattering studies suggest that incommensurate magnetic peaks that onsets at $T_{Canting}$ = $T_{SDW} \approx$ 60 K in the system arise from a SDW order instead of the AFM double cone structure. Here we use inelastic neutron scattering to show two distinct spin excitations exist below $T_{Canting}$ corresponding to two coexisting magnetic orders in the system in both sets of annealed samples with and without CDW. While CDW order or no order can dramatically affect the onset temperature of $T_{Canting}$ and elastic incommensurate magnetic scattering, its impact on low-energy spin fluctuations is more limited. In both samples, a pair of gapless incommensurate spin excitations arising from the SDW order wavevector coexist with gapped commensurate spin waves from the A-type AFM order across $T_{Canting}$. Low-energy spin excitations for both samples couple dynamically to the lattice through enhanced magnetic scattering intensity on cooling below $T_{CDW}$, regardless the status of the static long-range CDW order. The incommensurate SDW order in the long-range CDW ordered sample also induces a tiny in-plane lattice distortion of the kagome lattice that is absent in the no CDW ordered sample.

We present a comprehensive first-principles investigation of the structural, electronic, optical, and thermodynamic properties of BeX compounds (X = S, Se, Te) under hydrostatic pressures ranging from 0 to 10 GPa. Calculations were performed using density functional theory (DFT) within the Generalized Gradient Approximation (GGA) using the Perdew-Burke-Ernzerhof (PBE) functional, as implemented in the CASTEP code. Phonon dispersion analyses confirm the dynamical stability of all compounds across the studied pressure range, as indicated by the absence of imaginary frequencies throughout the Brillouin zone. The electronic band structure reveals pressure-induced band modifications, with BeS retaining the widest bandgap. Optical properties, including the dielectric function, absorption coefficient, reflectivity, and energy loss spectra, were computed for photon energies up to 30 eV. The materials exhibit strong optical absorption in the ultraviolet region, suggesting potential for UV optoelectronic applications. Thermodynamic parameters such as Debye temperature, heat capacity, and entropy were evaluated, showing pressure-dependent trends. Notably, increasing pressure leads to reduced atomic vibrations and heat capacity, while the Gibbs free energy exhibits a consistent slope with temperature, reflecting entropy variation. These results highlight the suitability of BeX compounds for pressure-sensitive optoelectronic and thermoelectric devices, as well as thermal barrier applications.

Increasing the spin coherence time (T2) is a major area of interest for spin defect systems such as the silicon (V$_Si$) and carbon (V$^\pm _C$) vacancies in 4H-SiC. Usually as temperature increases, T2 decreases due to the thermal bath. Observations of electron-paramagnetic resonance and direct systematic measurements of T2 has seen an anomaly where T2 increases with increasing temperature. In this work, we investigate the mechanisms that cause the T2 temperature anomaly. We find that due to a spontaneous symmetry lowering from a motional Jahn-Teller distortion, a polaron quasi-particle is generated from the vibronic coupling. Initially, for temperatures from 8 to 20 - 40K, the coherence temperature dependence is dominated by phonon-assisted spin relaxation. At temperatures around 20 - 40K, depending on the vacancy, a thermally activated polaron hopping turns on and motional narrowing dominates and increases T2 with increasing temperature. As temperatures reach 120 - 160K, the energy barrier gets high enough to slow the polaron hopping. At this point the Larmor precession dominates, leading to decoherence. Our calculated temperature-dependent coherence agrees with what has been seen experimentally, giving a full theoretical framework for the mechanisms that cause the T2 temperature anomaly of increasing T2 with increasing temperature. The theoretical framework presented here also gives insight into these mechanisms being a probable universal phenomenon that could occur in many other defect center spin systems.

The tetraboride HoB4 crystallizes in a tetragonal structure (space group P4/mbm), with the Ho atoms realizing a Shastry-Sutherland lattice. It orders antiferromagnetically at TN1 = 7.1 K and undergoes further magnetic transition at TN2 = 5.7 K. The complex magnetic structures are attributed to competing order parameters of magnetic and quadrupolar origin with significant magnetoelastic coupling. Here, we investigate the response of the lattice of HoB4 across the antiferromagnetic phase transitions by using low-temperature powder x-ray diffraction and ultrasound-velocity measurements, supported by crystal electric field (CEF) calculations. Below TN2, the crystal structure of HoB4 changes to monoclinic (space group P21/b) as a macroscopic manifestation of the quadrupolar ordering. Between 300 and 3.5 K, the total distortion amplitude is 0.46~Å and the relative volume change is $3.5 \times 10^{-3}$. This structural phase transition is compatible with the huge softening of the modulus $C_{44}$ observed around TN2 due to ferroquadrupolar order. A lattice instability developing immediately below TN1 is seen consistently in x-ray and ultrasound data. CEF analysis suggests a quasi-degenerated ground state for the Ho$^{3+}$ ions in this system.

Identifying optimal strategies for efficient spatial exploration is crucial, both for animals seeking food and for robotic search processes, where maximizing the covered area is a fundamental requirement. Here, we propose position resetting as an optimal protocol to enhance spatial exploration in active matter systems. Specifically, we show that the area covered by an active Brownian particle exhibits a non-monotonic dependence on the resetting rate, demonstrating that resetting can optimize spatial exploration. Our results are based on experiments with active granular particles undergoing Poissonian resetting and are supported by active Brownian dynamics simulations. The covered area is analytically predicted at both large and small resetting rates, resulting in a scaling relation between the optimal resetting rate and the self-propulsion speed.

In this study, using the Dirac continuum model combined with the split-operator technique, we investigate the propagation dynamics of wave packets in graphene in the presence of circular potential barriers arranged in square and triangular geometries. Our results reveal a non-monotonic dependence of the wave packet transmission on the number of barrier rows along the propagation direction: the transmission initially decreases as rows of barriers are removed, but then increases again when additional rows are eliminated. To explain the observed nonlinear behavior, the time evolution of the transmission probability is analyzed, providing insight into the interplay between wave packet dynamics and the spatial arrangement of potential barriers. These findings offer a pathway for designing graphene-based devices with tunable transport properties through engineered potential landscapes.

We explore the critical dynamics of driven interfaces propagating through a two dimensional disordered medium with long range spatial correlations, modeled using fractional Brownian motion. Departing from conventional models with uncorrelated disorder, we introduce quenched noise fields characterized by a tunable Hurst exponent H, allowing systematic control over the spatial structure of the background medium. The interface evolution is governed by a quenched Kardar Parisi Zhang equation modified to account for correlated disorder, namely QKPZ. Through analytical scaling analysis, we uncover how the presence of long-range correlations reshapes the depinning transition, alters the critical force Fc, and gives rise to a family of critical exponents that depend continuously on H. Our findings reveal a rich interplay between disorder correlations and the non-linearity term in QKPZ, leading to a breakdown of conventional universality and the emergence of nontrivial scaling behaviors. The exponents are found to change by H in the anticorrelation regime, while they are nearly constant in the correlation regime, suggesting a super-universal behavior for the latter. By a comparison with the quenched Edwards Wilkinson model, we study the effect of the non linearity term in the QKPZ model. This work provides new insights into the physics of driven systems in complex environments and paves the way for understanding transport in correlated disordered media.

Magnetically doped topological insulators (TIs) exhibit two distinct phases: the quantum anomalous Hall (QAH) phase when the Fermi level resides within the surface gap, and a metallic phase outside the gap. The QAH phase hosts unidirectional transport channels known as chiral edge states, while the metallic phase exhibits non-reciprocal transport due to unbalanced bidirectional edge states. Utilizing the chiral edge states in Cr-doped (Bi, Sb)2Te3 sandwich structures, we realize non-Hermitian conductance matrices in a one-dimensional Corbino chain with well-defined chirality. By tuning the boundary conditions from open to periodic, we reveal the non-Hermitian skin effect, where eigenstates localize exponentially at one end of the chain. In the metallic phase, we further observe asymmetric, bidirectional coupling between the neighboring sites in the conductance matrix, a direct consequence of the system's intrinsic non-reciprocity. These results establish magnetic TIs as a powerful platform for investigating emergent non-Hermitian phenomena in topological systems.

The Coulomb explosion is a process that occurs following the formation of multiple charges during Auger cascades, leading to the destruction of solid-state and molecular structures. For unstable multi-charged ions produced at Auger cascades, the destruction cross-section is directly related to the probability of Coulomb explosion, which depends on characteristic times of ion dissociation and electron neutralization. This study demonstrates that the atomic dissociation time decreases with charge. An expression for the neutralization time was obtained within the model, in which the probability of Coulomb explosion is considered as a competition of two processes, ion dissociation and electron neutralization. By using approximation of the effective mass, it was shown that the neutralization time is a function of the effective mass and the width of the valence band of solid states.

We present the experimental detection of coherent three-body interactions, often masked by stronger two-body effects, through nonequilibrium spin dynamics induced by controllably quenching lattice-confined spinor gases. Three-body interactions are characterized through both real-time and frequency domain analyses of the observed dynamics. Our results, well-described by an extended Bose-Hubbard model, further demonstrate the importance of three-body interactions for correctly determining atom distributions in lattice systems, which has applications in quantum sensing via spin singlets. The techniques demonstrated in this work can be directly applied to other atomic species, offering a promising avenue for future studies of higher-body interactions with broad relevance to strongly-interacting quantum systems.

Colloidal nanocrystal quantum dots (QD) enable the bottom-up assembly of designer solids. Among the multitudinous applications of QD solids, there has been great success in exploiting the tunable optical properties for LED displays, lighting, bioimaging and diagnostics. Applications dependent on electrical properties such as solar cells, photodetectors, and transistors have fallen short of their full potential because of poor control over electrical properties, and some of applications with the most promise for novelty, such as a solid-state quantum simulator for quantum computation and spintronics, are stagnant. Lack of clarity on the charge transport mechanism has been a significant barrier to progress, particularly as numerous sources of disorder are present. In this work, we make advancements in a nano-patterning technique to fabricate a 70-nm wide QD solid that is also free of several sources of structural defects. Owing to the small size and structural integrity, we isolate the charge dynamics of a single conductance channel within a percolation network. We tune parameters to measure ~10 channels, and with a time-resolved measurement, we find conductance noise that exceeds 100% of the average current. From observation of the long-time dynamics of the charge transport, including random telegraph noise, colored noise and attractor states, we model the transport with stochastic quasi-one-dimensional percolation paths. With this insight into the charge transport of QD solids unimpeded by structural defects, we provide a path for the rational design of a QD solid with electrical properties that reflect the underlying tunable, periodic potential.

Exascale computing is transforming the field of materials science by enabling simulations of unprecedented scale and complexity. We present exa-AMD, an open-source, high-performance simulation code specifically designed for accelerated materials discovery on modern supercomputers. exa-AMD addresses the computational challenges inherent in large-scale materials discovery by employing task-based parallelization strategies and optimized data management tailored for high performance computers. The code features a modular design, supports both distributed and on-node parallelism, and is designed for flexibility and extensibility to accommodate a wide range of materials science applications. We detail the underlying algorithms and implementation, and provide comprehensive benchmark results demonstrating strong scaling across multiple high performance computing platforms. We provide two example applications, the design of Fe-Co-Zr and Na-B-C compounds, to illustrate the code's effectiveness in accelerating the discovery and characterization of novel materials. With only a set of elements as input, exa-AMD automates the workflow on CPU or GPU-enabled clusters, outputs the structures and energies of promising candidates, and updates the phase diagram. exa-AMD is publicly available on GitHub, with detailed documentation and reproducible test cases to support community engagement and collaborative research. This work aims to advance materials science by providing a robust, efficient, and extensible tool ready for exascale this http URL for exascale platforms.

We introduce BigBang-Proton, a unified sequence-based architecture for auto-regressive language modeling pretrained on cross-scale, cross-structure, cross-discipline real-world scientific tasks to construct a scientific multi-task learner. BigBang-Proton incorporates three fundamental innovations compared to mainstream general-purpose LLMs: Theory-Experiment Learning paradigm aligns large-scale numerical experimental data with theoretical text corpora; Binary Patch Encoding replaces byte pair encoding(BPE) tokenization; Monte Carlo Attention substitutes traditional transformer architectures. Through next-word-prediction pretraining on cross-discipline scientific datasets of real-world problems mixed with general textual corpus, followed by fine-tuning and inference on downstream tasks, BigBang-Proton demonstrates 100\% accuracy in up to 50-digit arithmetic addition operations, performance on par with leading specialized models in particle physics jet tagging, matching MAE of specialized models in inter-atomic potential simulation, performance comparable to traditional spatiotemporal models in water quality prediction, and benchmark-exceeding performance in genome modeling. These results prove that language-guided scientific computing can match or exceed the performance of task-specific scientific models while maintaining multitask learning capabilities. We further hypothesize to scale the pretraining to the universe scale as a fundamental step toward developing material world foundational model.

Machine-Learned Interatomic Potentials (MLIPs) require vast amounts of atomic structure data to learn forces and energies, and their performance continues to improve with training set size. Meanwhile, the even greater quantities of accompanying data in the Hamiltonian matrix H behind these datasets has so far gone unused for this purpose. Here, we provide a recipe for integrating the orbital interaction data within H towards training pipelines for atomic-level properties. We first introduce HELM ("Hamiltonian-trained Electronic-structure Learning for Molecules"), a state-of-the-art Hamiltonian prediction model which bridges the gap between Hamiltonian prediction and universal MLIPs by scaling to H of structures with 100+ atoms, high elemental diversity, and large basis sets including diffuse functions. To accompany HELM, we release a curated Hamiltonian matrix dataset, 'OMol_CSH_58k', with unprecedented elemental diversity (58 elements), molecular size (up to 150 atoms), and basis set (def2-TZVPD). Finally, we introduce 'Hamiltonian pretraining' as a method to extract meaningful descriptors of atomic environments even from a limited number atomic structures, and repurpose this shared embedding space to improve performance on energy-prediction in low-data regimes. Our results highlight the use of electronic interactions as a rich and transferable data source for representing chemical space.

Microscopy techniques generate vast amounts of complex image data that in principle can be used to discover simpler, interpretable, and parsimonious forms to reveal the underlying physical structures, such as elementary building blocks in molecular systems or order parameters and phases in crystalline materials. Variational Autoencoders (VAEs) provide a powerful means of constructing such low-dimensional representations, but their performance heavily depends on multiple non-myopic design choices, which are often optimized through trial-and-error and empirical analysis. To enable automated and unbiased optimization of VAE workflows, we investigated reward-based strategies for evaluating latent space representations. Using Piezoresponse Force Microscopy data as a model system, we examined multiple policies and reward functions that can serve as a foundation for automated optimization. Our analysis shows that approximating the latent space with Gaussian Mixture Models (GMM) and Bayesian Gaussian Mixture Models (BGMM) provides a strong basis for constructing reward functions capable of estimating model efficiency and guiding the search for optimal parsimonious representations.

Prof. Michael Bonitz and his collaborators have made seminal contributions to the study of the uniform electron fluid and the electron-proton fluid, viz., hydrogen, in using {\it ab initio} simulations. These studies provide essential inputs to astrophysics as well as high-energy density physics. This is reflected in the contributions to this festshrift in his honour. The electron-proton system becomes particularly difficult for theoretical modeling when the temperature becomes comparable to the Fermi energy $E_F$, when the warm-dense matter (WDM) state of hydrogen is reached. In this study we briefly review the theoretical methods available for the study of WDM systems, and use the neutral-pseudo atom (NPA) method, and a classical map for quantum electrons to study fully and partially ionized hydrogen. It is shown that {\it both} fully and partially ionized states can independently exist at the {\it same density and temperature} in many cases. Recent studies using path-integral Monte Carlo methods, and $N$-atom Density Functional Theory (DFT) simulations have provided essential structure data including the electron-electron structure factor $S_{ee}(k)$ that enters into interpretation of X-ray Thomson scattering and other diagnostics. We show that these structure data can be rapidly and inexpensively evaluated, with sufficient accuracy, using classical-map schemes for fully ionized plasmas, and more generally, using one-atom (average-atom) DFT methods for partially ionized systems.

When training large-scale models, the performance typically scales with the number of parameters and the dataset size according to a slow power law. A fundamental theoretical and practical question is whether comparable performance can be achieved with significantly smaller models and substantially less data. In this work, we provide a positive and constructive answer. We prove that a generic permutation-invariant function of $d$ objects can be asymptotically compressed into a function of $\operatorname{polylog} d$ objects with vanishing error. This theorem yields two key implications: (Ia) a large neural network can be compressed to polylogarithmic width while preserving its learning dynamics; (Ib) a large dataset can be compressed to polylogarithmic size while leaving the loss landscape of the corresponding model unchanged. (Ia) directly establishes a proof of the \textit{dynamical} lottery ticket hypothesis, which states that any ordinary network can be strongly compressed such that the learning dynamics and result remain unchanged. (Ib) shows that a neural scaling law of the form $L\sim d^{-\alpha}$ can be boosted to an arbitrarily fast power law decay, and ultimately to $\exp(-\alpha' \sqrt[m]{d})$.

Graph states are entangled states that are essential for quantum information processing, including measurement-based quantum computation. As experimental advances enable the realization of large-scale graph states, efficient fidelity estimation methods are crucial for assessing their robustness against noise. However, calculations of exact fidelity become intractable for large systems due to the exponential growth in the number of stabilizers. In this work, we show that the fidelity between any ideal graph state and its noisy counterpart under IID Pauli noise can be mapped to the partition function of a classical spin system, enabling efficient computation via statistical mechanical techniques, including transfer matrix methods and Monte Carlo simulations. Using this approach, we analyze the fidelity for regular graph states under depolarizing noise and uncover the emergence of phase transitions in fidelity between the pure-state regime and the noise-dominated regime governed by both the connectivity (degree) and spatial dimensionality of the graph state. Specifically, in 2D, phase transitions occur only when the degree satisfies $d\ge 6$, while in 3D they already appear at $d\ge 5$. However, for graph states with excessively high degree, such as fully connected graphs, the phase transition disappears, suggesting that extreme connectivity suppresses critical behavior. These findings reveal that robustness of graph states against noise is determined by their connectivity and spatial dimensionality. Graph states with lower degree and/or dimensionality, which exhibit a smooth crossover rather than a sharp transition, demonstrate greater robustness, while highly connected or higher-dimensional graph states are more fragile. Extreme connectivity, as the fully connected graph state possesses, restores robustness.

Magic state distillation (MSD) is a cornerstone of fault-tolerant quantum computing, enabling non-Clifford gates via state injection into stabilizer circuits. However, the substantial overhead of current MSD protocols remains a major obstacle to scalable implementations. We propose a general framework for pre-distillation, based on composite pulse sequences that suppress systematic errors in the generation of magic states. Unlike typical composite designs that target simple gates such as $X$, $Z$, or Hadamard, our schemes directly implement the non-Clifford $\mathcal{T}$ gate with enhanced robustness. We develop composite sequences tailored to the dominant control imperfections in superconducting, trapped-ion, neutral-atom, and integrated photonic platforms. To quantify improvement in the implementation, we introduce an operationally motivated fidelity measure specifically tailored to the $\mathcal{T}$ gate: the T-magic error, which captures the gate's effectiveness in preparing high-fidelity magic states. We further show that the error in the channel arising from the injection of faulty magic states scales linearly with the leading-order error of the states. Across all platforms, our approach yields high-fidelity $\mathcal{T}$ gates with reduced noise, lowering the number of distillation levels by up to three. This translates to exponential savings in qubit overhead and offers a practical path toward more resource-efficient universal quantum computation.

We study the time evolution of weakly interacting Bose gases on a three-dimensional torus of arbitrary volume. The coupling constant is supposed to be inversely proportional to the density, which is considered to be large and independent of the number of particles. We take into account a class of initial states exhibiting quasi-complete Bose-Einstein condensation. For each fixed time in a finite interval, we prove the convergence of the one-particle reduced density matrix to the projection onto the normalized order parameter describing the condensate - evolving according to the Hartree equation - in the iterated limit where the volume (and therefore the particle number), and subsequently the density go to infinity. The rate of convergence depends only on the density and on the decay of both the expected number of particles and the energy of the initial quasi-vacuum state.

Computing condensed phase spectra from atomistic simulations requires calculating correlation functions from molecular dynamics and can be very expensive. A totally general, data-driven method to reduce cost is to employ an exact rewriting to a generalized master equation characterized by a memory kernel. The decay time of the kernel can be less than the original function, reducing the amount of data required. In this paper we construct the minimal projection operator to predict vibrational sum-frequency generation spectra and apply it to the air-water interface simulated using ab initio molecular dynamics. We are able to obtain a modest reduction in cost of just under 50\%. We explore various avenues to use more of the available data to expand the projector in an attempt to reduce the cost further. Interestingly, we are not able to effect any change by including quadrupoles, inter-molecular couplings, or a depth-dependence. How to strategically go about maximally reducing cost using projection operators remains an open question.

We developed a practical quantum advantage benchmarking framework that connects the accumulation of entropy in a quantum processing unit and the degradation of the solution to a target optimization problem. The benchmark is based on approximating from below the Gibbs states boundary in the energy-entropy space for the application of interest. We believe the proposed benchmarking technique creates a powerful bridge between hardware benchmarking and application benchmarking, while remaining hardware-agnostic. It can be extended to fault-tolerant scenarios and relies on computationally tractable numerics. We demonstrate its applicability on the problem of finding the ground state of the two-dimensional Fermi-Hubbard.

Reliable parameter identification in ductile damage models remains challenging because the salient physics of damage progression are localized to small regions in material responses, and their signatures are often diluted in specimen-level measurements. Here, we propose a sequential Bayesian Inference (BI) framework for the calibration of the Gurson-Tvergaard-Needleman (GTN) model using multimodal experimental data (i.e., the specimen-level force-displacement (F-D) measurements and the spatially resolved digital image correlation (DIC) strain fields). This calibration approach builds on a previously developed two-step BI framework that first establishes a low-computational-cost emulator for a physics-based simulator (here, a finite element model incorporating the GTN material model) and then uses the experimental data to sample posteriors for the material model parameters using the Transitional Markov Chain Monte Carlo (T-MCMC). A central challenge to the successful application of this BI framework to the present problem arises from the high-dimensional representations needed to capture the salient features embedded in the F-D curves and the DIC fields. In this paper, it is demonstrated that Principal Component Analysis (PCA) provides low-dimensional representations that make it possible to apply the BI framework to the problem. Most importantly, it is shown that the sequence in which the BI is applied has a dramatic influence on the results obtained. Specifically, it is observed that applying BI first on F-D curves and subsequently on the DIC fields produces improved estimates of the GTN parameters. Possible causes for these observations are discussed in this paper, using AA6111 aluminum alloy as a case study.

Large thermal fluctuations of the liquid phase obscure the weak macroscopic electric field that drives electrochemical reactions, rendering the extraction of reliable interfacial charge distributions from ab initio molecular dynamics extremely challenging. We introduce SMILE-CP (Scalar Macro-dipole Integrated LEarning - Charge Partitioning), a macro-dipole-constrained scheme that infers atomic charges using only the instantaneous atomic coordinates and the total dipole moment of the simulation cell - quantities routinely available from standard density-functional theory calculations. SMILE-CP preserves both the global electrostatic field and the local potential without invoking any explicit charge-partitioning scheme. Benchmarks on three representative electrochemical interfaces - nanoconfined water, Mg2+ dissolution in water, and a kinked Mg vicinal surface under anodic bias - show that SMILE-CP eliminates the qualitative errors observed for unconstrained charge decompositions. The method is computationally inexpensive and data-efficient, opening the door to charge-aware machine-learning potentials capable of bias-controlled, nanosecond-scale simulations of realistic electrochemical systems.

Spin glasses are models of statistical mechanics in which a large number of simple elements interact with one another in a disordered fashion. One of the fundamental results of the theory is the Parisi formula, which identifies the limit of the free energy of a large class of such models. Yet many interesting models remain out of reach of the classical theory, and direct generalizations of the Parisi formula yield invalid predictions. I will report here on some partial progress towards the resolution of this problem, which also brings a new perspective on classical results.

We study the renormalization group flow of the scale-dependent effective potential of a quark-diquark model with full field dependence at nonzero chemical potential. This includes a discussion of approximations in relation to complex bosonic fields and the Silver-Blaze property. The resulting flow equation for the scale-dependent effective potential can in principle be solved down to the infrared limit. For our quark-diquark model, which may serve as a low-energy model for dense strong-interaction matter, we find that a competition between the Bardeen-Cooper-Schrieffer singularity and bosonic fluctuations can trigger a first-order phase transition at low temperatures that turns into a second-order phase transition at a tricritical point as the temperature increases.

We study in-context learning (ICL) of linear regression in a deep linear self-attention model, characterizing how performance depends on various computational and statistical resources (width, depth, number of training steps, batch size and data per context). In a joint limit where data dimension, context length, and residual stream width scale proportionally, we analyze the limiting asymptotics for three ICL settings: (1) isotropic covariates and tasks (ISO), (2) fixed and structured covariance (FS), and (3) where covariances are randomly rotated and structured (RRS). For ISO and FS settings, we find that depth only aids ICL performance if context length is limited. Alternatively, in the RRS setting where covariances change across contexts, increasing the depth leads to significant improvements in ICL, even at infinite context length. This provides a new solvable toy model of neural scaling laws which depends on both width and depth of a transformer and predicts an optimal transformer shape as a function of compute. This toy model enables computation of exact asymptotics for the risk as well as derivation of powerlaws under source/capacity conditions for the ICL tasks.

Building on the geometric formulation of quantum mechanics, we develop a coherence theory for ensembles that exploits the probability-phase structure of the quantum state space. Standard coherence measures quantify superposition within density matrices but cannot distinguish ensembles that produce the same mixed state through different distributions of pure states. First, we introduce the probability-phase mutual information $I(P;\Phi)$, which measures statistical correlations between measurement-accessible probabilities and measurement-inaccessible phases across an ensemble. Then, we prove this satisfies the axioms of a coherence monotone, establishing it as a bona-fide measure of ensemble-level coherence. Eventually, through the definition of the \emph{coherence surplus} $\delta_{\mathcal{C}} \geq 0$, we show how ensemble coherence relates to, but exceeds, density-matrix coherence, thus quantifying structure lost in statistical averaging.

With the advent of exquisite quantum emulators, storing highly entangled many-body states becomes essential. While entanglement typically builds over time when evolving a quantum system initialized in a product state, freezing that information at any given instant requires quenching to a Hamiltonian with the time-evolved state as an eigenstate, a concept we realize via an Emergent Hamiltonian framework. While the Emergent Hamiltonian is generically non-local and may lack a closed form, we show examples where it is exact and local, thereby enabling, in principle, indefinite state storage limited only by experimental imperfections. Unlike other phenomena, such as many-body localization, our method preserves both local and global properties of the quantum state. In some of our examples, we demonstrate that this protocol can be used to store maximally entangled multi-qubit states, such as tensor products of Bell states, or fragile, globally distributed entangled states, in the form of GHZ states, which are often challenging to initialize in actual devices.

Majorana zero modes (MZMs), promising for topological quantum computation, are naturally hosted in vortices of two-dimensional topological superconductors (TSCs). However, precise control and braiding of these vortex-bound MZMs remains a significant challenge. This work proposes and numerically demonstrates a novel braiding scheme utilizing a programmable matrix of spin transfer torque (STT) devices (STT-matrix) integrated with a TSC layer. By selectively activating individual STT elements, their localized stray fields enable deterministic manipulation, including driving, braiding, and fusion, of superconducting vortices and their associated MZMs. We establish a comprehensive simulation framework combining finite element analysis for STT-induced vortex formation, time-dependent Ginzburg-Landau equations for vortex dynamics and time-dependent Bogoliubov-de Gennes equations for MZM evolution. Simulations confirm the STT-matrix's capability for high-fidelity vortex manipulation and demonstrate MZM braiding dynamics. We quantify the impact of vortex acceleration and finite MZM coupling on braiding fidelity, showing it can be optimized by adjusting STT spacing and vortex separation. Furthermore, we demonstrate controlled MZM fusion and measure the resultant energy splitting. This STT-matrix-based approach offers a highly versatile, scalable, and potentially practical platform for operating MZMs within TSC vortices, advancing towards fault-tolerant topological quantum computation.

The precise modulation of activity through inhibitory signals ensures that both insect colonies and neural circuits operate efficiently and adaptively, highlighting the fundamental importance of inhibition in biological systems. Modulatory signals are produced in various contexts and are known for subtly shifting the probability of receiver behaviors based on response thresholds. Here we propose a non-linear function to introduce inhibitory responsiveness in collective decision-making inspired by honeybee house-hunting. We show that, compared with usual linear functions, non-linear responses enhance final consensus and reduce deliberation time. This improvement comes at the cost of reduced accuracy in identifying the best option. Nonetheless, for value-based tasks, the benefits of faster consensus and enhanced decision-making might outweigh this drawback.

Predicting electronic band structures from crystal structures is crucial for understanding structure-property correlations in materials science. First-principles approaches are accurate but computationally intensive. Recent years, machine learning (ML) has been extensively applied to this field, while existing ML models predominantly focus on band gap predictions or indirect band structure estimation via solving predicted Hamiltonians. An end-to-end model to predict band structure accurately and efficiently is still lacking. Here, we introduce a graph Transformer-based end-to-end approach that directly predicts band structures from crystal structures with high accuracy. Our method leverages the continuity of the k-path and treat continuous bands as a sequence. We demonstrate that our model not only provides accurate band structure predictions but also can derive other properties (such as band gap, band center, and band dispersion) with high accuracy. We verify the model performance on large and diverse datasets.

A measure of how sensitive the entanglement entropy is in a quantum system, has been proposed and its information geometric origin is discussed. It has been demonstrated for two exactly solvable spin systems, that thermodynamic criticality is directly \textit{indicated} by finite size scaling of the global maxima and turning points of the susceptibility of entanglement entropy through numerical analysis - obtaining power laws. Analytically we have proved those power laws for $| \ \lambda_c(N)-\lambda_c^{\infty}|$ as $N\to \infty$ in the cases of finite 1D transverse field ising model (TFIM) ($\lambda=h$) and XY chain ($\lambda=\gamma$). The integer power law appearing for XY model has been verified using perturbation theory in $\mathcal{O}(\frac{1}{N})$ and the fractional power law appearing in the case of TFIM, is verified by an exact approach involving Chebyshev polynomials, hypergeometric functions and complete elliptic integrals. Furthermore a set of potential applications of this quantity under quantum dynamics and also for non-integrable systems, are briefly discussed. The simplicity of this setup for understanding quantum criticality is emphasized as it takes in only the reduced density matrix of appropriate rank.

The subject of this study is spin transport through a molecular orbital connected to two leads, and coupled via exchange interaction with a precessing anisotropic molecular spin in a constant magnetic field. The inelastic spin-flip processes between molecular quasienergy levels are driven by the molecular spin precession. By setting the Larmor frequency, the tilt angle of molecular magnetization with respect to the magnetic field, and the magnetic anisotropy parameter, one can modulate the spin current and noise, spin-transfer torque, and related torque coefficients. Moreover, the dc-spin current and spin-transfer torque components provide the quasienergy level structure in the orbital. Quantum interference effects between states connected with spin-flip processes manifest themselves as dips (minimums) and peaks (maximums) in spin-current noise, matching Fano-like resonance profiles with equal probabilities of interfering elastic and inelastic spin-flip pathways. By proper adjustment of the anisotropy parameter and magnetic field, the precession is suppressed and the torque vanishes, revealing the anisotropy parameter via a dc-spin current or torque measurement. The results of the study show that spin transport and spin-transfer torque can be manipulated by the anisotropy parameter even in the absence of the magnetic field.

A system's internal dynamics and its interaction with the environment can be determined by tracking how external perturbations affect its transition rates between states. Quantitative measurements of these rates are crucial for optimizing quantum systems at the atomic scale but are challenging, as these dynamics are often faster than experimental observation capabilities. Here, we show that driving a stochastic system periodically enables quantitative determination of its transition rates over a wide frequency range spanning from kilohertz to gigahertz. To perform this quantitative extraction, we provide an analytical model that is applicable irrespective of the details of the studied system. We name this method stochastic resonance spectroscopy (SRS). We apply it to quantify spin switching in individual magnetic atoms, Neel state reversal in nano-antiferromagnets and quasiparticle transport through Yu-Shiba-Rusinov states. We anticipate that the ability to characterize broadband stochastic dynamics at the atomic scale will enable insights into an even wider range of systems, e.g. dynamics driven by light-matter interaction. Another exciting prospect is the investigation of systems that exhibit non-Markovian dynamics due to correlations with the environment.

X-ray scattering has been an indispensable tool in advancing our understanding of matter, from the first evidence of the crystal lattice to recent discoveries of nuclei's fastest dynamics. In addition to the lattice, ultrafast resonant elastic scattering of soft X-rays provides a sensitive probe of charge, spin, and orbital order with unparalleled nanometre spatial and femto- to picosecond temporal resolution. However, the full potential of this technique remains largely unexploited due to its high demand on the X-ray source. Only a selected number of instruments at large-scale facilities can deliver the required short-pulsed and wavelength-tunable radiation, rendering laboratory-scale experiments elusive so far. Here, we demonstrate time-resolved X-ray scattering with spectroscopic contrast at a laboratory-based instrument using the soft-X-ray radiation emitted from a laser-driven plasma source. Specifically, we investigate the photo-induced response of magnetic domains emerging in a ferrimagnetic heterostructure with 9$\,$ps temporal resolution. The achieved sensitivity allows for tracking the reorganisation of the domain network on pico- to nanosecond time scales in great detail. This instrumental development and experimental demonstration break new ground for studying material dynamics in a wide range of laterally ordered systems in a flexible laboratory environment.

The resistance of a heavy metal can be modulated by an adjacent magnetic material through the combined effects of the spin Hall effect, inverse spin Hall effect, and dissipation of the spin accumulation at the interface. This phenomenon is known as the spin Hall magnetoresistance. The dissipation of the spin accumulation can occur via various mechanisms, with spin-transfer torque being the most extensively studied. In this work, we report the observation of spin Hall magnetoresistance at the interface between platinum and an insulating altermagnetic candidate, Ba$_2$CoGe$_2$O$_7$. Our findings reveal that this heterostructure exhibits a relatively large spin Hall magnetoresistance signal, which is anisotropic with respect to the crystal orientation of the current channel. We explore and rule out several potential explanations for this anisotropy and propose that our results may be understood in the context of the anisotropies of the spin current channels across the Pt/altermagnetic Ba$_2$CoGe$_2$O$_7$ interface.

Solid-state electrolyte batteries are expected to replace liquid electrolyte lithium-ion batteries in the near future thanks to their higher theoretical energy density and improved safety. However, their adoption is currently hindered by their lower effective ionic conductivity, a quantity that governs charge and discharge rates. Identifying highly ion-conductive materials using conventional theoretical calculations and experimental validation is both time-consuming and resource-intensive. While machine learning holds the promise to expedite this process, relevant ionic conductivity and structural data is scarce. Here, we present OBELiX, a database of $\sim$600 synthesized solid electrolyte materials and their experimentally measured room temperature ionic conductivities gathered from literature and curated by domain experts. Each material is described by their measured composition, space group and lattice parameters. A full-crystal description in the form of a crystallographic information file (CIF) is provided for $\sim$320 structures for which atomic positions were available. We discuss various statistics and features of the dataset and provide training and testing splits carefully designed to avoid data leakage. Finally, we benchmark seven existing ML models on the task of predicting ionic conductivity and discuss their performance. The goal of this work is to facilitate the use of machine learning for solid-state electrolyte materials discovery.

Metamaterials are a promising platform for a range of applications, from shock absorption to mechanical computing. These functionalities typically rely on floppy modes or mechanically frustrated loops, both of which are difficult to design. In particular, how to design multiple modes or loops with target deformations remains an open problem. We introduce a combinatorial approach that allows us to create an arbitrarily large number of floppy modes and frustrated loops. The design freedom of the mode shapes enables us to easily introduce kinematic incompatibility to turn them into frustrated loops. We demonstrate that floppy modes can be sequentially buckled by using a specific instance of elastoplastic buckling. We utilize our combinatorial floppy chains and frustrated loops to achieve matrix-vector multiplication in materia. Our findings bring about new principles for the design and the use of floppiness and geometric frustration in soft matter and metamaterials.

Molecular electronics and other technologies whose components comprise individual molecules have been pursued for half a century because the molecular scale represents the limit of miniaturisation of objects whose structure is tuneable for function. Despite the promise, practical progress has been hindered by the lack of methodologies for directed assembly of arbitrary structures applicable at the molecular scale. DNA nanotechnology is an emerging framework that uses programmed synthetic oligomers to encode the design of self-assembling structures with atomic precision at the nanoscale. Here, we leverage DNA-directed self-assembly to construct single-molecule electrical transport devices in high yield, precisely positioning a metal-porphyrin between two 60 nm gold nanoparticles. Following deposition on SiO2 substrates, we image and establish electrical contact via established nanofabrication techniques. Each step of the process has a high success rate and we demonstrate device yields dramatically better than is possible using conventional approaches. Our approach is inherently scalable and adaptable to devices incorporating multiple heterogenous functional molecular components, finally offering a realistic framework for the realisation of classical and quantum molecular technologies.

Excitons in a monolayer transition metal dichalcogenide (1L-TMD) are highly bound states characterized by a Rydberg-like spectrum of discrete energy levels. Among these, states with odd-parity are known as dark excitons due to selection rules, which make their stationary and transient characterization challenging using linear optical techniques. Here, we demonstrate that the dynamics of a 2p dark excitonic state in 1L-WS$_2$ can be directly retrieved by measuring the Autler-Townes splitting of bright states in a three-pulse experiment. The splitting of the bright 1s excitonic state, observed by detuning a mid-infrared control field across the 1s-2p transition, provides an accurate characterization of the 2p state. Following carrier photoinjection, we observe a qualitatively different dynamics of the 1s and 2p levels, which is indicative of symmetry-dependent screening and exciton-exciton interactions. These findings provide new insights into many-body effects in TMDs, offering potential avenues for advancing the next generation optoelectronics.

Monolayers (MLs) of semiconducting transition metal dichalcogenides (\mbox{S-TMDs}) emit light very efficiently and display rich spin-valley physics, with gyromagnetic ($g$-) factors of about -4. Here, we investigate how these properties can be tailored by alloying. Magneto-optical spectroscopy is used to reveal the peculiar properties of excitonic complexes in Mo$_{x}$W$_{1-x}$Se$_2$ MLs with different Mo and W concentrations. We show that the alloys feature extremely high $g$-factors for neutral excitons, that change gradually with the composition up to reaching values of the order of -10 for $x \approx 0.2$. First-principles calculations corroborate the experimental findings and provide evidence that alloying in S-TMDs results in a non-trivial band structure engineering, being at the origin of the high $g$-factors. The theoretical framework also suggests a higher strain sensitivity of the alloys, making them promising candidates for tailor-made optoelectronic devices.

Collective actuation in active solids - the spontaneous coherent excitation of a few vibrational modes - emerges from a feedback between structural deformations and the orientation of active forces. It is an excellent candidate as a basic mechanism for oscillatory dynamics and regulation in dense living systems, and a better control over its onset would open new avenues in the life sciences. Combining model experiments, simulations and theory, we study the dynamics of such an active solid in the presence of an external field that polarizes the active forces. The experiments reveal a novel oscillatory regime absent at zero field. The theoretical analysis of a single agent demonstrates that the small field oscillations and the large field ones can be mapped onto the bounded and unbounded phase dynamics of a nonlinear pendulum. In the many agents case, the transition to collective actuation is promoted at low field, leading to a reentrant transition.

Collective actuation in active solids, the spontaneous condensation of the dynamics on a few elastic modes, takes place whenever the deformations of the structure reorient the forces exerted by the active units composing, or embedded in, the solid. In a companion paper, we show through a combination of model experiments, numerical simulations, and theoretical analysis that adding an external field that polarizes the active forces strongly affects the dynamical transition to collective actuation. A new oscillatory regime emerges, and a reentrance transition to collective actuation takes place. Depending on the degeneracy of the modes on which the dynamics condensates, and on the orientation of the field with respect to the stiff direction of the solid, several new dynamical regimes can be observed. The purpose of the present paper is to review these dynamical regimes in a comprehensive way, both for the single-particle dynamics and for the coarse-grained one. Whenever possible the dynamical regimes and the transition between them are described analytically, otherwise numerically.

We show that zero-dimensional (0-D) systems can host non-trivial topology analogous to macroscopic topological materials in greater dimensions. Unlike macroscopic periodic systems with translational symmetry, zero-dimensional materials such as molecules, clusters and quantum dots can exhibit discrete rotation symmetry. The eigenstates can thus be grouped into discrete bands and Bloch-like wave functions. Since the symmetry is discrete, the Berry phase and the topological indices must be defined by discrete Wilson polygons. Here, we demonstrate non-trivial Z2 orders in two representative 0-D molecules, [m]-Cycloparaphenylene and [m]-iso-thianaphthene, where topological transitions occur when modifying the coupling between the repeating units. Similar to macroscopic topological systems in greater dimensions, localized boundary states emerge in composite nanohoops formed by segments that are topologically distinct. This opens up the possibility of non-trivial topological phases in 0-D systems.

In the past decade, there has been a significant interest in the use of machine learning approaches in materials science research. Conventional deep learning approaches that rely on complex, nonlinear models have become increasingly important in computational materials science due to their high predictive accuracy. In contrast to these approaches, we have shown in a recent work that a remarkably simple learned heuristic rule -- based on the concept of topogivity -- can classify whether a material is topological using only its chemical composition. In this paper, we go beyond the topology classification scenario by also studying the use of machine learning to develop simple heuristic rules for classifying whether a material is a metal based on chemical composition. Moreover, we present a framework for incorporating chemistry-informed inductive bias based on the structure of the periodic table. For both the topology classification and the metallicity classification tasks, we empirically characterize the performance of simple heuristic rules fit with and without chemistry-informed inductive bias across a wide range of training set sizes. We find evidence that incorporating chemistry-informed inductive bias can reduce the amount of training data required to reach a given level of test accuracy.

In this study, we investigate the ion-irradiation-induced phase transition in gallium oxide (Ga2O3) from the $\beta$ to the $\gamma$ phase, the role of defects during the transformation, and the quality of the resulting crystal structure. Using a multi-method analysis approach including X-ray diffraction (XRD), transmission electron microscopy (TEM), Rutherford backscattering spectrometry in channeling mode (RBS/c), Doppler broadening variable energy positron annihilation spectroscopy (DB-VEPAS) and variable energy positron annihilation lifetime spectroscopy (VEPALS) supported by density functional theory (DFT) calculations, we have characterized defects at all the relevant stages before, during, and after the phase transition. Reduction in backscattering yield was observed in RBS/c spectra after the transition to the $\gamma$ phase. This is corroborated by a significant decrease in the positron trapping center density due to generation of embedded vacancies intrinsic for the $\gamma$-Ga2O3 but too shallow in order to trap positrons. A comparison of the observed positron lifetime of $\gamma$-Ga2O3 with different theoretical models shows good agreement with the three-site $\gamma$ phase approach. A characteristic increase in the effective positron diffusion length and the positron lifetime at the transition point from $\beta$-Ga2O3 to $\gamma$-Ga2O3 enables visualization of the phase transition with positrons for the first time. Moreover, a subsequent reduction of these quantities with increasing irradiation fluence was observed, which we attribute to further evolution of the $\gamma$-Ga2O3 and changes in the gallium vacancy density as well as relative occupation in the crystal lattice.

A significant effort in condensed matter physics is dedicated to the search for exotic arrangements of electric dipoles in crystals. Non-collinear dipolar arrangements mimicking magnetic spin textures, such as polar vortices and skyrmions, have been realized, but others, like helices of dipoles, have remained elusive. While earlier work claimed the presence of a helical dipole modulation in ferroelectric BiCu$_{x}$Mn$_{7-x}$O$_{12}$, our results rule out such a structure, motivating a renewed search for helical textures. Using atomic-resolution imaging, we report a novel form of helical order in which polar domains self-organize into a mesoscopic helical pattern: from domain to domain, polarization rotation follows a consistent handedness. Both right- and left-handed chirality emerging from this helical ordering are observed. This discovery establishes mesoscopic ordering as novel mechanism for inducing helical textures, and hence chirality, in ferroelectric crystals, paralleling the efforts in liquid crystals and supramolecular assemblies.

The low-energy effective description of Weyl semimetals is defined by the axion electrodynamics, which captures the effects arising due to the presence of nodes of opposite chirality in the electronic structure. Here we explore the magnetoelectric response of time-reversal breaking (TRB) Weyl superconductors in the London regime. The influence of the axion contribution leads to an increase in the London penetration depth$-$a behavior that can be anticipated by first considering the photon spectrum of a TRB Weyl semimetal. Moreover, we find that both the Meissner state and the vortex phase feature an interplay between the electric and magnetic fields. This leads to a nonvanishing electromagnetic angular momentum, which we calculate for a number of geometrical configurations.

The absence of inversion symmetry in chiral tellurium (Te) creates exotic spin textures within its electron waves. However, understanding textured optical waves within Te remains a challenge due to the semi-classical limitations of long-wavelength approximation. To unveil these textured optical waves, we develop a spin-resolved deep-microscopic optical bandstructure for Te analogous to its electronic counterpart. We demonstrate that the degeneracies in this optical bandstructure is lifted by the twisted lattice of Te, which induces optical gyrotropy. Our theory shows excellent agreement with experimental optical gyrotropy measurements. At the lattice level, we reveal that the chirality of Te manifests as deep-microscopic optical spin texture within the optical wave. Our framework uncovers the finite-momentum origin of optical activity and provides a microscopic basis for light-matter interactions in chiral crystalline materials.

Diodes have a nonreciprocal voltage versus current relationship, produced by breaking the space and time reversal symmetry. However, developing high-end superconducting computers requires a superconducting analogue of the traditional semiconductor diode. Such a superconducting diode exhibits non-reciprocity, or a high asymmetry in its critical currents. We present a model of a perfect superconducting diode based on a superconducting quantum interference device made with multiple superconducting nanowires. The diode predicted by our model has a large positive critical current, while the negative critical current can be exactly zero. This 100\% diode efficiency ($\eta = 1$) remains stable against small changes of the magnetic field. Another important result is that under certain and quite broad conditions such devices can act as supercurrent range controllers. In such device a supercurrent can flow with zero voltage applied, but only if the supercurrent is contained in some narrow, adjustable range, which excludes zero current.

We propose an analytical model for the remote bonding potential of the substrate that permeates through graphene during remote epitaxy. Our model, based on a Morse interatomic potential, includes the attenuation due to the increased film-substrate separation and due to graphene free carrier screening. Compared with previous slab density functional theory calculations, which use the electrostatic potential as a proxy for bonding, our analytical model includes covalent and van der Waals bonding interactions, includes screening (which is often ignored), and is based on simple, physically interpretable, and well benchmarked parameters that build understanding. We show that for typical graphene free carrier concentrations of order $10^{12}$ cm$^{-2}$, the magnitude of $|\phi_{remote}|$ for most semiconductor and oxide substrates is few to tens of meV, similar to the van der Waals potential of graphene. This suggests interference between the graphene and remote substrate potentials must be considered when interpreting experiments on remote epitaxy. Furthermore, we show that (1) the strength of the remote potential is tunable by screening (graphene carrier density), (2) the remote potential is vanishingly weak through two or more graphene layers, (3) the spatial extent of the potential, rather than degree of ionicity, controls the strength of the permeated bonding potential. Our model provides a simple framework for benchmarking direct measurements of the remote epitaxial potential, and we propose several experimental paths to measure this quantity. De-convolving the effects of the native remote potential, graphene defects, and tunable growth kinetics is key to understanding and tuning the mechanisms of remote epitaxy.

Heterostructures involving transition metal dichalcogenides (TMDs) have attracted significant research interest due to the richness and versatility of the underlying physical phenomena. In this work, we investigate a heterostructure consisting of a rare-earth material, specifically a Gd monolayer, interfaced with WSe$_2$. We explore its electronic structure, magnetic properties, and transport behavior, with particular emphasis on the emergence of the anomalous Hall effect (AHE). Both Gd and W are heavy elements, providing strong spin-orbit coupling (SOC), which plays a crucial role in triggering the AHE. The combination of strong SOC and inversion symmetry breaking leads to pronounced asymmetries between the $\Gamma-K$ and $\Gamma-K^\prime$ directions in the Brillouin zone. Our calculations reveal a substantial anomalous Hall conductivity (AHC) at the ferromagnetic interface, primarily originating from numerous avoided crossings involving the d-states of both Gd and W near the Fermi level. Moreover, we demonstrate that the AHC is highly tunable, either by adjusting the in-plane lattice constant or by reducing the separation between Gd and WSe$_2$.

We present the structural, magnetic, and magnetocaloric properties of thin films with stoichiometry Tb$_{31}$Co$_{69}$ and Dy$_{31}$Co$_{69}$ deposited on naturally oxidized silicon Si (100) substrates. Samples with a thickness $d=50$ nm covered with a protective Au overlayer with a thickness $d_{\rm Au} =5 $ nm were produced using the pulsed laser deposition technique. X-ray diffraction analysis indicated the presence of crystallized Laves phases and amorphous phases in the prepared materials. Magnetization measurements as a function of temperature revealed ferrimagnetic behavior in both samples. We estimated the compensation temperature $T_{\rm comp}$ of the amorphous phase for Tb$_{31}$Co$_{69}$ at 81.5 K and for Dy$_{31}$Co$_{69}$ at 88.5 K, while we found the Curie temperature $T_{\rm C,\ Laves}$ of the crystallized Laves phases at 204.5 K and at 117 K, respectively. We investigated the magnetocaloric effect in a wide temperature range, covering $T_{\rm comp}$ of amorphous phases and $T_{\rm C,\ Laves}$ of crystallized Laves phases. The analysis for the magnetic field change of $\Delta \mu_0H=5$ T showed values of the magnetic entropy change of $-\Delta S_{\rm M}=4.9$ mJ cm$^{-3}$ K$^{-1}$ at $T_{\rm comp}$ and $-\Delta S_{\rm M}=6.6$ mJ cm$^{-3}$ K$^{-1}$ at $T_{\rm C,\ Laves}$ for Tb$_{31}$Co$_{69}$, while for Dy$_{31}$Co$_{69}$, we determined the values of $-\Delta S_{\rm M}=35$ mJ cm$^{-3}$ K$^{-1}$ at $T_{\rm comp}$ and $-\Delta S_{\rm M}=28$ mJ cm$^{-3}$ K$^{-1}$ at $T_{\rm C,\ Laves}$.

We investigate the formation of moiré quasicrystal patterns in Bose gases confined in twisted bilayer optical lattices via Floquet-engineered intralayer atomic interactions. Dynamical evolutions of the inverse participation ratio and the density wave amplitude reveal the stage for the emergence of moiré quasicrystal patterns, whose symmetry can be easily manipulated by the modulation frequencies and amplitudes. Reducing the frequencies and increasing the amplitudes can both facilitate lattice symmetry breaking and the subsequent emergence of rotational symmetry. Notably, a twelve-fold quasicrystal pattern emerges under specific parameters, closely resembling the moiré quasicrystal in twisted bilayer graphene. The momentum-space distributions also exhibit high rotational symmetry, which is consistent with the real-space patterns at specific evolution times. Our findings establish a new quantum platform for exploring quasicrystals and their symmetry properties in ultracold bosonic systems.

A generalization of the entropy production rate is proposed $\Pi_q$ in non-equilibrium systems by extending the formalism of classical stochastic thermodynamics to regimes with non-Gaussian fluctuations. Through the Rényi entropy $S_q$ , where entropic parameter $q$ modulates critical fluctuations, it is defined $\Pi_q$ and the postulated generalized $q$-affinity ${\cal A}_q$ for Markov processes, where it is demonstrated that $\Pi_q \geq 0$, generalizing the second thermodynamics this http URL derived formal framework was applied to the Rössler model, a nonlinear dynamical system exhibiting chaos. Numerical simulations show that the entropy production rate $\Pi_q$ can be used as an index of robustness and complexity by quantitatively corroborating the greater robustness of funnel-type chaos compared to spiral-type chaos. Our results reveal limitations of Gibbs-Shannon entropy in capturing non-Gaussian fluctuations induced by nonlinearity. On the contrary, it is found that $\Pi_q$ it can be a suitable magnitude to measure the intensity of chaotic dynamics through the entropy parameter $q$ , indicating a plausible link with Lyapunov exponents. The proposed formal framework extends the scope of stochastic thermodynamics to complex systems, integrating chaotic dynamics and the role of the entropic index q as a source of irreversibility and in capturing non-Gaussian contributions to entropy production.

Motivated by recent experimental observations of the possible spin supersolid states in triangular lattice compounds, we study the dynamical properties of various ground states in the spin-1/2 easy-axis antiferromagnetic Heisenberg model with impurities under magnetic fields using numerical methods. In both low- and high-field spin supersolid states, the gapless Goldstone mode at the $K$ points remains robust against impurities, which is related to the presence of spin superfluidity. By contrast, we find that impurities induce a splitting of the magnon bands at the same density level in the conventional magnetic state, the so-called up-up-down state. In addition, the finite superfluid stiffness probed by the twisted phase in the spin supersolid states is consistent with the excitation spectrum. We argue that this excitation spectrum with impurity provides direct evidence for the dissipationless dynamics in the spin supersolid states, which could be tested in neutron scattering experiments.

Applying angle-resolved photoemission spectroscopy and density functional theory calculations, we present compelling spectroscopic evidence demonstrating the intertwining and mutual interaction between the Kondo and kagome sublattices in heavy-fermion intermetallic compound YbV$_6$Sn$_6$. We reveal the Yb 4$f$-derived states near the Fermi level, along with the presence of bulk kagome bands and topological surface states. We unveil strong interactions between the 4$f$ and itinerant electrons, where the kagome bands hosting the Dirac fermions and van Hove singularities predominate. Such findings are well described using a $c$-$f$ hybridization model. On the other hand, our systematic characterization of magnetic properties demonstrates an unusually enhanced antiferromagnetic ordering, where the kagome-derived van Hove singularities near $E_F$ play a vital role in determining the unconventional nature of the Ruderman-Kittel-Kasuya-Yosida interaction and Kondo coupling. These unique kagome-state-mediated exchange interactions have never been reported before and could lead to a novel phase diagram and various quantum critical behaviors in YbV$_6$Sn$_6$ and its siblings. Our results not only expand the family of exotic quantum phases entangled with kagome structure to the strongly correlated regime, but also establish YbV$_6$Sn$_6$ as an unprecedented platform to explore unconventional many-body physics beyond the standard Kondo picture.

Low-angle grain boundaries (LAGBs) are often regarded as penetrable interfaces to dislocation motion, yet recent studies suggest they can also act as strong barriers. The origin of this duality remains debated, particularly regarding the role of elastic interactions. Here, large-scale molecular dynamics simulations are employed to investigate dislocation transmission across various tilt LAGBs in BCC Fe. The results show that transmission resistance varies widely with boundary-dislocation geometry. Contrary to the prevailing view that dislocation reactions dominate, elastic interactions between lattice and boundary dislocations emerge as the primary controlling factor. Screw and screw-like dislocations generate shear stresses that bend GB dislocations and produce strong barriers, whereas edge dislocations lack such stresses and transmit more readily. Consequently, barrier strength increases as the dislocation character angle decreases, with screw dislocations experiencing the strongest resistance. From these insights, we develop an analytical model that quantitatively links net transmission stress to dislocation character, boundary inclination, and boundary misorientation, reproducing the simulation results with excellent agreement. These results establish the dominant role of elastic interactions in dislocation-LAGB interactions and provide a predictive basis for designing materials strengthened by controlled boundary architectures.

Quantum Hall edge channels partition electric charge over N chiral (uni-directional) modes. Intermode scattering leads to partition noise, observed in graphene p-n junctions. While inelastic scattering suppresses this noise by averaging out fluctuations, we show that pure (quasi-elastic) dephasing may enhance the partition noise. The noise power increases by up to 50% for two modes, with a general enhancement factor of 1+1/N in the strong-dephasing limit. This counterintuitive effect is explained in the framework of monitored quantum transport, arising from the self-averaging of quantum trajectories.

Thermal rectification is observed in jointless Pb wires at temperatures near the superconducting transition of Pb under magnetic fields. Using different magnetic-field (H) response of temperature dependence of thermal conductivity (\k{appa}-T) under H parallel to J and H perpendicular to J where J is heat flow, we fabricated a jointless thermal diode. Thermal rectification is observed with the thermal rectification ratio (TRR) of 1.5 and the difference in \k{appa} of 330 W m-1 K-1 at T = 5.11 K under H = 400 Oe for a Pb wire with a 50%-bent (H perpendicular to J) and 50%-straight (H parallel to J) structure. The peak temperature of TRR can be tuned by the strength of applied magnetic field. By changing bent ratio to 40%-bent, a higher TRR exceeding 2 was observed. The Pb-jointless thermal diode will be a useful material for thermal management at cryogenic temperatures.

In this work, surface diffusion is studied with a different perspective by showing how the corresponding open dynamics is transformed when passing, in a continuous and smooth way, from a pure quantum regime to a full classical regime; the so-called quantum-to-classical transition. This continuous process is carried out from the Liouville-von Neumann equation by scaling Planck's constant. For this goal, the Brownian motion of an adsorbate on a flat surface is analyzed in order to show how this transition takes place. In particular, this open dynamics is studied from the master equation for the reduced density matrix within the Caldeira-Leggett formalism; in particular, the two extreme time behaviors, the ballistic and diffusive motions. It is also shown that the origin of the ballistic motion is different for the quantum and classical regimes. In this scenario, the corresponding Gaussian function for the intermediate scattering function is governed by the thermal velocity in the classical regime versus the initial spreading velocity of the wave packet for the quantum regime, leading to speak of classical and quantum ideal gas, respectively. Finally, in the diffusive regime, and starting from the Chudley-Elliott model, the quantum-to-classical transition is also discussed in terms of the well-known H-function for three surface temperatures in the diffusion of H and D on a Pt(111) surface. The main goal in this analysis is if one can discriminate the irreversibility coming from tunneling and thermal activation diffusion.

Polar metals are an underexplored material class combining two properties that are typically incompatible, namely a polar crystal structure and reasonable electrical conductivity. While intriguing given that metals favor centrosymmetry, these materials also exhibit potential functional properties relevant to memory, optoelectronic, catalytic, and other applications. The distortive polar metal (DPM) subclass forms through a centrosymmetry-lifting phase transformation into a polar crystal structure. In the process, domains with uniform geometric polar directions form, oftentimes separated by domain boundaries with polarity discontinuities arranged in "charged" head-to-head (H-H) or tail-to-tail (T-T) morphologies. To date, only metallic oxide DPM microstructures have been studied. Here we reveal in the intermetallic DPM Mn5Al8 different chemical reactivity and surface interactions at domain boundaries depending on their H-H or T-T character. Variable surface electron-transfer reactivity suggests localized changes in electronic work functions due to an increase (H-H) or depletion (T-T) in the electronic density of states. This behavior is unintuitive in a metal where electrostatic de-polarizing fields should not account for fluctuations in carrier densities. These findings suggest that metallic DPMs may offer functionalizable domain boundary behavior and deserve increased attention. Metallic DPMs allow highly tunable chemistries that can undergo various thermomechanical processing and transformation protocols. Ultimately, this study marks a milestone in metal physics and uncovers novel intermetallic properties, propelling the discovery and design of advanced electronic materials and devices.

Within a model where micrometer-size soft colloidal particles are viewed as liquid drops, we theoretically study the contact interaction between them. We compute the exact deformation energy across a broad range of indentations and for various model parameters, and we show that it can be reproduced using truncated superball and spheropolyhedral variational shapes in the attractive and the repulsive regime, respectively. At large surface tensions representative of microgels, this energy is pairwise additive well beyond small indentations and can be approximated by a power-law dependence on indentation with an exponent around 2.

Oxide Li-conducting solid-state electrolytes (SSEs) offer excellent chemical and thermal stability but typically exhibit lower ionic conductivity than sulfides and chlorides. This motivates the search for new oxide materials with enhanced conductivity. Crystal structure prediction is a powerful approach for identifying such candidates. However, the structural complexity of oxide SSEs, often involving unit cells with more than 100 atoms, presents significant challenges for conventional methods. In this study, we introduce TOPIC, a structure prediction algorithm that reduces configurational complexity by enforcing corner-sharing (CS) bond topology constraints. We demonstrate that TOPIC successfully reproduces the ground-state and metastable structures of known oxide SSEs, including LiTa$_2$PO$_8$ and Li$_7$La$_3$Zr$_2$O$_{12}$, which contain up to about 200 atoms per unit cell. By combining this approach with a pretrained machine-learning interatomic potential, we systematically screen quaternary oxide compositions and identify 92 promising candidates with CS frameworks. In particular, Li$_4$Hf$_2$Si$_3$O$_{12}$, which corresponds to the ground state at its composition, exhibits an ionic conductivity of 14 mS cm$^{-1}$, a hull energy of 21 meV atom$^{-1}$, and a band gap of 6.5 eV. Through our investigation, we identify the Li ratio as one of the key factors determining the stability of CS structures. Overall, our approach provides a practical and scalable pathway for discovering high-performance oxide solid electrolytes in previously unexplored chemical spaces.

The diffusion of tracer particles immersed in a granular gas under uniform shear flow (USF) is analyzed within the framework of the inelastic Boltzmann equation. Two different but complementary approaches are followed to achieve exact results. First, we maintain the structure of the Boltzmann collision operator but consider inelastic Maxwell models (IMM). Using IMM allows us to compute the collisional moments of the Boltzmann operator without knowing the velocity distribution functions of the granular binary mixture explicitly. Second, we consider a kinetic model of the Boltzmann equation for inelastic hard spheres (IHS). This kinetic model is based on the equivalence between a gas of elastic hard spheres subjected to a drag force proportional to the particle velocity and a gas of IHS. We solve the Boltzmann--Lorentz kinetic equation for tracer particles using a generalized Chapman--Enskog--like expansion around the shear flow distribution. This reference distribution retains all hydrodynamic orders in the shear rate. The mass flux is obtained to first order in the deviations of the concentration, pressure, and temperature from their values in the reference state. Due to the velocity space anisotropy induced by the shear flow, the mass flux is expressed in terms of tensorial quantities rather than the conventional scalar diffusion coefficients. The exact results derived here are compared with those previously obtained for IHS by using different approximations [JSTAT P02012 (2007)]. The comparison generally shows reasonable quantitative agreement, especially for IMM results. Finally, we study segregation by thermal diffusion as an application of the theory. The phase diagrams illustrating segregation are shown and compared with IHS results, demonstrating qualitative agreement.

This paper introduces a spectral analysis of time-seires data derived from real-time time-dependent density functional theory (TDDFT) using Singular Spectrum Analysis (SSA). TDDFT is a robust method for obtaining molecular excited states and optical spectra by tracking the time evolution of dynamical dipole moments. However, the spectral resolution can be compromised when Fourier transformation's total time duration is insufficient. SSA enabled the extraction of specific oscillation components from the time-series data, facilitating the generation of higher-precision spectra. Even with relatively short time-series dataset, the predictive extension of SSA yielded high-resolution spectra, demonstrating substantial agreement with results obtained through conventional methods. The efficacy of this approach was validated for several small molecules, including ethylene, benzene, and others. SSA's ability to conduct detailed spectral anasysis in specific energy regions enhance spectral resolution and facilitates the clarification of oscillation components within these regions. Real-time TDDFT combined with SSA provides a new analytical method for analyzing the optical properties of molecules, significantly improving the accuracy of the analysis of emission and absorption spectra analysis. This method is expected to have various applications.

The Sachdev-Ye-Kitaev (SYK) model is of paramount importance for the understanding of both strange metals and a microscopic theory of two-dimensional gravity. We study the interplay between Stabilizer Rényi Entropy (SRE) and entanglement entropy in both the ground state and highly excited states of the SYK4+SYK2 model interpolating the highly chaotic four-body interactions model with the integrable two-body interactions one. The interplay between these quantities is assessed also through universal statistics of the entanglement spectrum and its anti-flatness. We find that SYK4 is indeed characterized by a complex pattern of both entanglement and non-stabilizer resources while SYK2 is non-universal and not complex. We discuss the fragility and robustness of these features depending on the interpolation parameter.

The maximum entropy principle is foundational for statistical analyses of complex dynamics. This principle has been challenged by the findings of a previous work [arXiv:1701.07596], where it was argued that a quantum system driven in time by a certain aperiodic sequence without any explicit symmetries, dubbed the Thue-Morse drive, gives rise to emergent nonergodic steady states which are underpinned by effective conserved quantities. Here, we resolve this apparent tension. We rigorously prove that the Thue-Morse drive achieves a very strong notion of quantum ergodicity in the long-time limit: The time evolution of any initial state uniformly visits every corner of its Hilbert space. On the other hand, we find the dynamics also approximates a Floquet drive for arbitrarily long albeit finite periods of time with no characteristic timescale, resulting in a scale-free ergodic dynamics we call critically slow complete Hilbert-space ergodicity. Furthermore, numerical studies reveal that critically slow complete Hilbert-space ergodicity is not specific to the Thue-Morse drive and is, in fact, exhibited by many other aperiodic drives derived from morphic sequences, i.e., words derived from repeatedly applying substitution rules on basic characters. Our work presents a new class of dynamics in time-dependent quantum systems where full ergodicity is eventually attained, but only after astronomically long times.

Kitaev's toric code has become one of the most studied models in physics and is highly relevant to the fields of both quantum error correction and condensed matter physics. Most notably, it is the simplest known model hosting an extended, deconfined topological bulk phase. To this day, it remains challenging to reliably and robustly probe topological phases, as many state-of-the-art order parameters are sensitive to specific models and even specific parameter regimes. With the emergence of powerful quantum simulators which are approaching the regimes of topological bulk phases, there is a timely need for experimentally accessible order parameters. Here we study the ground state physics of the parallel field toric code on the honeycomb, triangular and cubic lattices using continuous-time quantum Monte Carlo. By extending the concept of experimentally accessible percolation-inspired order parameters (POPs) we show that electric and magnetic anyons are independently confined on the honeycomb and triangular lattices, unlike on the square lattice. Our work manifestly demonstrates that, even in the ground state, we must make a distinction between topological order and \mbox{(de-)confinement}. Moreover, we report multi-critical points in the aforementioned confinement phase diagrams. Finally, we map out the topological phase diagrams on the honeycomb, triangular and cubic lattices and compare the performance of the POPs with other topological order parameters. Our work paves the way for studies of confinement involving dynamical matter and the associated multi-critical points in contemporary quantum simulation platforms for $\mathbb{Z}_2$ lattice gauge theories.

Superconducting circuits comprising Josephson junctions have spurred significant research activity due to their promise to realize scalable quantum computers. Effective Hamiltonians for these systems have traditionally been derived assuming the junction connects superconducting islands of infinite size. We derive a quantized Hamiltonian for a Josephson junction between finite-sized islands and predict measurable corrections to the qubit frequency and charge susceptibility to test the theory.

Optimal tuning of functional parameters in density functional theory approximations, based on enforcing the ionization potential theorem, has emerged as the method of choice for the non-empirical prediction of the electronic structure of finite systems. This method has recently been extended to the bulk limit, based on an ansatz that generalizes the ionization potential theorem to the removal of an electron from a localized Wannier orbital. This Wannier-localization based optimal tuning method has been shown to be highly successful for a wide range of periodic systems, accurately predicting electronic and optical properties. However, a rigorous theoretical justification for its foundational ansatz has been lacking. Here, we establish an ionization potential condition for the removal of a localized electron, by extending the piecewise linearity and Janak's theorems in density functional theory. We also provide numerical evidence supporting our theory.

Twisted multilayer graphene, characterized by its moiré patterns arising from inter-layer rotational misalignment, serves as a rich platform for exploring quantum phenomena. Machine learning interatomic potentials (MLIPs) are a promising approach to model such systems. Our work develops a method to generate training and test datasets for fitting MLIPs that capture all possible misalignments but remain small-scale to facilitate efficient data generation and parameter estimation. To achieve this, we generate configurations with periodic boundary conditions suitable for DFT calculations, and then introduce an internal twist and shift within those supercell structures. Using this technique, supplemented with an active learning workflow, we fit an Atomic Cluster Expansion potential for simulating twisted multilayer graphene and test it for accuracy and robustness on a range of simulation tasks.

We introduce a compact simulation framework for modeling open quantum systems coupled to structured, memory-retaining baths using QuTiP. Our method models the bath as a finite set of layered qubits with adjustable connections, interpreted either as a physical realization or as a conceptual representation, rather than as a continuum. This explicit modeling enables direct control over non-Markovian dynamics and allows spectral diagnostics via Fast Fourier Transform (FFT) of system observables. Using a triangle-based bath motif and its extension to a six-qubit anisotropic fractal-like architecture, we demonstrate how spectral fingerprints encode bath topology and memory depth. Standard machine learning tools such as Principal Component Analysis (PCA) and gradient boosting can then be employed to infer bath parameters and estimate proximity to exceptional points (EPs). The results suggest that spectral analysis can serve as a unifying, quantum-platform agnostic tool across theory, simulation, and experiment, offering both a student-accessible and experimentally relevant approach to understanding coherence loss and memory flow in quantum hardware. Rather than treating noise as an adversary to be eliminated, our approach views structured baths as collaborative partners, enabling controlled memory and delocalized memory and information flow for engineered quantum dynamics. In addition to its diagnostic power, the framework offers a modular and reproducible platform for teaching open quantum systems. Ultimately, we frame this as a pedagogical tool: students can pair FFT-based spectral features with lightweight ML (e.g., PCA and gradient boosting) to extract data-rich, interpretable signatures of open-system and non-Hermitian dynamics.

Two-level systems (TLSs) are tunneling states commonly found in amorphous materials that electrically couple to qubits, resonators, and vibrational modes in materials, leading to energy loss in those systems. Recent studies suggest that applying a large alternating electric field changes the oxide structure, potentially improving the performance of qubits and resonators. In this study, we probe the effect of alternating bias at cryogenic temperatures on TLS dynamics within amorphous oxide parallel-plate capacitors operating in the strongly coupled regime. We bias the TLSs in the capacitors using an electric field. This allows us to spectroscopically image TLSs and extract their densities and dipole moments. When an in-situ alternating bias is applied, the steady-state spectra from the standard TLS model disappear. Post-alternating bias TLS spectroscopy reveals transient behavior, in which the TLS frequency fluctuates on the order of minutes. Thermal cycling above 10 K reverses these effects, restoring the TLS spectrum to its original state, indicating a reversible mechanism. Importantly, the intrinsic loss tangent of the LC oscillator remains unchanged before and after the application of the alternating bias. We propose that the disappearance of the steady-state spectrum are caused by non-equilibrium energy build up from strain in the oxide film introduced by the pulsed voltage bias sequence. Understanding this non-equilibrium energy could inform future models of time-dependent TLS dynamics.

The intrinsic equivalence between electron spin and qubit offers a natural foundation for quantum simulations of magnetic materials. However, incorporating magnetocrystalline anisotropy (MCA), a key feature of real magnets, remains a major challenge. Here, we develop a quantum simulation framework for MCA in CuSb2O6, a spin-1/2 antiferromagnet with alternating ferromagnetic chains arising from frustrated, anisotropic exchange interactions in a nearly square lattice. The $\mathrm{Cu}^{2+}$ spin network is modeled as a four-qubit square lattice, with four paired ancilla qubits introduced to encode angle-dependent MCA. This two-qubit representation per spin site resolves the limitation that squared Pauli operators yield only the identity, enabling MCA terms to be faithfully embedded into quantum circuits. Using the variational quantum eigensolver, we determine an exceptionally small easy-axis MCA constant, just 0.00022% of the nearest-neighbor exchange interaction, yet sufficient to drive a spin-flop transition with $90^{\circ}$ spin reorientation and strong angular variation in magnetic torque. Beyond this regime, the simulations uncover a half-saturated magnetic phase at ultra-high fields, stabilized by anisotropic next-nearest-neighbor interactions. Our findings demonstrate the feasibility of resource-efficient quantum simulations of complex magnetic phenomena in real materials.

Magnetically levitated spinning rotors are key elements in important technologies such as navigation by gyroscopes, energy storage by flywheels, ultra-high vacuum generation by turbomolecular pumps, and pressure sensing for process control. However, mechanical rotors are typically macroscopic and limited to room temperature and low rotation frequencies. In particular, sensing pressure at low temperatures remains a technological challenge, while emerging quantum technologies demand a precise evaluation of pressure conditions at low temperatures to cope with quantum-spoiling decoherence. To close this gap, we demonstrate wide range pressure sensing by a spinning rotor based on a micromagnet levitated by the Meissner effect at 4.2 Kelvin. We achieve rotational speeds of up to 138 million rotations per minute, resulting in very high effective quality factors, outperforming current platforms. Beside sensing applications, we envision the use of levitated rotors for probing fundamental science including quantum mechanics and gravity, enabled by ultralow torque noise.