Identifying quantum spin liquids, magnon breakdown, or fractionalized excitations in quantum magnets is an ongoing challenge due to the ambiguity of possible origins of excitation continua occurring in linear response probes. Recently, it was proposed that techniques measuring higher-order response, such as two-dimensional coherent spectroscopy (2DCS), could resolve such ambiguities. Numerically simulating nonlinear response functions can, however, be computationally very demanding. We present an efficient Lanczos-based method to compute second-order susceptibilities $\chi^{2}\omega_t,\omega_\tau)$ directly in the frequency domain. Applying this to extended Kitaev models describing $\alpha$-RuCl$_3$, we find qualitatively different nonlinear responses between intermediate magnetic field strengths and the high-field regime. To put these results into context, we derive the general 2DCS response of partially-polarized magnets within the linear spin-wave approximation, establishing that $\chi^2(\omega_t,\omega_\tau)$ is restricted to a distinct universal form if the excitations are conventional magnons. Deviations from this form, as predicted in our (Lanczos-based) simulations for $\alpha$-RuCl$_3$, can hence serve in 2DCS experiments as direct criteria to determine whether an observed excitation continuum is of conventional two-magnon type or of different nature.

Most of our intuition about the behavior of physical systems is shaped by observations at or near thermal equilibrium. However, even a thermal quench can lead to states far from thermal equilibrium, where counterintuitive, anomalous effects can occur. A prime example of anomalous thermal relaxation is the Mpemba effect, in which a system prepared at a hot temperature cools down to the temperature of the cold environment faster than an identical system prepared at a warm temperature. Although reported for water more than 2000 years ago by Aristotle, the recent observations of analogous relaxation speedups in a variety of systems have motivated the search for general explanations. We review anomalous relaxation effects, which all share a nonmonotonic dependence of relaxation time versus initial ``distance" from the final state or from the phase transition. The final state can be an equilibrium or a nonequilibrium steady state. We first review the water experiments and classify the anomalous relaxation phenomena related to the Mpemba effect. We then provide a modern definition of the Mpemba effect, focusing on the theoretical frameworks of stochastic thermodynamics, kinetic theory, Markovian dynamics, and phase transitions. We discuss the recent experimental and numerical developments that followed these theoretical advances. These developments paved the way for the prediction and observation of novel phenomena, such as the inverse Mpemba effect. The review is self-contained and introduces anomalous relaxation phenomena in single- and many-body systems, both classical and quantum. We also discuss the broader relevance of the Mpemba effect, including its relation with phase transitions and its experimental implications. We end with perspectives that connect anomalous speedups to ideas for designing optimal heating/cooling protocols, heat engines, and efficient samplers.

Integrating mirrors with magnetic components is crucial for constructing chiral optical cavities, which provide tunable platforms for time-reversal-asymmetric light-matter interactions. Here, we introduce single-crystal circular-polarization-selective mirrors based on chiral superconductors, which break time-reversal symmetry by themselves eliminating the need for additional components. We show that a circular-polarization-selective perfect reflection (CSPR) occurs for strong-coupling superconductors in the BCS-BEC crossover regime or beyond if the optical Hall conductivity is significant in the unit of conductivity quantum per unit layer, $e^2/ha_z$, where $a_z$ is the lattice constant along the surface normal. While the optical Hall conductivity in chiral superconductors is typically tiny, we classify three routes to obtain a large value. We demonstrate the significant optical Hall conductivity and the resulting CSPR with two examples: (1) superconductivity in doped quantum Hall insulators and (2) chiral pairing that preserves the Bogoliubov Fermi surfaces in the weak-pairing limit. We also discuss the application of our theory to the recently discovered chiral superconducting phase in rhombohedral graphene. Our theory reveals the potential of these classes of chiral superconductors as promising elements for building high-quality-factor terahertz chiral cavities.

CrSBr, a van der Waals material, stands out as an air-stable magnetic semiconductor with appealing intrinsic properties such as crystalline anisotropy, quasi-1D electronic characteristics, layer-dependent antiferromagnetism, and non-linear optical effects. In this study, we investigate the differences between the absorption and emission spectra, focusing on the origin of the emission peak near 1.7 eV observed in the photoluminescence spectrum of CrSBr. Our findings are corroborated by excitation-dependent Raman experiments. Additionally, we explore the anti-Stokes Raman spectra and observe an anomalously high anti-Stokes to Stokes intensity ratio of up to 0.8, which varies significantly with excitation laser power and crystallographic orientation relative to the polarization of the scattered light. This ratio is notably higher than that observed in graphene ($\approx$ 0.1) and MoS$_2$ ($\approx$ 0.4), highlighting the unique vibrational and electronic interactions in CrSBr. Lastly, we examine stimulated Raman scattering and calculate the Raman gain in CrSBr, which attains a value of 1 $\times$ 10$^{8}$ cm/GW, nearly four orders of magnitude higher than that of previously studied three-dimensional systems.

Understanding the behavior of materials under irradiation is crucial for the design and safety of nuclear reactors, spacecraft, and other radiation environments. The threshold displacement energy (Ed) is a critical parameter for understanding radiation damage in materials, yet its determination often relies on costly experiments or simulations. This work leverages the machine learning-based Sure Independence Screening and Sparsifying Operator (SISSO) method to derive accurate, analytical models for predicting Ed using fundamental material properties. The models outperform traditional approaches for monoatomic materials, capturing key trends with high accuracy. While predictions for polyatomic materials highlight challenges due to dataset complexity, they reveal opportunities for improvement with expanded data. This study identifies cohesive energy and melting temperature as key factors influencing Ed, offering a robust framework for efficient, data-driven predictions of radiation damage in diverse materials.

Ferromagnetism (FM) and superconductivity (SC) are two of the most famous macroscopic quantum phenomena. However, nature normally does not allow SC and FM to coexist without significant degradation. Here, we introduce the first fully iron-based SC/FM heterostructures, composed of Fe(Te,Se) and Fe3GeTe2, and show that in this platform strong FM and high-temperature SC robustly coexist. We subsequently discover that chemical proximity effect from neighboring layers can universally drive the otherwise non-superconducting FeTe films into a SC state. This suggests that the ground state of FeTe is so close to the SC state that it could be driven in and out of the SC state with various other perturbations. Altogether, this shows that Fe-Te-based heterostructures provide a unique opportunity to manipulate magnetism, superconductivity and topological physics, paving the way toward new superconducting technologies.

We study the competition between the RKKY quadratic and biquadratic spin-spin interactions of two magnetic impurities in twisted bilayer graphene away from the magic angle. We apply the Bistritzer-MacDonald model of two graphene layers twisted with respect to each other by a small angle. By reducing the model to the Dirac-type one with modified Fermi velocity, we derive expressions for the RKKY quadratic and biquadratic spin interactions using perturbation theory for the free energy. The biquadratic interaction is suppressed by a larger power of the interaction constant and decreases faster with a the distance between impurities comparing to the quadratic one. Nevertheless, due to the different period of oscillations with impurity separation distance, chemical potential, twist angle and temperature, it is possible to fine-tune the system to the regime of dominating biquadratic interaction. Such a regime might be characterized by non-conventional spin order parameters such as quadrupole order.

We report the magnetic and magnetotransport properties with electronic band structure calculation of the Bi square net system PrAgBi$_2$. The magnetization and heat capacity data confirm the presence of a crystalline electric field (CEF) effect in PrAgBi$_2$. Analysis of the CEF effect using a multilevel energy scheme reveals that the ground state of PrAgBi$_2$ consists of five singlets and two doublets. The de Haas-van Alphen (dHvA) quantum oscillations data show a single frequency with a very small cyclotron effective mass of approximately 0.11 $m_e$. A nontrivial Berry phase is also observed from the quantum oscillations data. The magnetotransport data shows linear and unsaturated magnetoresistance, reaching up to 1060\% at 2 K and 9 T. Notably, there is a crossover from a weak-field quadratic dependence to a high-field linear dependence in the field-dependent magnetoresistance data. The crossover critical field $B^*$ follows the quadratic temperature dependence, indicating the existence of Dirac fermions. The band structure calculation shows several Dirac-like linear band dispersions near the Fermi level and a Dirac point close to the Fermi level, located at the Brillouin zone boundary. \textit{Ab inito} calculations allowed us to ascribe the observed dHvA oscillation frequency to a particular feature of the Fermi surface. Our study suggests layered PrAgBi$_2$ is a plausible candidate for hosting the CEF effect and Dirac fermion in the Bi square net.

In light of breakthroughs in superconductivity under high pressure, and considering that record critical temperatures (T$_c$s) across various systems have been achieved under high pressure, the primary challenge for higher Tc should no longer solely be to increase T$_c$ under extreme conditions but also to reduce, or ideally eliminate, the need for applied pressure in retaining pressure-induced or -enhanced superconductivity. The topological semiconductor Bi$_{0.5}$Sb$_{1.5}$Te$_3$ (BST) was chosen to demonstrate our approach to addressing this challenge and exploring its intriguing physics. Under pressures up to ~ 50 GPa, three superconducting phases (BST-I, -II, and -III) were observed. A superconducting phase in BST-I appears at ~ 4 GPa, without a structural transition, suggesting the possible topological nature of this phase. Using the pressure-quench protocol (PQP) recently developed by us, we successfully retained this pressure-induced phase at ambient pressure and revealed the bulk nature of the state. Significantly, this demonstrates recovery of a pressure-quenched sample from a diamond anvil cell at room temperature with the pressure-induced phase retained at ambient pressure. Other superconducting phases were retained in BST-II and -III at ambient pressure and subjected to thermal and temporal stability testing. Superconductivity was also found in BST with T$_c$ up to 10.2 K, the record for this compound series. While PQP maintains superconducting phases in BST at ambient pressure, both depressurization and PQP enhance its T$_c$, possibly due to microstructures formed during these processes, offering an added avenue to raise T$_c$. These findings are supported by our density-functional theory calculations.

Transition metal oxides are a platform for exploring strain-engineered intriguing physical properties and developing spintronic or flexible electronic functionalities owing to strong coupling of spin, charge and lattice degrees of freedom. In this study, we exemplify the strain-engineered magnetism of La$_{2/3}$Sr$_{1/3}$MnO$_3$ in freestanding and rippled membrane forms without and with process-induced strain, respectively, prepared by epitaxial lift-off technique. We find that the deposition of Pt/Ti stressor suppresses the crack formation in the lift-off process and induces a ripple structure in the La$_{2/3}$Sr$_{1/3}$MnO$_3$ membrane. Laser micrograph and Raman spectroscopy show a ripple period of about 30 um and a height of a few um, where alternating convex and concave structures are subjected to tensile strain of 0.6% and compressive strain of 0.5%, respectively. While the freestanding La$_{2/3}$Sr$_{1/3}$MnO$_3$ membrane exhibits room-temperature ferromagnetism, the macroscopic magnetic transition temperature (TC) of the rippled membrane is reduced by as large as 27%. Temperature-variable Kerr microscopy observation in the rippled membrane reveals that the spatial variation of TC to be approximately 4% of the macroscopic TC, which coincides with the local strains at convex and concave structures. The large reduction of macroscopic TC in the rippled membrane may be ascribed to the lattice disorders due to strain gradient. Our demonstration of tuning ferromagnetism by the ripple structure validates the high potential of the process-induced strain in epitaxial lift-off technique and paves the way for strain-mediated emerging physical properties in various transition metal oxides.

We phenomenologically formulate and experimentally observe an adiabatic transverse thermoelectric conversion enhanced by a heat current re-orientation in artificially tilted multilayers (ATMLs). By alternately stacking two materials with different thermal conductivities and rotating its multilayered structure with respect to a longitudinal temperature gradient, off-diagonal components in the thermal conductivity tensor are induced. This off-diagonal thermal conduction (ODTC) generates a finite transverse temperature gradient and Seebeck-effect-induced thermopower in the adiabatic condition, which is superposed on the isothermal transverse thermopower driven by the off-diagonal Seebeck effect (ODSE). In this study, we calculate and observe the two-dimensional temperature distribution and the resultant transverse thermopower in ATMLs comprising thermoelectric Co$_{2}$MnGa Heusler alloys and Bi$_{2-a}$Sb$_{a}$Te$_{3}$ compounds. By changing the tilt angle from 0{\deg} to 90{\deg}, the transverse temperature gradient obviously appeared in the middle angles and the transverse thermopower increases up to -116.1 ${\mu}$V/K in Co$_{2}$MnGa/Bi$_{0.2}$Sb$_{1.8}$Te$_{3}$-based ATML at the tilt angle of 45{\deg} whereas the isothermal contribution is estimated to be -82.6 ${\mu}$V/K from the analytical calculation. This hybrid action derived from ODTC results in the significant variation of the maximum reduced efficiency for transverse thermoelectric conversion from 3.1% in the isothermal limit to 8.1% in the adiabatic limit.

We report high-pressure Raman spectra and resistance measurements of black arsenic (b-As) up to 58 GPa, along with phonon density of states (DOS) and enthalpy calculations for four reported arsenic phases up to 50 GPa. It is found that metastable b-As transforms into gray arsenic (g-As) phase at a critical pressure of 1.51 GPa, followed by subsequent transitions to simple cubic arsenic (c-As) and incommensurate host-guest arsenic (hg-As) phases at 25.9 and 44.8 GPa, respectively. Superconductivity emerges above 25 GPa in the c-As phase, with the superconducting transition temperature ($T$$\rm_c$) remaining nearly a constant of 3 K. Upon further compression, $T$$\rm_c$ steeply increases to a higher value around 4.5 K in the incommensurate hg-As phase above 43 GPa. We use our results to update the structural and superconducting phase diagrams under pressure for the novel semiconductor, black arsenic.

Conformal field theory underlies critical ground states of quantum many-body systems. While conventional conformal field theory is associated with positive central charges, nonunitary conformal field theory with complex-valued central charges has recently been recognized as physically relevant. Here, we demonstrate that complex-valued entanglement entropy characterizes complex conformal field theory and critical phenomena of open quantum many-body systems. This is based on non-Hermitian reduced density matrices constructed from the combination of right and left ground states. Applying the density matrix renormalization group to non-Hermitian systems, we numerically calculate the complex entanglement entropy of the non-Hermitian five-state Potts model, thereby confirming the scaling behavior predicted by complex conformal field theory.

We report electron transport studies of a (001) GdN film grown on the square net presented by the (001) surface of LaAlO3, motivated by recent advances in epitaxial thin-film growth of several lanthanide nitrides. The film we have grown for the purpose is characterised by in-situ RHEED and ex-situ XRD and XRR to show the best crystallinity and smoothest surfaces we have accomplished to date. It shows a clear ferromagnetic transition at $\sim70$ K with a saturation magnetisation within uncertainly of 7 $\mu$B/Gd$^{3+}$ ion, a remanence of 5 $\mu$B/Gd$^{3+}$ ion and a coercive field of $\sim$5 mT. It is doped by $\sim1$% nitrogen vacancies that introduce $\sim3\times10^{20}$ cm$^{-3}$ electrons into the conduction band. The resistivity shows transport in a conduction band doped to degeneracy by $\sim0.01$ electrons/formula unit with a residual resistance ratio of 2 and a Hall resistivity permitting easily-separated ordinary and anomalous Hall components. The mobility is an order of magnitude larger than we have found in earlier films.

Widefield magnetic imaging using ensembles of nitrogen-vacancy (NV) centres in diamond has emerged as a useful technique for studying the microscopic magnetic properties of materials. Thus far, this technique has mainly been implemented on custom-made optical microscopes. We have developed an add-on for a standard laboratory optical microscope that integrates the NV-diamond sensor and necessary light source, microwave antenna, and bias magnet, enabling NV-based magnetic imaging while retaining the typical optical measurements modes of the microscope. We demonstrate our retrofitted quantum diamond microscope by imaging a magnetic particle sample using brightfield, darkfield, and magnetic imaging modes. Furthermore, we employ an iso-magnetic field imaging technique to visualise the magnetic field of the sample within seconds, and finally demonstrate three-dimensional stray field imaging. Retrofitting existing microscopes exploits the stability and high quality of traditional optical microscope systems while reducing the cost and space requirements of establishing a standalone magnetic imaging system.

Flat-band Majorana bound states of nodal $p$-wave superconductors give rise to striking electromagnetic anomalies, reflecting their high degree of degeneracy at the Fermi level. However, experimental investigations of these states have been hindered by the scarcity of materials exhibiting intrinsic $p$-wave superconductivity. In this Letter, we show that Majorana flat bands can emerge in a hybrid system consisting of a conventional superconductor and a $p$-wave magnet, a recently proposed class of unconventional magnets that possess a unique composite symmetry known as the $[C_{2\perp}||\boldsymbol{t}]$ symmetry. The degeneracy of the flat-band Majorana bound states is protected by chiral symmetry from the BDI symmetry class, which originates from the $[C_{2\perp}||\boldsymbol{t}]$ symmetry of the $p$-wave magnet. Furthermore, we predict the robust appearance of a zero-bias conductance peak in a dirty normal-metal--superconductor junction containing a $p$-wave magnet, which serves as an unambiguous signature of anomalous proximity effects associated with the Majorana flat bands.

Atomic displacement parameters (ADPs) are crystallographic information that describe the statistical distribution of atoms around an atom site. Direct derivation of anisotropic ADPs by atom from molecular dynamics (MD) simulations, where the (co)valences of atom positions are taken over recordings at different time steps in a single MD simulation, was demonstrated on three thermoelectric materials, Ag8SnSe6, Na2In2Sn4, and BaCu1.14In0.86P2. Unlike the very frequently used lattice dynamics approach, the MD approach can obtain ADPs in disordered crystals and at finite temperature, but not under conditions where atoms migrate in the crystal. ADPs from MD simulations would act as a tool complementing experimental efforts to understand the crystal structure including the distribution of atoms around atom sites.

The emerging field of valleytronics harnesses the valley degree of freedom of electrons, akin to how electronic and spintronic devices utilize the charge and spin degrees of freedom of electrons respectively. The engineering of valleytronic devices typically relies on the coupling between valley and other degrees of freedom such as spin, giving rise to valley-spintronics where an external magnetic field manipulates the information stored in valleys. Here, the valley gapless semiconductor is proposed as a potential electrically controlled valleytronic platform because the valley degree of freedom is coupled to the carrier type, i.e., electrons and holes. The valley degree of freedom can be electrically controlled by tuning the carrier type via the device gate voltage. We demonstrate the proposal for realizing a valley gapless semiconductor in the honeycomb lattice with the Haldane and modified Haldane models. The system's valley-carrier coupling is further studied for its transport properties in an all-electrically controlled valley filter device setting. Our work highlights the significance of the valley gapless semiconductor for valleytronic devices.

The contact issue for two-dimensional (2D) materials-based field-effect transistors (FETs) has drawn enormous attention in recent years. Although ohmic behavior is achieved at room temperature, the drain current of 2DFETs shifts from ohmic to non-ohmic behavior at cryogenic temperatures. In this work, we demonstrate that the shift is attributed to the asymmetric current reduction at the metal-semiconductor contact at low temperature. Under low drain bias, carriers tunnel from the source to the channel but diffuse to the drain side due to the channel-to-drain barrier, resulting in the current suppression. By studying the property of ohmic metal-semiconductor contact at different temperatures, we analyzed the mechanisms behind this phenomenon and the dependence on metal-to-semiconductor barrier height. The work opens the semiconductor physics of 2D material contact at cryogenic temperature and the importance of contact metal selection in the development of 2DFET at cryogenic temperature.

The magnetoresistance of superconductor-topological insulator-superconductor structures, with indium as the superconductor and TaSe$_3$ as the topological insulator, shows stepwise resistance dependencies on an applied magnetic field. These resistance steps result from the suppression of superconductivity, induced by the proximity effect in both the bulk and surface states of the topological insulator. The position and amplitude of the steps, occurring at approximately 0.1 T, exhibit unusual dependence on the magnitude of uniaxial strain $\epsilon$. This behavior follows the expected transition sequence: semi-metal -- strong topological insulator -- trivial dielectric and proves the appearance of the surface states at $0.46\% \lesssim \epsilon \lesssim 1\%$.

Stoichiometric SiNx layers (x = [N]/[Si] = 1.33) are doped with Si atoms by ultra-low energy ion implantation (ULE-II) and subsequently annealed at different temperatures in inert ambient conditions. Detailed material and memory cells characterization is performed to investigate the effect of Si dopants on the switching properties and performance of the fabricated resistive memory cells. In this context extensive dc current-voltage and impedance spectroscopy measurements are carried out systematically and the role of doping in dielectric properties of the nitride films is enlightened. The dc and ac conduction mechanisms are investigated in a comprehensive way. Room temperature retention characteristics of resistive states are also presented.

The molecular dynamics of deep eutectic solvents (DESs) are complex, characterized by nanoscale spatial and temporal heterogeneity. Understanding these dynamics is crucial for tailoring transport properties like diffusion, viscosity and ionic conductivity. Molecular diffusion in DESs stems from transient caging and translation jumps, necessitating an understanding of how molecular structure regulates these processes. This study explores the influence of alkyl chain length on the nanoscopic dynamics of alkylamide-lithium perchlorate based DESs using quasielastic neutron scattering (QENS) and molecular dynamics (MD) simulations. QENS results show that, despite its shorter chain length and lighter mass, acetamide (ACM) exhibited the lowest mobility among the alkylamides, including propanamide (PRM) and butyramide (BUT). Detailed analysis of QENS data reveals that long-range jump diffusion is fastest in ACM and slowest in BUT, essentially due to their differences in molecular size, mass and also enhanced complexation in longer alkyl chain molecules. However, the localized dynamics follows an unusual trend, where PRM is the fastest and ACM is the slowest. Despite greater flexibility in BUT, the slower caged dynamics impedes its localized motion. These findings highlight the interplay between alkyl chain length and DES dynamics, emphasizing role of molecular structure in governing transport properties.

The interplay between electronic correlations, density wave orders, and magnetism gives rise to several fascinating phenomena. In recent years, kagome metals have emerged as an excellent platform for investigating these unique properties, which stem from their itinerant carriers arranged in a kagome lattice. Here, we show that electronic structure of the prototypical kagome metal, Fe$_3$Sn$_2$, can be tailored by manipulating the breathing distortion of its kagome lattice with external pressure. The breathing distortion is suppressed around 15 GPa and reversed at higher pressures. These changes lead to a series of Lifshitz transitions that we detect using broadband and transient optical spectroscopy. Remarkably, the strength of the electronic correlations and the tendency to carrier localization are enhanced as the kagome network becomes more regular, suggesting that breathing distortion can be a unique control parameter for the microscopic regime of the kagome metals and their electron dynamics.

Sliding ferroelectricity, which is a unique polarity recently discovered in bilayer van der Waals materials, achieves polarization switching through in-plane interlayer sliding. The unique mechanism, combining intralayer stiffness and interlayer slipperiness, leads to wider domain walls (DWs) and faster DW motion compared to conventional ferroelectrics. Herein, using machine-learning-assisted molecular dynamics simulations and field theory analysis, we find the DW in classical sliding ferroelectric bilayer 3R-MoS2 system exhibits uniformly accelerated motion under an external field, like the Newtonian particle with undamped motion. Remarkably, DW velocity remains constant even after the external field removal, completely deviating from the velocity breakdown observed in conventional ferroelectrics. We further propose an experimental approach to validate this undamped soliton-like DW behavior in sliding ferroelectric systems.

It is well-known that a thin sheet held in a rigid circular clamp has a larger flexural strength than when it is flat. Here, we report that the flexural strength of curved sheets is further increased with a softening of the clamping condition. This unexpected compliance effect relates to the geometrical properties of curvature-induced rigidity that we observe in controlled experiments and further analyze with numerical simulations. In addition, we identify another compliance effect in which opened curved sheets can be more resistant to bending than closed cylinders of same dimensions.

Potassium tantalate KTaO3 is a cubic, paraelectric perovskite ceramic that exhibits surprising ductility at room temperature as most recently reported. Much like strontium titanate (SrTiO3), plastic deformation is accommodated by dislocations gliding in {110} planes. In this work we propose a new interatomic potential for KTaO3, and apply it to model dislocations with <110> Burgers vector. We demonstrate that dislocations dissociate, and finely characterize their core structure and Peierls potential. Dislocations of edge character can carry a positive or negative electric charge, but we show that charge-neutral configurations are energetically more favorable. We also perform high-resolution electron microscopy to validate our simulation methodology. Comparing our results with other ductile perovskites, we confirm KTaO3 to be ductile, but stiffer than SrTiO3.

We study the effects of finite voltage bias on Caroli-de Gennes-Matricon (CdGM) states in topological Josephson junctions with a vortex lattice. The voltage drives vortices into steady motion, squeezing the CdGM spectrum due to quasi-relativistic dispersion. A finite voltage range allows well-defined states, but beyond a critical breakdown voltage, the states collapse to zero energy and become sharply localized, marking a dynamical transition. Additionally, finite bias modifies selection rules for CdGM state transitions. Notably, in the steady-state regime, the time-averaged current vanishes, revealing a novel interplay between vortex dynamics and quantum coherence.

In this study, the crystal structure and magnetic properties of La$_{2-x} A'_{x}$Ni$_{7}$ compounds with magnetic rare earth elements ($A$' = Sm, Gd) have been investigated combining X-ray powder diffraction and magnetic measurements. These intergrowth compounds crystallize in a mixture of 2$H$ hexagonal (Ce$_{2}$Ni$_{7}$-type) and 3$R$ rhombohedral (Gd$_{2}$Co$_{7}$-type) polymorphic structures which are related to the stacking of [$AB_{5}$] and [$A_{2}B_{4}$] subunits along the $c$-axis.The average cell volume decreases linearly versus $A$' content, whereas the $c/a$ ratio reaches a minimum at $x$ = 1, due to geometric constraints upon $A$' for La substitution between the two different subunits. The magnetic properties strongly depend on the structure type and the $A$' content. Hexagonal La$_{2}$Ni$_{7}$ is a weak antiferromagnet (wAFM) at low field and temperature and undergoes metamagnetic transitions towards weak ferromagnetic state (wFM) under applied field. Under an applied field of 0.1 T, La$_{2-x}A'_{x}$Ni$_{7}$ intermetallic compounds display two different transition temperatures $T_{1}$ and $T_{2}$ that both increase with $x$. $T_{1}$ is associated with a wFM-wAFM transition in the 2$H$ phase for $A$'= Sm, whereas $T_{2}$ is related to the Curie temperature of both 2$H$ and 3$R$ phases. A metamagnetic behaviour is observed between $T_{1}$ and $T_{2}$ with transition field $\mu_{0}H_{Trans}$ between 2 and 3.5 T for compounds with $A$' = Sm. The La$_{2-x}Sm_{x}$Ni$_{7}$ compounds ($x$ > 0} behave as hard magnets with a large coercive field $\mu_{0}H_{C}$ at low temperature ($\mu_{0}H_{C}$ > 9 T at 5 K for $x$ = 2), whereas the La$_{2-x} Gd_{x}$Ni$_{7}$ compounds ($x$ > 0) are soft ferrimagnets with a linear increase of the saturation magnetization versus Gd content.

In this letter, we report the structural, electronic and ferroelectric properties of the layered mixed-valent transition-metal compound, Sr$_{4}$Fe$_{6}$O$_{12}$ (SFO). We demonstrate how SFO undergoes a phase transition from a high-temperature (T) centrosymmetric tetragonal phase ($P4_{2}/mnm$) to a low-T polar orthorhombic phase ($Pmn2_{1}$). The transition is primarily driven by charge ordering at tetrahedral Fe-layer creating Fe$^{3+}$ and Fe$^{2+}$ cations between two edge sharing tetrahedra. This charge ordering induces electronic polarization, which is remarkably larger (3.5 times) in magnitude than ionic polarization and oppositely directed, giving a net polarization of 0.05 C/m$^2$ which is comparable to the state-of-the-art rare-earth nickelets and manganite perovskites. The direction of structural distortion, governed by the polar mode irrep $\Gamma_{5}^{-}$, depends sensitively on the type of magnetic ordering in the Fe-octahedral layer. Consequently, both the ionic and electronic polarization directions are influenced by magnetic ordering, suggesting the potential for multiferroic behavior with strong magneto-electric coupling in this material.

CrSb has recently gained immense attention as an altermagnetic candidate. This work reports on the experimental observation of direction-dependent conduction polarity (DDCP) in altermagnetic CrSb through Hall and Seebeck thermopower measurements. Conduction is dominated by holes along the c-axis and by electrons in the ab-plane of the hexagonal crystal of CrSb. Density functional theory (DFT) calculations indicate that DDCP in CrSb arises from a multicarrier mechanism, where electrons and holes living in distinct bands dominate conduction along different crystallographic directions. Furthermore, DFT predicts that DDCP exists within a narrow energy window near the Fermi level and is sensitive to small doping levels. This prediction is experimentally validated by the loss of DDCP in hole-doped Cr$_{0.98}$V$_{0.02}$Sb. These findings highlight the potential for tunable electronic behavior in CrSb, offering promising avenues for applications in devices that require both p-type and n-type functionalities within a single material.

Heat-assisted magnetic recording (HAMR) is a recent advancement in magnetic recording, allowing to significantly increase the areal density capability (ADC) of hard disk drives (HDDs) compared to the perpendicular magnetic recording (PMR) technology. This is enabled by high anisotropy FePt media, which needs to be heated through its Curie temperature ($T_C$) to facilitate magnetization reversal by an electromagnetic write pole. HAMR micromagnetic modeling is therefore challenging, as it needs to be performed in proximity to and above $T_C$, where a ferromagnet has no spontaneous magnetization. An atomistic model is an optimal solution here, as it doesn't require any parameter renormalization or non-physical assumptions for modeling at any temperature. However, a full track atomistic recording model is extremely computationally expensive. Here we demonstrate a true multiscale HAMR modeling approach, combining atomistic spin dynamics modeling for high temperature regions and micromagnetic modeling for lower temperature regions, in a moving simulation window embedded within a long magnetic track. The advantages of this approach include natural emergence of $T_C$ and anisotropy distributions of FePt grains. Efficient GPU optimization of the code provides very fast running times, with a 60~nm wide track of twenty-five 20~nm - long bits being recorded in several hours on a single GPU. The effects of realistic FePt L$_{10}$ vs simple cubic crystal structure is discussed, with the latter providing further running time gains while keeping the advantages of the multiscale approach.

The use of advanced X-ray sources plays a key role in the study of dynamic processes in magnetically ordered materials. The progress in X-ray free electron lasers enables the direct and simultaneous observation of the femtosecond evolution of electron and spin systems through transient X-ray absorption spectroscopy (XAS) and X-ray magnetic circular dichroism (XMCD), respectively. Such experiments allow us to resolve the response seen in the population of the spin-split valence states upon optical excitation. Here, we utilize circularly polarized ultrashort soft X-ray pulses from the new helical afterburner undulator at the free-electron laser FLASH in Hamburg to study the femtosecond dynamics of a laser-excited CoPt alloy at the Co $L_{3}$ absorption edge. Despite employing a weaker electronic excitation level we find a comparable demagnetization for the Co $3d$-states in CoPt compared to previous measurements on CoPd. This is attributed to distinctly different orbital hybridization and spin-orbit coupling between $3d$ and $4d$ vs. $3d$ and $5d$ elements in the corresponding alloys and multilayers.

Synchronization among a group of active agents is ubiquitous in nature. Although synchronization based on direct interactions between agents described by the Kuramoto model is well understood, the other general mechanism based on indirect interactions among agents sharing limited resources are less known. Here, we propose a minimal thermodynamically consistent model for the altruistic resource-sharing (ARS) mechanism wherein resources are needed for individual agent to advance but a more advanced agent has a lower competence to obtain resources. We show that while differential competence in ARS mechanism provides a negative feedback leading to synchronization it also breaks detailed balance and thus requires additional energy dissipation besides the cost of driving individual agents. By solving the model analytically, our study reveals a general tradeoff relation between the total energy dissipation rate and the two key performance measures of the system: average speed and synchronization accuracy. For a fixed dissipation rate, there is a distinct speed-accuracy Pareto front traversed by the scarcity of resources: scarcer resources lead to slower speed but more accurate synchronization. Increasing energy dissipation eases this tradeoff by pushing the speed-accuracy Pareto front outwards. The connections of our work to realistic biological systems such as the KaiABC system in cyanobacterial circadian clock and other theoretical results based on thermodynamic uncertainty relation are also discussed.

The layered structure of LiPdH was theoretically suggested to be a superconductor as a result of its larger electron-phonon coupling constant compared to that of PdH. However, the experimental results reported contrary findings, with no trace of superconductivity. We study the electronic, vibrational, and superconducting properties of the ambient pressure tetragonal phase of LiPdH ($P4/mmm$) within first principles density functional theory methods, both in the harmonic and anharmonic approximations for the lattice dynamics, and conclude that it does not show any superconducting behavior. High-pressure crystal structure prediction calculations indicate that no structural transition is expected to occur under pressure up to 100 GPa in LiPdH. Our theoretical calculations demonstrate that increasing pressure reduces the density of states at the Fermi surface and consequently weakens electron-phonon interactions, leading to a further suppression of the superconducting critical temperature.

Physical reservoir computing has emerged as a powerful framework for exploiting the inherent nonlinear dynamics of physical systems to perform computational tasks. Recently, we presented the magnon-scattering reservoir, whose internal nodes are given by the fundamental wave-like excitations of ferromagnets called magnons. These excitations can be geometrically-quantized and, in response to an external stimulus, show transient nonlinear scattering dynamics that can be harnessed to perform memory and nonlinear transformation tasks. Here, we test a magnon-scattering reservoir in a single magnetic disk in the vortex state towards two key performance indicators for physical reservoir computing, the short-term memory and parity-check tasks. Using time-resolved Brillouin-light-scattering microscopy, we measure the evolution of the reservoir's spectral response to an input sequence consisting of random binary inputs encoded in microwave pulses with two distinct frequencies. Two different output spaces of the reservoir are defined, one based on the time-averaged frequency spectra and another based on temporal multiplexing. Our results demonstrate that the memory and nonlinear transformation capability do not depend on the chosen read-out scheme as long as the dimension of the output space is large enough to capture all nonlinear features provided by the magnon-magnon interactions. This further shows that solely the nonlinear magnons in the physical system, not the read-out, determine the reservoir's capacity.

The quest for efficient and sustainable green energy solutions has led to a growing interest in half Heusler alloys, particularly for thermoelectric and spintronic applications. This study investigates the multifaceted nature of cobalt based half Heusler alloy, CoVAs, employing DFT with advanced computational techniques, such as the FLAPW method. The elastic, electronic, magnetic, thermodynamic, and optical properties of CoVAs are meticulously analyzed. Structural and mechanical evaluations reveal mechanical stability and brittleness under varying pressures. Electronic and magnetic properties are examined through band structure and DOS analysis, revealing a half metallic nature with a minority spin band gap. The total magnetic moment aligns with the Slater Pauling rule, further confirming ferromagnetism and half metallicity. Thermodynamic investigations, based on the quasi-harmonic Debye approximation, provide insights into temperature- and pressure dependent behavior, including thermal expansion, heat capacity, and Debye temperature, establishing CoVAs as a viable candidate for high temperature applications. Additionally, the optical properties underestimate its potential in optoelectronic applications due to high absorption in the UV region, showing a distinct absorption edge corresponding to the electronic band gap. Phonon dispersion relations reflect the stability of the alloy, and the figure of merit confirms the alloy's suitability for thermodynamics applications. The findings highlight the potential of CoVAs as a promising candidate for spintronic photovoltaic and optoelectronic applications, providing insights into its fundamental properties that could facilitate experimental synthesis and industrial implementation for green energy and advanced technological applications.

Granular materials, composed of discrete solid grains, can be modeled as simple mechanical systems. However, these materials can undergo spontaneous slow deformation, or creep, even under small forces and while in apparent mechanical equilibrium; a phenomenon central to understanding soil mechanics and the behavior of earthquake faults. We show that creep in granular materials originates from frictional dynamics at the contact points between grains. We reveal that the stability of these materials is governed by the interplay between creep and aging at these frictional contacts. Near the yield threshold, the frictional interactions result in anomalously accelerating creep, eventually leading to the delayed failure of the fragile packing. This behavior may serve as an early warning signal for catastrophic events like earthquakes and landslides.

Research has demonstrated that zeolite nucleation and growth can be controlled by fine-tuning chemical composition, temperature, and pressure, resulting in structures with diverse porosities and functionalities. Nevertheless, current energy delivery methods lack the finesse required to operate on the femto- and picosecond timescales of silica polymerisation and depolymerisation, limiting their ability to direct synthesis with high precision. To overcome this limitation, we introduce an ultrafast laser synthesis technique capable of delivering energy at these timescales with unprecedented spatiotemporal precision. Unlike conventional or emerging approaches, this method bypasses the need for specific temperature and pressure settings, as nucleation and growth are governed by dynamic phenomena arising from nonlinear light-matter interactions, such as convective flows, cavitation bubbles, plasma formation, and shock waves. These processes can be initiated, paused, and resumed within fractions of a second, effectively freezing structures at any stage of self-assembly. Using this approach, we traced the entire nucleation and growth pathway of laser-synthesized TPA-silicate-1 zeolites, from early oligomer formation to fully developed crystals. The unprecedented spatiotemporal control of this technique unlocks new avenues for manipulating reaction pathways and exploring the vast configurational space of zeolites.

This work explores spin filtration in a helical magnetic system within a tight-binding framework, where neighboring magnetic moments are aligned antiparallel. The helix experiences a slowly-varying diagonal disorder, following a cosine form, which creates a finite energy mismatch between up and down spin channels. Unlike earlier studies that relied on external electric fields, this investigation demonstrates that disorder alone can achieve high spin filtration, even at low bias and high temperatures. Higher-order electron hopping in the helix leads to a non-uniform energy level distribution, facilitating favorable spin filtration, sometimes reaching $100\%$. The interplay between higher-order hopping and atypical disorder may enable selective spin transmission through various antiferromagnetic helices, potentially opening new avenues for functional elements.

The flow of dry granular materials from silos is of great practical interest in industry and of theoretical import for understanding multiphase dynamics. Recent studies have demonstrated that one way to control the rate of flow from a silo is to tilt it. However, this may not be practical in many industrial applications. Here, we demonstrate in experiments of quasi-2D silo discharge of monodisperse grains that the flow rate can be modulated by rotating the orifice - through elevating and shifting one side of the base - instead of tilting the entire silo. We use high-speed image analysis to track the average motion of grains in the silo. We first show that the flow rate decreases with orifice angle, but that this decrease is not as strong as when a silo is tilted or when a lateral orifice is used. However, with the addition of a grain-sized ridge on each side of the orifice, the flow rate collapses with prior tilted-silo results. We then characterize the flow velocity of grains exiting the orifice and highlight key features of the stagnant zones and slip zones on each orifice side. Finally, we model our results based on these measurements, demonstrating the importance of horizontal creep along slip zones next to the orifice and the narrowest opening cross-section through which the material flows. These findings reveal a simple method for controlling both flow rate and direction, and highlight the importance of both dynamics within and geometry of the stagnant zones near the orifice.

The family of topological superconductors derived from $\mathrm{Bi}_{2}\mathrm{Se}_{3}$, $\mathrm{Cu}_x(\mathrm{PbSe})_{5}(\mathrm{Bi}_{2}\mathrm{Se}_{3})_{6}$ is unique in its surface termination of a single quintuple layer (QL) of the topological insulator (TI) $\mathrm{Bi}_{2}\mathrm{Se}_{3}$ on an ordinary insulator PbSe. Here, we report a combined scanning tunneling microscopy (STM) and density functional theory (DFT) characterization of the cleaved surface of the parent compound $(\mathrm{PbSe})_{5}(\mathrm{Bi}_{2}\mathrm{Se}_{3})_{6}$ (PSBS). Interestingly, the potential disorder due to the random distribution of native defects is only $\Gamma \sim 4~\mathrm{meV}$, comparable to the smallest reported for TIs. Performing high-resolution quasiparticle interference imaging (QPI) near the Fermi energy ($E-E_\mathrm{F} = -1~\mathrm{eV}$ to $0.6~\mathrm{eV}$) we reconstruct the dispersion relation of the dominant spectral feature and our $\textit{ab initio}$ calculations show that this surface feature originates from two bands with Rashba-like splitting due to strong spin-orbit coupling and inversion symmetry breaking. Moreover, a small hexagonal distortion of the calculated Fermi surface is seen in the full momentum space distribution of the measured scattering data. Interestingly, the scattering pattern at lower energies transforms into a flower-like shape with suppressed intensity along the $\overline{\Gamma K}$ direction. However, this effect is not due to the forbidden backscattering in the spin-momentum locked surface state in $\mathrm{Bi}_{2}\mathrm{Se}_{3}$ but reflects the threefold symmetry of the scattering potential.

Exploring the photoinduced dynamics of chiral states offers promising avenues for advanced control of condensed matter systems. Photoinduced or photoenhanced chirality in 1T-TiSe$_{2}$ has been suggested as a fascinating platform for optical manipulation of chiral states. However, the mechanisms underlying chirality training and its interplay with the charge density wave (CDW) phase remain elusive. Here, we use time-resolved X-ray diffraction (tr-XRD) with circularly polarized pump lasers to probe the photoinduced dynamics of chirality in 1T-TiSe$_{2}$. We observe a notable ($\sim$20%) difference in CDW intensity suppression between left- and right-circularly polarized pumps. Additionally, we reveal momentum-resolved circular dichroism arising from domains of different chirality, providing a direct link between CDW and chirality. An immediate increase in CDW correlation length upon laser pumping is detected, suggesting the photoinduced expansion of chiral domains. These results both advance the potential of light-driven chirality by elucidating the mechanism driving chirality manipulation in TiSe$_2$, and they demonstrate that tr-XRD with circularly polarized pumps is an effective tool for chirality detection in condensed matter systems.

Ni/Al reactive multilayers are promising materials for applications requiring controlled local energy release and superior mechanical performance. This study systematically investigates the impact of compositional variations, ranging from 30 to 70 at.% Ni, and bilayer thicknesses (30 nm and 50 nm) on the mechanical properties and reaction dynamics of Ni/Al multilayers. Multilayers with varying Ni-to-Al ratios were fabricated and subjected to instrumented nanoindentation testing to evaluate hardness and elastic modulus. Combustion experiments, conducted on dogbone-shaped multilayers deposited onto silicon wafers with thermal barrier coatings, characterized the reaction front's speed, temperature, and the resulting phases. The findings revealed that composition variations within this range enable precise tuning of reaction speed and temperature without significant changes in mechanical properties, while deviations in modulus and hardness at higher nickel concentrations suggest microstructural influences. Notably, phase formation in Al-rich samples deviated from equilibrium predictions, highlighting the role of kinetic factors, such as diffusion and rapid quenching, in driving non-adiabatic processes during phase evolution. Molecular dynamics simulations provided complementary atomistic insights into mechanical responses and reaction kinetics, bridging experimental observations with theoretical predictions. This integrated approach advances the understanding of Ni/Al multilayers, offering a framework for optimizing their composition and structural design to achieve tailored performance for application-specific requirements.

The outstanding opto-electronic properties of lead halide perovskites have been related to the formation of polarons. Nevertheless, the observation of the atomistic deformation brought about by one electron-hole pair in these materials has remained elusive. Here, we measure the diffraction patterns of single CsPbBr$_3$ quantum dots (QDs) with and without resonant excitation in the single exciton limit using serial femtosecond crystallography (SFX). By reconstructing the 3D differential diffraction pattern, we observe small shifts of the Bragg peaks indicative of a crystal-wide deformation field. Building on DFT calculations, we show that these shifts are consistent with the lattice distortion induced by a delocalized electron and a localized hole, forming a mixed large/small exciton polaron. This result creates a clear picture of the polaronic deformation in CsPbBr$_3$ QDs, highlights the exceptional sensitivity of SFX to lattice distortions in few-nanometer crystallites, and establishes an experimental platform for future studies of electron-lattice interactions.

Two-dimensional spin-spiral magnets provide promising building blocks for van der Waals heterostructures due to their tunable spin textures and potential for novel functionalities for quantum devices. However, due to its vanishing magnetization and two-dimensional nature, it is challenging to detect the existence of its noncollinear magnetization. Here, we show that a van der Waals junction based on a spin-spiral magnet and a quantum spin Hall insulator enables obtaining signatures of noncollinear magnetization directly from electrical measurements. Our strategy exploits the sensitivity of helical states to local breaking of time-reversal symmetry, enabling the detection of local magnetic orders even in the absence of net magnetization. We show that the combination of spin-spiral order and nonmagnetic disorder gives rise to scattering in the helical channels that can be directly associated with the spiral exchange coupling and residual nonmagnetic disorder strength. Our results show how electrical transport measurement provides a method to detect spin-spiral magnets by leveraging helical states in van der Waals heterostructures.

Antiferroelectrics are valuable dielectric materials, offering promise for both high energy storage and solid-state caloric cooling applications. However, few antiferroelectrics are known or available. Therefore, it is crucial to discover or design materials showing antiferroelectric behaviour. In this study, we fabricated highly ordered lead scandium tantalate ceramics doped with calcium. From calorimetry and polarization-electric field loops, we demonstrate the effect of calcium on the thermal properties and phase transition sequences of lead scandium tantalate. We identify an antiferroelectric phase appearing at temperatures intermediate between the ferroelectric and paraelectric phases, which becomes increasingly stable as the calcium concentration increases. These findings are supported by density functional theory calculations and Raman spectroscopy. Finally, we propose a phase diagram for calcium-doped lead scandium tantalate. Our results highlight the potential of stabilizing antiferroelectricity in ferroelectric perovskite materials through A-site doping.

Tysonite structure fluorides doped with divalent cations, represented by Ce0.95Ca0.05F2.95, are a class of good F- ion conductors together with fluorite-structured compounds. Computational understanding of the F- conduction process is difficult because of the complicated interactions between three symmetrically distinct F sites and the experimentally observed change in the F diffusion mechanism slightly above room temperature, effectively making first principles molecular dynamics (FP-MD) simulations, which are often conducted well above the transition temperature, useless when analyzing behavior below the transition point. Neural network potential (NNP) MD simulations showed that the F diffusion coefficient is higher when the divalent dopant cation size is similar to the trivalent cation size. The diffusion behavior of F in different sites changes at roughly 500 K in Ce0.95Ca0.05F2.95 because only the F1 site sublattice contributes to F diffusion below this temperature but the remaining F2 and F3 sublattices becomes gradually active above this temperature. The paradox of higher diffusion coefficients in CeF3-based compounds than similar LaF3-based compounds even though the lattice parameters are larger in the latter may be caused by a shallower potential of Ce and F in CeF3 compared to the LaF3 counterparts.

The driving of vibrational motion by external electric fields is a topic of continued interest, due to the possibility of assessing new or metastable material phases with desirable properties. Here, we combine ab initio molecular dynamics within the electric-dipole approximation with machine-learning neural networks (NNs) to develop a general, efficient and accurate method to perform electric-field-driven nuclear dynamics for molecules, solids, and liquids. We train equivariant and autodifferentiable NNs for the interatomic potential and the dipole, modifying the prediction target to account for the multi-valued nature of the latter in periodic systems. We showcase the method by addressing property modifications induced by electric field interactions in a polar liquid and a polar solid from nanosecond-long molecular dynamics simulations with quantum-mechanical accuracy. For liquid water, we present a calculation of the dielectric function in the GHz to THz range and the electrofreezing transition, showing that nuclear quantum effects enhance this phenomenon. For the ferroelectric perovskite LiNbO3, we simulate the ferroelectric to paraelectric phase transition and the non-equilibrium dynamics of driven phonon modes related to the polarization switching mechanisms, showing that a full polarization switch is not achieved in the simulations.

The molecular-to-atomic liquid-liquid transition (LLT) in high-pressure hydrogen is a fundamental topic touching domains from planetary science to materials modeling. Yet, the nature of the LLT is still under debate. To resolve it, numerical simulations must cover length and time scales spanning several orders of magnitude. We overcome these size and time limitations by constructing a fast and accurate machine-learning interatomic potential (MLIP) built on the MACE neural network architecture. The MLIP is trained on Perdew-Burke-Ernzerhof (PBE) density functional calculations and uses a modified loss function correcting for an energy bias in the molecular phase. Classical and path-integral molecular dynamics driven by this MLIP show that the LLT is always supercritical above the melting temperature. The position of the corresponding Widom line agrees with previous ab initio PBE calculations, which in contrast predicted a first-order LLT. According to our calculations, the crossover line becomes a first-order transition only inside the molecular crystal region. These results call for a reconsideration of the LLT picture previously drawn.

In this contribution, we give an overview of the ELPA library and ELSI interface, which are crucial elements for large-scale electronic structure calculations in FHI-aims. ELPA is a key solver library that provides efficient solutions for both standard and generalized eigenproblems, which are central to the Kohn-Sham formalism in density functional theory (DFT). It supports CPU and GPU architectures, with full support for NVIDIA and AMD GPUs, and ongoing development for Intel GPUs. Here we also report the results of recent optimizations, leading to significant improvements in GPU performance for the generalized eigenproblem. ELSI is an open-source software interface layer that creates a well-defined connection between "user" electronic structure codes and "solver" libraries for the Kohn-Sham problem, abstracting the step between Hamilton and overlap matrices (as input to ELSI and the respective solvers) and eigenvalues and eigenvectors or density matrix solutions (as output to be passed back to the "user" electronic structure code). In addition to ELPA, ELSI supports solvers including LAPACK and MAGMA, the PEXSI and NTPoly libraries (which bypass an explicit eigenvalue solution), and several others.

Deformable boundaries are omnipresent in the habitats of swimming microorganisms, leading to intricate hydroelastic couplings. Employing a perturbation theory, valid for small deformations, we study the swimming dynamics of pushers and pullers near instantaneously deforming boundaries, endowed with a bending rigidity and surface tension. Our results reveal that pushers can both reorient away from the boundary, leading to overall hydroelastic scattering, or become trapped by the boundary, akin to the enhanced trapping found for pullers. These findings demonstrate that the complex hydroelastic interactions can generate behaviors that are in striking contrast to swimming near planar walls.

We obtain the exact full counting statistics of a cellular automaton with freely propagating vacancies and charged particles that are stochastically scattered or transmitted upon collision by identifying the problem as a colored stochastic six-vertex model with one inert color. Typical charge current fluctuation at vanishing net charge follow a one-parameter distribution that interpolated between the distribution of the charged single-file class in the limit of pure reflection and a Gaussian distribution in the limit of pure transmission.

We present an automated protocol for tuning single-electron transistors (SETs) or single-hole transistors (SHTs) to operate as precise charge sensors. Using minimal device-specific information, the protocol performs measurements to enable the selection and ranking of high-sensitivity operating points. It also characterizes key device parameters, such as dot radius and gate lever arms, through acquisition and analysis of Coulomb diamonds. Demonstration on an accumulation-mode silicon SET at 1.5 K highlights its potential in the 1-2 K range for "hot" spin qubits in scalable quantum computing systems. This approach significantly reduces the tuning time compared to manual methods, with future improvements aimed at faster runtimes and dynamic feedback for robustness to charge fluctuations.

Recent results demonstrate how deviations from equilibrium fluctuation-dissipation theorem can be quantified for active field theories by deriving exact fluctuations dissipation relations that involve the entropy production [M. K. Johnsrud and R. Golestanian, arXiv:2409.14977]. Here we develop and employ diagrammatic tools to perform perturbative calculations for a paradigmatic active field theory, the Non-Reciprocal Cahn-Hilliard (NRCH) model. We obtain analytical results, which serve as an illustration of how to implement the recently developed framework to active field theories, and help to illuminate the specific non-equilibrium characteristics of the NRCH field theory.

Oil has become a prevalent global pollutant, stimulating the research to improve the techniques to separate oil from water. Materials with special wetting properties - primarily those that repel water while attracting oil - have been proposed as suitable candidates for this task. However, one limitation in developing efficient substrates is the limited available volume for oil absorption. In this study we investigate the efficacy of disordered fractal materials in addressing this challenge, leveraging their unique wetting properties. Using a combination of a continuous model and Monte Carlo simulations, we characterize the hydrophobicity and oleophilicity of substrates created through ballistic deposition (BD). Our results demonstrate that these materials exhibit high contact angles for water, confirming their hydrophobic nature, while allowing significant oil penetration, indicative of oleophilic behavior. The available free volume within the substrates vary from $60\%$ to $90\%$ of the total volume of the substrate depending on some parameters of the BD. By combining their water and oil wetting properties with a high availability of volume, the fractal substrates analyzed in this work achieve an efficiency in separating oil from water of nearly $98\%$, which is significantly higher compared to a micro-pillared surfaces made from the same material but lacking a fractal design.

Optical properties of the short period {CdO/ZnO} superlattices grown by plasma assisted MBE were analyzed. The superlattice (SLs) structures were successfully obtained at different growth temperatures from 360 to 550 {\deg}C. Interestingly, the growth temperature of the SLs influences quality of multilayers and also optical properties of these structures. After annealing at 900{\deg}C by rapid thermal method various defect luminescence located at different energetic positions , were detected, and intensity of luminescence strongly depends on applied growth temperature.

Mechanical strain presents an effective control over symmetry-breaking phase transitions. In quantum paralelectric SrTiO3, strain can induce the ferroelectric transition via modification of local Ti potential landscape. However, brittle bulk materials can only withstand limited strain range (~0.1%). Taking advantage of nanoscopically-thin freestanding membranes, we demonstrated in-situ strain-induced reversible ferroelectric transition in a single freestanding SrTiO3 membranes. We measure the ferroelectric order by detecting the local anisotropy of the Ti 3d orbital using X-ray linear dichroism at the Ti-K pre-edge, while the strain is determined by X-ray diffraction. With reduced thickness, the SrTiO3 membranes remain elastic with >1% tensile strain cycles. A robust displacive ferroelectricity appears beyond a temperature-dependent critical strain. Interestingly, we discover a crossover from a classical ferroelectric transition to a quantum regime at low temperatures, which enhances strain-induced ferroelectricity. Our results offer a new opportunities to strain engineer functional properties in low dimensional quantum materials and provide new insights into the role of the ferroelectric fluctuations in quantum paraelectric SrTiO3.

In the span of four decades, quantum computation has evolved from an intellectual curiosity to a potentially realizable technology. Today, small-scale demonstrations have become possible for quantum algorithmic primitives on hundreds of physical qubits and proof-of-principle error-correction on a single logical qubit. Nevertheless, despite significant progress and excitement, the path toward a full-stack scalable technology is largely unknown. There are significant outstanding quantum hardware, fabrication, software architecture, and algorithmic challenges that are either unresolved or overlooked. These issues could seriously undermine the arrival of utility-scale quantum computers for the foreseeable future. Here, we provide a comprehensive review of these scaling challenges. We show how the road to scaling could be paved by adopting existing semiconductor technology to build much higher-quality qubits, employing system engineering approaches, and performing distributed quantum computation within heterogeneous high-performance computing infrastructures. These opportunities for research and development could unlock certain promising applications, in particular, efficient quantum simulation/learning of quantum data generated by natural or engineered quantum systems. To estimate the true cost of such promises, we provide a detailed resource and sensitivity analysis for classically hard quantum chemistry calculations on surface-code error-corrected quantum computers given current, target, and desired hardware specifications based on superconducting qubits, accounting for a realistic distribution of errors. Furthermore, we argue that, to tackle industry-scale classical optimization and machine learning problems in a cost-effective manner, heterogeneous quantum-probabilistic computing with custom-designed accelerators should be considered as a complementary path toward scalability.

As the next step in extraterrestrial exploration, many engineers and scientists around the country revealed their intense interest to enable multiplanetary human life, including colonizing Mars. This study proposes that architecture on Mars can be realized by a synthetic lichen system, composed of diazotrophic cyanobacteria and filamentous fungi, which produce abundant biominerals and biopolymers to bond Martian regolith into consolidated building blocks. These self-growing building blocks can be assembled into a wide range of structures. Diazotrophic cyanobacteria will 1) fix carbon dioxide and dinitrogen from the atmosphere and convert them into oxygen and organic carbon and nitrogen sources to support filamentous fungi; and 2) give rise to high concentrations of carbonate ions because of photosynthetic activities. Filamentous fungi will 1) bind metal ions onto fungal cell walls and serve as nucleation sites to promote biomineral precipitates; and 2) assist the survival and growth of cyanobacteria by providing them water, minerals, additional carbon dioxide, and protection. This report presents the major progress of the project. It has been tested and confirmed that such co-culture systems can be created, and they grow very well solely on Martian regolith simulants, air, light, and an inorganic liquid medium without any additional carbon or nitrogen sources. The cyanobacterial and fungal growth in such co-culture systems is significantly better than their axenic growth due to mutual interactions. The amounts and morphologies of the precipitated crystals vary remarkably depending on the cultivation condition.

In the large$-N$ limit, no known no-go theorem rules out thermal time crystals that spontaneously break continuous time-translation, unlike in the large volume limit. If thermal time crystals exist in holographic CFTs, they would correspond to ensemble-dominating black holes with eternally time-varying exterior geometries. We point out that recent work on a conjectured non-linear instability of slowly rotating Kerr-AdS$_4$ produced viable candidates for such states. Then we show that the existence of holographic microcanonical time crystals would imply violations of the AdS Penrose inequality (PI). We proceed to look for violations of the PI in spherical symmetry, working with Einstein-scalar gravity with the most general possible boundary conditions compatible with boundary conformal invariance. We derive a set of ODEs for maximally PI-violating initial data. Solving these numerically, we find strong evidence that in the particular case of spherical symmetry, the PI holds iff the positive mass theorem (PMT) holds. This suggests that holographic CFT$_3$ time crystals can only possibly exist at non-zero angular momentum, at least in the absence of electric charge. We also discover neutral hairy black holes in a consistent truncation of M-theory that has a PMT and boundary conditions respecting conformal invariance, disproving an existing no-hair conjecture. Finally, we show that previous PI-violating solutions by the author all existed in theories where the PMT is violated. Unfortunately, our results imply that there currently are no known examples where the PI functions as a non-trivial Swampland constraint.

Polar materials with optical phonons in the meV range are excellent candidates for both dark matter direct detection (via dark photon-mediated scattering) and light dark matter absorption. In this study, we propose, for the first time, the metal halide perovskites MAPbI$_3$, MAPbCl$_3$, and CsPbI$_3$ for these purposes. Our findings reveal that CsPbI$_3$ is the best material, significantly improving exclusion limits compared to other polar materials. For scattering, CsPbI$_3$ can probe dark matter masses down to the keV range. For absorption, it enhances sensitivity to detect dark photon masses below $\sim 10~{\rm meV}$. The only material which has so far been investigated and that could provide competitive bounds is CsI, which, however, is challenging to grow in kilogram-scale sizes due to its considerably lower stability compared to CsPbI$_3$. Moreover, CsI is isotropic while the anisotropic structure of CsPbI$_3$ enables daily modulation analysis, showing that a significant percentage of daily modulation exceeding 1% is achievable for dark matter masses below $40~{\rm keV}$.

Monitored many-body systems can exhibit a phase transition between entangling and disentangling dynamical phases by tuning the strength of measurements made on the system as it evolves. This phenomenon is called the measurement-induced phase transition (MIPT). Understanding the properties of the MIPT is a prominent challenge for both theory and experiment at the intersection of many-body physics and quantum information. Realizing the MIPT experimentally is particularly challenging due to the postselection problem, which demands a number of experimental realizations that grows exponentially with the number of measurements made during the dynamics. Proposed approaches that circumvent the postselection problem typically rely on a classical decoding process that infers the final state based on the measurement record. But the complexity of this classical process generally also grows exponentially with the system size unless the dynamics is restricted to a fine-tuned set of unitary operators. In this work we overcome these difficulties. We construct a tree-shaped quantum circuit whose nodes are Haar-random unitary operators followed by weak measurements of tunable strength. For these circuits, we show that the MIPT can be detected without postselection using only a simple classical decoding process whose complexity grows linearly with the number of qubits. Our protocol exploits the recursive structure of tree circuits, which also enables a complete theoretical description of the MIPT, including an exact solution for its critical point and scaling behavior. We experimentally realize the MIPT on Quantinuum's H1-1 trapped-ion quantum computer and show that the experimental results are precisely described by theory. Our results close the gap between analytical theory and postselection-free experimental observation of the MIPT.

Grokking typically achieves similar loss to ordinary, "steady", learning. We ask whether these different learning paths - grokking versus ordinary training - lead to fundamental differences in the learned models. To do so we compare the features, compressibility, and learning dynamics of models trained via each path in two tasks. We find that grokked and steadily trained models learn the same features, but there can be large differences in the efficiency with which these features are encoded. In particular, we find a novel "compressive regime" of steady training in which there emerges a linear trade-off between model loss and compressibility, and which is absent in grokking. In this regime, we can achieve compression factors 25x times the base model, and 5x times the compression achieved in grokking. We then track how model features and compressibility develop through training. We show that model development in grokking is task-dependent, and that peak compressibility is achieved immediately after the grokking plateau. Finally, novel information-geometric measures are introduced which demonstrate that models undergoing grokking follow a straight path in information space.

This article reviews the concepts and methods of variational path sampling. These methods allow computational studies of rare events in systems driven arbitrarily far from equilibrium. Based upon a statistical mechanics of trajectory space and leveraging the theory of large deviations, they provide a perspective with which dynamical phenomena can be studied with the same types of ensemble reweighting ideas that have been used for static equilibrium properties. Applications to chemical, material, and biophysical systems are highlighted.

The discovery of new materials using crystal structure prediction (CSP) based on generative machine learning models has become a significant research topic in recent years. In this paper, we study invariance and continuity in the generative machine learning for CSP. We propose a new model, called ContinuouSP, which effectively handles symmetry and periodicity in crystals. We clearly formulate the invariance and the continuity, and construct a model based on the energy-based model. Our preliminary evaluation demonstrates the effectiveness of this model with the CSP task.

The original results of experimental investigations concerning the reduction of the seismic vulnerability of masonry vaults through Composite Reinforced Mortar CRM are presented in the paper. The transversal performances of full scale, masonry barrel vault samples, i.e. running bond pattern vaults and brick in folio vaults, carrying their own weight and reinforced at the extrados or at the intrados are investigated through cyclic tests. The connection of the reinforced vaults with the masonry abutment is particularly considered and discussed, due to the importance of this detail to avoid uplift and slip at the skewback sections and better exploit the CRM benefits. The experimental behavior of the vault samples is described and analyzed in terms of global behavior, crack pattern and load displacement curves, also in comparison with the unreinforced configurations. The CRM allowed significant improvements in both vaults strength and displacement capacities, as contrasted the cracks opening and foster the spreading of cracks all along the vault. Considerable performances emerged also in terms of dissipative capacities, with a mean damping value of about 0.13 in the post cracking configuration. The vault-to-wall connection, based on embedded steel and composite bars, resulted essential for avoiding dangerous vault sliding at skewback sections, that may reduce the vault performances and also cause the fall from the support.

Dielectric structures can support low-absorption optical modes, which are attractive for engineering light-matter interactions with excitonic resonances in two-dimensional (2D) materials. However, the coupling strength is often limited by the electromagnetic field being confined inside the dielectric, reducing spatial overlap with the active excitonic material. Here, we demonstrate a scheme for enhanced light-matter coupling by embedding excitonic tungsten disulfide (WS$_2$) within dielectric hexagonal boron nitride (hBN), forming a van der Waals (vdW) heterostructure that optimizes the field overlap and alignment between excitons and optical waveguide modes. To tailor diffractive coupling between free-space light and the waveguide modes in the vdW heterostructure, we fabricate Fourier surfaces in the top hBN layer using thermal scanning-probe lithography and etching, producing sinusoidal topographic landscapes with nanometer precision. We observe the formation of exciton-polaritons with a Rabi splitting indicating that the system is at the onset of strong coupling. These results demonstrate the potential of Fourier-tailored vdW heterostructures for exploring advanced optoelectronic and quantum devices.

The Tadah! code provides a versatile platform for developing and optimizing Machine Learning Interatomic Potentials (MLIPs). By integrating composite descriptors, it allows for a nuanced representation of system interactions, customized with unique cutoff functions and interaction distances. Tadah! supports Bayesian Linear Regression (BLR) and Kernel Ridge Regression (KRR) to enhance model accuracy and uncertainty management. A key feature is its hyperparameter optimization cycle, iteratively refining model architecture to improve transferability. This approach incorporates performance constraints, aligning predictions with experimental and theoretical data. Tadah! provides an interface for LAMMPS, enabling the deployment of MLIPs in molecular dynamics simulations. It is designed for broad accessibility, supporting parallel computations on desktop and HPC systems. Tadah! leverages a modular C++ codebase, utilizing both compile-time and runtime polymorphism for flexibility and efficiency. Neural network support and predefined bonding schemes are potential future developments, and Tadah! remains open to community-driven feature expansion. Comprehensive documentation and command-line tools further streamline the development and application of MLIPs.

The escalating plastic waste crisis demands global action, yet mechanical recycling - currently the most prevalent strategy - remains severely underutilized. Only a small fraction of the total plastic waste is recycled in this manner, largely due to the significant variability in recycled plastics' mechanical properties. This variability stems from compositional fluctuations and impurities introduced throughout the materials' lifecycle and the recycling process, deterring industries with stringent product specifications from adopting recycled plastics on a wider scale. To overcome this challenge, we propose a composite structure inspired by nacre's microstructure - a natural material known for its exceptional mechanical performance despite its inherent randomness across multiple length scales. This bio-inspired design features stiff recycled plastic platelets ("bricks") within a soft polymeric matrix ("mortar"). We use a tension-shear-chain model to capture the deformation mechanism of the structure, and demonstrate, through a case study of commercial stretch wrap, that the proposed design reduces variability in effective elastic modulus by 89.5% and in elongation at break by 42%, while achieving the same modulus as the virgin stretch wrap material. These findings highlight the potential of the proposed bio-inspired design to enhance the mechanical performance of recycled plastics, but also demonstrate that a universally applicable, chemistry-agnostic approach can substantially broaden their applications, paving the way for sustainable plastic waste management.

The uniform electron gas (UEG) is a cornerstone of density-functional theory (DFT) and the foundation of the local-density approximation (LDA), one of the most successful approximations in DFT. In this work, we extend the concept of UEG by introducing excited-state UEGs, systems characterized by a gap at the Fermi surface created by the excitation of electrons near the Fermi level. We report closed-form expressions of the reduced kinetic and exchange energies of these excited-state UEGs as functions of the density and the gap. Additionally, we derive the leading term of the correlation energy in the high-density limit. By incorporating an additional variable representing the degree of excitation into the UEG paradigm, the present work introduces a new framework for constructing local and semi-local state-specific functionals for excited states.

Particle suspensions in confined geometries can become clogged, which can have a catastrophic effect on function in biological and industrial systems. Here, we investigate the macroscopic dynamics of suspensions in constricted geometries. We develop a minimal continuum two-phase model that allows for variation in particle volume fraction. The model comprises a ``wet solid'' phase with material properties dependent on the particle volume fraction, and a seepage Darcy flow of fluid through the particles. We find that spatially varying geometry (or material properties) can induce emergent heterogeneity in the particle fraction and trigger the abrupt transition to a high-particle-fraction ``clogged'' state.

We present a constructive method utilizing the Cartan decomposition to characterize topological properties and their connection to two-qubit quantum entanglement, in the framework of the tenfold classification and Wootters' concurrence. This relationship is comprehensively established for the 2-qubit system through the antiunitary time reversal (TR) operator. The TR operator is shown to identify concurrence and differentiate between entangling and non-entangling operators. This distinction is of a topological nature, as the inclusion or exclusion of certain operators alters topological characteristics. Proofs are presented which demonstrate that the 2-qubit system can be described in the framework of the tenfold classification, unveiling aspects of the connection between entanglement and a geometrical phase. Topological features are obtained systematically by a mapping to a quantum graph, allowing for a direct computation of topological integers and of the 2-qubit equivalent of topological zero-modes. An additional perspective is provided regarding the extension of this new approach to condensed matter systems, illustrated through examples involving indistinguishable fermions and arrays of quantum dots.

The advent of 6G communication demands seamlessly integrated terminals operating above 100 GHz with low power consumption for human-centric applications. In this work, we report high-performance, flexible radio-frequency (RF) transistors based on aligned carbon nanotube (CNT) arrays, achieving, for the first time, as-measured current gain cutoff frequency ($f_{\mathrm{T}}$) and power gain cutoff frequency ($f_{\mathrm{max}}$) both exceeding 100 GHz. Electro-thermal co-design improves both heat dissipation and RF performance, despite the low thermal conductivity of the flexible substrate. The transistors deliver 0.947 mA/ $\mathrm{\mu}$m on-state current and 0.728 mS/ $\mathrm{\mu}$m transconductance. Peak extrinsic $f_{\mathrm{T}}$ and $f_{\mathrm{max}}$ reach 152 GHz and 102 GHz, with low power consumption of 199 mW/mm and 147 mW/mm, respectively, setting new performance records for flexible CNT-based RF transistors by nearly $100\times$, outperforming all other flexible RF devices. Additionally, flexible RF amplifiers achieve output power of 64 mW/mm and power gain of 11 dB in the K-band (18 GHz), marking a significant milestone in the development of flexible RF technologies for next-generation wireless communication systems.

We theoretically characterize gradient descent dynamics in deep linear networks trained at large width from random initialization and on large quantities of random data. Our theory captures the ``wider is better" effect of mean-field/maximum-update parameterized networks as well as hyperparameter transfer effects, which can be contrasted with the neural-tangent parameterization where optimal learning rates shift with model width. We provide asymptotic descriptions of both non-residual and residual neural networks, the latter of which enables an infinite depth limit when branches are scaled as $1/\sqrt{\text{depth}}$. We also compare training with one-pass stochastic gradient descent to the dynamics when training data are repeated at each iteration. Lastly, we show that this model recovers the accelerated power law training dynamics for power law structured data in the rich regime observed in recent works.

We consider the problem of how many samples from a Gaussian multi-index model are required to weakly reconstruct the relevant index subspace. Despite its increasing popularity as a testbed for investigating the computational complexity of neural networks, results beyond the single-index setting remain elusive. In this work, we introduce spectral algorithms based on the linearization of a message passing scheme tailored to this problem. Our main contribution is to show that the proposed methods achieve the optimal reconstruction threshold. Leveraging a high-dimensional characterization of the algorithms, we show that above the critical threshold the leading eigenvector correlates with the relevant index subspace, a phenomenon reminiscent of the Baik-Ben Arous-Peche (BBP) transition in spiked models arising in random matrix theory. Supported by numerical experiments and a rigorous theoretical framework, our work bridges critical gaps in the computational limits of weak learnability in multi-index model.

The discovery of new materials is essential for enabling technological advancements. Computational approaches for predicting novel materials must effectively learn the manifold of stable crystal structures within an infinite design space. We introduce Open Materials Generation (OMG), a unifying framework for the generative design and discovery of inorganic crystalline materials. OMG employs stochastic interpolants (SI) to bridge an arbitrary base distribution to the target distribution of inorganic crystals via a broad class of tunable stochastic processes, encompassing both diffusion models and flow matching as special cases. In this work, we adapt the SI framework by integrating an equivariant graph representation of crystal structures and extending it to account for periodic boundary conditions in unit cell representations. Additionally, we couple the SI flow over spatial coordinates and lattice vectors with discrete flow matching for atomic species. We benchmark OMG's performance on two tasks: Crystal Structure Prediction (CSP) for specified compositions, and 'de novo' generation (DNG) aimed at discovering stable, novel, and unique structures. In our ground-up implementation of OMG, we refine and extend both CSP and DNG metrics compared to previous works. OMG establishes a new state-of-the-art in generative modeling for materials discovery, outperforming purely flow-based and diffusion-based implementations. These results underscore the importance of designing flexible deep learning frameworks to accelerate progress in materials science.