Coarse-grained (CG) force field methods for molecular systems are a crucial tool to simulate large biological macromolecules and are therefore essential for characterisations of biomolecular systems. While state-of-the-art deep learning (DL)-based models for all-atom force fields have improved immensely over recent years, we observe and analyse significant limitations of the currently available approaches for DL-based CG simulations. In this work, we present the first transferable DL-based CG force field approach (i.e., not specific to only one narrowly defined system type) applicable to a wide range of biosystems. To achieve this, our CG algorithm does not rely on hard-coded rules and is tuned to output coarse-grained systems optimised for minimal statistical noise in the ground truth CG forces, which results in significant improvement of model training. Our force field model is also the first CG variant that is based on the MACE architecture and is trained on a custom dataset created by a new approach based on the fragmentation of large biosystems covering protein, RNA and lipid chemistry. We demonstrate that our model can be applied in molecular dynamics simulations to obtain stable and qualitatively accurate trajectories for a variety of systems, while also discussing cases for which we observe limited reliability.

Droplet generation under steady conditions is a common microfluidic method for producing biphasic systems. However, this process works only over a limited range of imposed pressure: beyond a critical value, a stable liquid jet can instead form. Furthermore, for a given geometry the pressure conditions set both the generation rate of droplets and their volume. Here, we report on-demand droplet production using a positive pressure pulse to the dispersed-phase inlet of a flow-focusing geometry. This strategy enables confined droplet generation within and beyond the pressure range observed under steady conditions, and decouples volume and production rate. In particular, elongated plugs not possible under steady conditions may be formed when the maximal pressure during the pulse reaches the jet regime. The measured volume of droplets-on-demand, as well as the onset of droplet generation are both captured with a simple model that considers hydraulic resistances. This work provides a strategy and design rules for processes that require individual droplets or elongated plugs in a simple microfluidic chip design.

By assuming gravity and matter to be subject to a joint statistical mechanical concept (JSMC) and interpreting Rindler horizon sections as open thermodynamic systems, one arrives at a specific new form of non-perturbative Lorentzian path integral quantisation in a compact space-time region, with well-determined gravitational measure, adequate fixing of boundary conditions and causal geometries. JSMC implies a space-time decomposition, leading to a sum over configurations in line with path integral methods. In these developments, we carefully distinguish the concepts of Boltzmann's statistical mechanics and the path integral.

We present the current status of the MATHUSLA (MAssive Timing Hodoscope for Ultra-Stable neutraL pArticles) long-lived particle (LLP) detector at the HL-LHC, covering the design, fabrication and installation at CERN Point 5. MATHUSLA40 is a 40 m-scale detector with an air-filled decay volume that is instrumented with scintillator tracking detectors, to be located near CMS. Its large size, close proximity to the CMS interaction point and about 100 m of rock shielding from LHC backgrounds allows it to detect LLP production rates and lifetimes that are one to two orders of magnitude beyond the ultimate reach of the LHC main detectors. This provides unique sensitivity to many LLP signals that are highly theoretically motivated, due to their connection to the hierarchy problem, the nature of dark matter, and baryogenesis. Data taking is projected to commence with the start of HL-LHC operations. We summarize the new 40m design for the detector that was recently presented in the MATHUSLA Conceptual Design Report, alongside new realistic background and signal simulations that demonstrate high efficiency for the main target LLP signals in a background-free HL-LHC search. We argue that MATHUSLA's uniquely robust expansion of the HL-LHC physics reach is a crucial ingredient in CERN's mission to search for new physics and characterize the Higgs boson with precision.

The energy calibration of calorimeters at collider experiments, such as the ones at the CERN Large Hadron Collider, is crucial for achieving the experiment's physics objectives. Standard calibration approaches have limitations which become more pronounced as detector granularity increases. In this paper we propose a novel calibration procedure to simultaneously calibrate individual detector cells belonging to a particle shower, by targeting a well-controlled energy reference. The method bypasses some of the difficulties that exist in more standard approaches. It is implemented using differentiable programming. In this paper, simulated energy deposits in the electromagnetic section of a high-granularity calorimeter are used to study the method and demonstrate its performance. It is shown that the method is able to correct for biases in the energy response.

Synchrotron radiation interferometry (SRI) is widely used in particle accelerators to monitor the transverse beam profile, and thus the critical beam emittance parameter. We introduce a novel technique to SRI using closure amplitudes, inspired by radio interferometry, to determine the two-dimensional profile of the synchrotron beam. Previous techniques have required multiple interferograms or accurate estimates of the non-uniform aperture illuminations. In contrast, our method using closure amplitudes avoids the need to estimate the aperture illuminations while determining the two-dimensional beam shape from a single interferogram. The invariance of closure amplitudes to even time-varying aperture illuminations makes it suitable to longer averaging intervals, with potential to reducing data rates and computational overheads. Using data from the ALBA synchrotron light source and having validated the results against existing methods, this paper represents one of the first real-world applications of interferometric closure amplitudes to directly determine the light source shape.

In this paper, we extend the geometric Particle in Cell framework on dual grids to a gauge-free drift-kinetic Vlasov--Maxwell model and its coupling with the fully kinetic model. We derive a discrete action principle on dual grids for our drift-kinetic model, such that the dynamical system involves only the electric and magnetic fields and not the potentials as most drift-kinetic and gyrokinetic models do. This yields a macroscopic Maxwell equation including polarization and magnetization terms that can be coupled straightforwardly with a fully kinetic model.

Flow instabilities within a fluid flow can cause laminar-to-turbulent transition over surfaces. These instabilities can result from upstream, wake-generating disturbances, leading to increased drag and turbulence-induced energy losses. Flow control strategies can address these issues through active methods, requiring energy input, or passive systems, which operate without added input. Here, we present a passive approach to flow control using embedded phononic metamaterials to alter vortex instability development, without changing the outer-surface's texture, roughness or compliance. Experiments confirm that our subsurface can suppress vortex growth at target frequencies, demonstrating the potential for energy-efficient flow management with phononic subsurfaces.

We present the design, fabrication, and optical characterization of ultra-compact mid-wave infrared photodetector pixels. Our design relies on a guided mode resonance structure to confine incident mid-infrared light to the 250 nm-thick absorber region of all-epitaxially-grown material stack, and a hybrid cavity-guided mode resonance to confine the mode in the lateral direction. The resulting pixel, with deep subwavelength thickness and lateral dimensions on the order of almost two times free space operating wavelength is predicted to achieve external quantum efficiency of the order of 50%. Our work opens the door for truly compact mid-wave infrared pixels that offer the combined benefits of low dark current, room temperature operation, and small lateral size.

We investigated the exciton transfer dynamics in photosynthetic light-harvesting complex 2 (LH2) coupled to an optical microcavity. Using computational simulations based on Redfield theory, we analyzed how microcavity coupling influences energy relaxation and transfer within and between LH2 aggregates. Our results show that the exciton transfer rate between B850 rings follows a square dependence on the light-matter coupling strength, in agreement with Fermi's golden rule. Interestingly, the energy transfer rate remains almost independent of the number of LH2 complexes. This behavior is explained by the molecular components of the polaritonic wavefunction overlaps. These findings highlight the crucial role of cavity-induced polaritonic states in mediating energy transport and provide a theoretical framework for optimizing microcavity environments to enhance exciton mobility in light-harvesting systems and related photonic applications.

We analyze the perturbation dynamics of a complex supersonic multi-stream rectangular jet. The dynamics are examined through application of spectral proper orthogonal decomposition (SPOD) to elicit coherent structure and linear resolvent analysis to reveal forcing-response characteristics. SPOD of a large-eddy simulation identifies Kelvin--Helmholtz coherent structures at the dominating frequency in the splitter plate shear layer region, formed by mixing core Mach $1.6$ and bypass Mach $1.0$ streams. Resolvent analysis leverages the time-averaged flowfield on the center plane with discounting to capture flow response over a finite time window, addressing base flow instabilities. The optimal and first sub-optimal resolvent energy amplifications peak near the dominant frequency for a wide range of frequencies and spanwise wavenumbers. Comparing the resolvent and SPOD results, we find that the linear operator over-optimizes the optimal mechanism, and the sub-optimal mode instead is more aligned with the leading SPOD mode. An intriguing shift phenomenon where the optimal and sub-optimal gain distributions crossover is observed; these events are associated with receptive regions in the different shear layers. Subsequent input-output analyses with state-variable and spatial restrictions provide insights into componentwise amplification of the jet flow response, thus providing direction for tailored practical flow control.

Natural systems often exhibit chaotic behavior in their space-time evolution. Systems transiting between chaos and order manifest a potential to compute, as shown with cellular automata and artificial neural networks. We demonstrate that swarm optimization algorithms also exhibit transitions from chaos, analogous to a motion of gas molecules, when particles explore solution space disorderly, to order, when particles follow a leader, similar to molecules propagating along diffusion gradients in liquid solutions of reagents. We analyze these `phase-like' transitions in swarm optimization algorithms using recurrence quantification analysis and Lempel-Ziv complexity estimation. We demonstrate that converging iterations of the optimization algorithms are statistically different from non-converging ones in a view of applied chaos, complexity and predictability estimating indicators. An identification of a key factor responsible for the intensity of their phase transition is the main contribution of this paper. We examined an optimization as a process with three variable factors -- an algorithm, number generator and optimization function. More than 9.000 executions of the optimization algorithm revealed that the nature of an applied algorithm itself is the main source of the phase transitions. Some of the algorithms exhibit larger transition-shifting behavior while others perform rather transition-steady computing. These findings might be important for future extensions of these algorithms.

We study the physical processes involved in the potential influence of Amazon (AM) hydroclimatology over the Tropical North Atlantic (TNA) Sea Surface Temperatures (SST) at interannual timescales, by analyzing time series of the precipitation index (P-E) over AM, as well as the surface atmospheric pressure gradient between both regions, and TNA SSTs. We use a recurrence joint probability based analysis that accounts for the lagged nonlinear dependency between time series, which also allows quantifying the statistical significance, based on a twin surrogates technique of the recurrence analysis. By means of such nonlinear dependence analysis we find that at interannual timescales AM hydrology influences future states of the TNA SSTs from 0 to 2 months later with a 90% to 95% statistical confidence. It also unveils the existence of two-way feedback mechanisms between the variables involved in the processes: (i) precipitation over AM leads the atmospheric pressure gradient between TNA and AM from 0 and 2 month lags, (ii) the pressure gradient leads the trade zonal winds over the TNA from 0 to 3 months and from 7 to 12 months, (iii) the zonal winds lead the SSTs from 0 to 3 months, and (iv) the SSTs lead precipitation over AM by 1 month lag. The analyses were made for time series spanning from 1979 to 2008, and for extreme precipitation events in the AM during the years 1999, 2005, 2009 and 2010. We also evaluated the monthly mean conditions of the relevant variables during the extreme AM droughts of 1963, 1980, 1983, 1997, 1998, 2005, and 2010, and also during the floods of 1989, 1999, and 2009. Our results confirm that the Amazon River basin acts as a land surface-atmosphere bridge that links the Tropical Pacific and TNA SSTs at interannual timescales. ...

In this paper we demonstrate the postulated mechanism of self-healing specifically due to orbital-angular-momentum (OAM) in radio vortex beams having equal beam-widths. In previous work we experimentally demonstrated self-healing effects in OAM beams at 28 GHz and postulated a theoretical mechanism to account for them. In this work we further characterize the OAM self-healing mechanism theoretically and confirm those characteristics with systematic and controlled experimental measurements on a 28 GHz outdoor link. Specifically, we find that the OAM self-healing mechanism is an additional self-healing mechanism in structured electromagnetic beams which is directional with respect to the displacement of an obstruction relative to the beam axis. We also confirm our previous findings that the amount of OAM self-healing is proportional to the OAM order, and additionally find that it persists beyond the focusing region into the far field. As such, OAM-assisted self-healing brings an advantage over other so-called non-diffracting beams both in terms of the minimum distance for onset of self-healing and the amount of self-healing obtainable. We relate our findings by extending theoretical models in the literature and develop a unifying electromagnetic analysis to account for self-healing of OAM-bearing non-diffracting beams more rigorously.

This work presents a matrix formulation for the induced metric on a brane, where non-commutative gauge fields play a central role. By starting from a general embedding of a p-brane in a higher-dimensional bulk, we derive the induced metric using commutator relations and extend the framework by incorporating gauge fields through a minimal coupling prescription. This approach not only draws an analogy with the effective acoustic metric in condensed matter systems but also provides insight into the emergence of light quanta as low-energy collective excitations of the quantum vacuum. In a simplified setting with a free Hamiltonian, we recover standard results in the appropriate limits while also uncovering new regimes characterized by a non-trivial coupling between the emergent gauge fields and the underlying matrix degrees of freedom. Our findings suggest potential pathways for connecting aspects of string theory matrix models with phenomenological features of emergent gravity.

This research explores the use of Cosmic Microwave Background (CMB) radiation as a reference signal for Initial Orbit Determination (IOD). By leveraging the unique properties of CMB, this study introduces a novel method for estimating spacecraft velocity and position with minimal reliance on pre-existing environmental data, offering significant advantages for space missions independent of Earth-specific conditions. Using Machine Learning (ML) regression models, this approach demonstrates the capability to determine velocity from CMB signals and subsequently determine the satellite's position. The results indicate that CMB has the potential to enhance the autonomy and flexibility of spacecraft operations.

Accurately modeling open quantum system dynamics is crucial for advancing quantum technologies, yet traditional methods struggle to balance accuracy and efficiency. Machine learning (ML) provides a promising alternative, particularly through recursive models that predict system evolution based on past history. While these models have shown success in predicting single observables, their effectiveness in more complex tasks, such as forecasting the full reduced density matrix (RDM), remains unclear. We extend history-based recursive ML approaches to complex quantum systems, comparing four physics-informed neural network (PINN) architectures: (i) single-RDM-predicting PINN (SR-PINN), (ii) SR-PINN with simulation parameters (PSR-PINN), (iii) multi-RDMs-predicting PINN (MR-PINN), and (iv) MR-PINN with simulation parameters (PMR-PINN). These models are applied to the spin-boson (SB) model and the Fenna-Matthews-Olson (FMO) complex. Our results show that SR-PINN and PSR-PINN, constrained by a narrow history window, fail to capture complex quantum evolution, leading to unstable long-term predictions, especially in nonlinear and highly correlated dynamics. In contrast, MR-PINN and PMR-PINN improve accuracy by extending the forecast horizon, incorporating long-range correlations, and reducing error propagation. Surprisingly, explicitly including simulation parameters such as temperature and reorganization energy in PSR-PINN and PMR-PINN does not consistently enhance accuracy and can even reduce performance, suggesting that these effects are already encoded in the RDM evolution. These findings highlight the limitations of short-sighted recursive forecasting and demonstrate the superior stability and accuracy of far-sighted approaches for long-term predictions.

In this work, we present typical challenges encountered when developing methods for controlling crowds of people (or animal swarms). We discuss which elements shall be considered and the role they play to achieve a robust control in a variety of conditions. In particular, four different studies are reviewed, each of them investigating in detail important elements encountered in crowd steering and control. More specifically synchronization, compliance, crowd (or swarm) density and human perception are studied showing the role they play in combination. Ultimately, the success of a control strategy is determined by carefully considering the effect each element has on individuals, but also on the interactions between them, leading to the creation of a collective behavior. We will also highlight the importance of psychological and cognitive factors when dealing with human crowds, hinting at the fact that automatic control systems may achieve optimal performance, but may be not necessarily well perceived by people in terms of comfort. The discussion aims at showing recent trends and potentialities of crowd control systems, but should also warn on the risk in choosing a solution prioritizing optimization toward people's safety or comfort.

Structural defects in one-dimensional heat conductors couple longitudinal (stretching) and transverse (bending) vibrations. This coupling results in the scattering of longitudinal phonons to transverse phonons and backwards. We show that the decay rate of longitudinal phonons due to this scattering scales with their frequencies as $\omega^{3/2}$ within the long wavelength limit ($\omega \rightarrow 0$), which is more efficient scattering compared to the traditionally considered Rayleigh scattering within the longitudinal band ($\omega^2$). This scattering results in temperature independent thermal conductivity depending on the size as $\kappa \propto L^{1/3}$ for sufficiently long materials. This predicted length dependence is observed in nanowires, though the temperature dependence is seen there possibly because of deviations from pure one-dimensional behavior. The significant effect of interaction of longitudinal phonons with transverse phonons is consistent with the earlier observations of a substantial suppression of thermal energy transport by kinks, obviously leading to such interaction, though anharmonic interaction can also be significant.

Based on the new decomposition of wave vectors and electric fields with respect to a charged planar interface between two isotropic lossy media, the incident, reflected, and refracted plane waves are found to be only determined by the tangential electric field of the incident plane wave. The complex wave vectors and their corresponding complex angles of the incident, reflected and refracted waves are easily calculated from the tangential wave vector based on the phase matching condition and Snell's law. The relationship between two different schemes of electric field compositions is interpreted and the electric field magnitudes of the incident, reflected and refracted waves were deduced from the tangential electric field magnitude of the incident wave where the tangential boundary condition of electric fields is directly utilized. The time-averaged Poynting vectors and the surface Joule heat density at the interface are also given to demonstrate the validity of our proposed methodology by the energy balance condition together with a specific example. It is also found that the external surface charges with a practical surface charge density have little effect on the reflection and transmission of electromagnetic waves since the surface conductivity of interface is negligibly small. Our work opens a new and fast route for calculating the reflected and transmitted waves at a charged and lossy planar interface without the need to perform the traditional polarization decomposition of arbitrarily polarized incident plane waves.

Solid-state quantum emitters are pivotal for modern photonic quantum technology, yet their inherent spectral inhomogeneity imposes a critical challenge in pursuing scalable quantum network. Here, we develop a cryogenic-compatible strain-engineering platform based on a polydimethylsiloxane (PDMS) stamp that is not obviously working properly at cryogenic temperature. In-situ three-dimensional (3D) strain control is achieved for quantum dots (QDs) embedded in photonic nanostructures. The compliant PDMS enables independent tuning of emission energy and elimination of fine structure splitting (FSS) of single QDs, as demonstrated by a 7 meV spectral shift with a near-vanishing FSS in circular Bragg resonators and an unprecedented 15 meV tuning range in the micropillar. The PDMS-based 3D strain-engineering platform, compatible with diverse photonic structures at cryogenic temperature, provides a powerful and versatile tool for exploring fundamental strain-related physics and advancing integrated photonic quantum technology.

Atomic oxygen is a critical and highly reactive chemical species responsible for key physical and chemical processes in the mesosphere and lower thermosphere.

We propose a general scheme to investigate photon triplet generation (PTG) via third-order spontaneous parametric downconversion (TOSPDC) in $\chi^{(3)}$ nonlinear structures. Our approach leverages the quantum-classical correspondence between TOSPDC and its reverse classical process, three-wave sum-frequency generation (TSFG), to efficiently estimate the PTG rate. We apply this framework to nonlinear metasurfaces supporting quasi-bound states in the continuum (qBICs) in the optical range. From numerical analysis of non-collinear TSFG with degenerate input waves at qBIC wavelengths, we predict wavelength-tunable three-photon emission with spatio-angular correlations. These findings establish a novel method for modelling TOSPDC and also highlight the potential of nonlinear resonant metasurfaces as compact free-space photon triplet sources with quantum state control.

Three-dimensional imaging through scattering media is important in medical science and astronomy. We propose a digital-twin imaging method based on Gaussian splatting to observe an object behind a scattering medium. A digital twin model built through data assimilation, emulates the behavior of objects and environmental changes in a virtual space. By constructing a digital twin using point clouds composed of Gaussians and simulating the scattering process through the convolution of a point spread function, three-dimensional objects behind a scattering medium can be reproduced as a digital twin. In this study, a high-contrast digital twin reproducing a three-dimensional object was successfully constructed from degraded images, assuming that data were acquired from wavefronts disturbed by a scattering medium. This technique reproduces objects by integrating data processing with image measurements.

In an increasingly interconnected world, understanding congestion-related phenomena in transportation and their underlying mechanisms is crucial for improving efficiency. As the transportation system becomes denser, different modes of transportation have more opportunities to interact with each other, giving rise to emergent dynamics that simple models cannot explain. In this study, we investigate the synchronized motion of indirectly coupled transportation modes. We develop a numerical simulation model on a one-dimensional periodic lattice, where each point represents a bus station. In this system, two types of buses operate: multiple local buses with non-overlapping routes, each serving a specific zone, and a single global bus that partially overlaps with the routes of the local buses. We perform numerical simulations to examine how close the arrival times of these buses are to each other -- that is, how synchronized their motions are. When the number of zones is two, three, or five, robust synchronization occurs not only between the global bus and the local buses, but also among the local buses themselves. In contrast, no synchronization is found for other numbers of zones. We developed a mathematical model using self-consistent equations and found that two distinct arrival patterns at the terminals must be considered. A stability analysis reveals which pattern is ultimately realized in the simulations. Our results show that transportation modes can exhibit coherent motion even when sharing only partial or no direct route overlaps. This outcome highlights that emergent behavior depends not only on local interactions but is also strongly shaped by the system's overall structural configuration.

Turbulent-flow control aims to develop strategies that effectively manipulate fluid systems, such as the reduction of drag in transportation and enhancing energy efficiency, both critical steps towards reducing global CO$_2$ emissions. Deep reinforcement learning (DRL) offers novel tools to discover flow-control strategies, which we combine with our knowledge of the physics of turbulence. We integrate explainable deep learning (XDL) to objectively identify the coherent structures containing the most informative regions in the flow, with a DRL model trained to reduce them. The trained model targets the most relevant regions in the flow to sustain turbulence and produces a drag reduction which is higher than that of a model specifically trained to reduce the drag, while using only half its power consumption. Moreover, the XDL model results in a better drag reduction than other models focusing on specific classically identified coherent structures. This demonstrates that combining DRL with XDL can produce causal control strategies that precisely target the most influential features of turbulence. By directly addressing the core mechanisms that sustain turbulence, our approach offers a powerful pathway towards its efficient control, which is a long-standing challenge in physics with profound implications for energy systems, climate modeling and aerodynamics.

In this article, we examine different approaches for calculating low frequency opacities in the warm dense matter regime. The relevance of the average-atom approximation and of different models for calculating opacities, such as the Ziman or Ziman-Evans models is discussed and the results compared to \textit{ab initio} simulations. We begin by recalling the derivation of the Ziman-Evans resistivity from Kubo's linear response theory, using the local approximation to the solutions of the Lippmann-Schwinger equation. With the help of this approximation, we explicitly introduce an ionic structure factor into the Ziman formula, without resorting to the Born approximation. Both approaches involve the calculation of scattering phase shifts, which we integrate from Calogero equation with an adaptive step numerical scheme based on a Runge-Kutta-Merson solver. We show that if the atomic number $Z$ is not too large, integrating the phase shifts in this way is more time-efficient than using a classical Numerov-type scheme to solve the radial Schr\"odinger equation. Various approximations are explored for phase shifts to further improve computation time. For the Born approximation, we show that using Born phase shifts directly in the scattering cross-section gives more accurate results than with the integral formula based on the Fourier transform of the electron-ion potential. We also compare an analytical formula based on a Yukawa fit of the electron-ion potential to a numerical integration. The average-atom results are compared with DFT-based molecular dynamics simulations for aluminum in the dilute regime and for copper, aluminum and gold at solid density and different temperatures.

During the study of resistive switching devices, researchers have found that the influence of the insertion layer cannot be ignored. Many reports have confirmed that the appropriate insertion layer can significantly improve the performance of the resistive switching devices. Therefore, in this work, we use magnetron sputtering to fabricate three devices: Cu/MgO/Cu, Cu/MgO/MoS2/Cu and Cu/MoS2/MgO/Cu. Through the characterization test of each device and the measurement of the I-V curve, it is found that the resistive switching characteristics of the Cu/MgO/Cu device will change greatly after adding an MoS2 insertion layer. The analysis results show that the inserted MoS2 layer does not change the main transmission mechanism (space charge limited conduction) of the device, but affects the regulating function of interfacial potential barrier, the effect also is related to the location of MoS2 inserted into the layer. Among the Cu/MgO/Cu, Cu/MgO/MoS2/Cu and Cu/MoS2/MgO/Cu devices, the Cu/MgO/MoS2/Cu device exhibits a larger switching ratio (about 103) and a lower reset voltage (about 0.21 V), which can be attributed to the regulation of the interface barrier between MgO and MoS2. In addition, when the MoS2 layer is inserted between the bottom electrodes Cu and MgO, the leakage current of the device is significantly reduced. Therefore, Cu/MoS2/MgO/Cu device has the highest commercial value from the point of view of practical applications. Finally, according to the XPS results and XRD results, we establish the conductive filament models for the three devices, and analyze the reasons for the different resistive switching characteristics of the three devices.

SNSPDs are indispensable for applications ranging from quantum information processing to deep-space optical communications, owing to their high detection efficiency, low dark counts, and excellent timing resolution. However, further improving the intrinsic detection efficiency (IDE) remains crucial for optimizing SNSPD performance. Ion irradiation has recently emerged as a powerful post-fabrication method to enhance SNSPD characteristics. Here, the effects of He-ion irradiation on the thermal properties of NbN SNSPDs. We systematically examine the evolution of thermal boundary conductance as a function of ion fluence (0-1.1E17 ions/cm2), observing a 57% decrease from 127 to 54 W/m^2K^4 with increasing fluence, followed by saturation at approximately 9E16 ions/cm2. At this fluence, the minimum hotspot relaxation time measurements indicate a 41% increase, rising from 17 to 24 ps, while the electron-phonon interaction time extends by 14%, from 11.2 to 12.8 ps at 10 K. TEM reveals defect formation at the NbN/SiO2 interface (6-8 nm) and He-bubble formation within the SiO2 layer (30-260 nm), contributing to the extended thermal relaxation time. These irradiation-induced modifications play a key role in enhancing the IDE of the treated devices. Furthermore, we demonstrate an irradiated NbN SNSPD exhibiting a well-defined saturated IDE plateau at 2000 nm from 2.7 K to 28 mK, enabled by irradiation-induced modifications and an avalanche-assisted detection mechanism with weak wavelength dependence. Our findings provide valuable insights into ion irradiation as a post-processing technique for SNSPDs, offering a pathway to enhancing IDE and tailoring thermal properties. This work also advances the understanding of SNSPD physics and defect engineering in superconducting thin films, expanding the potential applications of irradiation techniques in superconducting optoelectronics.

A theory for abelian plasma permeated by photons has been developed considering QED (quantum electrodynamics) generalized in Podolsky electrodynamics framework for consideration of higher order terms in electromagnetic theory. The theory traces out photonic degrees of freedom in plasma and accounts for plasma dynamics mediated by photons by calculated effective Hamiltonian. New modes of propagation have been predicted along with suppression of fields and collective behaviour. Non-Markovian behaviour is also discovered for plasma states and interactions in finite plasma system. This finds applicability in solid-state plasma, plasma confinement of magnetic and inertial nature, and laser-plasma interaction when theory is reduced to local interactions.

We investigate through numerical simulations the hydrodynamic interactions between two rigid spherical particles suspended on the axis of a cylindrical tube filled with an elastoviscoplastic fluid subjected to pressure-driven flow. The simulations are performed by the finite element method with the arbitrary Lagrangian-Eulerian formulation. We carry out a parametric analysis to examine the impact of the yield stress and relaxation time of the fluid and of particle confinement on the dynamics of the system. We identify master curves of the particle relative velocity as a function of the inter-particle distance. When the yield stress of the suspending phase is much lower than the viscous stress, those curves highlight short-range attractive interactions and long-range repulsive interactions between particles, with the latter specifically promoting their alignment. As the yield stress increases, the attractive interaction is replaced by stasis at short distance, characterized by a vanishing relative velocity and the formation of an unyielded region that connects the two spheres, where the fluid behaves like a viscoelastic solid. Additionally, the combined effects of plasticity and elasticity enhance the repulsion between the particles, promoting their ordering. Also increasing the confinement of the particles enhances repulsion, thus allowing to achieve ordering within shorter lengths in the flow direction. Reducing shear thinning amplifies peak relative velocities and expands the attractive region due to increased viscoelastic stresses and stress gradients. While a stable equilibrium may appear at larger separations, its impact is limited by low relative velocities.

Building upon the efficient implementation of hybrid density functionals (HDFs) for large-scale periodic systems within the framework of numerical atomic orbital bases using the localized resolution of identity (RI) technique, we have developed an algorithm that exploits the space group symmetry in key operation steps of HDF calculations, leading to further improvements in two ways. First, the reduction of $\mathbf{k}$-points in the Brillouin zone can reduce the number of Kohn-Sham equations to be solved. This necessitates the correct implementation of the rotation relation between the density matrices of equivalent $\mathbf{k}$-points within the representation of atomic orbitals. Second, the reduction of the real-space sector can accelerate the construction of the exact-exchange part of the Hamiltonian in real space. We have implemented this algorithm in the ABACUS software interfaced with LibRI, and tested its performance for several types of crystal systems with different symmetries. The expected speed-up is achieved in both aspects: the time of solving the Kohn-Sham equations decreases in proportion with the reduction of $\mathbf{k}$-points, while the construction of the Hamiltonian in real space is sped up by several times, with the degree of acceleration depending on the size and symmetry of the system.

A study of the coupling between lattice ion vibrations and electron waves in a piezoelectric semiconductor quantum plasma is presented. The nonlinearities have been analyzed, and solitons have been studied. The theory is built using the quantum hydrodynamic (QHD) model, incorporating the effects of Fermi pressure, quantum Bohm potential, and exchange-correlation potentials. The dispersion relation for the coupling is established. A set of nonlinear evolution equations has been derived using the two-time scale theory, and a soliton solution for the coupled nonlinear evolution equations is obtained using the modified quantum Zakharov equations. The solitons are found to have a cusp profile. It is also found that the solitons' field amplitude increases significantly with particle density and coupling strength in piezoelectric semiconductor quantum plasmas.

We consider thermo-optic bistability in resonant excitation of high-quality modes in two-dimensional dielectric resonators. We develop a coupled-mode theory approach which account for the frequency shift due to a temperature dependent dielectric permittivity. The model is applied to rectangular and hexagonal resonators supporting an isolated high-quality resonant mode. The results are verified in comparison with straightforward finite-element simulations. It is shown that the model accurately describes the effect bistabily which occurs under variation of the angle of incidence or the intensity of the incident wave. In particular, it is demonstrated that variation of the incident angle can optimize the coupling between the resonator and the incident waves leading to bistabily with low intensity incident waves $W_0 = 0.35 {\rm \mu W/\mu m}^2$. The bistability threshold is shown to be extremely sensitive to the imaginary part of the dielectric permittivity $\epsilon''$.

Dispersion engineering is a long-standing challenge in optical systems, and it is particularly important for metasurfaces, which naturally suffer from strong chromatic aberrations due to their ultralow profile. Stacks of metasurfaces have recently implemented dispersion control to address these challenges. However, these approaches still suffer from bottlenecks in terms of the available material refractive index and required aspect ratios, resulting in limited phase and group delay coverage, constraining their numerical aperture (NA), size and operating bandwidth. To address these challenges, we explore a dispersion compensation strategy combined with full-wave simulation-free inverse design to implement ultra-high NA, broadband dispersion control in metasurfaces, not requiring large refractive index materials and high aspect ratio processing technology. We experimentally demonstrate multiple meta-devices with highly customized dispersion engineering in the microwave regime, including broadband achromatic diffraction-limited meta-devices with NA=0.98 and 60% fractional bandwidth. Our proposed platform explores a paradigm for dispersion control with metasurfaces, which may facilitate advanced and scalable dispersion functionalities.

This study presents a novel workflow for constructing hybrid macropore-Darcy models from micro-CT images of microporous rocks. In our approach, macropore networks are extracted using established methods, while the microporosity is characterised through segmented phase classification and incorporated into the model as Darcy cells. Effectively, Darcy cells capture the micro scale connectivity variations that are missing in the macroscopic networks. This dual entity model thus incorporates both the conventional macroscopic pore structure and the critical flow pathways present in the under-resolved microporous regions. The proposed workflow is rigorously validated by comparing the permeability estimates with direct numerical simulation (DNS) results and experimental measurements. Our findings demonstrate that this hybrid approach reliably reproduces fluid flow behaviour in complex porous media while significantly reducing computational demands, offering a promising tool for advanced groundwater modelling and water resource management.

The Earth's main geomagnetic field arises from the constant motion of the fluid outer core. By assuming that the field changes are advection-dominated, the fluid motion at the core surface can be related to the secular variation of the geomagnetic field. The majority of existing core flow models are global, showing features such as an eccentric planetary gyre, with some evidence of rapid regional changes. By construction, the flow defined at any location by such a model depends on all magnetic field variations across the entire core-mantle boundary making it challenging to interpret local structures in the flow as due to specific local changes in magnetic field. Here we present an alternative strategy in which we construct regional flow models that rely only on local secular changes. We use a novel technique based on machine learning termed Physics-Informed Neural Networks (PINNs), in which we seek a regional flow model that simultaneously fits both the local magnetic field variation and dynamical conditions assumed satisfied by the flow. Although we present results using the Tangentially Geostrophic flow constraint, we set out a modelling framework for which the physics constraint can be easily changed by altering a single line of code. After validating the PINN-based method on synthetic flows, we apply our method to the CHAOS-8.1 geomagnetic field model, itself based on data from Swarm. Constructing a global mosaic of regional flows, we reproduce the planetary gyre, providing independent evidence that the strong secular changes at high latitude and in equatorial regions are part of the same global feature. Our models also corroborate regional changes in core flows over the last decade. Furthermore, our models endorse the existence of a dynamic high latitude jet, which began accelerating around 2005 but has been weakening since 2017.

We report on experimental investigation of nonperturbative high harmonic generation (HHG) in monolayer MoS2 in the ultraviolet spectral region driven by mid-infrared light. We study how the HHG is influenced by pre-excitation of the monolayer using resonant and near-resonant pulses in a pump-probe-like scheme. The resonant light creates high density exciton population. Due to ultrafast dephasing caused by electron-electron scattering, the HHG is suppressed in the presence of pre-excited carriers. In the case of near-resonant excitation with photon energy below the exciton transition, the dynamics of the observed suppression of the HHG yield contains a fast component which is a consequence of momentum scattering at carriers, which are excited by two-photon transition when the two pulses temporally overlap in the sample. This interpretation is supported by comparison of the experimental data with theoretical calculations of two-photon absorption spectrum of MoS2 monolayer. This work demonstrates a possibility to control HHG in lowdimensional materials on ultrashort timescales by combining the driving strong-field pulse with a weak near-resonant light.

We present a new simple and easy-to-implement one-dimensional phononic system whose spectrum exactly corresponds to the Hofstadter butterfly when a parameter is modulated. The system consists of masses that are coupled by linear springs and are mounted on flexural beams whose cross section (and, hence, stiffness) is modulated. We show that this system is the simplest version possible to achieve the Hofstadter butterfly exactly; in particular, the local resonances due to the beams are an essential component for this. We examine the various approaches to producing spectral butterflies, including Bloch spectra for rational parameter choices, resonances of finite-sized systems and transmission coefficients of sections of finite length. For finite-size systems, we study the localisation of the modes by calculating the inverse participation ratio, and detect a phase transition characterised by a critical value of the stiffness modulation amplitude, where the state of the system changes from mainly extended to localised, corresponding to a metal-insulator phase transition. The obtained results offer a practical strategy to realize experimentally a system with similar dynamical properties. The transmission coefficient for sections of finite length is benchmarked through the comparison with Bloch spectra of the same finite-sized systems. The numerical results for the transmission spectra confirms the evidence of a phase transition in the dynamical state of the system. Our approach opens significant new perspectives in order to design mechanical systems able to support phase transitions in their vibrational properties.

Small modular reactors (SMRs) are a class of advanced nuclear fission reactors characterized by their compact core size (typically <300 MWe) and passive safety systems. Their modular design enables on-site assembly, making them suitable for deployment in locations inaccessible to conventional large-scale reactors. With rising global energy demand, particularly driven by the growth of AI, SMRs have recently gained attention as a potential solution for powering data centers. This technical review aims to provide the public and relevant stakeholders with a foundational understanding of SMR technology. It begins with an overview of SMR concepts, historical context, and their current role in the U.S. energy mix. Detailed technical summaries of nine selected SMR designs are then presented, covering core design, fuel systems, reactivity control, and safety features. The report also outlines key regulatory frameworks, including 10 CFR Part 50, Part 52, and the technology-inclusive, risk-informed, and performance-based framework currently under development. Finally, major U.S. programs and legislative efforts supporting SMR deployment over the past decade are summarized.

Plasmonic many-particle systems with precisely tuned resonances and coupling strengths can exhibit emergent collective properties governed by universal principles. In one-dimensional chains with alternating couplings, known as Su-Schrieffer-Heeger (SSH) systems, this includes the formation of topologically protected mid-gap modes whose intensities localize at the chain's ends. This subwavelength localization at optical frequencies is crucial for achieving strong coupling of mid-gap modes to two-level systems under ambient conditions, extending topological protection to hybrid light-matter states. Here, we have fabricated SSH chains from plasmonic nanoslit resonators with strong inter-resonator coupling. The alternating distance between the nanoslit resonators is controlled with sub-nanometer precision, enabling accurate prediction and experimental observation of topologically protected mid-gap modes via photoemission electron microscopy (PEEM). Our results open the path towards experimental realizations of two-dimensional photonic metasurfaces exhibiting higher-order topological modes that can be strongly coupled to single emitters and quantum materials at ambient conditions.

Prior research suggests that using evidence-based pedagogies can not only improve learning for all students, it can also reduce the gender gap. We describe the impact of physics education research based pedagogical techniques in flipped and active-engagement non-flipped courses on the gender gap observed with validated conceptual surveys. We compare male and female students' performance in courses which make significant use of evidence-based active engagement (EBAE) strategies with courses that primarily use lecture-based (LB) instruction. The analysis presented here includes data from two-semester sequences of introductory algebra-based and calculus-based introductory physics courses. The surveys used to assess student learning in the first and second semester courses were the Force Concept Inventory and the Conceptual Survey of Electricity and Magnetism, respectively. The performance of male and female students in EBAE courses at a particular level is compared with LB courses in two situations: (I) the same instructor taught two courses, one of which was an EBAE course and the other an LB course, while the homework, recitations and final exams were kept the same, (II) student performance in all of the EBAE courses taught by different instructors was averaged and compared with LB courses of the same type also averaged over different instructors. In all cases, we find that students in courses which make significant use of EBAE strategies, on average, outperformed students in courses of the same type using primarily LB instruction even though there was no statistically significant difference on the pretest before instruction. However, the gender gap persisted even in courses using EBAE methods. We also discuss correlations between the performance of male and female students on the validated conceptual surveys and the final exam, which had a heavy weight on quantitative problem solving.

Quantum-logic spectroscopy has become an increasingly important tool for the state detection and readout of trapped atomic and molecular ions which do not possess easily accessible closed-optical-cycling transitions. In this approach, the internal state of the target ion is mapped onto a co-trapped auxiliary ion. This mapping is typically mediated by normal modes of motion of the two-ion Coulomb crystal in the trap. The present study investigates the role of spectator modes not directly involved in a measurement protocol relying on a state-dependent optical-dipole force. We identify a Debye-Waller-type effect that modifies the response of the two-ion string to the force and show that cooling all normal modes of the string allows for the detection of the rovibrational ground state of a N$_2^+$ molecular ion with a fidelity exceeding 99.99% improving on previous experiments by more than an order of magnitude. This marked improvement in sensitivity paves the way for simultaneously identifying multiple rovibrational states at a fixed set of experimental parameters.

While hydrodynamic coupling has long been considered essential for synchronisation of eukaryotic flagella, recent experiments on the unicellular biflagellate model organism {\it Chlamydomonas} demonstrate that -- at the single cell level -- intracellular mechanical coupling is necessary for coordination. It is therefore unclear what role, if any, hydrodynamic forces actually play in the synchronisation of multiple flagella within individual cells, arguably the building block of large scale coordination. Here we address this question experimentally by transiently blocking hydrodynamic coupling between the two flagella of single {\it Chlamydomonas}. Our results reveal that in wild type cells intracellularly-mediated forces are necessary and sufficient for flagellar synchronisation, with hydrodynamic coupling causing minimal changes in flagellar dynamics. However, fluid-mediated ciliary coupling is responsible for the extended periods of anti-phase synchronisation observed in a mutant with weaker intracellular coupling. At the single-cell level, therefore, flagellar coordination depends on a subtle balance between intracellular and extracellular forces.

Strong coupling typically occurs between two separate objects or between an object and its environment (such as an atom and a cavity). However, it can also occur between two different excitations within the same object, a situation that has been much less studied. In this study, we observe strong coupling between localized surface plasmon resonances and the interband transition in aluminum nanorods, as evidenced by optical spectroscopy and electron energy loss spectroscopy, and corroborated with numerical simulations. Strong coupling is observed between the interband transition and multiple orders of the surface plasmon mode, including dark ones. We also obtain experimental maps of the hybrid modes at the nanoscale. In each case, the associated Rabi energy, which corresponds to the energy splitting between the two polaritonic branches, is obtained. Finally, a dedicated numerical model was employed to calculate the hot electron generation rate in the nanorods. The calculations demonstrate that efficient generation of hot electrons can be achieved in the near-infrared region, when the interband transition is strongly coupled with a plasmon resonance. This high generation rate stems from the hybrid nature of the mode, as its plasmonic component provides a high absorption cross-section, while the IT part ensures efficient conversion to hot electrons. Consequently, aluminum nanorods represent an efficient source of hot electrons in the visible and near-infrared regions, with potential applications in local photochemistry, photodetection, and solar energy harvesting.

In this work, we present a planar laser-induced fluorescence (PLIF) system for two-dimensional (2D) spatial and phase-resolved ion velocity distribution function (IVDF) measurements. A continuous-wave tunable diode laser produces a laser sheet that irradiates the plasma, and the resulting fluorescence is captured by an intensified CCD (ICCD) camera. Fluorescence images recorded at varying laser wavelengths are converted into 2D IVDFs using the Doppler shift principle. Comparing six image filters, the singular-value decomposition (SVD)-based noise filtering is identified as the most effective for enhancing the signal-to-noise ratio while preserving the IVDF structure. The developed ICCD-based PLIF system is tested in an electron-beam generated $E \times B$ plasma with a moderate bulk plasma density of $\sim10^{10}$ $cm^{-3}$. The PLIF measurements are validated against a conventional single-point LIF method using photomultiplier tube (PMT)-based detection at various positions. The phase-resolving capability of the system is tested by oscillating the plasma between two nominal operating modes with different density profiles and triggering the ICCD camera with the externally driven plasma oscillation. The resulting oscillations in fluorescence intensity show good agreement with plasma density variations measured by electrostatic probes, demonstrating the systems ability to resolve phase-dependent dynamics. The measured IVDFs reveal several signatures of ion dynamics in this plasma source, including radially outflowing ions and anomalous ion heating in the plasma periphery, as anticipated by theoretical studies.

This study explores the thematic evolution of articles in The Physics Teacher and Physics Education journals, over a critical period in modern history, from the Cold War era to the pre-pandemic world (1966 - 2019). Using an NLP-based inductive topic modeling approach, we identify recurring themes that have shaped the physics education literature, including content-based topics, teaching methodologies, laboratory practices, curriculum development, and the influence of Physics Education Research (PER). Our findings reveal both overarching trends and distinct thematic preferences between the journals. Physics Education has historically emphasized curriculum structures, social aspects of education, and interdisciplinary connections, whereas The Physics Teacher has focused more on pedagogical strategies, demonstrations, and practical teaching tools. Over the past three decades, both journals have increasingly incorporated discussions on technology, computation, and PER-driven instructional practices. By tracing these developments over five decades, this study provides a broader perspective on how physics education has responded to changing educational priorities, technological advancements, and research developments.

To investigate the anisotropic properties of biomaterials, two distinct classes are considered: polymer-based (e.g., cellulose in plants) and crystalline-based (e.g., enamel in teeth), each demonstrating distinct structural and functional characteristics. Four-angle polarization (4-pol.) spectral mapping of sub-1 {\mu}m bamboo slices was carried out in the mid-IR spectral range (2.5-20 {\mu}m) to reveal the 3D organization of the chemical bonding of cellulose using the key characteristic absorption bands associated with C-O-C and C-N vibrational modes. The longitudinal and transverse microtome slices revealed a switch between the presence and absence of dichroism in parenchyma cell walls and vascular bundles. The cell wall showed continuous alignment of the C-O-C stretching vibrational mode (8.6 {\mu}m/1163 cm-1) down to the pixel resolution of ~ 4 {\mu}m (the step size in imaging) in the transverse slice; the cell wall thickness is ~ 1 {\mu}m. Thin microtomed slices of a tooth were measured in transmission and reflection modes. The single-point reflection measurements, performed using two perpendicular orientations, revealed orientational anisotropy in the enamel, which was absent in the dentin region. High sub-diffraction limited lateral resolution was numerically validated using a simplified-model of a Gaussian beam reading out material pixels with a defined orientation of absorption. It is shown that the orientation of small ~ {\lambda}/10 ~ 1 {\mu}m objects can be revealed using a focal spot of ~ {\lambda}/NA ~ 20 {\mu}m, defining the diffraction limit for the objective lens with a numerical aperture NA ~ 0.5.

Partially magnetized plasmas in ExB configurations - where the electric and magnetic fields are mutually perpendicular - exhibit a cross-field transport behavior, which is widely believed to be dominantly governed by complex instability-driven mechanisms. This phenomenon plays a crucial role in a variety of plasma technologies, including Hall thrusters, where azimuthal instabilities significantly influence electron confinement and, hence, device performance. While the impact of prominent plasma instabilities, such as the electron cyclotron drift instability (ECDI) and the modified two-stream instability (MTSI) on cross-field transport of electron species is well recognized and widely studied, strategies for actively manipulating these dynamics remain underexplored. In this study, we investigate the effect of targeted wave excitation on instability evolution and electron transport using one- and two-dimensional particle-in-cell simulations of representative plasma discharge configurations. A time-varying electric field is applied axially to modulate the spectral energy distribution of the instabilities across a range of forcing frequencies and amplitudes. Our results reveal that the so-called "unsteady forcing" can both suppress and amplify instability modes depending on excitation parameters. In particular, across both 1D and 2D simulation configurations, forcing near 40 MHz effectively reduces ECDI amplitude and decreases axial electron transport by about 30%, while high-frequency excitation near the electron cyclotron frequency induces spectral broadening, inverse energy cascades, and enhanced transport. These findings point to the role of nonlinear frequency locking and energy pathway disruption as mechanisms for modifying instability-driven transport. Our results offer insights into potential pathways to enhance plasma confinement and control in next-generation ExB devices.

We study the stability of a steady Eckart streaming jet that is acoustically forced at one end of a closed cylindrical cavity and impinges the wall at the other end, where a recirculation forms. This configuration generically represents industrial processes where acoustic forcing offers a contactless means of stirring or controlling confined flows. Successfully doing so, however, requires sufficient insight into the topology of the acoustically forced flow. This raises the question of whether the base acoustic streaming jet is stable and, when not, of which alternative states emerge. Using Linear Stability Analysis (LSA) and three-dimensional nonlinear simulations, we identify the instability mechanisms and determine the nature of the bifurcations that ensue. We show that the ratio $C_R$ between the cavity and the maximum beam radii determines the dominant unstable mode. For $4 \leq C_R \leq 6$, a non-oscillatory perturbation rooted in the jet impingement triggers a supercritical bifurcation. For $C_R = 3$, the flow destabilises through a subcritical non-oscillatory bifurcation. Further reducing $C_R$ increases the shear within the flow, and gradually relocates the instability in the shear layer between impingement-induced vortices: for $C_R = 2$, an unstable travelling wave grows out of a subcritical bifurcation, which becomes supercritical for $C_R=1$. For each geometry, the nonlinear 3D simulations validate the LSA, identify the saturated nonlinear state and its stability. This study offers fundamental insight into the stability of acoustically-driven flows in general, but also opens possible pathways to either induce turbulence acoustically, or to avoid it in realistic configurations.

Achieving high plasma density is essential for maximizing thermonuclear power and thus crucial for realizing economically viable fusion energy; however, this is often constrained by a fundamental density limit. This study investigates the L-mode density limit in negative triangularity (NT) plasmas on the DIII-D tokamak, and the results provide novel insights into this long-standing challenge. We report sustained operations at densities up to 1.8 times the conventional Greenwald limit with 13 MW of auxiliary heating power. Importantly, systematic power scans reveal distinct power scaling relationships for core ($n_{e} \propto P_{\text{SOL}}^{0.27\pm 0.03}$) and edge ($n_{e} \propto P_{\text{SOL}}^{0.42\pm 0.04}$) densities, which suggest different limiting mechanisms at play and point to a more nuanced picture than the traditional paradigm of a single, universal density limit. In this vein, detailed measurements were performed, revealing a complex interplay of macroscopic profiles, radiation patterns, and turbulent transport. Specifically, edge turbulent transport increased as density rose, leading to enhanced divertor radiation and subsequent MARFE onset. The edge density saturated abruptly following MARFE formation. In contrast, the core density continues to increase, ultimately limited by enhanced turbulence that exhibits characteristics of avalanche-like transport. Consistent with enhanced turbulence, toroidal rotation and the $E_r \times B$ flow shear also collapsed approaching the density limit. Taken together, these observations suggest that MARFE dynamics primarily govern the edge density limit, while turbulence-driven transport dominates the core density limit. These results also indicate the feasibility of operations significantly beyond the Greenwald density in high-power NT plasmas. This can potentially be attained through advanced control of core turbulence and MARFEs.

A personal recollection of early years in lattice gauge theory with a bias towards chiral symmetry and lattice fermions.

Hybrid integrated quantum photonics combines solid-state artificial atoms with reconfigurable photonic circuits, enabling scalable chip-based quantum networks. Self-assembled quantum dots (QDs) are ideal for this goal due to their ability to generate highly indistinguishable single photons with exceptional brightness. Integrating QDs into low-loss photonic circuits can facilitate complex quantum networks by enabling entanglement transfer via two-photon interference. However, challenges such as limited scalability, spectral inhomogeneity, and quantum interference between independent sources remain. We present a hybrid photonic architecture that integrates QD-containing waveguides with low-loss lithium niobate (LN) circuits, incorporating 20 deterministic single-photon sources (SPSs). Using the piezoelectric properties of thin-film lithium niobate (TFLN), we achieve on-chip local spectral tuning of QD emissions by up to 7.7 meV,three orders of magnitude greater than the transform-limited linewidth. This approach enables on-chip quantum interference with a visibility of 0.73 between two spatially separated QD SPSs connected by 0.48 mm long waveguides, establishing a functional quantum network.The large-scale integration of spectrally tunable QD-based SPSs into low-loss LN circuits, combined with fast electro-optical switching, paves the way for compact, lightweight, and scalable photonic quantum networks.

We report the first application of a tailored Complexity-Entropy Plane designed for binary sequences and structures. We do so by considering the daily up/down price fluctuations of the largest cryptocurrencies in terms of capitalization (stable-coins excluded) that are worth $circa \,\, 90 \%$ of the total crypto market capitalization. With that, we focus on the basic elements of price motion that compare with the random walk backbone features associated with mathematical properties of the Efficient Market Hypothesis. From the location of each crypto on the Binary Complexity-Plane (BiCEP) we define an inefficiency score, $\mathcal I$, and rank them accordingly. The results based on the BiCEP analysis, which we substantiate with statistical testing, indicate that only Shiba Inu (SHIB) is significantly inefficient, whereas the largest stake of crypto trading is reckoned to operate in close-to-efficient conditions. Generically, our $\mathcal I$-based ranking hints the design and consensus architecture of a crypto is at least as relevant to efficiency as the features that are usually taken into account in the appraisal of the efficiency of financial instruments, namely canonical fiat money. Lastly, this set of results supports the validity of the binary complexity analysis.

We find a design principle for tailoring thermal expansion properties in molecular networks. Using 2D fullerene networks as a representative system, we realize positive thermal expansion along intermolecular double bonds and negative thermal expansion along intermolecular single bonds by varying the structural frameworks of molecules. The microscopic mechanism originates from a combination of the framework's geometric flexibility and its transverse vibrational characteristics. Based on this insight, we find molecular networks beyond C$_{60}$ with tunable thermal expansion. These findings shed light on the fundamental mechanisms governing thermal expansion in molecular networks towards rational materials design.

We present a novel numerical framework that integrates the modified Langevin noise formalism into the multimode Jaynes- and Tavis-Cummings models, enabling a first-principles, non-Markovian analysis of atom-field interactions in dissipative electromagnetic (EM) environments that account for both radiative losses and absorptive dissipation in lossy dielectric media (or satisfying general inhomogeneous causal media exhibiting both dispersion and absorption effects). In the modified Langevin noise formalism, the boundary- and medium-assisted (BA and MA) fields, which constitute a continuum set of EM modes in dissipative EM environments, are numerically obtained using the finite-element method (FEM). Specifically, BA field modes are extracted by solving plane-wave scattering problems, while MA field modes are determined through point-source radiation problems. These numerically obtained BA and MA field modes are then incorporated into the multimode Jaynes- and Tavis-Cummings models such that the coupling strength between atoms and BA-MA field modes can be calculated for the study of atom-field interactions in dissipative EM environments. The proposed methodology captures non-Markovian atomic dynamics that cannot be described by traditional quantum master equations under the Markovian approximation. To validate the accuracy of the proposed numerical framework, we present four numerical examples: (i) a two-level system (TLS) in a perfect electric conductor (PEC) half-space; (ii) dissipative cavity electrodynamics with two limiting cases approaching spontaneous emission in free space and ideal Rabi oscillations; (iii) super-radiance in TLS arrays; and (iv) entanglement sudden death of two TLSs inside dissipative cavities. The proposed methodology can serve as a ground-truth numerical simulator for studying atom-field interactions in general dissipative EM environments.

Efficiently distinguishing photon numbers is a crucial yet challenging technology for various quantum information and quantum metrology applications. While superconducting transition edge sensors offer good photon-number-resolving (PNR) capabilities, they are hampered by low detection speed, timing jitter, and complex cooling and readout requirements. In this work, we present a significant advancement toward achieving high-fidelity PNR single-photon detectors. The unique twin-layer configuration of superconducting nanowire atop a dielectric mirror ensures the near-unity detection efficiency. The segmented design enables spatial multiplexing, establishing a mapping relationship between pulse amplitude and registered photons. The fabricated detector exhibits impressive performance metrics, including a single-photon system detection efficiency (SDE) of ~ 98% at a dark count rate of 20 cps and photon-number resolution capability up to 32. Further characterization through detector tomography reveals high fidelities for two-, three-, and four-photon events, approximately 87%,73%, and 40% respectively. Moreover, the detector operates at a high count rate of 41 MHz at 3dB-SDE, with a low timing jitter of as low as 40 ps. With its near-unity efficiency, high photon-number resolution, low dark count rate and fast detection speed, we expect significant interest in these detectors, promising substantial benefits for weak light detection and optical quantum information applications.

\ Nitrous oxide (N$_2$O) ice is likely to exist in trans-Neptunian objects such as Pluto and Triton, potentially formed through ultraviolet (UV) radiation from the Sun or cosmic ray irradiation of N$_2$ and CO ices. However, the mid-infrared spectral characteristics of N$_2$O ice in higher temperature regions (90-110 K), changes in mid-infrared spectra during UV irradiation, and the chemical network of nitrogen oxide (N$_x$O$_y$) ices remain insufficiently understood. This study aims to elucidate these aspects through in-situ mid-infrared spectral measurements of cryogenic particles using two-dimensional imaging Fourier transform infrared spectroscopy. Spectroscopic imaging confirmed strong absorption at 7.75 $\mu$m (N$_2$O $\nu_1$ vibrational mode), with weaker vibrational modes observed at 8.60 $\mu$m (N$_2$O 2$\nu_2$), 7.27 $\mu$m (N$_2$O torsion), and 5.29 $\mu$m (N$_2$O $\nu_1$+$\nu_2$). Annealing experiments simulating high-temperature conditions demonstrated that all vibrational modes irreversibly intensified with increasing temperature, indicating progressive crystallization. New spectral features appeared at approximately 12 $\mu$m and 14 $\mu$m at the condensed sample. N$_2$O ice was exposed to ultraviolet radiation (190-340 nm) using a D$_2$ lamp for 8.5 hours to investigate spectral changes during UV irradiation. After 60-90 minutes of irradiation, all N$_2$O vibrational modes disappeared, while absorption intensities of various nitrogen oxides, including NO, NO$_2$, N$_2$O$_3$, and O$_3$ increased. Beyond 180 minutes, vibrational modes of multiple nitrogen oxide ices exhibited intensity variations across different wavelengths, corresponding to other species such as cis-(NO)$_2$, N$_2$O$_4$, and N$_2$O$_5$.

Employing two synchronized mode-locked femtosecond lasers and interferometric detection of the pump-probe spectra -- referred to as asynchronous and interferometric transient absorption (AI-TA) -- we have developed a method for broad dynamic range and rapid data acquisition. Using AI-TA, we examined photochemical changes during femtosecond pump-probe experiments on all-inorganic cesium lead halide nanomaterials, including perovskite nanocrystals (PeNCs) and nanoplatelets (PeNPLs). The laser pulse train facilitates photoreactions while allowing real-time observation of charge carrier dynamics. In PeNCs undergoing halide anion photo-substitution, transient absorption spectra showed increasing bandgap energy and faster relaxation dynamics as the Cl/Br ratio increased. For colloidal PeNPLs, continuous observation revealed both spectral and kinetic changes during the light-induced coalescence of nanoplatelets, by analyzing temporal segments. This integrated technique not only deepens understanding of exciton dynamics and environmental influences in perovskite nanomaterials but also establishes AI-TA as a transformative tool for real-time observation of photochemical dynamics.

Understanding the stability of complex communities is a central focus in ecology, many important theoretical advancements have been made to identify drivers of ecological stability. However, previous results often rely on the continuous-time dynamics, assuming that species have overlapping generations. In contrast, numerous real-world communities consist of species with non-overlapping generations, whose quantitative behavior can only be precisely represented by discrete-time dynamics rather than continuous ones. Here, we develop a theoretical framework and propose a metric to quantify the stability of complex communities characterized by non-overlapping generations and diverse interaction types. In stark contrast to existing results for overlapping generations, we find that increasing self-regulation strength first stabilizes and then destabilizes complex communities. This pattern is further confirmed in both exploitative (E. aerogenes, P. aurantiaca, P. chlororaphis, P. citronellolis) and competitive (P. putida, P. veroni, S. marcescens) soil microbial communities. Moreover, we show that communities with diverse interaction types become the most stable, which is corroborated by empirical mouse microbial networks. Furthermore, we reveal that the prevalence of weak interactions can stabilize communities, which is consistent with findings from existing microbial experiments. Our analyses of complex communities with non-overlapping generations provide a more comprehensive understanding of ecological stability and informs practical strategies for ecological restoration and control.

We investigate a quasi-one-dimensional (Q1D) system of hard spheres confined within a cylindrical pore so narrow that only nearest-neighbor interactions are possible. By mapping the Q1D system onto a one-dimensional polydisperse mixture of nonadditive hard rods, we obtain exact thermodynamic and structural properties, including the radial distribution function, which had remained elusive in previous studies. We derive analytical expressions for limiting cases, such as small pore diameters, virial coefficients, and extreme pressures. Additionally, we identify a transition in the anisotropic pressure components, where the transverse pressure surpasses the longitudinal one at high densities if the pore diameter exceeds a critical threshold. Finally, we analyze spatial correlations in particle arrangements and fluctuations in radial positioning, providing insight into the emergence of ordering in confined systems.

Reinforcement fine-tuning has instrumental enhanced the instruction-following and reasoning abilities of large language models. In this work, we explore the applications of reinforcement fine-tuning to the autoregressive transformer-based materials generative model CrystalFormer (arXiv:2403.15734) using discriminative machine learning models such as interatomic potentials and property prediction models. By optimizing reward signals-such as energy above the convex hull and material property figures of merit-reinforcement fine-tuning infuses knowledge from discriminative models into generative models. The resulting model, CrystalFormer-RL, shows enhanced stability in generated crystals and successfully discovers crystals with desirable yet conflicting material properties, such as substantial dielectric constant and band gap simultaneously. Notably, we observe that reinforcement fine-tuning enables not only the property-guided novel material design ability of generative pre-trained model but also unlocks property-driven material retrieval from the unsupervised pre-training dataset. Leveraging rewards from discriminative models to fine-tune materials generative models opens an exciting gateway to the synergies of the machine learning ecosystem for materials.

There exist several initiatives worldwide to deploy quantum key distribution (QKD) over existing fibre networks and achieve quantum-safe security at large scales. To understand the overall QKD network performance, it is required to transition from the analysis of individual links, as done so far, to the characterization of the network as a whole. In this work, we undertake this study by embedding QKD protocols on complex networks, which correctly model the existing fiber networks. We focus on networks with trusted nodes and on continuous-variable (CV) schemes, which have much higher key rates than their discrete-variable (DV) counterparts. In the effective CV network, however, many of the unique properties of complex networks, such as small-worldness and the presence of hubs, are lost due to the fast decay of the key rate with physical distance for CV systems. These properties can be restored when considering a hybrid network consisting of both CV and DV protocols, achieving at the same time high average rate and inter-connectivity. Our work opens the path to the study of QKD complex networks in existing infrastructures.

The rotational dynamics of a freely suspended ferromagnetic particle in viscoelastic fluid subjected to a rotating magnetic field is studied by experiments and theory. Our result reveals that when the characteristic relaxation time of the fluid is much smaller than the inverse critical field frequency, the particle's rotation behavior aligns with that in Newtonian fluids. Increasing the relaxation time enhances the time-averaged rotation frequency of the particle that undergo asynchronous rotation. Moreover, the critical frequency is shown to scale linearly with the magnetic field intensity and inversely with the fluid's zero-shear viscosity. Our work is expected to guide precise manipulation of ferromagnetic particles in biomedical systems where viscoelastic environments dominate.

An analytical cancellation nanoflare model has recently been established to show the fundamental role that ubiquitous small-scale cancellation nanoflares play in solar atmospheric heating. Although this model is well-supported by simulations, observational evidence is needed to deepen our understanding of cancellation nanoflares. We present observations of a small-scale cancellation nanoflare event, analyzing its magnetic topology evolution, triggers, and physical parameters. Using coordinated observations from Solar Dynamics Observatory and Goode Solar Telescope, we identify a photospheric flow-driven cancellation event with a flux cancellation rate of ~10^{15} Mx/s and a heating rate of 8.7 x 10^6 erg cm^{-2} s^{-1}. The event shows the characteristic transition from $\pi$-shaped to X-shaped magnetic configuration before forming a two arcsecs current sheet, closely matching model predictions. This event provides critical observational support for the cancellation nanoflare model and its role in solar atmospheric heating.

The symbiotic relationship between the frameworks of classical game theory and evolutionary game theory is well-established. However, evolutionary game theorists have mostly tapped into the classical game of complete information where players are completely informed of all other players' payoffs. Of late, there is a surge of interest in eco-evolutionary interactions where the environment's state is changed by the players' actions which, in turn, are influenced by the changing environment. However, in real life, the information about the true environmental state must pass through some noisy channel (like usually imperfect sensory apparatus of the players) before it is perceived by the players: The players naturally are prone to sometimes perceive the true state erroneously. Given the uncertain perceived environment, the players may adopt bet-hedging kind of strategies in which they play different actions in different perceptions. In a population of such ill-informed players, a player would be confused about the information state of her opponent, and an incomplete information situation akin to a Bayesian game surfaces. In short, we contemplate possibility of natural emergence of symbiotic relationship between the frameworks of Bayesian games and eco-evolutionary games when the players are equipped with inefficient sensory apparatus. Herein, we illustrate this connection using a setup of infinitely large, well-mixed population of players equipped with two actions for exploiting a resource (the environment) at two different rates so that the resource state evolves accordingly. The state of the resource impacts every player's decision of playing particular action. We investigate continuous state environment in the presence of a Gaussian noisy channel. Employing the formalism of replicator dynamics, we find that noisy information can be effective in preventing resource from going extinct.

Dislocation-density based crystal plasticity (CP) models are introduced to account for the microstructral changes throughout the deformation process, enabling more quantitative predictions of the deformation process compared to slip-system resistance-based plasticity models. In this work, we present a stability analysis of slip rate driven processes for some established dislocation density-based models, including the Kocks and Mecking (KM) model and its variants. Our analysis can be generalized to any type of dislocation density model, providing a broader framework for understanding the stability of such systems. Interestingly, we demonstrate that even size-independent models can exhibit size-dependent effects through variations in initial dislocation density. Notably, the initial dislocation density significantly influences material hardening or softening responses. To further explore these phenomena, we conduct numerical simulations of micro-pillar compression using an Eulerian crystal plasticity framework. Our results show that dislocation-density-based CP models effectively capture microstructural evolution in small-scale materials, offering critical insights for the design of miniaturized mechanical devices and advanced materials in nanotechnology.

The propulsion of many eukaryotic cells is generated by flagella, flexible slender filaments that are actively oscillating in space and time. The dynamics of these biological appendages have inspired the design of many types of artificial microswimmers. The magnitude of the filament's viscous propulsion depends on the time-varying shape of the filament, and that shape depends in turn on the spatial distribution of the bending rigidity of the filament. In this work, we rigorously determine the relationship between the mechanical (bending) properties of the filament and the viscous thrust it produces using mathematical optimisation. Specifically, by considering a model system (a slender elastic filament with an oscillating slope at its base), we derive the optimal bending rigidity function along the filament that maximises the time-averaged thrust produced by the actuated filament. Instead of prescribing a specific functional form, we use functional optimisation and adjoint-based variational calculus to formally establish the link between the distribution of bending rigidity and propulsion. The optimal rigidities are found to be stiff near the base, and soft near the distal end, with a spatial distribution that depends critically on the constraints used in the optimisation procedure. These findings may guide the optimal design of future artificial swimmers.

We study the first-passage-time (FPT) properties of an active Brownian particle under stochastic resetting to its initial configuration, comprising its position and orientation, to reach an absorbing wall in two dimensions. Coupling a perturbative approach for low P\'eclet numbers, measuring the relative importance of self-propulsion with respect to diffusion, with the renewal framework for the stochastic resetting process, we derive analytical expressions for the survival probability, the FPT probability density, and the associated low-order moments. Depending on their initial orientation, the minimal mean FPT for active particles to reach the boundary can both decrease and increase relative to the passive counterpart. The associated optimal resetting rates depend non-trivially on the initial distance to the boundary due to the intricate interplay of resetting, rotational Brownian noise, and active motion.

There has been interest in the interactions between infectious disease dynamics and behaviour for most of the history of mathematical epidemiology. This has included consideration of which mathematical models best capture each phenomenon, as well as their interaction, but typically in a manner that is agnostic to the exact behaviour in question. Here, we investigate interacting behaviour and disease dynamics specifically related to behaviours around testing and isolation. This epidemiological-behavioural interaction is of particular interest as, prospectively, it is well-placed to be informed by real-world data temporally monitoring test results and compliance with testing policy. To carry out our investigation we extend an existing "behaviour and disease" (BaD) model by incorporating the dynamics of symptomatic testing and isolation. We provide a dynamical systems analysis of the ordinary differential equations that define this model, providing theoretical results on its behaviour early in a new outbreak (particularly its basic reproduction number) and endemicity of the system (its steady states and associated stability criteria). We then supplement these findings with a numerical analysis to inform how temporal and cumulative outbreak metrics depend on the model parameter values for epidemic and endemic regimes. As the presented interdisciplinary modelling approach can accommodate further extensions (including, but not limited to, adding testing capacity, decay in behavioural effects and multiple pathogen variants), we hope that our work will encourage further modelling studies integrating specific measured behaviours and disease dynamics that may reduce the health and economic impacts of future epidemics.

Photo-evaporation shapes the observed radii of small exoplanets and constrains the underlying distributions of atmospheric and core masses. However, the diversity of atmospheric chemistries corresponding to these distributions remains unelucidated. We develop a first-principles carbon-hydrogen-oxygen-sulfur-silicon (CHOSSi) outgassing model that accounts for non-ideal gas behavior (via fugacities) at high pressures, as well as the tendency for water and hydrogen to dissolve in melt (via solubility laws). We use data-driven radius valley constraints to establish the relationship between the atmospheric surface pressures and melt temperatures of sub-Neptunes. Sub-Neptunes with less massive rocky cores retain less of their primordial hydrogen envelopes, which leads to less heat retention and diminished melt temperatures at the surfaces of these cores. Lower melt temperatures lead thermodynamically to the dominance of carbon-, oxygen-, sulfur- and silicon-bearing molecules over molecular hydrogen, which naturally produce a diversity of mean molecular weights. Our geochemical outgassing calculations robustly predict a gradient of mean molecular weight across the radius valley, where the strength of this gradient is primarily driven by the oxygen fugacity of the molten cores and not by the carbon enrichment (or "metallicity") of the atmosphere. Smaller sub-Neptunes are predicted to have less hydrogen-dominated atmospheres. The precise relationship between the observed and outgassed chemistries requires an understanding of how convection near the core interacts with large-scale atmospheric circulation (driven by stellar heating) near the photosphere, as well as the influence of photochemistry.

We present a method where a bioactive functional layer on an electrically conductive thin film with high sheet resistance can be effectively used for complementary electrochemical impedance spectroscopy biosensing. The functional layer's properties, such as double-layer capacitance and charge-transfer resistance, influence the complex impedance of the thin film in direct contact with the layer. These measurements can be performed using a simple low-frequency setup with a lock-in amplifier. When graphene is used as the resistive thin film, the signal may also include contributions from graphene's quantum capacitance, which is sensitive to charge transfer to and from the graphene. Unlike in traditional graphene biosensors, changes in electrolyte properties over time, such as those caused by the dissolution of ambient gases, do not significantly affect AC measurements. This technique supports biosensor miniaturization, ensures stable operation, and provides reliable biomarker detection with a high signal-to-noise ratio.

In this report, we derive analytical expressions for the time resolution limits of standard silicon sensors, LGADs, and 3D trench sensors. We separately examine the effects of Landau fluctuations and electronic noise. To analyze Landau fluctuations, we relate the time resolution of a single electron-hole pair generated at a random position in the sensor to the time resolution associated with the full ionization pattern produced by a charged particle. For electronic noise, we explore optimal filtering techniques that minimize its impact on time resolution, and evaluate how closely these can be approximated by practical filters. Finally, we demonstrate that the combined effect of Landau fluctuations and electronic noise cannot, in general, be simply expressed as the quadratic sum of the individual contributions.

Cosmic rays (CR), both solar and Galactic, have an ionising effect on the Earth's atmosphere and are thought to be important for prebiotic molecule production. In particular, the $\rm{H_2}$-dominated atmosphere following an ocean-vaporising impact is considered favourable to prebiotic molecule formation. We model solar and Galactic CR transport through a post-impact early Earth atmosphere at 200Myr. We aim to identify the differences in the resulting ionisation rates, $\zeta$, particularly at the Earth's surface during a period when the Sun was very active. We use a Monte Carlo model to describe CR transport through the early Earth atmosphere, giving the CR spectra as a function of altitude. We calculate $\zeta$ and the ion-pair production rate, $Q$, as a function of altitude due to Galactic and solar CR. The Galactic and solar CR spectra are both affected by the Sun's rotation rate, $\Omega$, because the solar wind velocity and magnetic field strength both depend on $\Omega$ and influence CR transport. We consider a range of input spectra resulting from the range of possible $\Omega$, from $3.5-15\, \Omega_{\rm{\odot}}$. To account for the possibility that the Galactic CR spectrum outside the Solar System varies over Gyr timescales, we compare top-of-atmosphere $\zeta$ resulting from two different scenarios. We also consider the suppression of the CR spectra by a planetary magnetic field. We find that $\zeta$ and $Q$ due to CR are dominated by solar CR in the early Earth atmosphere for most cases. The corresponding $\zeta$ at the early Earth's surface ranges from $5 \times 10^{-21}\rm{s^{-1}}$ for $\Omega = 3.5\,\Omega_{\rm{\odot}}$ to $1 \times 10^{-16}\rm{s^{-1}}$ for $\Omega = 15\,\Omega_{\rm{\odot}}$. Thus if the young Sun was a fast rotator, it is likely that solar CR had a significant effect on the chemistry at the Earth's surface at the time when life is likely to have formed.

We investigate the physics of ultracold dipolar molecules using path-integral quantum Monte Carlo simulations, and construct the complete phase diagram extending from weak to strong interactions and from small to mesoscopic particle numbers. Our calculations predict the formation of self-bound quantum droplets at interaction strengths lower than previously anticipated. For stronger interactions, the droplet continuously loses superfluidity as correlations develop, and is eventually found to undergo a transition to a crystalline monolayer that remains self-bound without external confinement. The spontaneous formation of such two-dimensional phases from a three-dimensional quantum gas is traced back to the peculiar anisotropic form of the dipole-dipole interaction generated by microwave-dressing of rotational molecular states. For sufficiently large particle numbers, crystallization takes place for comparably low interaction strengths that do not promote two-body bound states and should thus be observable in ongoing experiments without limitations from three-body recombination.

This work presents a novel approach for characterizing the mechanical behavior of atrial tissue using constitutive neural networks. Based on experimental biaxial tensile test data of healthy human atria, we automatically discover the most appropriate constitutive material model, thereby overcoming the limitations of traditional, pre-defined models. This approach offers a new perspective on modeling atrial mechanics and is a significant step towards improved simulation and prediction of cardiac health.

Quantum emitters driven by resonant two-photon excitation are a leading source for deterministically generated entangled photon pairs, essential for scalable photonic quantum technologies. However, conventional resonant schemes are highly sensitive to laser power fluctuations and pose additional experimental challenges for emitters with small biexciton binding energies. Here, we demonstrate how biexciton preparation schemes with significantly improved robustness and reduced laser filtering requirements can be identified using a novel design principle beyond resonant and adiabatic driving: ultrafast all-optical Floquet engineering. This is achieved by employing two strongly and symmetrically detuned dichromatic pulses, whose superposition generates a stroboscopic Hamiltonian that enables direct coupling between ground and biexciton states. Moreover, a pulse delay serves as a tuning knob, introducing an effective magnetic field that concentrates the Bloch sphere trajectory at the biexciton state for a wide range of parameters, making biexciton preparation particularly robust. Experimentally, we achieve a biexciton occupation exceeding 96% and preserve photon-pair entanglement with a fidelity of 93.4%. Our scheme highlights the great impact of Floquet-engineered multicolour excitation protocols for on-demand quantum light sources.

The confluence of Non-Hermitian (NH) topology and crystal defects has culminated significant interest, yet its experimental exploration has been limited due to the challenges involved in design and measurements. Here, we showcase experimental observation of NH dislocation bound states (NHDS) and the dislocation-induced NH skin effect in two-dimensional acoustic NH Chern lattices. By embedding edge dislocations in such acoustic lattices and implementing precision-controlled hopping and onsite gain/loss via active meta-atoms, we reveal robust defect-bound states localized at dislocation cores within the line gap of the complex energy spectrum. These NHDS survive against moderate NH perturbations but gradually delocalize and merge with the bulk (skin) states as the system arrives at the shore of fostering exceptional points in the Brillouin zone under periodic (open) boundary conditions. Furthermore, our experiments demonstrate that the dislocation core can feature weak NH skin effects when its direction is perpendicular to the Burgers vector in periodic systems. Our findings pave an experimental pathway for probing NH topology via lattice defects and open new avenues for defect-engineered topological devices.