Papers

Magnetic interactions have long served as the most robust and widely used approach for realizing nonreciprocity, with an externally applied magnetic field breaking time-reversal symmetry (TRS) and chiral photon-magnon interactions introducing spatial asymmetry. In this work, we investigate the chirality mechanisms essential for magnetic nonreciprocity from a unified experimental and theoretical perspective. We begin by examining conventional chiral interactions that generate chiral electromagnetic fields through specially designed structures, and then place particular emphasis on synthetic chirality enabled by nontrivial phase accumulation in traveling-wave-mediated coupling systems. We establish a microscopic theoretical framework that maps field polarization onto the phase of a complex coupling strength and validate it with systematic experiments, thereby providing a consistent formalism that describes both conventional and synthetic chirality. Notably, we highlight the symmetry properties and the unique features of synthetic chirality that distinguish it from conventional nonreciprocal mechanisms.

We study finite-temperature $P$-form $\mathbb Z_N$ homological codes via an exact finite-Trotter quantum-to-classical map to a $(d+1)$-dimensional spacetime model with electric and magnetic topological background charges. The resulting background-resolved partition functions admit an exact reformulation in terms of closed magnetic and electric defect polymers, with opposite-species interactions governed by linking phases. By bounding this complex polymer gas by positive same-species hard-core majorant gases, we obtain an explicit low-activity criterion under which all background-dependent partition functions are uniformly controlled and homologically nontrivial polymers are exponentially suppressed on the scale of the spacetime systole. We also derive an exact higher-form Kramers-Wannier duality exchanging electric and magnetic backgrounds, Wilson and 't Hooft operators, and $P$-form and $(d-P)$-form theories. Finally, for prime $N$, we identify an exact source-free gauge-theory specialization coupled to the plaquette random-cluster model, which imports sharp phase-transition results on special geometries into the spacetime framework.

Diamond and gallium nitride are complementary semiconductors for forming p-n junctions because of their respective doping limitations. Understanding the band alignment of grafted diamond/GaN heterojunctions is therefore essential for optimizing diode performance. In this study, the band alignment of diamond/Al2O3/GaN and diamond/Al2O3/SiNx/GaN heterostructures was determined by X-ray photoelectron spectroscopy. Both structures exhibit type-II band alignment, but with different band offsets. The band offsets of the diamond/Al2O3/SiNx/GaN heterojunction are larger by 0.42 eV than those of diamond/Al2O3/GaN. This difference is attributed to a modification of the interfacial electrostatic potential, which may arise from a reduced density of positive fixed charges in the interfacial dielectric near the diamond/Al2O3 interface after insertion of the SiNx layer. These results demonstrate that interfacial-layer engineering provides an effective strategy for tailoring the band alignment of grafted diamond/GaN heterojunctions, offering guidance for the design of p-n diodes with tunable rectifying characteristics.

Modeling the dynamical flows on networks of biomolecular machines often entails computing node populations and edge fluxes with Master Equations and correlating machine performance with entropy production. But this alone is not sufficient for design, optimization and evolution because it doesn't treat cost-benefit tradeoffs, or small-system misflows (backsteps, futile cycles, ineffective actions), or differential properties for flow design. Here we develop CFT Design, based on the recently developed Caliber Force Theory (CFT). We apply it to: designing faster molecular motors through “traffic control”; optimizing speed, energy, and accuracy in kinetic proofreaders; and designing better enzyme inhibitors. CFT Design provides a general framework for optimizing nonequilibrium flow networks.

We present a theoretical analysis of valley pseudospin control in the transition metal dichalcogenide (TMD) monolayer by utilizing the magnetic proximity effect of 2D magnetic layer and, propose self-consistent analysis of photoluminescence (PL) polarization peculiarities in TMD/magnetic material van der Waals heterostructures. We attribute observed peculiarities to the interplay between spin-dependent interlayer charge transfer and intervalley scattering of excitons and trions. The ratio between the electron tunneling timescale and the exciton and trion intervalley scattering lifetimes and radiative lifetimes determine the PL dynamics. A possibility to switch PL polarization sign due to the quasi-particles dynamics under circularly polarized laser excitations is revealed. We also discuss generalization of the proposed model due to the careful analysis of both intervalley and intravalley scattering processes between bright and dark excitons. Obtained results allow a long-distance manipulation of exciton and trion behaviors and open the possibilities for the effective control under spin and valley pseudospin in multilayer magnetic-semiconductor van der Waals heterostructures.

Magnetic skyrmions are topologically protected spin textures in ferromagnetic materials that hold great promise for both classical information storage and processing, as well as for fault-tolerant quantum computing. Realizing practical skyrmion-based devices demands an energy-efficient and precise method for their flexible manipulation. In this paper, we theoretically propose such a tool, leveraging the magnetoelectric effect induced by a localized electric field generated by one or several charged tips. Combining complementary numerical simulations and analytical approaches, we develop a consistent theory describing the stability and dynamics of Néel-type skyrmions under the influence of the electric field from a charged tip. Specifically, we demonstrate that the electric field can create, drive, and annihilate skyrmions of both chiralities, as well as more complex textures such as skyrmioniums and target skyrmions. We identify several distinct dynamical regimes of skyrmion motion near the tip and map them onto a phase diagram. Finally, we discuss the feasibility of a practical device capable of controlled skyrmion manipulation based on this principle.

The current catalyst discovery and development pipeline for energy-intensive applications like methane conversion remains bottlenecked by expensive trial-and-error experimentation, irreproducible chemical intuition, and a lack of frameworks linking complex catalytic design spaces to performance. This work presents an interpretable machine learning framework that integrates SHAP-based feature importance analysis (Explainable AI) with tree-based ensembles (Random Forest and Bayesian-optimized CatBoost) to characterize Fe-zeolite and oxide-supported catalysts for the partial oxidation of methane (POM). Despite limited data, the framework decodes complex structure-performance relationships by identifying and ranking thermodynamic, structural, and geometric microdescriptors that influence the electronic band gap and govern macroscale performance metrics such as selectivity, activity, and stability. This work explicitly demonstrates that thermodynamic lattice stability and geometric factors are the primary drivers of electronic band gap (a critical proxy for redox reactivity) rather than bulk stoichiometry. Non-linear models achieve an R2 of 0.61 - 0.77, significantly outperforming traditional linear baselines (R2 = 0.32). This workflow provides both a light-weight generalizable methodology and a prioritized list of physical features for accelerated catalyst screening - and these features can subsequently be integrated into microkinetic and reaction engineering models to create digital twins of complex reactor systems and to enable predictive optimization in autonomous R&D laboratories.

We used angle-resolved Brillouin-Mandelstam light-scattering spectroscopy to monitor surface and bulk acoustic phonons in diamond along the <100> and <110> crystallographic directions across a temperature range from 10 K to 300 K. The frequencies and phase velocities were measured for three types of surface acoustic phonons: Rayleigh waves, shear horizontal waves, and high-frequency pseudo-longitudinal waves. All surface acoustic phonons exhibit weak temperature dependence, with the largest observed change of 1.6% across the examined temperature range. The frequencies of all three types of surface acoustic phonons agree with the theoretical values within the experimental uncertainty. Cryogenic surface-acoustic-phonon data are important for diamond-based quantum sensors, surface acoustic wave devices, and other electronic technologies. Knowledge of surface acoustic phonons can also be used for developing accurate models for thermal transport between interfaces.

We study an exactly solvable model that can be interpreted as an ideal one-dimensional electron gas confined with an anisotropic quantum wire potential of oscillator-shaped profile. The homogeneous nature of the quantum wire is broken by the introduction of the effective electron mass, which changes with radial distance. We solve the problem described both within the canonical and the non-canonical approach. Analytical expressions of the wavefunctions of the stationary states for both cases in terms of the Laguerre polynomials are obtained, as well as the discrete energy spectrum related to these wavefunctions. Additionally, an exact solution to the angular position part of the position-dependent mass Schrödinger equation within the non-canonical approach leads to the angular-part wavefunctions of the even and odd states expressed through the Gegenbauer polynomials. Possible limit relations and special cases are studied too.

Probability spaces are known to undergo a concentration of measure in high dimensions. In particular, if a $K$-dimensional probability distribution is sampled from a $(K-1)$-dimensional simplex with uniform measure, with high probability its empirical distribution of components is logarithmic. Here, we extend this result to the subset of distributions populating level sets of de simplex defined by a fixed Shannon entropy $H_0$. We show that the empirical distribution of components of the large majority of sampled distributions undergoes a phase transition. A critical entropy $H_c \approx \log K - 1 + \gamma $ exists, below which the overwhelming majority of sampled distributions are found in a condensed state, in which a single component captures a macroscopic fraction of the total probability, while the remaining components form a homogeneous incompressible fluid background. We derive the magnitude of the critical entropy, as well as the empirical distribution of components both above and below threshold. These results provide insight into how the level sets of fixed entropy in the simplex are populated.

Crystal generative models mainly learn what stable crystals look like, with little explicit supervision for what makes them stable. We reveal a substantial representation gap between state-of-the-art crystal generative models and pretrained universal machine learning interatomic potentials (MLIPs) via energy probing, and show this gap can be closed by a simple training-time alignment. We propose Crystal REPresentation Alignment (CrystalREPA), a plug-and-play framework that aligns the atom-wise hidden states of generative encoders with frozen MLIP representations through an element-aware contrastive objective, transferring stability-aware atomistic priors with marginal training overhead and no additional inference cost. Across three generative frameworks, ten MLIP teachers, and two benchmark datasets, CrystalREPA consistently improves the thermodynamic stability, structural validity, and structural fidelity of generated crystals. Equally important, we find that an MLIP's transfer effectiveness is poorly predicted by its accuracy on standard leaderboards (e.g., Matbench Discovery) but strongly predicted by the distinguishability of its atom-wise representation space, yielding a practical, accuracy-independent criterion for selecting MLIP teachers for generative transfer. Code is available at https://github.com/Chengqian-Zhang/CrystalREPA.

We introduce a Wannier-type formulation of periodic local vibrational mode theory that yields real-space-localized vibrational modes associated with individual internal coordinates in crystalline solids. These modes are constructed as locally coherent superpositions of wavevector-resolved local modes, yielding a smooth and gauge-consistent real-space representation without the need for additional phase-fixing procedures. The resulting Wannier-type local modes provide well-defined force constants and frequencies that enable robust, chemically interpretable measures of bond and interaction strengths in periodic systems. Moreover, our framework demonstrates that phonon dispersion behavior makes important contributions to the bond and interaction strengths calculated via local vibrational mode theory. We demonstrate the method for representative ionic and covalent systems, including MgO, tetrahedrally-coordinated C, Si, SiC, and two polymorphs of CaCO3. Our framework establishes a direct analog of molecular local modes for fully periodic systems and opens new avenues for quantitative bonding analysis in crystalline materials.

Ferromagnetic solids acquire nontrivial magnetic and caloric properties when the temperature of the structural phase transition approaches the Curie point. Deciphering magneto-structural transitions, i.e. determining their characteristic temperatures and elucidating the related properties, remains challenging. In the present paper, three types of transformational behaviour of Ni50Mn25-xCuxGa25 (x = 6.25, 6.5, 6.75, 7) and Ni50.5Mn18.5Cu6.5Ga24.5 alloys have been identified, arising from small variations in chemical composition: (i) structural martensitic transformation (MT) in the ferromagnetic phase; (ii) magneto-structural phase transition from paramagnetic austenite to ferromagnetic martensite; (iii) MT in paramagnetic phase. The temperature-dependent values of magnetization, M(T), and of magnetic susceptibility, $\chi(T)$, were measured for each alloy. A novel thermodynamic analysis was used to determine the Curie points and MT temperatures. The novelty lies in considering the interplay between structural and magnetic characteristics of the alloys through the impact of the structural transition on the spin-exchange parameter. The theoretical analysis of experimental data revealed that this impact results in a large difference ($\geq$ 50 K) between the Curie temperatures computed for the austenitic and martensitic states of each alloy. The characteristic temperatures, corresponding to the extrema of the dM(T)/dT and $\chi(T)$ functions, were calculated. The correlation of these temperatures with the Curie temperatures and the MT temperatures is not straightforward and depends strongly on the type of transformational behaviour (i) - (iii). The proposed approach provides a robust framework for extracting unmeasurable characteristic temperatures from standard magnetization data, applicable to ferromagnetic Heusler systems and other multiferroic ferromagnetic materials.

The thermal-equilibrium canonical distribution is currently obtained by maximizing the Boltzmann-Gibbs-von Neumann-Shannon entropy $S_{BG}(p)=k\sum^{W}_{i=1}p_{i}\ln 1/p_{i}$ constrained to $\sum^{W}_{i=1}p_{i}=1$ and $\sum^{W}_{i=1}p_{i}\,e_{i}=U$, $e_{1}\leq\ldots\leq e_{W}$ being the energies of the $W$ possible states and $U\in[e_{1},e_{W}]$ their mean value. We revisit a generalized version of this optimization problem grounded in the nonadditive entropy $S_{q}(p)=k\,(\sum^{W}_{i=1}p_{i}^{q}-1)/(1-q)$ (frequently, though not necessarily, $q\in(0,1)$; $S_1=S_{BG}$), and the constraint $\sum^{W}_{i=1} p_{i}^{q^{\prime}}e_{i} / \sum^{W}_{i=1}p_{i}^{q^{\prime}}=U$, $q^{\prime}>0$. Sufficient conditions for existence, strict positivity, and uniqueness of solutions are derived, along with a theorem that enables their closed-form calculation. We apply these results to deepen the understanding of the two standard cases in the literature ($q^{\prime}=1$ and $q^{\prime}=q$), as well as of a new one ($q^{\prime}=2-q$). We prove that these standard cases are the only ones yielding optimizing probability distributions of $q$-exponential form. Furthermore, we define an effective temperature $T_{q,q^{\prime}}$ through a Clausius-like relation $1/T_{q,q^{\prime}}=\partial S_{q} / \partial U$ and derive a Helmholtz-like energy $F_{q,q^{\prime}}=U-T_{q,q^{\prime}}S_{q}$, with the former grounding the validity of the $0^{th}$ Principle of Thermodynamics within this generalized statistical mechanics. Finally, we show that the case with a linear constraint (i.e., $q^{\prime}=1$) with $q\in(0,1)$ (i) preserves the Third Law of Thermodynamics; (ii) can be used to model classical many-body Hamiltonian systems with arbitrarily-ranged interactions; and (iii) resembles features of low-dimensional nonlinear dynamical systems at the edge of chaos.

The rapid progress of electron spin resonance scanning tunneling microscopy experiments has enabled the manipulation of individual adsorbate spin states physisorbed on ultrathin oxide layers supported on metal substrates. Electron resonance requires unpaired spin density on the adsorbate, which can be achieved, for instance, through charge transfer from the supporting substrate. This requires the correct energy-level alignment between the energy levels of the adsorbate and the Fermi energy of the substrate. Experiments on molecules and single atoms adsorbed on metal-insulator systems have revealed complex phenomena, including electronic bandgap narrowing, charge transfer, Fermi-level pinning, and the re-ordering of adsorbate orbitals after charge transfer. Despite these advances, a predictive first-principles approach based on accurate methods such as quasiparticle GW, capable of capturing these effects without the prohibitive cost of full adsorbate/oxide/metal simulations, remains an open challenge. In this work, we present a theoretical approach to determine the energy-level alignment of adsorbates on oxide/metal substrates. Our method transparently exposes all physical processes and strikes a balance between computational cost and accuracy. Ionization potentials and electron affinities of the isolated adsorbates are obtained using GW calculations, electronic bandgap polarization is quantified through the quasiparticle renormalization caused by the substrate, Fermi-level pinning is evaluated within the integer charge transfer model, and work function shifts arising from Pauli pushback or from the adsorbate-metal dipole are determined from the local variations of the electrostatic potential. This computationally efficient framework paves the way for highthroughput screening of molecular qubits and organic electronic interfaces.

How do solute concentration and molecular chemistry govern the transition from membrane saturation to destabilization? We address this using microsecond-scale molecular dynamics simulations of dipalmitoylphosphatidylcholine (DPPC) bilayers with chloroform (CHCl$_3$) and a homologous series of alkanols (methanol, ethanol, octanol) over $0-50\%$ concentrations. Although complete membrane melting is not observed within $1000\, ns$, all systems exhibit clear precursors of destabilization, including enhanced thickness fluctuations, reduced lipid order, and mechanical softening. Chloroform induces pronounced thinning and large fluctuations, consistent with deep, transient insertion. Methanol perturbs primarily the headgroup region, while ethanol shows intermediate behavior with partial insertion. Octanol preserves bilayer thickness at high concentrations due to lipid-like insertion but significantly increases fluctuations and interdigitation. Across all systems, increasing concentration decreases the area compressibility modulus and deuterium order parameter, accompanied by smoothing of lateral pressure profiles, indicating stress redistribution. Free energy analysis reveals increased membrane partitioning and reduced translocation barriers with concentration, strongest for octanol and weakest for methanol. These results demonstrate that membrane destabilization is governed by the interplay of insertion depth, interfacial crowding, and lipid packing disruption.

High-entropy MBenes (HE-MBenes) represent a promising, unexplored class of 2D materials for electrocatalysis. In this work, we present a systematic computational screening of 56 equiatomic quinary HE-MBene compositions from the {Ti, V, Cr, Mo, Nb, Ta, Zr, Hf} pool for CO$_2$ adsorption and electroreduction. Using the Monte Carlo Special Quasirandom Structure (MCSQS) algorithm, we generated disordered M$_1B_1$-type supercells and assessed structural stability via DFT (PBE+D3) in VASP. Of the 56 candidates, 55 passed relaxation, with 45 exhibiting negative formation energies, confirming thermodynamic stability. To efficiently screen CO$_2$ adsorption across disordered surfaces, we developed a machine-learning interatomic potential (MLIP) using the MACE architecture. Fine-tuned on our DFT dataset, the model achieved energy RMSEs of 3.49 and 3.0 meV/atom for adsorbed and pristine sets, respectively. Active sites were identified via PDOS analysis, matching metal d-orbital signatures with CO$_2$ molecular orbitals. The rate-determining step of the CO$_2$-to-CO pathway was evaluated using the computational hydrogen electrode (CHE) model. Short-time structural integrity was assessed via AIMD at 500 K over 2.5 ps; phonon-based stability remains a priority for future work. Our results establish an integrated DFT-MLIP-AIMD framework for the rational design of high-entropy 2D materials tailored for CO$_2$ conversion.

The homogeneous spectral linewidth associated with light-matter interactions is a fundamental descriptor of the optical properties of materials, governed by the quantum dynamics of the condensed-matter system. We discuss here that the homogeneous linewidth measured by means of two-dimensional electronic spectroscopy depends not only on the intrinsic microscopic dynamics of the material, but also on the observable through which those dynamics are projected onto the measurement. In this Perspective, we develop a unified framework showing that identical microscopic dynamics can yield different experimentally inferred dephasing times because different detection operators project different sectors of the nonequilibrium dynamics. For coherent emitted-field measurements, the observed linewidth largely retains its conventional connection to the optical coherence time $T_2$. By contrast, in population-detected modalities such as photoluminescence, photocurrent, and other action-detected two-dimensional spectroscopies, the apparent linewidth can additionally encode excited-state population redistribution dynamics, leading naturally to an effective coherence time $T_{2,\mathrm{eff}}$. Using a coupled-mode model propagated under a common Liouvillian, we show that identical microscopic dynamics yield distinct apparent dephasing times when projected onto coherent-emission and population-derived observables. The detection observable is therefore not merely part of the experimental implementation, but determines what dynamical information remains experimentally observable and how homogeneous linewidths should be interpreted as materials descriptors.

Injection and shift currents are generally regarded as distinct nonlinear optical responses with separate microscopic origins. Here, we uncover a general hidden connection between them through interband Berry-curvature and quantum-metric dipoles. In systems with approximately linear electronic dispersion near the Fermi level and at low photon energies, this relation sharpens into an emergent equivalence, with injection and shift currents governed by the same interband quantum-geometric dipole. This regime is naturally realized in Dirac and Weyl semimetals, as well as in strained graphene, where measurements of injection and shift currents probe a unified geometric property of the electronic wavefunctions rather than distinct dynamical processes. Our results establish a new framework for interpreting nonlinear optical experiments and suggest that quantum geometry may provide a broader organizing principle linking seemingly distinct nonlinear optical responses in solids.

Based on classical concept, solidification of alloys is a direct transition from liquid phase to solid phase, by which dendrites and dendritic segregation are produced. Through in-situ and real time morphology observation and XRD test during solidification of three steels, a new superite phase featured as statistically oriented tiny structures was identified, and a general liquid-superite-solid phase transformation process is revealed. In the early solidification stage, the liquid alloys transit to dendrites composed of superite phase. Initiated from the boundaries of dendritic arms or dendrite grains, the superite phase transits to austenite grains within an initial dendritic arm, and expels solute elements to the residual superite phase. Mixed multi-phase microstructures are subsequently produced from the residual enriched superite phase. Here, although three steels exhibit different phase proportion and phase constitution in the superite-solid transition, they all follow above general transition mode. Multiscale microstructures and segregations are produced in the transition from superite to solid. These new findings change the basic understanding about the solidification of alloys, rediscover the formation mechanism on segregations and multiscale solidification microstructures, including dendrite pattern, solid dendritic arm, dendritic segregation, the mixed multi-phase microstructures, eutectic, inclusions and precipitate. These new findings are also crucial to the control of solidification microstructures and segregation in metals.

Accurate calculation of free energies and their derivatives is central to assessing the thermodynamic stability of molecular and particulate systems across length scales. Yet such quantities can be difficult to compute reliably in strongly interacting systems, such as solutions of ionic species in polar solvents. One important example is the chemical potential of water in aqueous electrolytes, which can be estimated through staged particle insertion by gradually coupling an inserted molecule to its environment. Although the resulting insertion free energy should be independent of the alchemical pathway, the order and manner in which van der Waals and electrostatic interactions are activated can strongly affect convergence and, in some cases, yield inconsistent estimates. Here, we examine this issue by calculating water's chemical potential in aqueous KCl solutions using eight alchemical insertion pathways that differ in the extent and order of van der Waals and Coulombic coupling. We find that concurrently activating these interactions, particularly in fully coupled and partially end-coupled protocols, can produce chemically implausible insertion free energies. These anomalies arise from intermediate states in which the inserted water molecule develops strong electrostatic interactions with a chloride ion before sufficient short-range repulsion has been established. In contrast, pathways that activate short-range van der Waals interactions before electrostatics yield more consistent and chemically plausible estimates. These findings demonstrate that practical alchemical calculations in polar and ionic environments can be highly sensitive to pathway design, underscoring the importance of decoupling short-range and electrostatic interactions in staged insertion alchemical protocols.

The performance of superconducting resonators underpins a wide range of modern quantum technologies, yet their quality factor often deviates at low temperatures from standard Mattis-Bardeen predictions. This discrepancy is often attributed to nonthermal quasiparticles generated by microwave readout power, which limits the sensitivity of superconducting devices. We present a macroscopic model based on modified Rothwarf-Taylor equations that incorporates a power-dependent phonon generation term, providing an explicit relationship between quality factor, bath temperature and readout power. The model shows excellent agreement with temperature sweep measurements of NbN microstrip resonators with e̱ta}-Ta terminations over a wide dynamic range of readout power levels, accurately capturing the transition between thermally-dominated and microwave-induced loss regimes. This framework provides a predictive tool for optimizing superconducting resonators and advancing the design of high-Q devices for quantum sensing and quantum information processing.

Hopfield networks and their generalizations have established deep connections among biological associative memories, statistical physics, and transformers. Yet most models treat retrieval as a fixed query-to-memory mapping, ignoring the role of external context in recall. In this work, we propose a two-stage associative memory architecture, wherein a context-gate subcircuit reshapes the retrieval energy landscape before and during recall. We show theoretically that context gating increases inter-memory separation while inducing sparsity, translating into exponential improvements in retrieval. Crucially, we prove that the system admits a unique self-consistent fixed point, revealing that the resulting retrieval state is driven by both a direct contextual bias and a second-order retrieval-gate feedback loop. We then bridge this theory to transformers; specifically, we evaluate a first-order approximation on Llama-3, confirming that in-context learning acts as context-gated retrieval. Native dynamics mirror our theory: context localizes a memory subspace, enabling the zero-shot query to cleanly discriminate. Ultimately, this framework provides a mechanistic link between associative memory theory and LLM phenomenology.

While magnetic fields and superconductors are both central to classical and quantum technologies, their combined use is often challenging, as magnetic fields significantly affect superconducting device performance. In superconducting nanowire single-photon detectors (SNSPDs), magnetic fields drastically reduce detection efficiencies, hampering their application in magnetically-active classical and quantum photonics. Here, we systematically characterize the performance of NbTiN SNSPDs under magnetic fields and show the enhancement of their intrinsic detection efficiency (IDE) at lower bias currents and its suppression at higher currents. This leads to SNSPD performance degradation through reduced or disappearing saturation plateaus. We show that the magnitude of this degradation is highly dependent on nanowire width and demonstrate width-optimized SNSPDs with saturating IDE for a wide range of photon energies under application-relevant magnetic fields. Minimizing degradation in superconducting devices under magnetic fields enables applications like detector-integrated spin-optic and atomic quantum processors, high-sensitivity magnetometry, and quantum transduction.

We develop a reduced stochastic framework for thermally assisted octupole moment dynamics in Mn3Sn by combining the reduced Landau–Lifshitz–Gilbert (LLG) equation with the Fokker–Planck formalism. The reduced model is benchmarked against the complete three-sublattice octupole dynamics and is shown to capture the essential switching behavior with good accuracy. We then derive the corresponding Fokker–Planck equation, which is implemented and solved via a CUDA-accelerated solver. The analysis shows that the octupole dynamics are highly sensitive to the out-of-plane grid resolution because ultrafast rotation of the octupole is controlled by its very small deviations from the basal plane. The solver is validated against Monte Carlo simulations through equilibrium distributions, relaxation trajectories, and switching times. Finally, we apply the method to thermally assisted field-driven switching and demonstrate efficient access to ultra-low error probabilities beyond the practical reach of direct Monte Carlo simulations.

Chiral phonons act as a phononic conjugate field to net magnetization, enabling phononic detection and control of ferromagnetic order. Whether an analogous phononic coupling exists for the compensated Néel order of antiferromagnets has remained open. Here we show that, in $\mathcal{P}\mathcal{T}$-symmetric antiferromagnets, phonons with sublattice-staggered angular momentum can couple to the Néel vector like a conjugate field. Such coupling can be induced by the molecular Berry curvature-induced gyroscopic coupling between Raman and infrared-active phonons. The gyroscopic coupling is odd under both $\mathcal{P}$ and $\mathcal{T}$ while preserving their product. $\mathcal{P}\mathcal{T}$ symmetry forbids the resulting normal modes to have a net phonon angular momentum (PAM) while allows counter-rotating local motion on inversion-related sublattices, which are dubbed the antiferro-chiral phonons (AFCPs). Reversing the Néel vector reverses the staggered phonon chirality and the sign of the coupling. Our results indicate AFCPs can serve as probes and control knobs of Néel order.

Multiscale modeling is essential for understanding the complex behavior of materials. However, accurately transferring all relevant information from one scale to another has remained an outstanding challenge. Neural operators, discretization-independent generalizations of neural networks, is proving to be a powerful tool in addressing this challenge. This article provides an introduction to neural operators, and illustrates their use in multiscale modeling of materials through three selected examples.

Diffusion with an incorporated resetting mechanism provides a reference framework for modeling a wide range of natural phenomena. Within this framework, the optimal resetting rate is a key quantity that arises from the optimization of the mean first-passage time. While substantial work has focused on the study of the optimal resetting rate in unbounded one dimensional domains, little is still known about the optimization of the mean first-passage time in bounded systems, in particular when multiple resetting sites are available. In this work, we consider a particle diffusing along a circular circumference and under resetting, with an absorbing target site at a fixed location. Using the appropriate free propagator for this system, we compute the Laplace transform of the survival probability when resetting occurs to multiple sites drawn from an arbitrary probability density function. We also calculate the mean first-passage time at the target site, and study the dependence of the optimal resetting rate in terms of the relevant parameters of the system in a two-resetting site configuration. Depending on the arc length between one of the resetting sites and the absorbing target site, and the weight of the remaining resetting site, the optimal resetting rate can exhibit abrupt ("first order”) and continuous ("second order”) transitions. Moreover, the behavior of the mean first-passage time is rich enough to allow both critical and tri-critical points to exist in the parameter space. All the transitions have "mirror symmetry” around the selected target site and its corresponding diametrically opposite site.

Tip-Enhanced Raman Spectroscopy (TERS) can be used to make nanoscale spatial measurements of 2D materials, such as graphene and transition metal dichalcogenides (TMDs). The TERS theory introduced in [L. Cançado et al., Phys. Rev. X 4, 031054 (2014)], however, was tailored for graphene, whose out-of-plane Raman response is neglected. In the present work, we include the out-of-plane response in the TERS theory. In doing so, we provide an exact analytical expression for the field propagation between the tip and the sample, and show that the contribution to the TERS signal that scatters first at the sample, then at the tip (sample-tip, or TS) is important only when the out-of-plane response is significant. We extensively study the variation of TERS experimental measurements when varying physical parameters of the system, like the tip radius, the out-of-plane response, the TERS coherence length, and others. It becomes evident that the TERS enhancement is very sensitive to the out-of-plane Raman response of the phonon mode, while normalized tip-approach measurements are more sensitive to the coherence length, and we show that the medium refractive index leads to an effective tip enhancement factor $f_e$. Our results lead to the conclusion that, in general, a strong TERS enhancement is a necessary condition for investigating the physics discussed here, which here means surveying the difference in TERS signals between different Raman modes. We use our model to analyze some graphene TERS experiments, showing that they are consistent with a negligible out-of-plane Raman response and a nonzero TERS coherence length in the fitting.

Non-radiative decay in photoexcited molecular systems is driven by nuclear motion toward conical intersections (CIs), where electronic states become degenerate and nonadiabatic transitions occur. Identifying the nuclear degrees of freedom responsible for CI access from nonadiabatic molecular dynamics (NAD) simulations remains challenging because the underlying motions are high-dimensional and collective. Here, we introduce an unsupervised, information-theoretic framework based on Differentiable Information Imbalance (DII) to identify the nuclear coordinates governing CI access directly from trajectory surface hopping (TSH) simulations. By quantifying correlations between structural descriptors and electronic observables, including energy gaps and oscillator strengths, the method ranks nuclear degrees of freedom by predictive relevance. A multi-step protocol then extracts low-dimensional, physically interpretable modes associated with non-radiative decay. We apply the framework to the methaniminium cation, furan, L-glutamine, L-pyroglutamine-ammonium, and a photoactive molecular motor. Across all systems, the method recovers known mechanistic coordinates while revealing the relative importance of competing modes when multiple structural distortions contribute to CI access. The analysis also reveals a systematic distinction between observables: energy gaps are typically governed by a small number of localized coordinates, whereas oscillator strengths depend on more collective and distributed structural rearrangements. Overall, the DII-based framework combines predictive power with direct interpretability, providing a general and scalable route for extracting mechanistic insight from high-dimensional NAD data and constructing reduced-dimensional models of excited-state dynamics.