Papers

First-principles studies of superconductivity often neglect anharmonic effects (AHE), despite their crucial role in achieving quantitative accuracy in many materials. To bridge this gap, we introduce a general computational approach, termed anharmonic superconducting density functional theory (ah-SCDFT) which systematically incorporates anharmonic corrections into standard SCDFT. This approach allows for high-fidelity predictions of superconducting properties with only a modest increase in computational cost for a limited number of superconducting calculation convergence steps. We demonstrate the effectiveness and reliability of ah-SCDFT by applying it to the prototypical superconductor MgB2, accurately reproducing its superconducting behavior under both ambient conditions and applied pressure in excellent agreement with experiment. Our results establish ah-SCDFT as a powerful, efficient, and broadly applicable approach for quantitatively reliable studies of superconductivity and a promising tool for the prediction of new superconducting materials.

The iso-orbital indicator $\alpha = (\tau - \tau^\mathrm{vW})/\tau^\mathrm{UEG}$ is a key ingredient of meta-generalized gradient approximation (meta-GGA) functionals, but diverges in low-density tails , causing unphysical exchange potentials and systematic band gap errors as noted in [J. Chem. Phys. 150, 161101 (2019)]. We replace the denominator of $\alpha$ with a physically motivated Pauli KED drawn from the orbital-free DFT literature, eliminating the divergence in the low density atomic tail without any empirical regularization parameter. Testing two such enhancement factors: LKT and PGS, within the r$^2$SCAN and MS2 exchange functionals, we find that the modified indicators suppress spurious oscillations in the semilocal exchange potential and restore correct electron localization in atomic tails. For a ten-member cubic semiconductor benchmark, the band gap mean absolute error is reduced by 41.1 % for r$^2$SCAN@PGS and 48.8 % for MS2@PGS, while cohesive energy accuracy is largely preserved. The consistent improvement across two functionals with distinct constructions confirms a physical rather than functional specific origin, and motivates further development of meta-GGA functionals with constraint satisfying iso-orbital indicators.

Quantitative quantum sensing with shallow electron spins, such as those hosted by nitrogen-vacancy (NV) centers in diamond, requires accurate knowledge of the spin's depth below the host material's surface. A widely used approach infers this depth from the 1H nuclear magnetic resonance (NMR) signal of immersion oil on the diamond surface that can be detected using dynamical decoupling sequences such as XY8. However, finite-width pulses make XY8 sensitive to subharmonic responses, including unwanted contributions from nearby 13C spins, and its instrument-limited spectral resolution provides only sparse sampling of the narrow 1H NMR lineshape. Here, we introduce Spin-Lock NMR as an alternative approach to single-NV depth determination. By tuning the Spin-Lock Rabi frequency to the 1H Larmor frequency, the NV probes the 1H NMR signal through the Hartmann-Hahn resonance without the harmonic ambiguities of pulsed decoupling sequences and with substantially higher instrument-limited spectral resolution. We derive a quantitative Spin-Lock NMR fit function from a Markovian master equation that directly relates the measured spectrum to the NV depth. Our approach yields NV depth estimates in excellent agreement with the established XY8-based protocol across multiple NV centers and establishes Spin-Lock NMR as a robust alternative for quantitative single-NV depth determination. To demonstrate its applicability, we employ our method to investigate the 1H nuclear spin signal that is regularly reported to be present on diamond, even in the absence of immersion oil.

Nonradiative charge transfer processes play a central role in a wide range of physical phenomena, including reliability phenomena in semiconductor devices such as bias temperature instability, hysteresis, random telegraph noise, and trap-assisted tunneling. nonradiative multiphonon (NMP) theory provides a physically rigorous framework for describing such charge transitions, but its full quantum-mechanical formulation is computationally too demanding for large-scale simulations. In this work, we present a systematic and implementation-oriented treatment of NMP-based models for practical large-scale simulations. Starting from the quantum-mechanical foundations of coupled electron–phonon dynamics, we derive computationally efficient approximations for charge capture and emission rates and clearly identify the underlying assumptions and validity regimes. In particular, we introduce an effective crossing-preserving approximation that yields fully analytic, numerically stable, and computationally inexpensive transition rates while retaining the essential quantum-mechanical physics. The resulting expressions are therefore well suited for large-scale device simulations, where capture coefficients must be evaluated repeatedly over broad multidimensional parameter spaces. Furthermore, we derive continuum formulations for transitions between localized defect states and extended electronic bands, enabling direct incorporation into semiconductor-device simulations. The resulting framework bridges microscopic defect physics and practical large-scale simulations of charge transfer processes in complex semiconductor devices. At the same time this work serves as a practical guide for implementing physically grounded NMP-based models, providing both a systematic derivation of the underlying theory and a clear guidance on the validity limits.

Active chiral fluids can support a nondissipative transport coefficient known as odd (or Hall) viscosity. Hydrodynamic descriptions of such fluids typically introduce odd viscosity phenomenologically. How such a response emerges from specific microscopic interactions remains incompletely understood. Here, building on classical shear rheology, we microscopically derive an odd rheological response in active chiral films: thin layers of torque-exerting, elongated particles anchored to a no-slip surface. A canonical realization of such a film is the bacterial carpet, in which flagellated bacteria are tethered head-down to a solid surface while their flagella remain free to spin and inject angular momentum into the surrounding fluid. Using a kinetic theory for the orientational dynamics of these anchored particles, we derive their stress response to an imposed shear flow. We reveal that shear-induced reorientation leads to a flow-aligned polarization and a transverse surface traction from which the odd-viscosity tensor follows in closed form. Numerical solutions of the nonlinear kinetic theory further highlight saturation of the transverse traction at strong shear, driven by shear-induced orientation dynamics – signaling departure from linear response. Our results demonstrate how odd viscosity can emerge self-consistently as a coarse-grained rheological signature of active fluid-structure interaction and establish active chiral films as a new controllable setting for odd hydrodynamics.

Magnetic suppression of the non-Hermitian skin effect (NHSE) offers a viable route for its control. While the NHSE has been realized in various classical-wave platforms, only pseudomagnetic fields (PMFs), which preserve time-reversal symmetry, can be engineered in such systems; however, their interplay with the NHSE remains underexplored. Here, we investigate this interplay in a non-Hermitian honeycomb lattice by considering two distinct mechanisms for generating PMFs: monotonically increasing strain and spatially modulated gain and loss. We show that in both scenarios, PMFs can efficiently suppress the NHSE by driving skin modes into the bulk, accompanied by a reduction of the skin topological area and a contraction of the complex-energy spectrum under periodic boundary conditions. This mechanism is insensitive to boundary details and holds for various edge terminations, including zigzag, bearded, armchair, and twig edges. Our results establish PMFs as a versatile and effective means to control the NHSE, and point toward feasible implementations in a broad range of artificial platforms, including photonic and acoustic metamaterials as well as topolectrical circuits.

The composition-dependent magnetic properties of B2-ordered \zfr~alloys with substitutional disorder on the Fe sublattice are investigated using first-principles calculations within the coherent potential approximation. By systematically substituting Mn and Co on the Fe sublattice, we establish $d$-band filling as the primary control parameter governing magnetic stability in this itinerant system. Mn substitution (hole doping) shifts the Fermi level into the minority-spin bonding states, driving a collapse of spin polarization (crossing zero at $x \approx 0.5$) and the emergence of competing antiferromagnetic interactions ($\eta_\mathrm{Mn} < 0$). Even though the ferromagnetic configuration remains energetically well separated from the G-type AFM-II configuration across the studied range ($\Delta E$ up to $\sim$0.35~eV/atom), this exchange competition drives an “itinerant magnetic softness” that suppresses the Curie temperature by $\sim$450~K – a finite-temperature instability set by the near-cancellation of competing exchange interactions rather than by AFM–FM energy proximity. In contrast, Co substitution (electron doping) acts as a “magnetic hardener” by pinning the Fermi level within the majority-spin pseudogap, preserving high spin polarization ($|P| \approx 0.75$) and stabilizing ferromagnetic exchange across the full composition range. These results show that tuning the Fermi level relative to the pseudogap provides a systematic, microscopic framework for controlling magnetic stability in B2-ordered itinerant magnets, distinct from simple magneto-volume models.

While particle-laden interfaces play a central role in many natural and industrial processes, predicting their mechanical properties remains a major challenge. These systems combine granular characteristics conferred by particle-particle contacts with elastic behavior originating from capillary interactions, making them very sensitive to their history. Using the relaxation of uniaxially compressed particle rafts through a local constriction as a model experiment, we demonstrate the existence of a reproducible and continuous aging process. Aging is observed for both front- and back-compressed rafts and is characterized by a progressive increase in particle mobility and raft deformability. Macroscopic changes are seen, for example, in the extent of relaxation and are correlated with flow modifications observed at the mesoscopic level among which are increased particle fluxes, broader shear zones and enhanced particle rearrangements. While aging can be attributed unambiguously to the constrained passage of the particles through a constriction, its microscopic origin remains hypothetical, the results suggesting that contact lines around the particles may evolve. Beyond providing new insight into the effects of raft history, the proposed constriction flow experiment offers a simple method to control and compare aging in different particulate assemblies.

The shape and arrangement of particles in a material determine its macroscopic properties. The generation of synthetic data with varying particle structure, often represented as 3D voxel images, combined with simulation of macroscopic properties reveals structure-property relations. Most particle generation models focus on single-particle characteristics like shape and size. We aim at fitting the topology of the particle system using tools from persistent homology. However, the large size of the required 3D image data makes existing methods computationally infeasible. We bridge this gap by introducing a novel graph representation of particle systems and transferring the computation of persistent homology from the image domain to the graph domain. This yields a postprocessing method for synthetic images of particle systems, that is independent of the underlying generation method and improves topological and geometrical agreement with real particle systems while preserving morphological characteristics such as the particle size distribution.

We develop an analytical theory of Landau quantization for tilted anisotropic Dirac fermions in an exponentially decaying magnetic field. Using anisotropy scaling and a Lorentz transformation, we recast the laboratory-frame problem into the isotropic Dirac equation in the boosted frame, where the exponentially decaying magnetic-field problem admits an exact solution. Transforming the boosted-frame spectrum back to the laboratory frame yields an implicit quantization condition with an intrinsically energy-dependent guiding-center parameter. We identify the conditions for physically admissible states. We further show that the formalism recovers the known uniform-field spectrum of tilted anisotropic Dirac fermions in the appropriate limit. Our results extend the Lorentz-covariant treatment of tilted anisotropic Dirac fermions to an exponentially decaying magnetic field and reveal the energy-dependent guiding-center structure generated by the inverse transformation to the laboratory frame.

Commercial fusion energy requires materials that survive intense neutron bombardment whilst extracting extreme heat loads for conversion to electricity. The CuCrZr alloy, the leading heat-sink material for fusion reactors, derives its strength from a fine dispersion of nano-precipitates formed during prime-ageing heat-treatment. Whether this precipitation-hardening strategy can withstand fusion-relevant irradiation remains untested. Here we show, combining in situ transmission electron microscopy under heavy-ion irradiation and He implantation with thermodynamic and transmutation modelling, that the hardening precipitates dissolve under two opposing kinetic regimes: ballistic dissolution dominates at low temperatures, whilst dissolution and re-precipitation dominate at high temperatures. Although the accelerated dose rates inherent to ion irradiation shift the balance between ballistic mixing and thermal back-diffusion relative to reactor conditions, precipitate degradation at both kinetic extremes indicates that the prime-aged microstructure is unlikely to remain unaltered under prolonged neutron exposure. He bubbles and Kr-rich voids nucleate once vacancies become mobile, and transmutation over five service years irreversibly redirects the alloy chemistry towards Ni-Zr intermetallics. These three independent mechanisms converge to challenge the strategy on which CuCrZr performance depends, suggesting that the long-term performance of age-hardenable Cu-based heat-sink alloys in fusion reactors warrants further assessment. Our findings reveal a new materials challenge for fusion reactor design and commercialisation: the need for new Cu-based heat-sink alloys able to retain engineered strength whilst their chemistry is irreversibly rewritten - thermodynamically and ballistically - by the fusion neutron spectrum.

While crystals are defined by periodic order, the nature of amorphous solids remains elusive due to their disordered, diverse, and nonequilibrium structures. Here, we focus on jammed elastic packings and systematically tune structure from crystalline to fully disordered to unveil the universal underlying characteristics. We demonstrate that their mechanical properties are universally governed by jamming criticality, featuring characteristic scaling behaviors near the jamming transition, excepting the singular close-packed point. This is facilitated by random nonaffine elasticity arising from contact-level disorder. Consequently, the jamming density can approach close packing, suggesting a fundamental decoupling between jamming criticality and the glass transition physics. Moreover, we uncover a universal coordination-number distribution and contact hyperuniformity in marginally jammed states, independent of particle-level structure. These findings suggest a general organizing mechanism for emergent rigidity in disordered solids, underscore the broad relevance of jamming physics, and complement principles of mechanical self-organization.

Interface-induced superconductivity in FeTe-based heterostructures provides a promising route toward topological superconductivity, yet the roles of the neighboring layers topology, symmetry, and electronic structure remain unresolved. In this work, we employ molecular beam epitaxy to grow Pb1-xSnxTe/FeTe bilayers and use angle-resolved photoemission spectroscopy to track the evolution of the Pb1-xSnxTe layer from a trivial insulator to a topological crystalline insulator hosting multiple Dirac surface states. Electrical transport measurements reveal robust superconductivity throughout the entire composition range, with a nearly constant superconducting transition temperature of ~12 K despite substantial changes in the electronic structure and topology of Pb1-xSnxTe. Double-coil mutual-inductance measurements further reveal comparable superfluid stiffness across the topological phase transition and nearly thickness-independent superfluid stiffness despite large variations in the constituent-layer thicknesses, demonstrating that superconductivity is confined near the interface. These results establish that superconductivity in FeTe-based heterostructures is largely insensitive to the topology, crystal symmetry, and detailed electronic structure of the neighboring layer, supporting a primary origin in modifications to the FeTe layer. The coexistence of interface-confined superconductivity and tunable multiple Dirac surface states in Pb1-xSnxTe/FeTe bilayers provides a versatile platform for exploring topological superconductivity and interactions among multiple Majorana zero modes.

Simulating the nonequilibrium dynamics of interacting open quantum systems remains challenging beyond small system sizes. Quantum phase-space representations provide a scalable approach, but their useful simulation time can be limited by broad distribution tails and the associated boundary terms. We introduce the neural gauge-$P$ representation for open bosonic systems, in which stochastic gauges are parameterized by neural networks and optimized using exact moment equation residuals. For the driven-dissipative Bose–Hubbard model in both single-site and square-lattice settings, the neural gauge-$P$ representation remains accurate during long-time evolution toward the steady state, whereas the corresponding ungauged representation becomes unreliable at substantially earlier times. These results demonstrate the potential of the neural gauge-$P$ representation for accurate simulations of nonequilibrium open quantum many-body dynamics.

The properties of strongly correlated electron materials exhibit a surprising sensitivity to small lattice distortions, providing an opportunity for their tuning by selective distortion driving, usually achieved by optical excitations. Using inelastic electron tunneling in scanning tunneling microscopy, we demonstrate that at the surface of a strongly correlated electron material, we can drive vibrational excitations out of equilibrium, by studying the dynamics of localized modes on the Pd-terminated surface of the delafossite oxide PdCrO2. This surface forms a tiling of hydrogen clusters of varying sizes and shapes upon hydrogen adsorption. Our findings reveal that vibrational excitations in the clusters exhibit longer lifetimes than on typical metal surfaces. Detailed analysis of the spectroscopy data reveals signatures of non-equilibrium effects in the excitations which we attribute to the extended lifetimes of these modes. Theoretical calculations support that the long-lived nature of the excitations is related to the unique properties of the substrate.

How much does an algorithm's running-time distribution under independent randomness reveal about its behavior when independence is no longer guaranteed? We study sources satisfying $\nu[w]\le DP[w]^s$ for every finite prefix $w$, where $P$ is an independent reference law, $0<s\le1$, and $D\ge1$. The constraint controls complete-prefix probabilities while allowing individual choices to be predictable, even fully determined by the past. For retry tasks, all deterministic history-dependent selectors have the same independent-source running-time law. Yet two orders have worst-case failure probabilities $1$ and $\exp[-\Theta(n)]$ at the same linear deadline under the same source constraint. We identify a static priority rule that is optimal at every deadline and every $D$. For the standard local walk on a $k$-CNF with at least $r$ true literals per clause under some assignment, $k/2<r<k$, we determine the sharp source threshold $s_*$. At and above it, the expected flip count is $O_{k,r}(\min\{L^3,L/(s-s_*)\})$, where $L=h+\log D+1$, $h$ is the initial Hamming distance to that assignment, and $L/0=\infty$. The bound allows arbitrary clause overlap and history-dependent clause selection. Matching instances admit one source forcing this delay with probability one for every selector. At criticality and fixed $D$, the delay is cubic despite a linear independent-source expectation. Variable-depth prefix covers, together with classical tree max-flow/min-cut, yield an exact criterion for restoring exponential tails by restarting on the same tape. We synthesize updates and restarts for explicit finite-state processes. Under a sufficient prefix guarantee, we also obtain noisy predecessor search with error at most $\eta$ and expected query count polynomial in the correct leaf's depth and $\log(D/\eta)$, without knowing the depth or tree height.

This study combines high-throughput density functional theory (DFT) calculations with machine learning (ML) to uncover the key descriptors governing the nitrogen reduction reaction in 47 intermetallic compounds (IMCs) composed of Co, Ni, Al, Zn, V, Fe, Cu, and Pt, and the adsorption energies of key intermediates (*N2, *N2H, and *NH3) were systematically evaluated across all accessible surface sites, yielding approximately 1,200 data points. Among the IMCs studied, Fe9Co7 and Fe3Co emerge as the most balanced catalysts, exhibiting favorable adsorption energies across all three intermediates. By incorporating intrinsic material properties along with local and global electronic descriptors including s-, p- and d-band centers and fillings, as well as Bader charges of atoms neighboring the adsorbate, predictive ML models were developed with mean absolute errors (MAEs) of 0.27 eV for *N2, 0.39 eV for *N2H, and 0.17 eV for *NH3 adsorption. Importantly, accurate adsorption-energy predictions were achieved using only 20 key features for *N2H and *NH3 and 38 features for *N2, enabling the use of simple and computationally efficient ML models. SHAP analysis indicates that p-band and s-band characteristics play a more prominent role in determining adsorption strength than the traditionally used d-band center, particularly for *N2. Beyond their established importance in systems containing p-block elements or nearly filled d-band metals, s- and p-orbitals are also found to contribute significantly to transition metal alloy activity such as Fe-Co. By challenging the d-band-centric paradigm and identifying s- and p-band descriptors as critical yet overlooked contributors, this work redefines the electronic descriptor space for intermetallic NRR catalysts and lays the groundwork for DFT-ML-guided discovery of non-noble, compositionally complex materials for sustainable ammonia synthesis.

First-principles calculations are rarely single solver calls: they are multistage workflows in which structures, settings, and saved densities must pass correctly between dependent stages. Language models can write a valid single input, but reliability collapses once stages are chained: a dropped dependency, wrong file handoff, or hallucinated keyword can invalidate results even when the solver runs, and such errors surface only after costly execution. We introduce LatticeMind, a validation-gated agentic framework that converts natural-language requests into executable, checkable density functional theory (DFT) projects. A workflow contract specifies required stages, files, and dependencies; deterministic validators inspect the project before any solver launch; failed checks trigger bounded repair; and reports remain traceable to project files. On a 44-case RESCU benchmark spanning total-energy, density-of-states, band-structure, magnetic, phonon workflows, three non-flagship LLM backends reproduced every reference value; 119 of 132 runs passed on the first validated plan and the rest after one repair cycle. Ablations identify the workflow contract and pre-execution validation as the principal reliability mechanisms; a conventional trial-and-repair baseline reaches 71% at twice the token cost per success. The same architecture reproduces every reference value on a 19-case VASP benchmark, demonstrating transfer across solvers. Beyond these task families, LatticeMind generated and validated the 23 inputs of a multistage study of Rh-induced electronic responses at a Rh$_6$/In$_x$Ga$_{1-x}$N photocatalyst interface. These results establish workflow contracts, deterministic validation, bounded repair, and traceable records as a practical foundation for reliable AI-assisted scientific computing, where preventable errors are caught before execution and the solver is never the first validator.

Simulating societies of many large language model (LLM) agents is expensive, yet the questions asked of such simulations are usually macroscopic: phase behaviour, stylised facts, and scaling with the number of agents $N$, not the cognition of any single agent. We turn a statistical-physics observation into a method: replace each LLM agent by a low-parameter model fitted from a few hundred to a few thousand cheap queries, then run the society at any $N$ on a laptop. Whether this works is decided before the simulation runs, chiefly by what each agent perceives. We introduce an [interaction order x memory] taxonomy that maps perception and memory to an effective theory and a predicted $N$-trend of the surrogate error. We validate it on a faithful reimplementation of the LLM macroeconomy EconAgent and seven further named LLM simulations, with agent decisions cloned from genuine LLM elicitations (primarily DeepSeek) for a few dollars; the predicted error trends hold cell by cell, and the two refuted predictions, both on a strongly saturating response and traced to its curvature, are themselves matched quantitatively by the theory with no free parameters.

Weyl semimetals exhibit anomalous transport controlled by their gapless chiral nodes, while gapped Weyl systems are often expected to lose such distinctive responses. Here we show that Weyl excitonic insulators instead host a new form of axial-field-driven transport that exists only in the massive phase. Starting from the low-energy Breit-type Hamiltonian for a gapped Weyl system coupled to strain-induced axial potentials, we develop a semiclassical wave-packet theory and identify a dissipative transverse current generated by a dynamical axial potential. This response is qualitatively distinct from both ordinary vector-potential transport in gapped systems and axial responses in gapless Weyl semimetals. Physically, it originates from a mass-induced Berry structure of the reconstructed Weyl bands, which becomes active when the system is driven out of equilibrium by a chiral chemical-potential imbalance. We show that transverse sound waves provide a natural route to generate the required dynamical axial field and estimate the resulting current for realistic material parameters. Our results reveal sound-induced Hall transport as a direct probe of Weyl excitonic order and provide a transport signature of interaction-generated mass in Weyl materials.

The disordered and defect-rich structure of amorphous solids forms heterogeneous, high-dimensional energy landscapes. Such an energy landscape can be described by a discrete-state network of transitions between stable energy minima. Under low-frequency mechanical oscillations, defect-mediated, thermally activated transitions provide a microscopic mechanism for mechanical dissipation that are the dominant cause of mechanical loss in the mirror coatings of ground based gravitational waves detectors. Using molecular simulations, we find spatially correlated and strongly interacting transitions that require a general network description instead of a superposition of independent two-level systems as traditionally assumed. An annealing study combined with an analysis of dominant relaxation paths in the energy landscape reveals novel mechanisms for reducing room temperature mechanical loss.

We extend a recent GPU implementation of the finite-temperature Lanczos method (FTLM) for Heisenberg spin Hamiltonians, which uses only total-magnetization symmetry, to the full permutation symmetry, including non-Abelian point and space groups. For highly symmetric clusters such as icosahedral polyhedra, the multidimensional irreducible representations (irreps) of the permutation group reduce the block dimensions substantially further than any Abelian subgroup. Here, we provide a matrix-free formalism (avoiding explicit storage of the projected Hamiltonian) for using such symmetries. The implementation applies equally to Abelian groups, retaining the advantages of GPU acceleration. Several cluster topologies are built in; beyond these, symmetry groups can be supplied as site-permutation generators, with irrep matrices computed automatically, so that user-defined clusters run without any code changes. We demonstrate the approach in production runs on a single NVIDIA B200 accelerator for the s=3/2 Heisenberg antiferromagnet on the dodecahedron (Hilbert-space dimension 4^20 ~ 1.1x10^12) and for the s=1/2 square lattice of 5x8 sites (M=0 dimension 1.4x10^11). With R=24 random vectors per symmetry block and 60 Lanczos steps, the dodecahedron campaign (with the largest iterated symmetry block having a dimension of 3.6x10^9) requires about 50 GPU-hours. The code is openly available under the Apache-2.0 license at https://github.com/ghasdeke/ftlm-pg-gpu, archived at DOI: 10.5281/zenodo.21445872.

Superconducting quantum interference devices (SQUIDs) show exceptional sensitivity to magnetic flux. In scanning SQUID microscopy (SSM), SQUID size and its distance to the sample are minimized in order to map weak magnetic fields with best possible spatial resolution. SQUID-on-lever (SOL) architectures have proven especially effective as SSM probes due to their small sensor size, robustness, and ease of integration with conventional atomic force microscopy hardware. In order to optimize magnetic microscopy carried out with SOL probes and to accurately reconstruct the magnetic fields that they measure, it is essential to know their point spread function (PSF). The size and shape of this PSF are determined by magnetic flux focusing effects, which depend on the characteristic length-scales of the superconductor and the sensor geometry. By simulating the coupling to sources of magnetic flux, this work provides a mathematical description of the SOL PSF, which contains a full description of the probe's magnetic sensitivity and spatial resolution. We then use measurements of a single magnetic skyrmion to measure the magnetic flux response of a real SOL. We demonstrate excellent agreement with flux responses that are obtained from simulations, thereby confirming the calculated PSF and spatial resolution.

We classify the symmetry-constrained forms of the Berry curvature dipole $\mathbf{D}$, gyrotropic magnetic tensor $\mathbf{K}$, and magnetoelectric electro-optic (EO) tensor $\mathbf{G}$, which describe metallic optical and EO effects in time-reversal symmetric, noncentrosymmetric metals. We identify 11 space groups (SGs) in which $\mathbf{D}$ and $\mathbf{K}$ vanish by symmetry while $\mathbf{G}$ remains allowed, thereby providing a more direct route to observing the recently predicted magnetoelectric EO effects associated with $\mathbf{G}$. First-principles based calculations confirm that $\mathbf{D}$ and $\mathbf{K}$ vanish for representative materials, while $\mathbf{G}$ remains allowed and tunable via Fermi level shifting. We further show that the choices of SG and experimental configuration provide complementary paths for isolating $\mathbf{G}$-driven EO effects, including cases where $\mathbf{D}$ and $\mathbf{K}$ are also symmetry-allowed. In an oblique-incidence geometry, the $\mathbf{D}$-driven response produces a helicity-even absorption or gain correction, whereas the $\mathbf{G}$-driven response couples the $s$ and $p$ optical sectors and produces a bias-induced circular dichroism with a characteristic $\sin\theta\cos\theta$ angular dependence. This provides a direct experimental route for separating the $\mathbf{D}$- and $\mathbf{G}$-driven EO signatures in noncentrosymmetric metals.

The nonlinear Hall effect (NLHE) enables the generation of a transverse charge current in nonmagnetic materials with broken inversion symmetry while preserving time-reversal symmetry through the Berry curvature dipole (BCD). However, in crystals with $C_{3v}$ symmetry, the threefold rotational symmetry forces the BCD to vanish, thereby suppressing the intrinsic NLHE despite the presence of finite local Berry curvature. Here, using first-principles density functional theory combined with Wannier-based transport calculations, we demonstrate that uniaxial strain induces the NLHE in monolayer Janus AsTeBr by lowering the crystal symmetry from $C_{3v}$ to $C_{1}$ and generating a finite BCD. The resulting anisotropic redistribution of Berry-curvature hotspots produces pronounced nonlinear Hall conductivity and nonlinear Hall current, with the maximum response obtained at 2% tensile strain. To elucidate the accompanying electronic-structure evolution, we further investigate the strain-dependent optical properties through the joint density of states, dielectric function, optical absorption, and reflectance. The optical spectra exhibit a systematic red shift and enhanced low-energy interband transitions, consistent with the strain-induced reconstruction of the electronic structure. Our results establish a microscopic connection between symmetry breaking, Berry-phase geometry, nonlinear Hall transport, and optical response, demonstrating that uniaxial strain provides an effective strategy for tailoring multiple functional properties in Janus two-dimensional materials.

Quantitative prediction of rapid-solidification microstructures requires phase field models that represent the velocity dependence of interfacial properties, including solute partitioning, kinetic liquidus response, solute drag, and kinetic undercooling. These response functions control both microsegregation and morphology selection, but are difficult to prescribe accurately in phase field simulations that employ enlarged interfaces for numerical efficiency. We introduce an optimization-based calibration strategy that embeds target sharp-interface response functions into a dilute alloy phase field formulation by treating the interfacial diffusivity interpolation function as a response-matching degree of freedom. The optimized diffusivity functions are obtained from one-dimensional steady-state phase field solutions constrained to reproduce prescribed continuous-growth-model targets for velocity-dependent solute trapping and drag-modified liquidus kinetics. We demonstrate the accuracy and versatility of the calibrated model in dilute Al-Cu by reproducing the prescribed response functions for intermediate solute drag coefficients relevant to rapid solidification. Two-dimensional simulations are carried out over a range of drag coefficients and pulling velocities relevant to additive manufacturing, demonstrating that quantitative changes in the prescribed interface kinetics can systematically shift the morphology from cellular to banded growth. Additionally, we extend the formulation to dilute multicomponent alloys, enabling independent specification of equilibrium partition coefficients and liquidus slopes for multiple solute species. The framework separates the physical specification of nonequilibrium interface kinetics from their diffuse-interface realization and provides a practical route for embedding response functions into quantitative phase field computations.

We develop a path-integral-based field theory for deriving Breit-type low-energy Hamiltonians for gapped Dirac systems coupled to both vector and axial gauge fields. Treating the mass gap as the large energy scale, we integrate out the high-energy component of the Dirac spinor and obtain a canonical Schrödinger description for the remaining low-energy degrees of freedom. For the ordinary Dirac equation, our method reproduces the conventional Breit Hamiltonian order by order. In the presence of axial gauge fields, however, the resulting Hamiltonian contains additional vector-axial couplings that have no analogue in the traditional electromagnetic case. We illustrate the method using three- and two-dimensional Dirac models and discuss its relevance to gapped Weyl systems, where dynamical axial fields can generate distinctive low-energy transport signatures.

Richards' equation for unsaturated water flow is derived from the kinetic theory of the pore-filling distribution g(r,x,t) of a companion paper. It separates two limits that macroscopic theory usually conflates. The spatial limit is purely kinematic: contracting the representative elementary volume (REV) to a point yields the closed continuum kinetic equation (CKE) d_t g + div F = C[g], with F a pore-resolved pre-closure flux and C[g] the occupancy-gated redistribution operator. The dynamics lies in the temporal limit, the subject of this paper: a Chapman-Enskog (CE) reduction of the CKE controlled by the Damkohler number Da (redistribution time over forcing time), the structural analogue of the passage from Boltzmann to Navier-Stokes. The linearized redistribution operator J is self-adjoint and negative semidefinite in the mass inner product, with a one-dimensional kernel fixing a single invariant (water) and hence one macroscopic equation; the CE hierarchy inverts the same J at every order, only the source changing. Four results follow: the equilibrium step defines the retention curve; the linearized water budget plus the inter-REV source set the first-order equation; its solvability is mass conservation, i.e. Richards' equation; and the response function gives the macroscopic flux, identifying the conductivity K as a first-order transport coefficient, the counterpart of viscosity. Mean-field reduction recovers the standard integral formula; the serial-path correction gives Mualem's heterogeneity penalty. A bimodal pore-size distribution opens a gap in the relaxation spectrum; projecting onto the bands and applying CE within each, with cross-band relaxation surviving at O(1), derives the dual- and multiple-permeability models from first principles, the exchange coefficient set by inter-band connectivity. When Da is not small the expansion breaks down and the full CKE is needed.

We investigate colored $\Delta_T$ noise, i.e., finite-frequency $\Delta_T$ noise, as a probe of edge-mode (EM) transport in quantum Hall and quantum spin Hall systems. Colored $\Delta_T$ noise probes finite-frequency nonequilibrium current fluctuations and dynamical transport properties that are often obscured in DC measurements of conductance and noise. Since $\Delta_T$ noise is driven solely by a temperature and voltage bias under zero average charge current conditions, it eliminates current-induced Joule heating and directly probes intrinsic thermal fluctuations. We show that chiral, spin-conserving helical, and spin-flip helical (trivial) EMs exhibit distinct colored $\Delta_T$-noise signatures under appropriate bias protocols. Incorporating energy-dependent scattering through a quantum point contact, we demonstrate that electron-hole asymmetry significantly modifies the finite-frequency spectrum while preserving these distinguishing features. Notably, colored $\Delta_T$ noise exhibits a frequency-dependent sign reversal absent in the corresponding white ($\omega=0$) $\Delta_T$ noise. We further investigate zero-temperature colored quantum shot noise and find that it vanishes identically for chiral EMs, whereas the spin-conserving helical response changes sign with frequency. By contrast, spin-flip helical (trivial) EMs exhibit a positive colored shot-noise spectrum. However, the corresponding colored $\Delta_T$ noise retains its characteristic sign reversal, providing a robust distinction between spin-conserving helical and spin-flip helical (trivial) EM transport. These results establish colored $\Delta_T$ noise as a robust, experimentally accessible, complementary probe for identifying chiral, spin-conserving helical, and spin-flip helical (trivial) EM transport in mesoscopic topological systems.

We employ machine learning techniques to estimate the amount of information contained in three Krylov-space observables: the spread complexity $C(t)$, the discrete Wigner negativity $N(t)$, and the normalized negativity $\chi(t)=N(t)/|S(t)|$, where $S(t)$ is the survival amplitude. We study thermofield-double evolutions on GUE, GOE and Poisson spectra, and on the integrable $SL(2,R)$ Krylov chain of a two-dimensional CFT primary, with Lanczos coefficients $b_n=\alpha\sqrt{n(n+2h-1)}$. To introduce chaos we add a GUE random matrix to the integrable chain, $H(\varepsilon)=H_{SL(2,R)}+\varepsilon R_0 W_{GUE}$, where $R_0$ is its spectral half-width. Either $C(t)$ or $N(t)$ alone determines the thermofield temperature, with $R^2\simeq0.999$. However, neither can reconstruct the fine structure of the spectral form factor. In the integrable sector all three observables carry the same information. When we turn on chaos an asymmetry appears: $\chi$ predicts $C$ better than $C$ predicts $\chi$. This gap grows from $+0.33$ to $+0.77$, while the same gap for the raw negativity decays to zero. The extra information comes from the survival amplitude, and $\chi(t)$ carries it while $C(t)$ can still be recovered from $\chi(t)$. We derive a lower bound on this gap, set by the fraction of the variance of $\chi$ that comes from $S$.