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Physics Condensed Matter

cond-mat Watch Condensed Matter

Saturday 19 September

Mesoscale and Nanoscale Physics

Collective depinning of dipolar skyrmion chains: thermal and athermal rounding of an elastic polymer in a quenched landscape

R. L. Silva, R. C. Silva and R. L. Stamps

The dynamics of interacting dipole skyrmion chains in a weak pinning landscape is studied through numerical solutions of the stochastic Thiele equation. Chains of different lengths with periodic boundary conditions are driven across quenched attractive pinning sites under different magnetic fields. A clear threshold spin current is identified as the critical depinning force. Three main results emerge: (i) for chains of 50 skyrmions or more, the depinning threshold is independent of chain length and remains close to one third of that of an isolated skyrmion. (ii) The transition rounding is only partly thermal: the width changes from w = 0.334 +/- 0.004 decades at T = 0 to 0.633 +/- 0.002 at 300 K, while the intrinsic Larkin correlation length remains about 2.6 bonds below kBT ~ V0/25. (iii) The width is nearly unchanged up to kBT ~ 0.14 V0, but increases almost fourfold by kBT ~ 0.23 V0, mainly through broadening of the creep regime. It is independent of chain length, ruling out finite-size rounding. Increasing the field from 30 to 40 mT changes the transition shape, widening its core by 26% while shortening the creep tails. For chains of about 200 skyrmions, depinning proceeds through a sequence of internal deformations - growth of the Larkin length and roughness, transient bond stretching, and subsequent recovery of mobility and Hall angle. These collective effects are relevant for skyrmion-based devices in which chains, rather than isolated textures, act as information carriers.
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Soft Condensed Matter

An active soft glassy rheology model

Raffaele Mendozza, Tobias Müller and Peter Sollich

Biological materials such as the cytoskeleton and confluent cell monolayers are active, dense systems continuously subjected to internal stresses and strains, making their rheological characterization essential. While activity in soft matter can be modeled across multiple length scales, its mechanical consequences remain strongly model dependent and no unified theoretical framework has yet emerged. Here, we study the rheology of dense active amorphous materials using the Soft Glassy Rheology (SGR) model, incorporating activity at the mesoscopic scale of local elements as a stochastic strain rate that is persistent on some timescale $\tau_p$. We show that activity opens a long-time relaxation channel, driving a crossover from SGR-like power-law rheology to Maxwell-like behavior at the lowest frequencies. Combining analytical arguments in limiting regimes with numerical simulations, we characterize the resulting fluidisation time scale and its dependence on the activity parameters, which shows strong analogies with effective temperatures introduced elsewhere that similarly encode activity-induced fluidisation. Our active SGR model provides a minimal mesoscopic route to understanding how driving by activity modifies the rheology of dense amorphous materials.
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Strongly Correlated Electrons

Correlation-assisted spin-selective metallicity in strained and bilayer altermagnets

Marnin J. Di Nunzio, Frank Lechermann and Ilya M. Eremin

Altermagnets combine vanishing net magnetization with a momentum-dependent spin-split electronic structure, providing a route to spin-polarized carriers without ferromagnetism. Here, we investigate how electronic correlations, doping, uniaxial strain, and interlayer coupling control altermagnetism within a minimal Hubbard-type model for mono- and bilayer systems. Comparing Hartree–Fock theory with the rotationally invariant slave-boson (RISB) approach, we demonstrate the robustness of altermagnetic order against quasiparticle renormalization and reveal a separation between the onset of magnetic order and the loss of quasiparticle coherence at stronger coupling. In the monolayer, doping produces a pronounced particle–hole asymmetry, while its combination with uniaxial strain generates a fully spin-polarized Fermi surface close to half-filling. In the bilayer, stacking that favors ferroic alignment of the layer altermagnetic order parameters allows their momentum-dependent spin splittings to combine constructively. Weak asymmetric doping additionally induces intra-unit-cell charge order, resulting in fully spin-polarized low-energy carriers. At a bilayer filling of five electrons in four orbitals, we find a continuous paramagnet-to-altermagnet transition followed, at stronger coupling, by an evolution toward a Mott-like regime with strongly suppressed quasiparticle weight. Our results establish correlations, strain, doping, and stacking as complementary means of controlling altermagnetic metals and generating fully spin-polarized Fermi surfaces.
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Mesoscale and Nanoscale Physics

Magnetic Quadrupole Lens and Current-Induced Quadrupolar Dynamics of Antiskyrmion

Linfeng Du, Yang Liu, Peng Yan et al. (+1 more)

We demonstrate that antiskyrmions can serve as magnetic quadrupole lenses that focus or defocus electric currents traversing them. We showcase the antiskyrmion core as a focal point where electron beams converge for specific injection directions, leading to anisotropic and nonuniform current distributions. Thus the current-induced antiskyrmion dynamics is profoundly modified by the magnetic quadrupole lensing via the spin-transfer torque. By incorporating quantum transport and micromagnetic simulations iteratively, we self-consistently capture the coupled dynamics of conduction electrons and antiskyrmions. Our results unveil a quadrupolar antiskyrmion Hall effect that is highly anisotropic with respect to the current direction and can be effectively tuned by the spin-orbit coupling. In particular, the current focusing (defocusing) dramatically enhances (suppresses) the antiskyrmion speed while simultaneously reducing its Hall angle, thereby overcoming a key challenge for antiskyrmion racetrack memories. Our work establishes the intrinsic current lensing as a powerful mechanism for manipulating topological magnetic textures and opens new avenues for antiskyrmion-based spintronic devices.
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All authors Linfeng Du, Yang Liu, Peng Yan, Ying Su

Superconductivity · Cross-listed from quant-ph

Performance optimization of cascaded traveling wave Josephson parametric amplifiers

Ilari Lilja, Ekaterina Mukhanova, Stanislav Khaldeev et al. (+3 more)

Traveling-wave parametric amplifiers (TWPAs) based on Josephson metamaterials provide broadband gain with near-quantum-limited added noise. Whereas long nonlinear metamaterial devices can deliver high gain, short arrays suffer less from dissipation, pump depletion, and internal standing waves which can degrade noise performance. Here, we demonstrate a cascaded TWPA architecture that combines the advantages of both approaches by employing a short (736-element), low-dissipation Superconducting Nonlinear Asymmetric Inductive eLement (SNAIL)-based TWPA as the first amplification stage, followed by a conventional long (1632-element) TWPA that provides additional gain. The resulting amplifier cascade achieves nearly 30 dB of total gain over a tunable bandwidth of approximately 1 GHz while maintaining added noise close to the quantum limit. Our results establish a cascade of TWPAs as a practical approach for high-gain, broadband, quantum amplification with applications in quantum information processing, multi-mode entanglement, and quantum sensing applications at microwave frequencies.
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All authors Ilari Lilja, Ekaterina Mukhanova, Stanislav Khaldeev, Ilya Golokolenov, Visa Vesterinen, Pertti Hakonen

Mesoscale and Nanoscale Physics

Non-Hermitian Topology from Edge Transport in Hermitian Quantum Anomalous Hall Systems

Humian Zhou, Ming Lu, Chui-Zhen Chen et al. (+1 more)

Non-Hermitian physics, known for exotic phenomena like exceptional points and the skin effect, has been most prominently realized in engineered systems relying on controlled gain and loss. Here we show that it can also arise naturally as an intrinsic transport response of a globally Hermitian quantum anomalous Hall system, without the need for external non-Hermitian engineering. We show that the interplay between unidirectional chiral edge modes and diffusive normal edge modes induces intrinsic non-reciprocal transport described by a continuum Hatano-Nelson model. Consequently, the non-Hermitian skin effect is encoded directly in experimentally accessible Hall-bar observables: the electrochemical potential and local heat dissipation acquire chirality-dependent exponential spatial profiles, while the longitudinal conductance decays exponentially with system size and the Hall conductance remains quantized. Using Landauer–B{"u}ttiker simulations, we confirm these transport signatures and identify magnetic topological insulators as a realistic platform for an intrinsic non-Hermitian transport response. Our results bridge non-Hermitian topology with mesoscopic transport, opening a pathway toward non-Hermitian topological devices in solid-state systems.
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All authors Humian Zhou, Ming Lu, Chui-Zhen Chen, X. C. Xie

Soft Condensed Matter

Apparent Breakdown of the Stress-Optic Rule in Rigid-Rod Suspensions: A Stress-Partitioning Interpretation

William Kai Alexander Worby, Yuto Yokoyama, Misa Kawaguchi et al. (+1 more)

A fundamental problem in the field of anisotropic macromolecular materials concerns how the flow-induced orientational order connects microscopic structure to macroscopic rheological stress and optical anisotropy. This study considered cellulose nanocrystal suspensions as rigid-rod model systems for the purpose of isolating orientational effects from chain stretching. Simultaneous rheo-optical measurements of birefringence, orientation angle, and shear stress were combined with a Fokker-Planck orientation model and stress decomposition. Our results show that, at low values of the Peclet number, birefringence and total stress exhibit proportionality similar to the stress-optic rule. However, the concentration dependence indicates that this proportionality reflects stress partitioning rather than a unique material coefficient. With increasing flow strength, orientational saturation is accompanied by a reduced relative Brownian stress contribution and a corresponding change in the total stress-based relation. Referencing the optical response to an estimated Brownian stress contribution yields a substantially more unified response across concentrations and flow conditions, supporting a stress-partitioning interpretation of apparent stress-optic rule breakdown.
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All authors William Kai Alexander Worby, Yuto Yokoyama, Misa Kawaguchi, Yoshiyuki Tagawa

Materials Science

From Local Atomic Motifs to Thermodynamic State: An Interpretable Physics-Informed Framework for Cu-Zr Metallic Glasses

Prashil S. Joshi

Machine-learning models that relate local atomic structure to the thermodynamic state of metallic glasses typically assess physical consistency after training rather than enforcing it during learning. Here, we develop a multi-task physics-informed neural network (PINN) that predicts temperature directly from Voronoi-motif population histograms while incorporating autograd-derived gradient constraints representing physically motivated relationships between structural motifs, quench rate, and temperature. The model simultaneously classifies each configuration as liquid, supercooled/transition, or glass through an auxiliary classification head. The classification task achieves 96.6% test accuracy with a macro-F1 score of 0.95, while the regression head yields a mean absolute error of 23.4 K on a trajectory-disjoint held-out test set. Five-fold trajectory-grouped cross-validation, deep-ensemble predictions, and Monte Carlo dropout are used to assess model robustness and predictive uncertainty. Sensitivity analyses demonstrate that physics constraints can be incorporated over a broad range of loss weights without compromising predictive accuracy, while substantially improving compliance with the prescribed physical trends. Benchmarking against conventional machine-learning regressors further demonstrates competitive predictive performance. SHAP analysis across the cross-validation ensemble identifies the coupled near-icosahedral motif family, particularly the full icosahedral motif and its single-atom-perturbed counterpart, as the dominant structural fingerprints of the glassy state. These results demonstrate that physically motivated constraints can be embedded directly into motif-based structure-property models, providing a pathway from post-hoc interpretability toward physically constrained machine learning for metallic glasses.
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Materials Science · Cross-listed from quant-ph

Efficient creation of shallow NV$^-$ ensembles by high-angle ion implantation

Kento Sasaki, Hideyuki Watanabe, Tokuyuki Teraji et al. (+3 more)

Negatively charged nitrogen-vacancy (NV$^-$) centers located a few nanometers below the diamond surface are key quantum defects for nanoscale sensing of external spins. However, the creation of shallow NV$^-$ centers with high yield remains a materials challenge. Here, we demonstrate that high-angle ion implantation enhances the creation efficiency of shallow NV$^-$ centers. By implanting $^{15}$N ions at angles exceeding 60$^\circ$, we achieve high NV$^-$ yields approaching 10% with effective NV$^-$ depths below 10 nm. These yields are significantly higher than those typically reported for shallow NV$^-$ creation. The enhanced NV$^-$ yield is consistent with an increased vacancy-to-nitrogen ratio in the near-surface region, which is expected to promote NV formation during annealing. The created NV$^-$ ensembles show coherence properties comparable to those of single shallow NV$^-$ centers at similar depths, and allow detection of nuclear spins in van der Waals materials attached to the diamond surface. Our results establish geometric control of ion implantation as a simple and broadly applicable approach to engineer shallow vacancy-related quantum defects.
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All authors Kento Sasaki, Hideyuki Watanabe, Tokuyuki Teraji, Takashi Taniguchi, Kenji Watanabe, Kensuke Kobayashi

Disordered Systems and Neural Networks · Cross-listed from physics.plasm-ph

Interaction renormalization and the plasma staircase

Alexander V. Milovanov, Alexander Iomin and Jens Juul Rasmussen

We resolve an existing question concerning dynamical and structural stability of the E {\times} B staircases in magnetically confined fusion plasma. The problem has stirred considerable interest in the literature due to a unique combination of its scientific and practical aspects. Here, we report a new approach to the problem by combining the paradigmatic Hasegawa-Wakatani model of electrostatic drift-wave turbulence with an idea of interaction renormalization, imported from quantum field theory. It is shown based on the Schrödinger-Newton equation with renormalized interaction constant that the plasma staircase is robust and stable as soon as the nonadiabaticity parameter, {\delta}, goes above a certain critical value, and is unstable otherwise. This critical value is an exact result of the interaction model and is found to be {\delta}c = {\pi}. For {\delta} < {\delta}c , the unstable system expands in the radial direction, resulting in a radial second moment that grows with time t as t^(2/3). The results obtained bear important implications with regard to the implementation of arrays of semipermeable transport barriers in tokamaks, suggesting a threshold condition for their generation.
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Strongly Correlated Electrons

On the precise boundary of the Néel antiferromagnetic phase in the Shastry-Sutherland model

Rongyi Lv, Xiangjian Qian and Mingpu Qin

The ground state phase diagram of the Shastry-Sutherland model remains controversial. In particular, the nature of the transition between the plaquette valence bond solid (PVBS) phase and the Néel antiferromagnetic (AFM) phase is still under debate. While some studies suggest a direct transition between the two phases, others propose the existence of a narrow intermediate quantum spin liquid regime. To address this issue, we perform large-scale Density Matrix Renormalization Group calculations to determine the Néel AFM phase boundary in the Shastry-Sutherland model. By applying staggered boundary pinning fields and directly measuring the bulk staggered magnetization, and through systematic extrapolations with respect to truncation error as well as careful finite-size scaling, we find that the staggered magnetization remains finite across the controversial region $0.78 \lesssim J_{1}/J_{2} \leq 0.81$, which was suggested to host a quantum spin liquid phase in some studies. Together with the previously established consensus placing the PVBS phase boundary at $J_{1}/J_{2} \approx 0.78$, these results provide evidence against the existence of an intermediate quantum spin liquid phase and support a direct PVBS–Néel AFM transition in the Shastry-Sutherland model.
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Materials Science

Device contacts as spin-state selectors for silicon vacancies in 4H-SiC

Aurora Teien, Maria Mendes Martins, Andreas Gottscholl et al. (+11 more)

Optically addressable defect spins in semiconductors are promising building blocks for scalable quantum technologies. Yet, the consequences of conventional contact schemes used in semiconductor device integration for the quantum spin environment remain largely unexplored. Using the silicon vacancy (V$_\mathrm{Si}$) in silicon carbide (SiC) as a model system, we show that a widely used contact metal, nickel (Ni), intrinsically perturbs the defect spin state and quenches the characteristic emission from the spin-quartet channel of V$_\mathrm{Si}$. Low-energy muon spin rotation further reveals that Ni contacts create a magnetically contaminated region extending at least $\sim$110 nm into the SiC, in stark contrast to non-magnetic contacts such as Ti and Al. Moreover, cross-sectional cathodoluminescence measurements on samples with high defect density demonstrate a suppressed quartet-state luminescence from the V$_\mathrm{Si}$ up to 500 nm beneath the Ni contact. This drastic influence on the defect's magnetic environment is accompanied by the appearance of a signature consistent with photoluminescence from the spin-doublet state of V$_\mathrm{Si}$ under the Ni layer, which was absent in other material stacks. These results establish that standard device configurations can drive quantum defects into unwanted charge and spin configurations, underscoring the necessity of precise design to preserve quantum-grade spin environments in semiconductor devices.
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All authors Aurora Teien, Maria Mendes Martins, Andreas Gottscholl, Axel Erlebach, Piyush Kumar, Erlend Lemva Ousdal, Viktor Bobal, Augustinas Galeckas, Thomas Prokscha, Hannes Kraus, Corey J. Cochrane, Ulrike Grossner, Lasse Vines, Marianne Etzelmüller Bathen

Statistical Mechanics · Cross-listed from physics.comp-ph

Exact ballistic energy transport and emergent XXZ dynamics in an integrable three-state chain

Hanbing Liang and Fujun Liu

We investigate the coupling dependence of ballistic energy transport and the emergent spin dynamics in an integrable Hermitian three-state chain that connects a clock interaction to a highly degenerate flag limit. By constructing a regular $R$-matrix to establish a globally conserved energy current, we analytically evaluate its full variance to obtain the exact, strictly positive leading high-temperature coefficient of the thermal Drude weight and the ballistic growth rate of the energy-correlation second moment. In the strong-coupling limit, the degeneracy is lifted by virtual transitions of a delocalized third-color spectator state, which generates an effective spin-$1/2$ XXZ Hamiltonian with anisotropy $\Delta = -1/2$ and fundamentally selects the all-active two-color sector as the true ground state. For periodic boundaries, this virtual spectator motion introduces a positive length-changing XXZ supercharge squared that, for $L\ge4$, strictly annihilates all states within a finite, length-independent energy interval above the ground state. Consequently, we rigorously prove that the full periodic effective theory perfectly replicates the exact low-energy XXZ spectrum, including all state multiplicities, as well as its macroscopic bulk free-energy density.
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Materials Science

Photoresist-Free Lithography via Light-Induced Redox Patterning of Oxide Thin Films

Johannes Frantti, Yukari Fujioka, Christopher Rouleau et al. (+2 more)

Lithographic patterning of nanoscale devices typically depends on photoresists, wet processing and multistep pattern-transfer workflows that impose both environmental and scaling constraints. Focused laser irradiation of (Ni,Co)1+2xTi1-xO3 under a reducing atmosphere drives localized oxygen removal, directly converting the insulating oxide into embedded metallic features without etching or chemical processing. Here we demonstrate a photoresist-free patterning method based on light-induced redox transformations in (Ni0.4Co0.6)3O3 (x = 1) thin films. Our results indicate that the transformation is self-limiting, as the high optical absorption of the emerging metallic phase restricts further energy penetration and confines the reduction front, producing conductive layers with electrical properties comparable to bulk metals. This reversible, orientation-preserving transformation is characteristic of a topotactic redox process, enabling direct nanoscale patterning without photoresists. The process is reversible through re-oxidation and is compatible with standard semiconductor wafer substrates. The role of Ti as a reduction inhibitor is discussed. These results establish a route to direct nanoscale patterning based on controlled redox chemistry, offering a potential alternative to conventional lithography for functional thin-film materials.
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All authors Johannes Frantti, Yukari Fujioka, Christopher Rouleau, Alexander Puretzky, Ilia Ivanov

Superconductivity

Pressure-induced unconventional charge-density-wave states in kagome metal AV3Sb5 (A = K, Rb, Cs)

Zhimian Wu, Linpeng Nie, Ye Yang et al. (+6 more)

Since the discovery of charge density wave (CDW) and superconductivity, kagome metal AV3Sb5 (A = K, Rb, Cs) provides a new platform for exploring novel many-body quantum phenomena. In CsV3Sb5, a stripe-like CDW with commensurate wave vector q = 3/8 was observed under moderate pressures, which leads to a peculiar superconducting double-dome behavior in pressure-dependent phase diagram. Previous density functional theory (DFT) calculations indicate that the pressure-induced stripe-like CDW is beyond conventional phonon softening scenario, suggesting a nontrivial role of electronic correlations. However, an in-depth understanding for the pressure-induced unconventional CDW remains elusive. Here, we performed pressure-dependent 51V nuclear magnetic resonance (NMR) measurements on KV3Sb5 and RbV3Sb5. Although the superconducting double-dome behavior is absent in pressurized KV3Sb5 and RbV3Sb5, a pressure-induced CDW phase, ascribed to a possible incommensurate triple-Q CDW, is identified by NMR spectra in both materials, indicating that the pressure-induced unconventional CDW beyond DFT calculations is a common feature for kagome metal AV3Sb5. In contrast to the stripe-like CDW, the pressure-induced incommensurate triple-Q CDW does not strongly suppress the superconducting temperature (Tc) but coincide with an almost plateau behavior at intermediate pressure regime in the pressure-dependent superconducting phase diagram. Furthermore, by systematically analyzing the Korringa relation between Knight shift and nuclear spin-lattice relaxation rate in AV3Sb5, van Hove singularities (vHSs) driven electronic fluctuations are revealed as an effective knob for the pressure-induced unconventional CDW. Finally, our present findings underscore the pressure-induced unconventional CDW as a novel correlated quantum state in kagome metal AV3Sb5.
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All authors Zhimian Wu, Linpeng Nie, Ye Yang, Kuanglv Sun, Huachen Rao, Dan Zhao, Zhongjun Li, Tao Wu, Xianhui Chen

Superconductivity

Comment on "Topography of Fermi arcs in t-PtBi$_2$ using high-resolution angle-resolved photoemission spectroscopy" arXiv:2503.08841 (cond-mat)

Sergey Borisenko

Angle-resolved photoemission spectroscopy (ARPES) and scanning tunneling spectroscopy have established surface superconductivity in the Weyl semimetal t-PtBi$_2$, whereas O'Leary et al. concluded from an independent ARPES experiment that superconducting signatures are absent above 3 K. Here we reanalyze the complete deposited data of O'Leary et al. Using only experimentally determined momentum-distribution-curve (MDC) maxima, energy-distribution-curve (EDC) peak positions, and leading edges, we find a strongly anisotropic low-energy gap and dispersion back-bending that closely reproduce the magnitude and angular dependence reported independently by Changdar et al. We further show that the temperature-dependent data of Ref.~\cite{Oleary} originate from the other surface termination and were presented using temperature-dependent energy translations, momentum translations, and momentum rescalings. Registering the original temperature-dependent datasets using the metallic bulk Fermi cutoff reveals finite gaps of approximately 2, 2, 1, and 0.8 meV at the four Fermi crossings. Thus the independently acquired data of O'Leary et al., obtained on different samples and with a different photon energy, confirm rather than contradict the previously reported anisotropic superconducting gap and additionally show that an anisotropic low-energy suppression persists to 19 K.
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Materials Science

Three-dimensional atom-by-atom measurement of interface diffusion dynamics

Doojin Park, Hyesung Jo, Yongmin Kwon et al. (+7 more)

Diffusion at interfaces governs how materials and devices form, evolve and function. It is usually measured through smooth concentration profiles and bulk transport coefficients, which average over the discrete atomic rearrangements. At nanoscale interfaces only a few atomic layers wide, however, such coarse-graining obscures the local three-dimensional (3D) atomic transport, and scalar diffusion coefficients cannot fully describe species-, layer- and facet-resolved redistribution. The essential observable is the discrete 3D redistribution of atoms themselves, beyond an averaged profile. Here we combine micro-electro-mechanical systems (MEMS) pulse-quench heating with atomic electron tomography (AET) to reconstruct five 3D atomic configurations of the same coherent Pd@Pt core-shell nanoparticle, each corresponding to a well-defined thermal state. Species-conserving one-to-one assignment links neighbouring configurations, and labelled reference simulations correct the displacement bias caused by indistinguishable same-species atoms. The corrected Pd diffusivities follow Arrhenius behaviour, giving an apparent activation energy of 1.10 eV, consistent with migration-limited vacancy-mediated transport. Atomic-layer transition statistics further show that increasing 3D mobility can coexist with declining net chemical transfer and reveal facet-dependent pathways hidden by the scalar diffusivity. Together, these measurements establish a 3D atom-by-atom framework that connects identity-corrected mobility to species-, layer- and facet-resolved transport at buried nanointerfaces.
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All authors Doojin Park, Hyesung Jo, Yongmin Kwon, Seokjo Hong, Jaewhan Oh, Youngjoo Whang, Eunjik Lee, Gu-Gon Park, Sang Woo Han, Yongsoo Yang

Statistical Mechanics · Cross-listed from nlin.AO

Discrete-time Kuramoto model with phase lag: Linear stability analysis and onset of synchronization

Prashant M. Gade and Shamik Gupta

We investigate the discrete-time version of the Kuramoto model with phase lag, which comprises globally-coupled phase oscillators of distributed frequencies that are evolving under a nonlinear map. In the continuum limit of an infinite number of oscillators ($N\to \infty$), we derive the exact Frobenius-Perron equation for the time evolution of the single-oscillator probability density, and study linear stability of the incoherent state. Instability signals onset of synchronization. The corresponding synchronization threshold is obtained analytically for the case of a Lorentzian distribution of the oscillator frequencies. The threshold differs from that of the continuous-time Kuramoto model, reflecting the fundamentally different stability conditions for discrete-time maps and continuous-time flows. Beyond synchronization threshold, we observe several interesting nonlinear phenomena: Unlike the classical Kuramoto model, the discrete-time version exhibits periodic and chaotic states. Numerical simulations of the finite-$N$ system confirm the analytical prediction for the synchronization threshold, while highlighting breakdown of the celebrated Ott-Antonsen ansatz invoked to conveniently study the continuous-time Kuramoto model in terms of a low-dimensional description.
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Mesoscale and Nanoscale Physics

Electrical Probing of Dark Excitons through Microwave Permittivity

Alex Stram, Zhida Liu, Ziheng Zhang et al. (+17 more)

Excitons in atomically thin semiconductors are almost always probed through their optical signatures, because the short lifetimes of these transient quasiparticles are generally assumed to preclude electrical detection. Here we show that photoexcited excitons in monolayer tungsten disulfide produce a large, optically tunable permittivity at gigahertz frequencies, and that the effect provides a contact-free electrical route to imaging dark excitons at the nanoscale. Using laser-illuminated microwave impedance microscopy, we find that high-purity encapsulated flakes exhibit a purely dielectric response resonant with the exciton spectrum, whereas defect-rich samples are governed by conventional photoconductivity. Spatial mapping of diffusion and sublinear power dependence identify long-lived dark excitons as the dominant contributors, and first-principles modelling of exciton polarizability reproduces the measured susceptibility. Our results establish excitons as optically tunable dielectric elements and introduce microwave microscopy as a direct electrical probe of dark-exciton transport with sub-100 nm resolution.
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All authors Alex Stram, Zhida Liu, Ziheng Zhang, Yangchen He, Xuejian Ma, Kyoung Pyo Lee, Lisa Frammolino, Fuxiang Chen, Robert J. Boyd, Sirapas Tangton, Anand Swain, Kan Yao, Kenji Watanabe, Takashi Taniguchi, Yuebing Zheng, Chih-Kang Shih, Daniel Rhodes, Li Yang, Xiaoqin Li, Keji Lai

Materials Science

GRAINSMITH: A Generator of Polycrystalline Models for Atomistic Simulations with Statistical and Grain-Boundary Morphology Control

Oguzhan Orhan and Soner Özgen

Atomistic studies of grain-boundary engineering, grain-size effects and dopant enrichment require reproducible models with prescribed microstructural features. We present GRAINSMITH, an open-source Python package for generating statistically controlled polycrystalline models with selectable grain-boundary morphologies for molecular dynamics and subsequent relaxation. Within supported feature combinations, a single configuration specifies grain-size and volume distributions, crystallographic texture, boundary-area-weighted disorientation-angle distributions, phase composition and grain-boundary dopant placement. Crystal construction supports 230 crystallographic space groups. Periodic Voronoi and volume-targeted Laguerre tessellations provide planar boundaries, while distinct geometry backends generate smoothly curved and band-limited self-affine boundaries. A registry of twenty-six checks assesses applicable inputs, construction properties and outputs. Each run exports LAMMPS data and Extended XYZ files together with structural and statistical descriptors and machine-readable provenance. For a fixed software version and computational environment, the configuration and random seed determine byte-reproducible atomic configurations and scientific data across supported worker counts. By combining statistical specification, boundary-morphology control and reproducible atomistic output, GRAINSMITH supports systematic studies of microstructural effects and quantitative comparisons across generated models.
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Friday 18 September

Materials Science · Cross-listed from cs.LG

Hybrid Machine Learning-Assisted Raman Spectroscopy with Generative Feature Augmentation for Pharmaceutical Identification

Quach Thi Thai Binh, Ton Nu Quynh Trang, Thang B. Phan et al. (+2 more)

Rapid and reliable identification of pharmaceutical residues is important for safeguarding public health, ensuring food safety, and enabling practical Raman-based screening. In this study, we propose HyMLRaman, a hybrid Raman spectroscopy framework that combines deep spectral feature extraction, generative models, and classical machine-learning classifiers to identify six pharmaceutical compounds, including amoxicillin, chloramphenicol, ciprofloxacin, tetracycline, ibuprofen, and paracetamol. Raman spectra are converted into spectral images and encoded with several deep neural-network backbones, among which EfficientNet-B3 yields the most effective representation. The resulting 1536-dimensional embeddings are then used to train downstream classifiers, including SVM, KNN, logistic regression, random forest, XGBoost, and ANN, using stratified 10-fold cross-validation. The hybrid EfficientNet-B3–SVM configuration achieves the strongest baseline performance, reaching 96.31% accuracy and a macro-F1 score of 96.36%, outperforming the standalone CNN baseline. To address limited-data conditions, a generative model, a DDPM-based feature augmentation, is introduced in a PCA-reduced EfficientNet-B3 latent space. The low-data ablation results show that DDPM augmentation provides selective benefits, particularly for KNN with reduced training fractions, and that its effect remains classifier-dependent. Finally, an application-level Raman Pharmaceutical Analyzer demonstrates the feasibility of embedding the trained model into an interactive Raman analysis workflow. These results suggest that HyMLRaman provides a practical and interpretable route for rapid Raman-based pharmaceutical screening.
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All authors Quach Thi Thai Binh, Ton Nu Quynh Trang, Thang B. Phan, Vu Thi Hanh Thu, Nguyen Tuan Hung

Statistical Mechanics

Migration Flows: Population Scaling and Heavy Tails

Cook Hyun Kim, Sangjoon Park, Seoyoung Jin et al. (+1 more)

We show how migration between counties in different cities can explain both the population scaling of mean intercity flows and heavy-tailed intercity net-flow distributions. Density-dependent departure and arrival activities determine how mean flows scale with the populations of the origin and destination cities. We assume Gaussian county-pair net flows with standard deviations proportional to their mean directional flows. At a fixed correlation between county-pair net flows, their sum is Gaussian. Averaging this conditional Gaussian density over the correlation distribution can produce an intermediate power law with a Gaussian cutoff. We also present a stochastic model that generates the variance distribution used in this mixture.
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All authors Cook Hyun Kim, Sangjoon Park, Seoyoung Jin, Jaiyong Lee

Materials Science

Thermally Robust and Strongly Pressure-Responsive NIR Luminescent Manometer Based on Cr3+-Ni2+ Emission

Weijia Xie, Maja Szymczak, Tongxi Luo et al. (+3 more)

The increasing demand for highly sensitive luminescent manometers capable of precise pressure determination, particularly those operating in the near-infrared (NIR) spectral range, motivates the continuous search for new pressure-responsive luminescent materials. In this work, we introduce NaLu2Ga3Ge2O12:Cr3+, Ni2+ as a highly sensitive NIR luminescent manometer in which pressure not only induces pronounced spectral shifts of the Cr3+ and Ni2+ emission bands but also strongly modulates their relative luminescence intensities. Remarkably, the 3T2(3F)->3A2(3F) emission band of Ni2+ exhibits a record-high absolute pressure sensitivity of SA = 34 nm GPa-1. Furthermore, by appropriately selecting narrow spectral ranges within the pressure-responsive emission bands, a ratiometric NIR luminescent manometer was developed, providing a maximum relative pressure sensitivity of SR = 158% GPa-1. Most importantly, the proposed ratiometric readout exhibits a thermal-invariance manometric factor (TIMF) of 19,900 K GPa-1, which, to the best of our knowledge, is the highest value reported to date for a luminescent manometer. The combination of exceptionally high-pressure sensitivity, NIR operation, and remarkable resistance to thermal interference establishes NaLu2Ga3Ge2O12:Cr3+, Ni2+ as a highly promising luminescent pressure sensor for reliable pressure determination under conditions involving simultaneous temperature variations.
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All authors Weijia Xie, Maja Szymczak, Tongxi Luo, Chan Wang, Lukasz Marciniak, Xinguo Zhang

Materials Science

Multimodal Visual Sensing of Temperature and Pressure: From Spectroscopic Readout to Multiple Linear Regression-Enhanced RGB Analysis

Maja Szymczak, Yufan Meng, Guanjun Xiao et al. (+4 more)

Transforming a single luminescent host into distinct temperature- and pressure-sensing systems through composition control provides a powerful route toward multifunctional optical sensors. Here, we introduce a concentration-tunable KGaGeO4:Bi3+,Eu3+ platform whose sensing function can be selectively directed toward thermometry or manometry by adjusting the dopant balance. Spectroscopically distinct Bi3+ centers and Eu3+ emission exhibit differentiated responses to temperature and pressure, enabling multimodal readout through ratiometric luminescence, chromaticity coordinates, spectral shifts, and visible color changes. Importantly, these color changes were translated into quantitative temperature and pressure maps using RGB imaging combined with multiple linear regression (MLR). By simultaneously exploiting multiple color channels, MLR increased the maximum relative thermal sensitivity from approximately 1% K-1 for conventional RGB ratios to 8.8% K-1 and the pressure sensitivity from 169% GPa-1 to nearly 721% GPa-1. This work presents the first application of MLR-assisted RGB analysis for quantitative luminescence pressure sensing. The proposed strategy integrates composition-controlled functionality, multimodal spectroscopic sensing, direct visual readout, and data-assisted imaging, demonstrating the synergy between material engineering and multivariate analysis for highly sensitive multifunctional optical sensing.
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All authors Maja Szymczak, Yufan Meng, Guanjun Xiao, Miguel A. Hernández-Rodríguez, Iga Sawaryn, Bo Zou, Lukasz Marciniak

Materials Science

Highly Lattice-Mismatched Selective Area Epitaxy and Coalescence of PbSe Nanostructures on GaAs

Ashlee M. García, Hosni A. Kaissi, Jarod E. Meyer et al. (+9 more)

Selective area growth of PbSe has the potential to realize deterministic placement of high-density, defect-tolerant nanostructure networks toward a scalable quantum platform. PbSe is a narrow bandgap semiconductor with advantageous (opto)electronic properties that has been shown to have a desirable defect-tolerance, enabling bright emission even when grown on highly-dissimilar platforms, and could be leveraged in combination with selective growth for site-selective quantum emitters and low-disorder hybrid nanowire networks. In this work, we achieve site-selective growth of well-faceted and ordered PbSe nanostructures, despite a large 8% lattice mismatch. Structural and morphological characterization reveal that $>$99% of selectively grown islands within 100 nm opening are single-orientation and cube-on-cube oriented with sub-nm root-mean-square surface roughness. Defect analysis showed that 74% of the islands and 86% of the coalesced regions between different mask openings were free of threading dislocations. These PbSe islands achieved equivalent emission in the mid-infrared despite having a higher surface-to-volume ratio than the planar control. Further, we present a gate-tunable two-terminal Josephson junction fabricated from the PbSe nanowires grown with conditions identified in this study. The combination of the accessible selective growth regime, morphological control of island growth and demonstrations of optical and electrical transport properties indicates promise for PbSe SAG as a defect-tolerant scalable quantum platform.
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All authors Ashlee M. García, Hosni A. Kaissi, Jarod E. Meyer, Kira J. Martin, Maksim Gomanko, Laura A. Stern, Pooja D. Reddy, SeongJin Park, Wilson J. Yánez-Parreño, Sergey M. Frolov, Vlad S. Pribiag, Kunal Mukherjee

Disordered Systems and Neural Networks

Extreme-Scale Ising Machines with Cluster Mean-Field Theory

Xiuqi Zhang, Shuvro Chowdhury, Shaila Niazi et al. (+3 more)

Scaling analog and digital Ising machines to larger problems requires overcoming finite device capacity and the cost of communication between devices. We present cluster mean-field theory (CMFT), a framework that partitions a large interaction graph into clusters sized to fit available hardware. Each cluster performs local updates independently, while interactions across cluster boundaries enter through periodically updated effective biases computed from boundary-spin averages. To reduce the error introduced by fixed cluster boundaries, we introduce dynamic partitioning, which cycles through multiple partitions so that interactions approximated by mean fields at one stage can act through instantaneous spins at another. On three-dimensional spin glasses and planted Pegasus instances, dynamic CMFT exhibits power-law decay of residual energy over sweep budgets. This shows that solution quality continues to improve with computational effort despite the mean-field approximation. An automated graph partitioner combined with a weighted recovery ratio provides a practical heuristic for selecting partition combinations on graphs without natural cut directions. We demonstrate CMFT on four GPUs with approximately four million p-bits, reaching comparable energy densities up to 15 times faster than a single-GPU implementation of the full graph. By coupling locally evolving clusters through programmable effective biases, CMFT provides a route to extreme-scale Ising machines on both analog and digital hardware.
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All authors Xiuqi Zhang, Shuvro Chowdhury, Shaila Niazi, Christian Z. Pratt, Navid Anjum Aadit, Kerem Y. Camsari

Strongly Correlated Electrons

Probing $d$-wave pairing in the $t$-$t'$-$U$ Hubbard model with tensor-backflow wave functions

Xiao Liang

Building on the recently developed tensor-backflow method, which accurately describes energies and stripe states in the Fermi-Hubbard model, we investigate $d$-wave pairing in the two-dimensional $t$-$t'$-$U$ Hubbard model. For the $8\times8$ lattice, we improve the wave function using symmetry projections followed by one Lanczos step, whereas for the $12\times 12$ and $16\times 16$ lattices, we apply one Lanczos step without symmetry projection. We focus primarily on the parameter regime with filling $n=0.875$, on-site repulsion $U=8$ and next-nearest-neighbor hopping $t'=-0.2t$, a regime in which enhanced $d$-wave pairing has been reported. The resulting energies are competitive with those obtained using state-of-the-art neural quantum states. For example, on a $16\times 16$ lattice with periodic boundary conditions, the tensor-backflow wave function after one Lanczos step without explicit symmetry enforcement achieves a relative energy difference of $4.4\times 10^{-3}$ from the symmetry-preserving neural quantum state result. From the real space pair correlations, for $t'=-0.2t$, we observe stronger $d$-wave pair correlations together with the characteristic relative sign between horizontal and vertical bond-pair components. Compared with $t'=0$, finite negative $t'$ increases the spectral weight of the corresponding pair-density matrix, which indicates the enhanced overall $d$-wave pair fluctuations. The leading eigenvalue is enhanced on the $8\times8$ lattice for both with and without symmetry projections. For larger lattices such as $12\times 12$ and $16\times 16$, the leading pair-density matrix spectral weight is distributed among several nearly degenerate eigenmodes rather than being concentrated in a single dominant mode. This indicates enhanced and more broadly distributed $d$-wave pair fluctuations, but no single eigenvalue exhibits the extensive scaling required for ODLRO.
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Materials Science

LiNiO2/NiO Phase Prediction Using Artificial Neural Networks

Jonas Scheunert, Shamail Ahmed, Thomas Demuth et al. (+2 more)

In the realm of material analysis, identifying different material phases is of key importance. Artificial intelligence in the form of neural networks provides a very fast and, once trained, computationally inexpensive method for analysing large amounts of image data, like the sets of diffraction patterns generated during four-dimensional scanning transmission electron microscopy (4DSTEM) dataset acquisition. In this work, we train multiple network architectures on images of this type to distinguish between the phases of LiNiO2 and NiO, an important and challenging distinction in the lithium-ion battery community, since the formation of NiO limits battery capacity. We test both classical convolutional neural networks (CNNs) and different forms of vision transformers (ViTs). Our networks are trained on synthetic images and tested on experimentally recorded diffraction patterns. Additionally, we also investigate the decision-making of our networks using the GradCAM method. We test our networks on both synthetic as well as experimental diffraction patterns. Our networks exhibit very robust results, especially when dealing with highly varying data, an area where traditional template-matching methods typically struggle.
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All authors Jonas Scheunert, Shamail Ahmed, Thomas Demuth, Andreas Beyer, Kerstin Volz

Disordered Systems and Neural Networks · Cross-listed from nlin.AO

Deviations from global coupling in adaptive oscillator networks: a mean-field theory for the variance of coupling weights

Richard Gast, Shotaro Takasu, Juergen Kurths et al. (+1 more)

A wide range of physical and biological systems are adaptive networks, in which the dynamics of the nodes and of the edges connecting them co-evolve. Mean-field reductions of such systems typically track only the average coupling strength, and therefore cannot determine when the coupling stays effectively homogeneous and when structured connectivity emerges. Here, we present a second-order moment closure that allows us to derive mean-field equations for the coupling-weight variance in networks of heterogeneous phase oscillators with adaptive coupling, starting from uniform coupling weights. In agreement with network simulations, we find a nonlinear, non-monotonic dependence of the relative weight variance on the oscillator heterogeneity that is mediated by the phase coherence. Moreover, we find that deviations from global coupling strongly depend on an interaction between the oscillator heterogeneity and the adaptation rule. Whereas symmetric adaptation causes a strongly coupled core of coherent oscillators to emerge and creates a bistable regime that is absent without adaptation, antisymmetric adaptation leads to antisymmetric coupling within the same core, thereby destabilizing it. Our equations therefore delineate the regimes in which adaptive networks behave like globally coupled systems from those in which more complex coupling patterns form.
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All authors Richard Gast, Shotaro Takasu, Juergen Kurths, Ann Kennedy

Strongly Correlated Electrons

Structural and magnetic properties of TbCuAs$_2$ studied by X-ray and neutron scattering

M. G. Kim, T. Heitmann, S. Boney et al. (+8 more)

We investigated antiferromagnetic metal TbCuAs$_2$, which exhibits an anomalous resistivity upturn at low temperatures. This resistivity upturn has been proposed to originate from the material's magnetic ground state; however, the precise nature of the antiferromagnetic ordering in this compound has not been previously established. Here, we present a combined single crystal neutron diffraction, X-ray resonant magnetic scattering, and single crystal X-ray diffraction study of TbCuAs$_2$. These measurements unambiguously determine the Tb magnetic moment direction, the antiferromagnetic arrangement along high symmetry directions, the interplay between structure and magnetism, and their temperature dependence. Our observations are compared with previous studies on sister compounds in the rare-earth copper arsenide family ($R$CuAs$_2$, $R$ = Sm and Gd), which also displays resistivity anomalies. We suggest a common underlying physics governing the structural and magentic properties of rare-earth copper arsenides that exhibit low-temperature resistivity anomalies.
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All authors M. G. Kim, T. Heitmann, S. Boney, C. Neupane, R. Acevedo-Esteves, A. Sapkota, D. Evans, P. C. Canfield, C. Nelson, E. D. Mun, J.-W. Kim