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Physics Condensed Matter

cond-mat Watch Condensed Matter

Sunday 12 July

Statistical Mechanics · Cross-listed from quant-ph

Learning Topological Quantum Phases from Limited Subsystems

Mehran Khosrojerdi, Sougato Bose, Alessandro Cuccoli et al. (+3 more)

Characterizing quantum topological phases requires measuring non-local string order parameters, demanding access to the full system, which is often experimentally unfeasible. In this work, we introduce a data-efficient supervised learning framework that circumvents this limitation by recognizing quantum phases from small subsystems. Our protocol utilizes a quantum kernel constructed from the reduced density matrices of these subsystems, which can be efficiently estimated experimentally. We benchmark our framework with the classification of the phase diagrams of two spin models on one-dimensional lattices, namely the generalized cluster-Ising spin-1/2 chain and the anisotropic Haldane spin-1 chain. Remarkably, our approach achieves high accuracy in phase classification when operations are limited to as few as one to four sites, and it also generalizes to longer chains even when trained on moderate system sizes. These findings demonstrate that local reduced density matrices preserve vital signatures of global topological phases, offering a practical route to characterize rich phase diagrams of quantum many-body systems.
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All authors Mehran Khosrojerdi, Sougato Bose, Alessandro Cuccoli, Paola Verrucchi, Abolfazl Bayat, Leonardo Banchi

Soft Condensed Matter

Enhanced diffusion of colloidal tracers due to enzymatic activity

Mauricio Gomez, Erick Leyva, Justine Miqueu-Petit et al. (+5 more)

Enzymatic catalysis can generate nonequilibrium fluctuations, but how these couple to tracer motion at larger length scales depends on physical context. Here, we investigate colloidal tracers in two configurations: passive particles dispersed in an enzymatically active solution, and enzyme-decorated particles where catalysis occurs directly at the tracer surface. We combine differential dynamic microscopy (DDM), which probes ensemble-averaged long-time diffusion, with optical tweezer (OT) measurements of short-time force fluctuations, and compare several complementary metrics for quantifying activity-induced enhancement. For 1 $\mu$m tracers, we observe activity-induced enhancements in both configurations, with the strongest effects for enzyme-decorated particles, which exhibit enhanced diffusion and increased non-thermal force fluctuations. For 200 nm tracers, enhancements are more subtle and method-dependent: DDM detects modest increases in diffusion for bare particles, while corresponding signatures are not resolved by the OT. These results demonstrate that enzymatic activity can be transduced from molecular to microscale motion and forces, but that the apparent magnitude and detectability of enhancement depend strongly on tracer size, localization of activity, the timescales probed by the measurement, and the metric used to quantify enhancement. More broadly, understanding how enzyme activity modifies transport and fluctuations across scales is important for interpreting nonequilibrium dynamics in active soft matter, intracellular transport, and chemically crowded biological environments.
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All authors Mauricio Gomez, Erick Leyva, Justine Miqueu-Petit, Dakota Feldcamp, Anthony Estrada, W. Benjamin Rogers, Jennifer L. Ross, Wylie W. Ahmed

Materials Science

Nonlinear Tellegen limit

Abhinava Chatterjee and Nikhil Kalyanapuram

The Tellegen limit is the fundamental electromagnetic stability bound on magnetoelectric media. We show that nonlinear magnetoelectric coupling gives rise to a new Tellegen limit, which we term the nonlinear Tellegen limit. Unlike the linear Tellegen limit, which is fixed by material parameters, the nonlinear Tellegen limit is field-tunable – a static electric or magnetic field drives the system toward electromagnetic instability at a material-specific critical field determined by the symmetry-allowed nonlinear magnetoelectric couplings and electromagnetic response. The approach to this limit is accompanied by a field-tunable linear birefringence, whose maximum is bounded by the nonlinear Tellegen limit – beyond which the medium becomes electromagnetically unstable. We demonstrate the nonlinear Tellegen limit and the field-space stability phase diagram in two magnetically ordered material systems – a $d$-wave altermagnet and an M-type hexagonal ferrite – showing that the symmetry of the magnetic point group governs both the structure of the nonlinear magnetoelectric tensor and the resulting electromagnetic instability.
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Mesoscale and Nanoscale Physics

Spectral-Domain Deep Learning of Intrinsic Scattering Operators for Arbitrarily Shaped Compact 3D Particles

Daize Li, Jiafu Shen, Yifei Liu et al. (+2 more)

Rapid prediction of optical scattering from arbitrarily shaped three-dimensional particles is important for particle optics and photonic characterization, but remains challenging because of the large variability of complex morphologies and the strong angular dependence of their scattering responses. To address both issues, a dual spectral-domain neural scattering model is introduced in which morphology and scattering are represented in physically ordered bases: particle geometry is compressed into only 256 spherical-harmonic coefficients, and the optical response is encoded by the complex T-matrix in a spherical-vector-wave basis. The morphology spectrum replaces high-dimensional Euclidean geometry representations, such as voxel grids, point clouds, or meshes, with a compact ordered descriptor, while the T-matrix represents a geometry-determined scattering operator that can be queried for different incidence directions, polarizations, and observation angles. A spectral-token Transformer trained on 50{,}000 irregular particles at 1064~nm maps the morphology spectrum directly to the T-matrix. The predicted operators recover modal structure and reproduce full-angle differential scattering maps and incidence-angle scans. Generalization to out-of-distribution synthetic shapes and natural sand-particle morphologies shows that the dual spectral architecture learns an intrinsic relation from the geometry spectrum to multipolar scattering. This establishes spectral-domain operator learning as a compact route for reusable, angle- and polarization-resolved optical scattering prediction of complex 3D particles.
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All authors Daize Li, Jiafu Shen, Yifei Liu, Bonan Zhang, Heping Xie

Other Condensed Matter · Cross-listed from hep-th

Quantum Horizon and Quantum Membrane Paradigm from Black Hole Quantum Mechanics

Chong-Sun Chu

We develop a microscopic quantum membrane paradigm from the matrix quantum mechanics of black holes [1]. It was proposed that a quantum black hole is described by a fuzzy sphere together with a half-filled Fermi sea of horizon partons. We show that the topology of the fuzzy sphere induces a Berry monopole, providing a microscopic origin for the monopole appearing in the tunneling description of the decay of quantum black hole. Because the partons couple to the fuzzy sphere as fundamental degrees of freedom, they are sensitive to this monopole and form Lowest-Landau-Level (LLL) states rather than ordinary propagating two-dimensional fermions. Their guiding-center dynamics generates Ohmic, Hall, and polarization currents on the horizon. To couple these currents to an external electromagnetic field, we introduce a two-block matrix configuration comprising black-hole, environmental, and bifundamental link sectors. Off-diagonal link modes become tachyonic near the fuzzy sphere and condense, dynamically locking the horizon gauge field to the boundary value of the external Maxwell field. The parton current thereby becomes a physical boundary source for the exterior field. Our construction replaces the fictitious membrane of the classical paradigm with a dynamical quantum membrane populated by microscopic LLL degrees of freedom. The resulting boundary condition generalizes the classical ingoing membrane condition and yields explicit quantum, frequency-dependent, and helicity-dependent corrections, offering a possible probe of the microscopic quantum structure of the horizon.
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Disordered Systems and Neural Networks

Spectral Signatures of Replica Symmetry Breaking in Optimization-Induced Random Matrices

Isaac Pérez Castillo

We study optimization-induced matrix ensembles generated by Gibbs measures. The same quenched disorder that weights configurations also supplies the matrix entries observed on them. For glassy Gibbs measures this raises a natural question: does the induced spectrum inherit the underlying glassy Gibbs geometry? In a dense tensor optimization model we find a selective answer. A single induced matrix has a universal leading bulk that washes out the glassy organization. The difference of two matrices built from independent thermal samples in the same disorder does not: its spectrum gives an explicit image of the glassy Gibbs geometry, encoded by the distribution of mutual overlaps between samples. Parisi theory and Monte Carlo confirm this mechanism across simple and glassy phases.
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Statistical Mechanics · Cross-listed from math-ph

Rigorous bound on the aspect ratio for the formation of a nematic phase in hard rod and hard rectangle systems on $\mathbb{Z}^2$

Qidong He

We prove the existence of a nematic phase in a model of $l\times w$ hard rectangles on the square lattice with two allowed orientations and a large aspect ratio $k:=l/w$. The proof is based on a two-scale cluster expansion method developed previously by Disertori–Giuliani for hard rods in 2D and Disertori–Giuliani–Jauslin for hard plates in 3D. Our main contributions lie in explicitly tracking the constants and parameters and completing the arguments left implicit in these works. Hence, the proof produces a sufficient set of quantitative conditions from which estimates for the required aspect ratio can be extracted. A non-optimized evaluation of these conditions yields the bound $k\ge 10^{72}$. Although it vastly overshoots the numerical prediction, $k_{\min}=7$, our result appears to be the first rigorous estimate of the aspect ratio required for the formation of a nematic phase in hard rectangle systems.
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Materials Science

Surface Variables Description of Axion Topological Materials

Francisco J. Solis and Hugo García-Compeán

We study the response of axion topological materials under the presence of external static electric and magnetic fields. We focus on the macroscopic quasi-static magnetoelectric response of topological insulators. We use techniques based on surface variables that have been previously employed in soft condensed matter problems for the description of heterogeneous systems composed of multiple homogeneous materials. A complete description of the whole system is written in terms of surface degrees of freedom, which in this case correspond to effective surface charge and surface current densities. We obtain a set of integral equations satisfied by these variables. We present exact analytic solutions for axial-symmetric cases. We develop a numerical method for the solution of the integral equations by means of a boundary finite element method. We apply the numerical method to topological insulators with different geometries such as spheres, hollow spheres and toroidal surfaces. We show that that a variational principle can be used to recover the surface variables equations.
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Saturday 11 July

Disordered Systems and Neural Networks · Cross-listed from cs.LG

Learning from Noise: Effective-Rank Collapse and Out-of-Distribution Rejection in Restricted Boltzmann Machines

Oshada Rathnayake and Nikhil Shukla

Restricted Boltzmann machines (RBMs) represent data by shaping an energy landscape over visible and hidden configurations, but their discriminative use is fragile under out-of-distribution (OOD) inputs: samples outside the training distribution can be absorbed into one of the learned class basins rather than rejected. Here, we analyze this failure mode through the spectrum of the induced visible–visible interaction $J=WW^{T}$, where \(W\) is the visible–hidden weight matrix. Relative to a Marchenko–Pastur random-matrix reference, conventional training spreads spectral weight into many weak, bulk-compatible directions, increasing the effective rank of $J$. When auxiliary random binary images are assigned to a rejection label during training, the learned interaction undergoes effective-rank collapse: weak bulk-like modes are depleted, spectral weight concentrates into fewer dominant eigendirections, and the effective rank of $J$ approaches that of the empirical data covariance matrix. The resulting RBM rejects structured OOD image datasets while preserving MNIST classification accuracy, showing that random auxiliary exposure can reshape both the interaction spectrum and the free-energy landscape of an energy-based classifier.
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Statistical Mechanics

A Cascade of Volterra-Operator BBP Transitions in a Correlated Wigner Matrix

Masato Hisakado

We study a Wigner-type random matrix in which the off-diagonal correlation between entries is generated by a random factor shared among all entries in a given row and column, with the coupling strength held fixed as the matrix size grows. Although the bulk spectral moments remain those of the pure semicircle law, we show that the underlying correlation matrix decomposes into a vanishing bulk together with a countable family of outlier eigenvalues that, at fixed rank $k$, converge to the singular values of a compact Volterra (cumulative-sum) integral operator – obtained in closed form via the classical Karhunen–Loève expansion of Brownian motion and confirmed numerically to better than one percent across the top twenty such values. Each singular value drives an independent Baik–Ben Arous–Péché (BBP) transition as the coupling strength increases, producing an evenly spaced, discrete hierarchy of critical points – rather than a single transition – at each of which one further eigenvalue detaches from the semicircle edge, in close agreement with direct diagonalization. We show that this mechanism generalizes to a broader family of correlation structures, with the critical hierarchy in every case set by the spectrum of an associated compact integral operator.
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Mesoscale and Nanoscale Physics

Nonperturbative magnetotransport from band geometry in Weyl semimetals

L. Medel Onofre and A. Martín-Ruiz

We develop a nonperturbative semiclassical theory of magnetotransport in Weyl semimetals, retaining the full magnetic-field dependence of the Fermi-surface conductivity in the presence of Berry curvature and orbital magnetic moment effects. We obtain closed-form expressions valid to all orders in the magnetic field within the semiclassical regime. We show that the exact continuum formulation exhibits an intrinsic infrared sensitivity associated with the singular behavior of the orbital magnetic moment, requiring a physically motivated regularization. While the full conductivity tensor reduces to the standard quadratic magnetoconductivity, we demonstrate that magnetic-field expansion and momentum integration do not commute, leading to nonanalytic contributions at the level of scalar transport coefficients. Our results identify a regime, relevant for low carrier densities or moderate magnetic fields, where magnetotransport becomes intrinsically nonperturbative and cannot be captured by conventional weak-field expansions.
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Superconductivity

Effect of superconducting fluctuations on nonreciprocal dichroism and gyrotropy

Alex Levchenko

We study the spatially dispersive conductivity of a two-dimensional noncentrosymmetric superconductor, demonstrating that it acquires a nonreciprocal, odd-in-wavevector component from fluctuation-induced Cooper pairs above the critical temperature $T_c$. Utilizing time-dependent Ginzburg-Landau theory generalized to include particle-hole asymmetry and the cubic Lifshitz invariant of trigonal superconductors, we compute the Aslamazov-Larkin contribution to the gyrotropic conductivity in closed form, including its complete frequency dependence. The dissipative part describes nonreciprocal directional dichroism: it is odd in frequency and displays a nonmonotonic dependence, peaking at frequencies comparable to the decay rate of fluctuating Cooper pairs. Its Kramers-Kronig dual component describes gyrotropic birefringence, which remains finite in the static limit and is strongly enhanced as the temperature approaches $T_c$, as long as the probe frequency stays below the pair decay rate. Both effects require simultaneously broken inversion and time-reversal symmetries, are dependent on particle-hole asymmetry in close analogy to the fluctuation Hall effect, and trace to the same asymmetric Cooper-pair dispersion responsible for the superconducting diode effect and the giant magnetochiral anisotropy observed near $T_c$. In this regime this critical enhancement dominates over the smooth normal-state gyrotropy, which we evaluate for the same band model as a baseline. Finally, we frame our analysis within the context of gated transition metal dichalcogenides like MoS$_2$, discussing the implications for probing superconducting dynamics through nitrogen-vacancy-center quantum noise spectroscopy.
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Materials Science

Chiral, Electronically Decoupled Layers of 1T'-WS2 Topological Insulator via Neutral-Molecule Intercalation

Jiaze Xie, Fatmagül Katmer, Fang Yuan et al. (+9 more)

Monolayer 1T'-WS2 is predicted to be a two-dimensional topological insulator, but its intrinsic electronic properties are masked by strong interlayer coupling in its metallic and superconducting bulk parent phase, 2M-WS2. Isolating monolayers by mechanical exfoliation is also hindered by this coupling, preventing experimental examination of monolayer properties. Here we show that 2M-WS2 undergoes amine intercalation through a simple wet-chemical reaction, yielding superlattices in which the 1T' layers are structurally preserved but electronically decoupled by neutral molecular spacers. Intercalation expands the interlayer spacing from 0.5 to 1-4 nm and reconstructs the stacking while preserving the intralayer 1T' framework. Controlled (de)intercalation reversibly switches the system between a superconducting metal and an insulator with an activation gap matching that of the isolated monolayer. Density functional theory indicates that the electronically decoupled layers retain the nontrivial Z2 topology of the monolayer. Chiral amine intercalation further induces chiroptical activity in WS2 electronic transitions. Overall, the successful intercalation challenges the long-held view that group VIB dichalcogenides are inert toward neutral-molecule intercalation and demonstrates molecular intercalation as a general chemical route for realizing monolayer-like topological-insulator physics and enabling chiral van der Waals superlattices in bulk single crystals.
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All authors Jiaze Xie, Fatmagül Katmer, Fang Yuan, Jaime M. Moya, Guangming Cheng, Connor J. Pollak, Xiaoyu Song, Nirmal Roy, Yakov Bloch, Moshe Ben Shalom, Jennifer Cano, Leslie M. Schoop

Statistical Mechanics · Cross-listed from hep-th

Krylov Complexity for Time-Dependent Hamiltonians

Amin Faraji Astaneh and Parsa Kafashi

We investigate Krylov spread complexity for states evolving under time-dependent Hamiltonians. For periodically driven systems, we formulate the problem within Floquet theory and show how the Magnus expansion provides a systematic approximation when the Floquet Hamiltonian is not available in closed form. We then extend this framework beyond periodic driving and demonstrate that, in addition to the globally truncated Magnus expansion, a piecewise Magnus expansion provides a reliable method when the global expansion loses convergence or accuracy. Our results provide practical tools for analyzing complexity growth in a broad class of time-dependent quantum systems.
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Soft Condensed Matter

Growing, Buckling, and Swirling: motility from polymerization

Naveen Kumar D, Michael J. Shelley and Brato Chakrabarti

Locomotion in low-Reynolds-number environments is achieved through a remarkable diversity of strategies, from flagellar rotation and ciliary beating to large-scale body deformations. A distinct and biologically important class of propulsion arises when surface-anchored filaments grow and collectively reorient - as seen in the cellulose-extruding bacterium Acetobacter xylinum and in recent experiments on actin-propelled synthetic colloids inspired by the motility of Listeria monocytogenes - suggesting that polymerization itself is a generic route to self-propulsion. Developing a theoretical framework for this class of problems requires simultaneously resolving filament kinetics, their orientational dynamics, and fluid-structure interactions - all self-consistently coupled to the resulting locomotion. To address this, we formulate a continuum framework in which the active forces driving locomotion emerge self-consistently from filament nucleation, growth, catastrophe, and hydrodynamic interactions. We show analytically that polymerization-induced compressive forces drive a long-wavelength buckling instability, leading to spontaneous symmetry breaking of the filament carpet and large-scale flows. In coupling this framework to a force- and torque-free motile spheroidal particle, a wide variety of behaviors emerge - this includes spontaneous spinning, directed motility, and chiral swimming - whose selection is governed by the spatial patterning of polymerizing filaments. These results establish a general theoretical foundation for motility, driven by collective dynamics of polymerizing filaments and point towards new design principles for synthetic micron-scale swimmers.
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Materials Science

Connecting Diffuse Scattering to Atomic-Site-Resolved Occupancy and Displacement Fields through Fourier Filtering

Maksim Eremenko, Victor Krayzman, Matthew G. Tucker et al. (+1 more)

Local structural correlations are encoded in diffuse scattering, but identifying atomic motifs that produce specific diffuse features can be challenging. We introduce MOSAIC, a computational framework for this task when an atomistic configuration is available and a phase-bearing scattering amplitude can be calculated. Our approach relies on applying the Fourier filter to this amplitude over the reciprocal-space regions encompassing the scattering features of interest to obtain maps of atomic displacements and site occupancies responsible for those features. The method is effective in interrogating the nature and spatial distributions of interatomic correlations in large-scale structural models, such as obtained using Reverse Monte Carlo refinements from experimental data, molecular dynamics, or Monte Carlo simulations, or 2D structural projections derived from atomic-resolution electron microscopy images.
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All authors Maksim Eremenko, Victor Krayzman, Matthew G. Tucker, Igor Levin

Materials Science · Cross-listed from cs.CE

Data-efficient continuous conditional denoising diffusion model for microstructure generation

Tarakram Ramgopal, Gowtham Nimmal Haribabu, Hussein Farahani et al. (+2 more)

Traditional computational models, such as cellular automata and phase-field methods, are effective for simulating microstructural evolution but often face computational bottlenecks, limiting their application in high-throughput and on-demand process optimization. Generative machine learning approaches, such as denoising diffusion models, have emerged as powerful tools for surrogate modeling of process-structure maps, specifically producing representative microstructures conditioned on process parameters. However, they often require large amounts of data for training, particularly when process conditions are continuous rather than discrete categorical variables. To address this, we present a continuous conditional denoising diffusion model for generating microstructures conditioned on processing parameters. Trained on a compact dataset of process-microstructure pairs, this framework first adds noise to microstructure images and then trains a neural network to progressively remove the noise, learning the underlying statistical patterns of the microstructure. To address data inefficiencies associated with continuously valued process conditions, we propose a vicinal-loss training strategy that associates process conditions in data-sparse regions with nearby conditions in the dataset. Combined with classifier-free guidance and denoising diffusion implicit sampling, this approach enables data-efficient continuous conditional generation of microstructures compared to classical denoising diffusion models. The model successfully generates representative microstructures for low-carbon steel conditioned on manganese composition, matching key physical features such as phase and grain morphology, grain size distribution, phase fraction, and interfacial area distribution. More generally, this approach opens avenues for efficient process design and optimization of materials and their microstructures.
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All authors Tarakram Ramgopal, Gowtham Nimmal Haribabu, Hussein Farahani, Cornelis Bos, Siddhant Kumar

Materials Science

The evolution of AI from image interpretation toward scientific inference in nanoparticle electron microscopy

Evropi Toulkeridou, Jiafei Li, Leonardo Lari et al. (+1 more)

Artificial intelligence (AI) is transforming electron microscopy by enabling quantitative analysis of increasingly large and complex datasets for nanoparticle characterization. Recent advances in machine learning (ML) and deep learning (DL) have expanded microscopy from a descriptive imaging technique into a data-driven platform for structural interpretation, dynamic analysis, and scientific inference. This review examines AI methodologies for nanoparticle electron microscopy, focusing on transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM), scanning transmission electron microscopy (STEM), and in situ TEM. The discussion is organized around the principal challenges in nanoparticle characterization, including particle detection, segmentation, morphology quantification, atomic-resolution restoration, defect identification, two-dimensional-to-three-dimensional structural inference, and analysis of dynamic processes in situ. We review computational approaches from conventional ML and convolutional neural networks to transformer architectures, self-supervised learning, foundation models, multimodal AI, and physics-informed learning. We further discuss integrating microscopy data with simulations, metadata, and autonomous experimentation to relate nanoparticle structure, dynamics, synthesis conditions, and functional properties. The advantages, limitations, benchmarking, and data requirements of current methodologies are critically assessed. Finally, emerging opportunities for foundation models, AI-guided microscopy, closed-loop experimentation, and autonomous materials discovery are discussed. By integrating advances across computer vision, materials informatics, and electron microscopy, this review highlights the role of AI in next-generation nanoparticle characterization and accelerated materials discovery.
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All authors Evropi Toulkeridou, Jiafei Li, Leonardo Lari, Panagiotis Grammatikopoulos

Statistical Mechanics

Revisiting the non-equilibrium phase transitions of the continuous-trait Axelrod model

Sandro M. Reia, Paulo R. A. Campos and José F. Fontanari

We investigate the non-equilibrium phase transitions of the continuous-trait Axelrod model, an agent-based framework where individual culture is represented by a vector of $F$ continuous features confined to the interval $(0,1)$. Local interactions are governed by a metric similarity threshold $d$, which acts as a continuous control parameter of social tolerance. The dynamics inevitably freeze into one of two absorbing configuration classes: an ordered, homogeneous monocultural state at high tolerance, or a highly fragmented, disordered state at low tolerance. While previous studies characterized the transition as hybrid based on the continuous behavior of the domain density $\mu$ alongside a discontinuous jump in the largest domain fraction $\rho$, we show that this apparent continuity is an artifact of severe finite-size masking effects. By shifting the methodological focus to the scaling of the median $\tilde{\mu}$ and analyzing the full probability distributions $P(\mu)$, we unveil a clear bimodal structure with disjoint maxima across independent simulation runs. Our results reveal that for $F=2$, the system undergoes a genuinely hybrid transition in the contemporary sense, featuring a tiny but finite latent jump ($\mu_c \approx 0.089$) at the critical threshold $d_c \approx 0.0784$ while scaling toward it from below via a non-analytical power law with a mean-field exponent $\beta \approx 1/2$. Conversely, for $F=3$, the higher trait-space dimensionality suppresses local fluctuations, yielding a traditional, non-hybrid first-order transition. We apply this framework to the alternative discrete Poisson variant of the model, successfully confirming its known continuous transition for $F=2$ and discontinuous, non-hybrid transition for $F=3$, thereby establishing a unified characterization of phase transitions in Axelrod-like systems.
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Materials Science

Why Do Thick MOCVD-Grown beta-Ga2O3 Epilayers on (001) Substrates Crack: Crystallographic Origin

Martin Frentrup, Indraneel Sanyal, Dan Lamb et al. (+5 more)

Thick, defect free epitaxial layers grown using industry standard techniques are a fundamental requirement for the widespread adoption of fully vertical power devices based on ultra wide bandgap gallium oxide (Ga2O3). However, metal-organic chemical vapour deposition (MOCVD) of such layers on native beta-Ga2O3 substrates with the largest diameter (001) orientation remains relatively unexplored, and the origins of the reported surface roughening and cracking with increasing thickness are not yet fully understood. To address this, we report a systematic study of MOCVD grown beta-Ga2O3 epilayers deposited at growth rates of ~3.5 um/h, with thicknesses from 0.3 to 3.5 um. The epilayers exhibit a relatively smooth but striated surface morphology, with progressively increasing nanometre-scale roughness beyond coalescence and crack formation observed from ~1.8 um thickness. High resolution X ray diffraction reveals that, despite growth on (001) substrates, the epilayers adopt a predominantly (-401)-oriented structure from the earliest stages of growth. Rocking curve analysis further indicates a higher degree of in-plane twist than tilt, both decreasing with increasing epilayer thickness. While the epilayer and substrate are lattice-matched along the [010] in plane direction, the epitaxial alignment in the orthogonal epilayer [104] in plane direction imposes, in theory, a maximum tensile in-plane strain of approximately +4.1% arising from the underlying lattice mismatch, thereby driving crack formation perpendicular to this direction. Our results suggest that this epitaxial relationship is likely associated with faceted reconstruction of the (001) substrate surface during annealing, driven by the minimisation of surface energy under oxygen-rich MOCVD growth conditions.
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All authors Martin Frentrup, Indraneel Sanyal, Dan Lamb, Ciaran P. Llewelyn, Jonathan Evans, Owen J. Guy, Mike Jennings, Saptarsi Ghosh

Soft Condensed Matter

Numerical analysis of capillarity-driven thinning rheometry for polydisperse polymer solutions

Isaac Pincus, Vincenzo Calabrese, Simon J. Haward et al. (+1 more)

Liquid bridges of polymer solutions that are self-thinning due to the action of capillarity undergo a transition from Newtonian-like linear thinning to exponential elastocapillary (EC) thinning when the polymer chains are stretched by the elongational flow and the resulting elastic contribution to the stress exceeds the viscous stress. As the Oldroyd-B model predicts that the EC thinning rate is set by the relaxation time ($\tau$) of the polymer, the characteristic thinning timescale extracted from the exponential decay ($\tau_{EC}$) is commonly interpreted as a direct measure of $\tau$. Here we show that for real polydisperse polymer solutions, $\tau_{EC}$ reflects only a subset of the molecular weight (MW) distribution – those chains actively stretched by the flow. We demonstrate this using a multi-mode FENE-PM model that explicitly incorporates the molecular weight distribution, validated against the filament thinning experiments of Calabrese et al. [Phys. Rev. X 15, 021025 (2025)] on bidisperse blends of narrowly-distributed low-MW and high-MW polystyrene solutions. The model predicts that only chains with effective Weissenberg number $Wi = \dot{\varepsilon} \tau > 1/2 $ are extended by the flow and contribute elastic stress; this threshold naturally favors high molecular weight species, whose longer relaxation times allow them to remain stretched throughout the elastocapillary regime. The measured $\tau_{EC}$ is therefore set by this stress-contributing sub-ensemble rather than the full distribution. Further, our model predicts that $\tau_{EC}$ depends on both the molecular weight distribution and total polymer concentration, as well as experimental parameters including pre-stretch and initial filament diameter, confirming that it is best understood as an experiment-specific quantity rather than an intrinsic fluid property.
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All authors Isaac Pincus, Vincenzo Calabrese, Simon J. Haward, Gareth H. McKinley

Materials Science

Anomalous Compressibility and Electronic Robustness of Metallic Delafossite PdCoO$_2$ under Pressure

Cheng Peng, Pahuni Jain, Tyler Harper et al. (+2 more)

The layered delafossite PdCoO$_2$ is an exceptional oxide metal whose ultrahigh conductivity arises from a Pd-derived nearly-free-electron band. Here, high-pressure single-crystal X-ray diffraction combined with first-principles calculations is used to investigate its structural, bonding, and electronic evolution up to 10 GPa. PdCoO$_2$ retains the rhombohedral R-3m structure throughout the investigated pressure range, with no structural phase transition. The lattice exhibits an unusual anisotropic compression, with the in-plane a-axis contracting more strongly than the stacking c-axis, opposite to the behavior of most layered materials. Despite this anomalous compressibility, only minor changes are observed in the local Pd-O and Co-O coordination environments, indicating a remarkably rigid bonding framework. Crystal orbital Hamilton population analysis reveals only subtle strengthening of the existing bonding interactions, without the emergence of destabilizing Pd-related antibonding states. Consistent with these findings, the Pd-derived metallic band and quasi-two-dimensional Fermi surface remain essentially unchanged under compression. Boltzmann transport calculations further show that the in-plane conductivity is nearly pressure-independent, whereas the out-of-plane conductivity decreases modestly, resulting in a slight increase in transport anisotropy. These results demonstrate that the anomalous compressibility of PdCoO$_2$ originates from its robust chemical bonding network, which preserves both the crystal structure and the highly conductive Pd-derived metallic state under pressure.
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All authors Cheng Peng, Pahuni Jain, Tyler Harper, Chris Leighton, Weiwei Xie

Mesoscale and Nanoscale Physics

Staggered orbital magnetization from itinerant electrons: orbital antiferro- and ferrimagnetic phases

Lucas L. Lage, Kevin J. U. Vidarte, Tarik P. Cysne et al. (+3 more)

Because electronic orbital angular momentum in solids is inherently non-local, its contribution to magnetism is usually cast in terms of a net orbital magnetization. Here, we show that itinerant electrons can generate orbital magnetic phases with ferromagnetic, antiferromagnetic, or ferrimagnetic orders. We demonstrate this possibility in a honeycomb lattice, using both the standard and a modified Haldane model. Employing real-space formulations, we decompose the itinerant orbital magnetization into sublattice contributions, $M_A$ and $M_B$. Their net ($M_z=M_A+M_B$) and staggered ($M_z^s=M_A-M_B$) combinations are then used to identify the orbital order. By varying the sublattice potential and the Fermi energy, we find distinct regimes: a (PT)-symmetric orbital antiferromagnet in the modified Haldane model, an orbital ferromagnet in the standard Haldane model, ferrimagnetic metallic states where net and staggered orbital magnetizations coexist, and insulating regimes in which the ferro- and antiferromagnetic orbital characters can be interchanged. These findings are explained by a low-energy theory in terms of two distinct valley mechanisms: valley-dependent Dirac masses in the standard Haldane model and valley-dependent energy shifts in its modified version.
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All authors Lucas L. Lage, Kevin J. U. Vidarte, Tarik P. Cysne, Tatiana G. Rappoport, A. Latgé, R. B. Muniz

Superconductivity

Anomalous field evolution of the mixed-state linewidth in the second superconducting dome of LaFeAsO$_{1-x}M_x$ ($M={\rm F,H}$)

Rustem Khasanov, Pierre Dalmas de Réotier, Samuele Sanna et al. (+9 more)

We report a transverse-field muon-spin rotation/relaxation ($\mu$SR) study of the internal-field distribution in the mixed state of LaFeAsO$_{0.89}$F$_{0.11}$ and LaFeAsO$_{0.75}$H$_{0.25}$, representative of the first (SC1) and second (SC2) superconducting domes of the LaFeAsO$_{1-x}M_x$ ($M={\rm F,H}$) family, respectively. Below the superconducting transition temperature $T_{\rm c}$, the linewidth of the internal-field distribution increases in both samples, indicating the formation of a vortex lattice. Above $T_{\rm c}$, the linewidth remains field dependent and increases approximately linearly with field, consistent with broadening of the powder spectrum caused by an anisotropic Knight shift. After subtraction of this normal-state contribution, the superconducting linewidth $\sigma_{\rm sc}$ exhibits qualitatively different field dependences in the two samples. At 4K, the SC1 ($x_{\rm F}=0.11$) sample shows the expected monotonic decrease with increasing field, whereas the SC2 ($x_{\rm H}=0.25$) sample develops a pronounced local maximum near 3T. A contour representation of $\sigma_{\rm sc}(T,H)$ further reveals a ridge of local maxima whose field position, $H_{\sigma,\max}(T)$, shifts to lower fields upon warming and disappears near $T_{\rm c}$. The anomalous field evolution observed in the SC2 sample is consistent with an additional field-induced contribution associated with enhanced Pauli-paramagnetic effects, highlighting the distinct electronic character of the two superconducting domes.
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All authors Rustem Khasanov, Pierre Dalmas de Réotier, Samuele Sanna, Gianrico Lamura, Hubertus Luetkens, Matteo Moroni, Pietro Carretta, Rhea Kappenberger, Rowena Wachtel, Bernd Büchner, Sabine Wurmehl, Nikolai D. Zhigadlo

Materials Science

Oxygen-nonstoichiometry-driven phase transition in $\mathrm{Sr}_{1-x}\mathrm{Nd}_{x}\mathrm{CoO}_{3-\delta}$ ($x = 0.1, 0.2, 0.3$) perovskites

Nina Tereshko, Roman Lanovsky, Olivier Toulemonde et al. (+5 more)

We report a systematic study of the interplay between oxygen nonstoichiometry, crystal structure, and magnetic/electrotransport properties in $\mathrm{Sr}_{1-x}\mathrm{Nd}_{x}\mathrm{CoO}_{3-\delta}$ ($x = 0.1, 0.2, 0.3$). High-resolution neutron powder diffraction combined with synchrotron x-ray powder diffraction reveals that increasing the oxygen content induces a structural transition from a layered $I4/mmm$ ($2a_p \times 2a_p \times 4a_p$) to an oxygen-deficient orthorhombic $Pmmm$ ($a_p \times a_p \times 2a_p$) phases with preferential oxygen-vacancy occupation. This transition is accompanied by a crossover from G-type antiferromagnetic with a weak ferromagnetic component to a ferromagnetic state, and a drastic decay in resistivity. The evolution of the magnetic and transport properties is discussed in terms of changes in the Co spin state, enhanced Co $3d$ - O $2p$ orbital overlap upon oxygen uptake, and a magnetically inhomogeneous ferromagnetic state associated with residual oxygen vacancies and mixed $\mathrm{Co}^{3+}/\mathrm{Co}^{4+}$ valence. Our findings experimentally confirm that the stabilization of the layered "314" structure is driven by the presence and ordering of oxygen vacancies rather than A-site cation ordering, whereas the oxygen-deficient oxidized compounds represent an intermediate orthorhombic state preceding fully stoichiometric phases.
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All authors Nina Tereshko, Roman Lanovsky, Olivier Toulemonde, Maxim Bushinsky, Stanislav Savvin, Vadim Sikolenko, Lingyan Xu, Aleksandr Nikitin

Materials Science

Enabling temperature controlled in-situ vapor dosing for lab source X-ray reflectivity measurements

Erin E. Dunphy, Mara A. Fischer, Sasha R. Neefe et al. (+4 more)

X-ray Reflectivity (XRR) is a valuable technique for probing buried interfaces in complex systems relevant to thin-film, membrane, and battery applications, among others. However, many operando and in situ reflectivity cells are designed for use at synchrotron facilities, limiting the broader accessibility of these measurements. We present an XRR transmission cell that enables in situ vapor dosing and temperature-dependent experiments on in-house diffractometers. We demonstrate its capabilities with two case studies: the adsorption of water into polyamide (PA) membranes on silicon and temperature-dependent restructuring of polystyrene (PS) pseudo brushes on alumina. Vapor dosing allows for controlled release of vapor into the cell, allowing operation across a wide range of conditions from rough vacuum to saturation. We demonstrate that the manifold can reach 90-95% of saturated pressures, with the measurements presented here spanning 0-250 mbar, which is desirable for adsorption isotherms. Heating studies performed between 25 and 200C demonstrate the ability to resolve Ångstrom scale structural changes in a surface bound polymer. These results establish a novel streamlined approach to temperature controlled vapor dosing on a laboratory diffractometer, offering straightforward probe-molecule exchange, vacuum-sealed operations, and variable temperature capabilities.
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All authors Erin E. Dunphy, Mara A. Fischer, Sasha R. Neefe, Devin L. Shaffer, Anthony P. Straub, Michael F. Toney, J. Will Medlin

Disordered Systems and Neural Networks

Interwoven long-range order induced by random fields

Jeremiah Bender and Thomas Vojta

We propose a distinct type of long-range ordered phase that can occur in classical and quantum many-particle systems. It is induced by impurities and defects that locally break a subset of the order-parameter symmetries, i.e., by random-field disorder that couples to a composite vestigial order parameter. The proposed “implectic” phase is characterized by spontaneous symmetry breaking on the background of the spatially interwoven domain structure created by the random fields. We explicitly demonstrate the existence of this phase in a layered $J_1-J_2$ Ising magnet by means of large-scale Monte Carlo simulations. We then discuss numerous potential applications in systems featuring charge and spin density wave order including frustrated magnets, cuprate and iron-based superconductors, and ultracold atoms.
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Superconductivity

Superconducting dome and field-enhanced superconductivity of PLD synthesized Nd1-xEuxNiO2 thin films

Wenlong Yang, Qiang Zhao, Xingke Fu et al. (+8 more)

We report on the synthesis of infinite-layer Nd1-xEuxNiO2 (0<x<0.7) thin films using pulsed laser deposition (PLD) followed by topotactic reduction with CaH2. Resistivity measurements on these films reveal a superconducting dome within the doping range 0.2<x<0.5, which is wider than that achieved by molecular beam epitaxy and comparable to that obtained by chemical synthesis. The x=0.3 PLD film exhibits the optimal superconducting transition temperature Tc~31 K, much higher than those grown by other vacuum epitaxial techniques. This result indicates that PLD is an ideal approach for fabricating high-quality, high-Tc Nd1-xEuxNiO2 superconducting films. Magneto-transport measurements reveal robust field-enhanced and re-entrant superconductivity in both underdoped and overdoped regimes. At low temperatures just above the onset Tc, the Hall resistance exhibits nonlinear behavior, which may originate from magnetic impurity scattering. These results highlight the crucial role of magnetic rare-earth Eu2+ ions in producing the exotic physical properties of the infinite-layer nickelates.
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All authors Wenlong Yang, Qiang Zhao, Xingke Fu, Gaofei Ren, Zhongjing Wu, Zhen Chen, Jianping Sun, Boseng Wang, Jiacai Nie, Pengtao Yang, Jinguang Cheng

Mesoscale and Nanoscale Physics

Lifshitz-Kosevich Theory of Anomalous Landau Levels in Topological Flat Bands

Chao-Xing Liu

In conventional metals, quantum oscillations arise from Landau quantization of Fermi-surface cyclotron orbits, whose dynamics are governed by the Fermi velocity and cyclotron effective mass within Lifshitz-Kosevich (LK) theory. A perfectly flat band, by contrast, has vanishing group velocity, which would naively imply an infinite cyclotron mass and complete thermal suppression of quantum oscillations. Yet topological flat bands can support anomalous Landau levels (LLs) whose finite-field spacing is generated by quantum geometry rather than band curvature, allowing quantum oscillations to persist. This work addresses how such anomalous flat-band LLs behave within the LK framework and whether their thermal damping can reveal quantum geometric information. Using a minimal model with exactly flat topological bands, we derive an LK theory for these anomalous LLs and analyze fixed-density magnetization oscillations. The resulting oscillations exhibit a finite LK effective mass that is substantially larger than the normal-band value and possesses a strong magnetic-field dependence. In the weak-field limit, this anomalous mass reflects the quantum geometric origin of the LL spacing and scales inversely with both the magnetic field and the trace of the quantum metric. Thus, thermal damping of flat-band quantum oscillations directly measures the quantum metric, establishing quantum oscillations as a probe to flat-band quantum geometry.
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Mesoscale and Nanoscale Physics

Retarded interaction between opposite chiral edges in anomalous Hall crystals

Wangqian Miao, Mu-Yang Chen, Binghai Yan et al. (+1 more)

An anomalous Hall crystal combines spontaneous electronic crystallization with a Chern insulating gap, supporting both chiral edge modes and low-energy electronic phonons. We show that this coexistence produces a distinct dynamical effect from ordinary Chern insulators: transverse bulk phonons can mediate a retarded interaction between counterpropagating chiral edge modes on opposite sides of the sample, realizing a Luttinger-liquid variant with delayed inter-edge coupling. Using microscopic time-dependent Hartree–Fock calculations for rhombohedral pentalayer graphene, we find that lowering the carrier density softens the long-wavelength transverse phonon mode. Near this instability regime, the resulting boundary-projected phonon continuum inevitably overlaps with the edge dispersion, thereby enabling their coupling. A smoking-gun probe is a nonlocal measurement: a drive applied to one edge can induce a response on the other edge, delayed by the transverse phonon time of flight across the sample.
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All authors Wangqian Miao, Mu-Yang Chen, Binghai Yan, Chunli Huang