Statistical Mechanics · Cross-listed from astro-ph.CO
Statistics of large-scale structure from the transition probability of Lagrangian trajectories
Lawrence Dam
We describe a probabilistic approach to gravitational clustering. Working purely in configuration space, we show that the two-point function can be formulated in terms of a transition probability describing the likely final position of a particle given its initial position. The transition probability is initially sharply peaked and then over time broadens out in a
diffusion-like manner. The effect is more pronounced for widely-separated particles (e.g.\ at the baryon acoustic scale), leading to an effective suppression of the two-point function in what is normally referred to as infrared resummation.
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Statistical Mechanics · Cross-listed from quant-ph
Deep thermalization and Hilbert space ergodicity
Daniel K. Mark, Manuel Endres, Matteo Ippoliti et al. (+2 more)
Recent advances in
quantum simulation have enabled the discovery of novel forms of universality in
quantum many-body dynamics. In this Review, we discuss deep thermalization and
Hilbert space ergodicity–two recently discovered phenomena characterized by the emergence of distributions of
quantum states that are "maximally random" in a precise sense. They offer a new perspective on how irreversible statistical mechanics arises from reversible
unitary quantum dynamics, going beyond conventional theories of
quantum thermalization and equilibration. We review a unifying framework, rooted in
quantum information theory and principles of maximum
entropy, that explains the different forms of ergodicity which arise under various physical constraints. We discuss open questions and active research directions, including generalizations beyond ensembles of pure
quantum states, phase transitions in deep thermalization tied to deeper forms of ergodicity-breaking, connections to broader topics in
quantum thermalization and ergodicity, and applications in
quantum information science, such as for benchmarking or
tomography.
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All authors Daniel K. Mark, Manuel Endres, Matteo Ippoliti, Wen Wei Ho, Soonwon Choi
Materials Science
Molecular Beam Epitaxy of AgTaO3
Tobias Schwaigert, Joshua Maile, Olivia Peek et al. (+6 more)
We report the first synthesis of single-
crystal AgTaO3 thin films using molecular-beam epitaxy (MBE). High-quality epitaxial AgTaO3 films were grown on both (001)- and (111)-oriented SrTiO3 substrates using sequential deposition of atomic silver and TaO2 layers under an ozone/oxygen atmosphere (80 % O3 + 20 % O2). X-ray diffrac- tion and reciprocal space mapping demonstrate that the films are coherently strained to the SrTiO3 substrates with sharp rocking curves comparable to the substrates, indicating high structural perfection. High-angle annular dark-field scanning trans- mission electron microscopy (HAADF-STEM) confirms coherent, low defect growth for (001)pc-oriented films. For (111)pc-oriented films, initial coherent growth proceeds up to 10 nm before transitioning into a Ta-rich surface region. Energy-dispersive X-ray spectroscopy (EDX) reveals a narrow cation intermixing region at the sub- strate interface for both orientations. This work demonstrates an effective synthesis route for single-
crystal AgTaO3 thin films, providing a platform to investigate strain engineering and emergent interfacial properties in silver-based tantalates.
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All authors Tobias Schwaigert, Joshua Maile, Olivia Peek, Eric Biedke, Paul T. Malinowski, Kyle M. Shen, Salva Salmani-Rezaie, Darrell G. Schlom, Kaveh Ahadi
Statistical Mechanics · Cross-listed from quant-ph
Variational Multi-Gaussian Quantum Trajectories
Zejian Li and Jacopo Tosca
We propose a variational framework for the efficient simulation of
stochastic quantum dynamics in interacting bosonic systems. Our method generalizes the time-dependent variational principle to accommodate
quantum state
diffusion processes and is tailored for describing
quantum trajectories unraveled from a master equation. We adopt a wavefunction ansatz composed of a coherent superposition of Gaussian wavepackets, which allows the fully analytical assembly of the variational equations of motion while capturing both the
quantum trajectory dynamics and the Lindblad
evolution beyond semiclassical approximations. The method is carefully benchmarked on a Bose-Hubbard dimer, and applied to extended Bose-Hubbard
lattices in both 1D and 2D. In particular, we show the emergence of a
symmetry-breaking phase transition in 2D
lattices, which is absent in 1D chains.
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Mesoscale and Nanoscale Physics
Incipient superconductivity and tunable Chern insulators in twisted bilayer-trilayer graphene
Derek Waleffe, Aryana Bhattacharyya, Manish Kumar et al. (+7 more)
Moiré superlattices assembled by twisting Bernal and rhombohedral multilayer
graphene host a rich set of interaction-driven
magnetic and topological states, yet superconductivity has not been observed in these systems except in proximity to a transition-metal dichalcogenide. Here we report incipient superconductivity and tunable Chern
insulators in twisted bilayer-trilayer
graphene encapsulated by hexagonal boron nitride. Across twist angles from $\theta = 1.05^\circ$ to $1.50^\circ$, Chern
insulators form at integer and fractional moiré fillings for electron doping, with Chern numbers up to |C| = 3 set by twist angle and tuned by doping. At $\theta = 1.18^\circ$, a
symmetry-broken metallic region forms for hole doping and hosts a trivial
insulator at band filling $\nu = -2$. Displacement field alone drives this
insulator into a pocket of incipient superconductivity with a sharp transition, a well-defined critical current, and a critical temperature that peaks near the insulating boundary, although the resistance does not fall to zero. In-plane
magnetic field expands the pocket, which persists to more than four times the weak-coupling Pauli limit, and stabilizes a second pocket in which Fraunhofer-like modulation of the critical current signals phase-coherent pairing. Twisted bilayer-trilayer
graphene thus offers a single gate-tunable system in which pairing can be interfaced with Chern
insulators whose
topology is itself an adjustable parameter.
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All authors Derek Waleffe, Aryana Bhattacharyya, Manish Kumar, Eric Maginnis, Anna Okounkova, Tobias Faehndrich, Kenji Watanabe, Takashi Taniguchi, Joshua Folk, Matthew Yankowitz
Materials Science · Cross-listed from cs.LG
Beyond Compression: Training Latent Representations for Stable Long-Horizon Rollout in Neural Surrogate Solvers
Andreas E. Robertson, Ashley T. Lenau, John D. Shimanek et al. (+5 more)
Latent neural surrogate solvers, or latent dynamics models, accelerate simulations of time-dependent physical systems by evolving a compressed latent space rather than resolving full-resolution fields directly. In principle this reduces computational cost and simplifies learning, but in practice errors often accumulate rapidly during long autoregressive rollouts, limiting predictive utility. We show that this instability does not stem from the latent representation itself, but arises when it is trained solely for reconstruction, producing representations poorly suited to long-horizon forecasting. We systematically evaluate training-level interventions that align latent representations with long-horizon rollout: Koopman operator learning and Hamming noise injection during autoencoder training to improve compression, together with noise injection and multi-step rollout fine-tuning to improve dynamics. Interventions that improve long-horizon rollout stability often degrade conventional training metrics, including reconstruction and one-step prediction accuracy. Collectively, these interventions reduce long-rollout error by approximately 40% and match or exceed the accuracy of full-resolution models on two physics
benchmarks, while requiring 2 orders of magnitude fewer floating point operations and half the GPU
memory. Applied to mesoscale
crystal-plasticity simulations of high-cycle fatigue, the resulting surrogate achieves stable extrapolation over horizons orders of magnitude beyond those observed during training. More broadly, these results show that neural compression should be designed not merely to reduce dimensionality, but to restructure the solution space for stable dynamical
evolution, a key requirement for reliable, efficient neural surrogates in scientific applications.
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All authors Andreas E. Robertson, Ashley T. Lenau, John D. Shimanek, Benjamin A. Jasperson, Vivek Oommen, David L. Damm, Krishna Garikipati, Remi Dingreville
Strongly Correlated Electrons
From dimensional reduction to tetramerization in mixed ferro-antiferro breathing pyrochlores
Sourin Chatterjee, Kelvin Salou-Smith, Benedikt Schneider et al. (+8 more)
We study the
spin-1/2 nearest-neighbor Heisenberg model on the breathing pyrochlore
lattice in the mixed ferro-antiferromagnetic regime, where one tetrahedral sublattice is antiferromagnetic and the other ferromagnetic. The classical ground-state
manifold is then that of the nearest-neighbor face-centered-cubic (fcc) antiferromagnet built from composite tetrahedral moments. Classical Monte Carlo simulations and the self-consistent Gaussian approximation show that thermal order-by-disorder lifts its subextensive degeneracy and selects the collinear Type-I state with wave vector $X=(1,0,0)$ through a strongly first-order transition. Pseudofermion functional renormalization group calculations for $S=1/2$ and $S=1$ reveal a nonmagnetic window adjacent to the decoupled antiferromagnetic-tetrahedron limit, beyond which $X$ order reappears. Density
matrix renormalization group calculations show that this window is not featureless: the antiferromagnetic tetrahedra develop nearly ideal tetramer correlations, with four bonds carrying $\langle\mathbf{S}_i\cdot\mathbf{S}_j\rangle\simeq-1/2$ and the two opposite bonds $\simeq+1/4$, while the structure factor retains broad maxima at $X$. A third-order effective
Hamiltonian in the tetrahedral-singlet
manifold explains this: reversing the sign of the inter-tetrahedron coupling converts Tsunetsugu's dimer selection into a uniform tetramer selection, as confirmed by exact diagonalization. A dynamic high-temperature expansion traces how local tetrahedral excitations give way to low-energy $X$-centered spectral weight. Finally, we place density-functional parameters for eight structures of
spin-3/2 breathing chromium thiospinels in the classical phase diagram. The mapping reproduces the $\mathbf{k}=(1,0,0)$ order of CuInCr$_4$S$_8$, accounts for the absence of order in LiGaCr$_4$S$_8$, and predicts Type-I order for LiInCr$_4$S$_8$.
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All authors Sourin Chatterjee, Kelvin Salou-Smith, Benedikt Schneider, Imre Hagymási, Arnaud Ralko, Johannes Reuther, Jeffrey G. Rau, Karlo Penc, Harald O. Jeschke, Ludovic D. C. Jaubert, Yasir Iqbal
Statistical Mechanics · Cross-listed from q-bio.PE
Consistent determination of stability regimes in natural ecological communities from abundance time series
Alberto Megías, Vicente J. Ontiveros, David Alonso et al. (+1 more)
The stability of an ecological community is conventionally defined through species interactions, which quantify how species affect one another. Interaction strengths are notoriously difficult to measure in species-rich assemblages. Long-term monitoring of species-rich communities, however, provides species abundance time series, increasingly available across habitats and taxa but not yet connected to the stability properties of the communities they describe. Here we develop a statistical framework that infers stability regimes in large ecological communities directly from abundance time series. We study
stochastic Generalized Lotka–Volterra dynamics with random interactions and environmental fluctuations using dynamical mean-field theory, reducing the multispecies system to an effective
stochastic process for a representative species. The theory predicts three stability regimes (stable coexistence, intermittent dynamics close to extinction, and unbounded growth) separated by analytical boundaries, and shows that environmental stochasticity systematically destabilizes coexistence by promoting intermittent low-abundance dynamics. The resulting steady-state species abundance distribution is a Gamma law that ties the dynamical phases to the variability-based stability metrics used in empirical studies. Recasting the effective dynamics as a multivariate regression model, we infer interaction statistics, environmental variability and the characteristic timescale of the dynamics from community data, without reconstructing the interaction network. Applied to natural communities spanning a broad range of habitats and taxa, the method resolves contrasting stability regimes and yields quantitative estimates of species extinction risk.
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All authors Alberto Megías, Vicente J. Ontiveros, David Alonso, José A. Capitán
Disordered Systems and Neural Networks · Cross-listed from quant-ph
Disorder-induced quantum Fisher information in topological quantum systems
Advay Burte, Keshav Das Agarwal, Leela Ganesh Chandra Lakkaraju et al. (+1 more)
The topological order of the Kitaev toric code is insensitive to disorder in its couplings since all
star and plaquette operators commute; consequently, the stabilizer ground-state
manifold is independent of the individual coupling strengths, and the phase remains stable against weak local perturbations. This insensitivity, however, is a property of the eigenstates and not of the dynamics they generate, and we show that the disorder sensitivity of a probe prepared outside that eigenbasis can be a metrological resource. In particular, we investigate the estimation of the strength of three topological-order-breaking perturbations, the nonlinear Castelnovo-Chamon deformation, nearest-neighbor Ising interactions, and a
magnetic field along horizontal edges, encoded on an initially separable probe through
unitary evolution under the disordered toric code
Hamiltonian. We demonstrate that the quenched average
quantum Fisher information (QFI), a figure of merit for metrological precision, exceeds that of its ordered counterpart in suitable regimes of perturbation strength and encoding time. For the ordered case, we further identify optimal product probes, for which the quadratic and cubic terms of the short-time expansion vanish identically, leaving a transient quartic scaling of QFI. Interestingly, this window persists as long as the multipartite
entanglement generated by the encoding continues to increase, and it survives under local dephasing, bit-flip, and amplitude damping noise acting independently on each site, with the non-unital channel being the least detrimental.
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All authors Advay Burte, Keshav Das Agarwal, Leela Ganesh Chandra Lakkaraju, Aditi Sen De
Materials Science
AI-guided high-throughput discovery of iridium- and ruthenium-free palladium-oxide catalysts for durable acidic oxygen evolution
Ken J. Jenewein, Faezeh Habib Zadeh, Xiaoxiao Wang et al. (+19 more)
Catalyzing acidic oxygen
evolution at the
proton-exchange-membrane water electrolysis (PEMWE) anode relies almost entirely on iridium or ruthenium, drawn from concentrated supply chains that constrain gigawatt-scale deployment. We report an artificial intelligence (AI)-guided, human-supervised closed-loop platform (>90% automation) integrating combinatorial sputter synthesis, high-throughput screening, machine-learning composition-property models, adaptive multi-objective optimization, and context-aware large-
language-model
reasoning, where lead catalysts advanced to long-term validation in 1 M H2SO4 at 10 mA cm-2. Navigating a combinatorial metal oxide space, the platform iteratively evaluated the activity-stability trade-off of 2,942 catalysts across 53 material systems and 26 elements, surfacing Ir- and Ru-free complex oxides such as InMnPdOx and NiTaPdOx that conventional design logic, and off-the-shelf
language models, would not predict. In retrospective benchmarking, our sequential learning
agent advanced the activity-stability frontier faster than fixed-policy
Bayesian optimization or in-context
language-model selection. During long-term testing, NiTaPdOx operated at lower overpotential than PdOx, but both eventually exceeded 0.5 V: PdOx at ~200 h and NiTaPdOx at ~470 h. InMnPdOx showed a similar overpotential improvement in addition to a dramatic increase in operational stability, retaining overpotential below 0.5 V over 1,000 h of operation. The additive elements promote the formation of a nanostructure that is associated with catalytic activity while stabilizing Pd against corrosion. The results highlight the power of AI-driven science in addressing long-standing challenges in materials chemistry, and the greater availability of Pd relative to incumbent Ir and Ru offers a near-term option to ease supply constraints on scaled electrochemical H2 generation.
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All authors Ken J. Jenewein, Faezeh Habib Zadeh, Xiaoxiao Wang, Gustavo Malkomes, Huafan Zhang, Natalie Page, Jae Jin Bang, Peter J. Santiago, Karla V. Contreras, Katherine K. Li, Allison Perna, Lorena M. Britton, Fahrettin Kilic, Kevin J. Cruse, Armin Taheri, Krishnanand Mallayya, Harley Quinn, Rebecca A. Durr, Peter A. Beaucage, Santiago Miret, John M. Gregoire, Rafael Gómez-Bombarelli
Mesoscale and Nanoscale Physics
Pomeranchuk-like electronic localization above 100 K in twisted MoS$_{2}$
Zhiren Xiong, Jianqi Huang, Ruyue Han et al. (+8 more)
Twisted transition-metal dichalcogenides (TMDs) have manifested a rich variety of emerging physical phenomena, yet experimental studies have so far been largely limited in their valence bands (p-doped). Here, we show correlated electronic states in the conduction bands (n-doped) of near-AA-twisted bilayer MoS$_2$ with twist angles ranging from $\sim2.3^\circ$ to $\sim3.5^\circ$, down to the mK temperature regime. A strongly reconstructed correlated phase diagram as a function of twist-angle has been observed - correlated gaps persist to temperatures approaching $160$ K at small twist angles, but collapse to only $\sim20$ K at intermediate angles, where a richer landscape of interaction-driven states emerges. At the largest twist-angle $\sim 3.5\,^{\circ}$, correlated resistance at 1 electron per moiré unit
cell is enhanced upon heating, consistent with thermally assisted localization, or, a Pomeranchuk-like behaviour. Its
magnetic-field response, however, is highly anisotropic, which differs markedly from that of canonical isospin moiré Pomeranchuk effect in
graphene systems. Strikingly, such signature can persist even above 100 K around a filling of 2 electrons per moiré, despite of its weak resistive nature. Our results establish the twisted MoS$_2$ as a platform for studying the complexity of charge localization, internal flavour degrees of freedom, and band
topology in conduction bands of semiconducting moiré systems.
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All authors Zhiren Xiong, Jianqi Huang, Ruyue Han, Hanwen Wang, Hui Ding, Jianming Lu, Jianpeng Liu, Zheng Vitto Han, Xingdan Sun, Siwen Zhao, Baojuan Dong
Quantum Gases
Characterizing quasiparticles in strongly correlated systems using nonlinear spectroscopy in quantum simulators
Luka Skolc, Utso Bhattacharya, Jonathan B. Curtis et al. (+2 more)
Characterizing carrier type in strongly correlated
quantum systems conventionally relies on the Hall effect. In cold-atom
quantum simulators, implementing Hall transport measurements typically requires synthetic gauge fields, which introduces significant heating. Here, we present nonlinear spectroscopic and fluctuation-based protocols that establish an alternative route to identifying the sign of quasiparticle charge. We demonstrate that second-order density and current responses to finite-momentum quenches and drives-as well as
equilibrium third-order density cumulants-distinguish electron- from hole-like quasiparticles. For a Fermi-Hubbard multi-leg ladder on a square
lattice, numerical simulations reveal a crossover from hole- to electron-like carriers upon hole-doping away from half-filling, matching the sign change in the Hall coefficient. To demonstrate the applicability of our protocols beyond fermionic systems, we show that the nonlinear density response to a finite-momentum, finite-frequency drive reveals the sign of charge carriers in a hard-core
boson ladder, and that the nonlinear signal can be significantly enhanced when driving near resonance with a nonlinear collective mode. Our results establish nonlinear density and current response and
equilibrium non-Gaussian fluctuations as complementary probes, offering
quantum simulators a direct route to characterize the carrier sign, without the experimental hurdles of conventional transport setups.
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All authors Luka Skolc, Utso Bhattacharya, Jonathan B. Curtis, Immanuel Bloch, Eugene Demler
Soft Condensed Matter
Large integration time-step in molecular dynamics simulation artificially enhances the strength of hydrophobic interaction
Dilipkumar N. Asthagiri
Molecular dynamics simulations are used to compute the potential of mean force (PMF) between two united-atom methane molecules at several temperatures and integration time-steps. At a fixed time-step, the contact minimum of the PMF deepens with increasing temperature, as expected for hydrophobicity driven association. Compared with a time-step of 0.5 fs, one that preserves equipartition, larger time-steps alter the PMF and make the contact minimum more favorable. Thus even relative free energy values are sensitive to time-steps that break equipartition. Using quasichemical theory, we partition the free energy of association into hydrophobic and hydrophilic contributions. The hydrophilic contribution opposes association and is insensitive to the time-step. Thus the artificial enhancement of association at larger time-steps comes entirely from the hydrophobic contribution. We explain this behavior through the temperature dependence of the internal pressure of the
liquid. The same analysis also accounts for earlier observations of the
liquid's p-V behavior under conditions that break equipartition.
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Strongly Correlated Electrons · Cross-listed from quant-ph
Leg-Tied Tensor Network States: Entanglement Beyond Virtual Bonds
Shuoyi Hu and Bing Gu
We introduce a class of tensor-network states in which physical legs are shared among local tensors, termed leg-tied tensor ansätze (LETTA). Physical leg ties encode long-range correlations directly, while a virtual
matrix product state (MPS) backbone retains short-range multipartite
entanglement. The linear virtual backbone allows us to develop a deterministic density
matrix renormalization group-like variational optimization
algorithm using exact contractions over the active tie-boundary sets and local minimization. We demonstrate the advantages of LETTA for the two-dimensional frustrated $J_1$–$J_2$ Heisenberg model and the three-dimensional transverse-field Ising model. Our results show that LETTA is substantially more accurate than same-bond-dimension MPS calculations and can typically reach the accuracy of much larger MPS calculations using one order of magnitude fewer variational parameters. LETTA thus opens the door for explicitly correlated tensor-network states that can encode long-range correlation beyond virtual bonds.
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Materials Science
Ultrafast Electron Microscopy: A Quantitative Platform for Nonequilibrium Materials Research
David J. Flannigan and Swarit Ahmed Shadman
Macroscopic materials function is determined not merely by
equilibrium structure, but by how carriers,
phonons, fields, defects, interfaces, and collective order dynamically evolve after perturbation. Ultrafast electron microscopy (UEM) uniquely bridges this gap, coupling femtosecond-to-nanosecond timing with real-space, reciprocal-space, and energy-resolved contrast. Here, we review how these integrated capabilities now quantitatively map energy flow and conversion in electronic materials, decode electronic-structural coupling in
quantum and correlated systems, and isolate the localized propagation of carriers, polaritons, strain, and
phonons across optoelectronic and nanomechanical architectures. We emphasize the predictive design rules now emerging from direct metrology of carrier-
lattice coupling, momentum-resolved
phonon thermalization, defect-controlled phase transformations, and authentic operando switching. We critically assess UEM's ongoing maturation from a qualitative, proof-of-concept experiment into a rigorous, quantitative materials platform. This paradigm shift is actively driven by integrated
multimodal detection, advanced energy-resolved spectroscopy, high-repetition-rate sources, multidimensional (4D and 5D) acquisition, and physically constrained forward modeling. Ultimately, the central opportunity lies in establishing a complete, causal link from initial excitation to localized energy flow, transient structure, and macroscopic device function. By prioritizing quantitative reproducibility and robust mechanistic interpretation, UEM is positioned to engineer materials in functional states that
equilibrium thermodynamics simply cannot describe.
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Strongly Correlated Electrons · Cross-listed from quant-ph
Beyond Bond Gauge: Exact Tensor-Network Tangent Spaces at Weighted Graph States
Song Cheng
For normal PEPS, the fundamental
theorem settles at the finite level whether virtual-bond gauge exhausts a tensor network's representation freedom. We ask the first-order question at a fixed representation, from both sides of the differential: which tensor variations leave the state unchanged without being bond gauges, and which physical directions can no variation reach? We answer both exactly for weighted graph state (WGS) tensor networks with equal physical and bond dimension $q\ge2$, which include the graph-state resources of measurement-based
quantum computation. Dividing a single-tensor variation by the nonvanishing amplitude turns it into an arbitrary function on the closed neighborhood of its vertex. Overlapping neighborhoods give the complete kernel. Its non-bond part is generated on periodic regular-polygon tilings by triangles, chordless squares, and edge-sharing diamonds. Under stated period conditions, generic gauge completeness on all thirty-nine families studied identifies this nullity as a WGS rank drop: for thirty-three families at every $q\ge2$, and for six at $q=2$. Supports outside every neighborhood give the missing directions: at
qubit graph states on the eleven Archimedean tilings every nearest-neighbor $XX$ and $YY$ direction is missing, including on honeycomb, where the non-bond kernel is empty. On large honeycomb and square
tori, small nonzero coherent $XX$ errors leave the bond-two PEPS set on the same graph. Removing redundant parameters and supplying missing directions are therefore distinct operations.
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Materials Science
From Processing to Functionality: Engineering Accessible Material States in Cu-Embedded SiO$_x$ Memristive Devices
Tobias Gergs, Rouven Lamprecht, Sahitya Yarragolla et al. (+5 more)
Resistive switching in oxide-based devices is widely governed by
stochastic defect processes, yet a predictive link between fabrication conditions and functional behavior remains elusive. Here, we establish a multiscale framework connecting
plasma-defined deposition conditions to macroscopic device functionality in sputtered SiO$_x$/Cu/SiO$_x$-based systems. By combining large-scale statistical analysis of more than 50,000 experimentally characterized devices with physics-based
plasma and atomistic simulations, we show that device behavior does not emerge from deterministic process-to-performance mappings, but from a probabilistic cascade spanning defect formation, defect-state
evolution, and functional-regime emergence. Data-driven clustering reveals a continuous functional state space composed of operational switching types, while inverse modeling identifies the reconstructed oxygen-vacancy density as an effective latent descriptor capturing the combined influence of structural disorder and defect
topology. This latent descriptor is strongly coupled to both Cu redistribution and electrical response, linking otherwise hidden material properties to observable device characteristics. Furthermore, macroscopic switching behavior is argued to arise from ensemble integration across spatially heterogeneous subdomains, providing a physical explanation for the pronounced variability of large-area devices. These findings shift the perspective from deterministic defect engineering toward probabilistic defect-state design and establish a physically grounded framework for understanding and controlling functional variability in such oxide-based systems, such as memristive or resistive-switching devices.
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All authors Tobias Gergs, Rouven Lamprecht, Sahitya Yarragolla, Ole Gronenberg, Luca Vialetto, Hermann Kohlstedt, Thomas Mussenbrock, Jan Trieschmann
Soft Condensed Matter
Orientational Ordering of Janus Particle Arrays as Classical Compass Spin Systems
Zhijie Fan, Myeonggon Park, Marija Vucelja et al. (+1 more)
Janus-particle arrays provide a soft-matter platform in which particle orientations act as classical
spins with anisotropic, bond-dependent interactions. Motivated by recent experiments on triangular arrays of metallodielectric Janus particles exhibiting sixfold orientational order and directly observable
vortices and antivortices, we study effective models beyond the isotropic XY description. A classical $120^\circ$ compass model captures the minimal bond-directional interaction, while an effective Kern–Frenkel model incorporates the geometry of the Janus surface interaction more directly. Monte Carlo simulations show that both models exhibit a low-temperature sixfold ordered phase, a high-temperature disordered phase, and an intermediate quasi-long-range-ordered regime consistent with two Berezinskii–Kosterlitz–Thouless transitions. In both cases, the sixfold order arises through thermal order-by-disorder from a continuously degenerate ferromagnetic
manifold. We further show that higher-order extensions of the $120^\circ$ interaction can alter the orientational selection: a quadratic term reverses the fluctuation-induced sixfold anisotropy, while a cubic term lifts the degeneracy energetically and selects the
lattice-aligned directions that coincide with those observed experimentally. These results connect the microscopic anisotropy of Janus-particle interactions to emergent XY-like
vortex physics and illustrate how distinct microscopic mechanisms can produce similar sixfold orientational order.
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All authors Zhijie Fan, Myeonggon Park, Marija Vucelja, Gia-Wei Chern
Mesoscale and Nanoscale Physics · Cross-listed from physics.app-ph
Topological-Insulator Heterophase Gate Stacks for Transistor Electrostatics
Minuk Song, Jiwan Kim, MD Gius Uddin et al. (+25 more)
Conventional gate-stack scaling reduces dielectric thickness and increases permittivity while largely treating the position and electronic character of the gate-side screening boundary as fixed. Here we show that this boundary can be engineered by converting the surface of the topological
insulator Bi\textsubscript{2}Se\textsubscript{3} into insulating high-$\kappa$ BiF\textsubscript{3}. Position-resolved calculations reveal a gap-opened immediate amorphous-BiF\textsubscript{3}/crystalline-Bi\textsubscript{2}Se\textsubscript{3} interface and a reconstructed gap-closed Bi\textsubscript{2}Se\textsubscript{3}-derived state in the adjacent subinterface layer, accompanied by a localized interfacial dipole. Capacitor measurements independently resolve a finite series response consistent with electronic compressibility at this boundary; this response lowers the nominal stack capacitance. Despite this capacitance penalty, MoS\textsubscript{2} transistors with closely matched BiF\textsubscript{3} thicknesses and a common BiF\textsubscript{3}/MoS\textsubscript{2} channel-side material interface exhibit near-thermionic-limit switching, negligible hysteresis and substantially weaker subthreshold drain-bias dependence than BiF\textsubscript{3}-only controls. These results identify the position and electronic character of the gate-side screening boundary as additional design variables for transistor electrostatics beyond nominal dielectric capacitance.
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All authors Minuk Song, Jiwan Kim, MD Gius Uddin, Wonseok Kim, Jihun Park, Han Uk Lee, Dong Won Jeon, Dohyung Lee, Lide Yao, Jouko Lahtinen, Gyunghyun Jang, Soohyun Min, Yonas Tsegaye Megra, Xiaoqi Cui, Seungwoo Choi, Yunyun Dai, Sang Hoon Chae, Keun Su Kim, Dong-Ho Kang, Hyeon-Jin Shin, Wooseok Song, Seth Ariel Tongay, Chul-Ho Lee, Manish Chhowalla, Sung Beom Cho, Zhipei Sun, Kibog Park, Hoon Hahn Yoon
Mesoscale and Nanoscale Physics
Real-axis least-squares bath discretization for real-time transport in quantum-dot Josephson junctions
Ruixin Zhou, Bing Dong and Yiyan Wang
Efficient real-time methods are essential for resolving transient coherence and nonlinear transport in driven superconducting nanostructures. Such simulations remain challenging because finite representations of the BCS continuum generate recurrences, while the damping used to suppress them smears gap-edge structure and artificially shortens coherent lifetimes; finite-broadening regularization of the gap-edge singularity likewise imposes a lifetime-resolution floor. Here we extend the driven Liouville–von Neumann approach to superconducting reservoirs—a noninteracting
quantum dot with Bogoliubov–de Gennes leads—building an explicit-
Hamiltonian framework that hosts a family of bath discretizations (uniform and Gaussian baselines and a new real-axis least-squares recipe, with mode energies, spectral weights, and mode-resolved dampings optimized jointly under gap-aware constraints)—making the broadening an independently calibrated numerical parameter whose leading long-time effect extrapolates controllably along the joint ($\gamma\to0$, $N_b\to\infty$) refinement path while cutting computational cost by over an order of magnitude versus the high-resolution DLvN reference. The compressed baths recover established current-phase relations, multiple-Andreev-reflection structure, quasiparticle-trapping oscillations, and integer and fractional Shapiro locking; the lifetime analysis yields the parameter-free leading-order relation $\kappa\simeq w_{\mathrm{bath}}\gamma_{\mathrm{eff}}$ and resolves damping-induced decay rates below the resolution scale of a previous finite-broadening calculation. As an explicit
Hamiltonian reservoir representation, the framework generalizes naturally to multiterminal normal–superconducting geometries and offers a route toward interacting impurity solvers, while finite-gap strong-drive locking amplitudes mark its present quantitative boundary.
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Materials Science
Crystal symmetry predicts unconventional magnetism
Ziyin Song, Zhong Fang, Chen Fang et al. (+1 more)
Unconventional compensated magnets combine zero net magnetization with momentum-dependent
spin polarization, but identifying them usually requires knowledge of their
magnetic order. Here we show that
crystal symmetry can constrain unconventional
magnetic character before the
magnetic ground state is known. Starting from a non-
magnetic crystal structure and a specified
magnetic sublattice, we generate
symmetry-compatible compensated orders and classify their
spin textures using
spin-space-group
symmetry. We identify materials whose generated candidates are all unconventional, either across a defined search space or after restricting the
magnetic-
cell size. Within the experimental
benchmark, 68% of the prioritized materials are unconventional, compared with 9% of the remaining materials. Screening the Materials Project yields thousands of promising candidates for unconventional compensated magnetism. First-principles calculations for $\mathrm{VGe_3}$ and tetragonal $\mathrm{Fe_2SiO_4}$ connect these
symmetry predictions to the energetics and
spin textures of competing
magnetic orders. In $\mathrm{VGe_3}$, a noncoplanar candidate permits mixed-wave
spin polarization along a fixed axis without
spin-orbit coupling, combining components that are odd and even under momentum reversal. This framework enables crystallography-guided searches for unconventional compensated magnets without first determining their
magnetic ground states.
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All authors Ziyin Song, Zhong Fang, Chen Fang, Hongming Weng
Materials Science
Atom-Resolved Machine Learning of Dielectric and Piezoelectric Response
Jinyu Liu, Yingwei Chen, Liyang Ma et al. (+2 more)
Predicting dielectric and piezoelectric responses in structurally complex materials requires large simulation
cells, for which density-functional perturbation theory (DFPT) calculations scale as $\mathcal{O}(N^4)$ and become computationally prohibitive. However, machine-learning approaches have remained challenging, limited either by the large amounts of expensive DFPT data required for direct regression or by the cubic cost of reconstruction. We here propose a machine-learning framework that learns the ionic response as an atom-indexed field: DART (Direct Atom-Resolved response-Tensor learning) learns these fields directly and achieves high accuracy from small training sets, whereas LARS (Linear-scaling Atom-Resolved Response Solver) reconstructs them from learned microscopic ingredients through sparse linear solves and requires no DFPT labels for the ionic dielectric or piezoelectric tensors. Using DART, we extrapolate to 314 stackings of AlN/ScN superlattices absent from training and identify a high-response polar candidate, for which DFPT gives a laterally clamped piezoelectric strain coefficient $d_{33,f}=14.511$ pC/N and $k_t^2=20.46\%$, exceeding the ordered 1AlN/1ScN reference by 63% and 66%.
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All authors Jinyu Liu, Yingwei Chen, Liyang Ma, Hongyu Yu, Hongjun Xiang
Materials Science
Subnanometer thermodynamic overlayers on bimetallic nanoparticles
Caitlin A. McCandler, Xianzhuo Lao, Jie Liu et al. (+3 more)
Nanoparticle properties are governed by their surfaces, yet their atomic-scale surface structures remain challenging to predict. Here, we report that bimetallic nanoparticles can form a thermodynamically controlled "shell-dimer" architecture in which one metal forms an overlayer only a few atomic layers thick on another. Using Au-Rh as a model system, atomic-resolution imaging and molecular dynamics show that an ultrathin Au overlayer forms on Rh, stabilized by competition among surface, interfacial, and strain energies. Anisotropic strain limits its growth to the subnanometer scale, and changes in surface chemistry can destabilize the overlayer altogether. Across a range of bimetallic nanoparticles, we found that overlayer formation is associated with elemental immiscibility and
lattice mismatch. These findings provide a basis for understanding and controlling surface structures in multimetallic nanoparticles.
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All authors Caitlin A. McCandler, Xianzhuo Lao, Jie Liu, Huipu Liu, Kristin A. Persson, Peng-Cheng Chen
Soft Condensed Matter
Extracting hydrogel properties by watching hydrogel particles moving through solid ice
Yanxia Feng, Se-Hyeong Jung, Camillo Sirvinski et al. (+4 more)
Strikingly, when hydrogel particles are embedded in ice in a temperature gradient, they move through the solid ice towards warmer temperatures, while swelling as they warm up. This motion comes from a flow of unfrozen water through the hydrogel mesh, driven by a process known as `cryosuction'. Here, we show how one can use this behavior to measure – with extremely high resolution – a range of different hydrogel transport properties, and how these change as a hydrogel deswells. These properties include permeability, compressibility, and poroelastic diffusivity: all of which are challenging to measure, but widely important for phenomena involving swelling, dehydration, transpiration and filtration. We demonstrate the measurement technique using poly(ethylene glycol) diacrylate (PEGDA) hydrogels. The technique uses picoliter-scale hydrogel volumes, and yields measurements of hydrogel properties that are consistent with existing literature data. The high resolution of our measurements also allows us to test commonly-used, classical predictions for hydrogel properties (derived assuming an idealized, homogeneous
polymer network in the hydrogel). We show that these classical predictions do not work well, highlighting the need for new models that can accurately describe real hydrogels.
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All authors Yanxia Feng, Se-Hyeong Jung, Camillo Sirvinski, Dan Balkanyi, Federico Paratore, Lucio Isa, Robert W. Style
Disordered Systems and Neural Networks · Cross-listed from hep-lat
Accurate Sampling from Diffusion Models
Dénes Sexty
A new proposal called DM-SMC (
Diffusion Model - Sequential Monte Carlo) is investigated, which samples ensembles defined in terms of an action, using
diffusion models trained on samples from the ensemble. The SMC setup allows for accurate sampling in spite of an approximate
diffusion model and the finite stepsize used in the numerical solution of the
stochastic process. Improved update strategies are also investigated. Results are presented for a $Z_2$ symmetric scalar field theory in 2 dimensions near its 2nd order phase transition.
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Materials Science
Local order in natural sanidine disentangled via single crystal diffuse scattering
Christin Wiggers, Daniel A. Chaney and Ella M. Schmidt
Natural sanidine commonly preserves metastable chemical disorder at ambient conditions, but the local structural correlations associated with this disorder remain poorly understood due to a reliance on average-structure analysis alone. Here, we investigate single-
crystal diffuse scattering in a natural sanidine from Drachenfels, Germany, with consistent observations across additional samples from Laacher See, Germany, and Vesuvio, Italy. The diffraction data reveal pronounced anisotropic diffuse features, including characteristic bowtie-like intensity distributions in reciprocal space. To resolve the origin of these features, we combine three-dimensional difference pair distribution function (3D-$\Delta$PDF) analysis with force-field calculations and Monte Carlo modelling. The 3D-$\Delta$PDF shows correlated deviations from the average structure and indicates a strong coupling between occupational and displacive disorder. Force-field calculations demonstrate that the aluminosilicate framework responds strongly to the local alkali occupancy, with the largest structural variation occurring along the $a$ direction. Guided by these observations, we construct a disorder model in which K/Na occupational short-range order is combined with chemically constrained Al/Si distributions and local framework relaxations. The model reproduces the main experimental diffuse-scattering features and shows that the bowtie-like diffuse scattering arises from correlated framework distortions driven primarily by local K/Na order.
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Superconductivity
Bounds on Bose-Einstein Condensation of Higgs modes in a Superconductor
Z. E. Krix and Daniel Loss
Collective modes in a
superconductor correspond to fluctuations in the amplitude (
Higgs mode) or the phase (Goldstone mode) of the order parameter. Starting from the BCS
Hamiltonian, we derive a microscopic
Hamiltonian for the coupled
Higgs-Goldstone-electron system that contains all interactions among these degrees of freedom. The
Higgs subsystem is a weakly interacting Bose gas:
Higgs modes experience a mutual attraction mediated by the virtual exchange of Bogoliubov quasi-particle pairs. They also interact with external electromagnetic-fields with a coupling constant that we derive explicitly. We use this theory to examine whether an optically pumped gas of
Higgs modes can undergo Bose-Einstein condensation. We identify a density window, bounded below by the
equilibrium condensation criterion and above by collapse due to the attractive interaction, in which condensation can occur and we derive the expected density of
Higgs-modes due to external pumping. This pumping depends crucially on non-parabolic corrections to the electron dispersion around the Fermi-energy. We show that the pumped mode density is compatible with condensation for realistic material parameters. We suggest possible experimental signatures of this non-
equilibrium condensate.
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Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
Avoided crossings in spin-boson systems: consequences for adiabatic state preparation
Joona Marjamäki, Robert van Leeuwen and Riku Tuovinen
Avoided crossings in the correlated many-body spectrum play a central role in determining the conditions for adiabatic state preparation in interacting
quantum systems. We investigate this connection in finite
spin-
boson systems by combining exact diagonalization of the many-body spectrum with time-dependent simulations of adiabatic switching protocols. By comparing the adiabatically prepared state with the exact ground state, we determine the switching times required for reliable preparation as a function of the
spin-
boson coupling strength and bosonic mode structure. We show that regions of small many-body level spacings, associated with avoided crossings, impose the strongest constraints on adiabatic preparation and explain the observed dependence of the required switching times on the interaction strength. Furthermore, while the ground-state energy follows the overall spectral trends, local observables such as Pauli
matrix expectation values exhibit additional non-monotonic behavior arising from coherent oscillations in finite systems. These findings can provide concrete
benchmarks for both the theoretical treatment of open
quantum systems and practical implementations in
quantum simulation and
qubit control.
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Mesoscale and Nanoscale Physics
Spin-Polarized Magnetic Metal Electrodes for Magnetic Tunnel Junctions
Zhiyuan Duan, Peixin Qin, Li Liu et al. (+7 more)
Magnetic tunnel junctions are foundational components of spintronic
memory, sensing, and computing, and their performance depends critically on the
magnetic metallic electrodes. This Perspective examines electrode materials through the lens of
magnetic order and the distinct microscopic mechanisms that generate
spin-selective tunneling. Conventional ferromagnets, including CoFeB and half-metallic Heusler
alloys, support exchange-split electronic states and
symmetry-filtered tunneling, whereas compensated collinear and noncollinear antiferromagnets exploit sublattice selectivity,
spin-orbit anisotropy, vector
spin textures, and
magnetic multipoles. Altermagnets provide a collinear, zero-net-moment route based on
symmetry-allowed momentum-dependent
spin splitting. Across these material classes, we compare the origins of tunneling polarization, the roles of barrier evanescent states and interface termination, and strategies for electrically writing and reading the relevant
magnetic order. This comparison reveals a broader design principle: effective electrode polarization is not a scalar bulk quantity, but a momentum-, orbital-,
symmetry-, and interface-resolved transport property. Beyond the pursuit of ever larger tunneling magnetoresistance, future progress will depend on converting the unconventional
spin polarization of emerging
magnetic metals into electrically addressable, thermally robust, and reproducible tunneling functionality at realistic interfaces.
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All authors Zhiyuan Duan, Peixin Qin, Li Liu, Guojian Zhao, Sixu Jiang, Xiaoyang Tan, Jingyu Li, Xiaoning Wang, Ziang Meng, Zhiqi Liu
Soft Condensed Matter
Superadiabatic Dynamical Density Functional Theory for One-Dimensional Brownian Hard-Rod Fluids
Jens Weimar, Daniel de las Heras and Martin Oettel
We study the relaxation dynamics of a one-dimensional system of hard rods at the level of one-body fields using superadiabatic dynamical density functional theory, and compare the results with Brownian dynamics simulations. The theory uses the exact
equilibrium excess free energy functional and incorporates superadiabatic effects from first principles via an adiabatic closure relation at the three-particle level. The predicted superadiabatic response shows very good agreement with simulation data, provided that initial-state ensemble differences between theory and simulations remain small. Furthermore, we evaluate an approximate power functional theory based on a velocity-gradient expansion, which also yields an accurate superadiabatic response, although requiring a
memory kernel extracted from simulation data.
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