Strongly Correlated Electrons
Mixed-spin Heisenberg ladders in a magnetic field
D. S. Almeida, A. S. Bibiano, W. M. da Silva et al. (+1 more)
In this work, we study alternating mixed-
spin $(s,S)$ Heisenberg ladders in the
magnetic field $h$ using density
matrix renormalization group and linear
spin-wave calculations. The $h$ versus interchain coupling $J_\perp$ phase diagram for the $(1/2,1)$ case is investigated in detail. { In particular, we demonstrate the compatibility between the critical line estimates and
magnetic ordering by analyzing chains with variable values of $J_\perp$ and of $h$ along the chain, $J_\perp$ and $h$ scans, and considering the usual case of chains with uniform couplings}. The magnetization plateau at 1/3 of saturation magnetization, 1/3 - plateau, is observed for $J_\perp>0$ and in a limited range for $J_\perp<0$. The critical Kosterlitz-Thouless transition point, where the 1/3 - plateau closes, is identified through a finite-size analysis of the transverse
spin correlation functions.
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All authors D. S. Almeida, A. S. Bibiano, W. M. da Silva, R. R. Montenegro-Filho
Strongly Correlated Electrons
Vortex-enhanced photovoltaic current in disordered topological materials
Pavlo Sukhachov, Penghao Zhu, Ella Banyas et al. (+2 more)
In disordered topological materials, real-space crystalline defects interplay with momentum-space wave function singularities to enhance the bulk photovoltaic current. What's singular is the interband Berry phase, or equivalently the phase of the optical dipole
matrix element, which has a
vortex structure in momentum space. Such optical vorticity is guaranteed to exist in all topological materials associated with nontrivial Chern numbers. These
vortices enhance electron-
impurity skew scattering, which manifests as a ballistic photovoltaic current that is sensitive to (a) the topological material class, (b) the
symmetry class of crystalline defects, and (c) the light polarization. This sensitivity manifests in two ways: firstly, by (a-c)-dependent frequency exponents for the photovoltaic current $\propto \omega^{\text{exponent}}$ in topological semimetals, with $\omega$ the frequency of the light source. Secondly, by (a-c)-dependent constraints of the bulk photovoltaic tensor, which are explainable only by emergent,
magnetic symmetries of time-reversal-invariant topological materials. These ideas are concretized by case studies on multifold
fermions, 3D $m$-order Weyl semimetals and 2D $n$-order Dirac systems, which include $n$-layer rhombohedral
graphene, transition metal dichalcogenides, and topological surface states. Theoretical guidance is provided for a tri-pronged experimental program that combines frequency-tuned photoconductivity measurements, defect characterization and defect engineering.
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All authors Pavlo Sukhachov, Penghao Zhu, Ella Banyas, Liang Z. Tan, A. Alexandradinata
Materials Science
Microscopic and macroscopic characterization: MBE-grown versus sputter-deposited Au/Co/Au thin films for CISS and MIPAC effect studies
Lokesh Rasabathina, Thi Ngoc Ha Nguyen, Aleksandr Kazimir et al. (+12 more)
Chirality-induced
spin selectivity (CISS) enables
spin-dependent transport at
chiral molecule/Au(111) interfaces and is used in spintronics when combined with
ferromagnetic thin films in
spin-valve-type hybrids. However, the influence of substrate microstructure on CISS and the related magnetization induced by the proximity of adsorbed
chiral molecules (MIPAC) effect is still not well understood. In this study, we compare the effects of the adsorption of L-
chiral alpha-helical alanine-rich peptides on Au/Co/Au
ferromagnetic thin films fabricated by molecular beam epitaxy (MBE) and magnetron sputtering. X-ray reflectivity and X-ray diffraction show sharper interfaces and a narrower Au(111) rocking-curve width for the MBE-grown sample. However, atomic force microscopy and scanning tunneling microscopy images reveal that both sample types have locally smooth Au(111) surface regions suitable for peptide adsorption, despite clear differences in larger-scale morphology. Microscopic scanning tunneling spectroscopy after peptide exposure yields similar magnetization-direction-dependent tunneling currents in both sample types, confirming a similar magnitude CISS effect on the molecular scale. In contrast, macroscopic magneto-optical Kerr effect hysteresis loops and effect microscopy reveals that only sputter-deposited samples show slight coercivity enhancements and a consistent reduction in domain wall velocity after peptide exposure. These results suggest that microscopic CISS signatures are robust for both sample types, whereas macroscopic MIPAC-type
magnetic responses are more sensitive to the substrate microstructure.
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All authors Lokesh Rasabathina, Thi Ngoc Ha Nguyen, Aleksandr Kazimir, Rico Ehrler, Julia Krone, Franziska Schölzel, Zihao Liu, Peter Heinig, Markus Gößler, Irene Coin, Christina Lamers, Georgeta Salvan, Lech Tomasz Baczewski, Christoph Tegenkamp, Olav Hellwig
Strongly Correlated Electrons
Monotonic and non-Nonmonotonic Impurity Entropy flows in a $\mathscr{PT}$-Symmetric Kondo Model
Pradip Kattel, Abay Zhakenov and Natan Andrei
Quantum impurity models provide a paradigmatic setting for studying Kondo screening, boundary criticality, and
impurity entropy. While these phenomena are well understood in
unitary systems, their fate in non-Hermitian many-body settings remains largely unexplored. We study a $\mathscr{PT}$-symmetric
quantum impurity model consisting of a
unitary SU(2)$_1$ Wess–Zumino–Witten bulk attached to two
impurity spins through complex-conjugate Kondo couplings. Using an integrable
lattice realization solved by the Bethe Ansatz and benchmarked against finite-temperature
matrix-product-state calculations, we determine the
impurity free energy,
entropy, and the corresponding $g$-function. We identify three distinct
impurity phases. In the Kondo-screened phase, the spectrum remains real and the
impurity entropy decreases monotonically from $\ln 4$ in the ultraviolet to $0$. Remarkably, this monotonic flow persists despite the nonunitary boundary interaction, beyond the standard domain of the $g$-
theorem. The Yu–Shiba–Rusinov phase instead exhibits spontaneous $\mathscr{PT}$-
symmetry breaking and loss of boundary conformal invariance, while the local-moment phase displays cyclic renormalization-group flow, with identical
impurity entropy and $g$-value in the ultraviolet and infrared limits.
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Disordered Systems and Neural Networks
Spectral phase transitions and trainability in neural network learning dynamics
Chanju Park, Dario Bocchi, Francesco D'Amico et al. (+2 more)
The emergence of low-dimensional structures in the spectra of neural network weight
matrices is a common empirical feature of trained models, but the dynamical origin of this phenomenon during learning remains an open problem. We formulate neural network training as the
stochastic evolution of an initially random
matrix ensemble, driven by
stochastic gradient descent (SGD) updates that reshape the spectral bulk while amplifying signal strength. This induces a Baik-Ben Arous-Péché (BBP) transition during training, where isolated
eigenvalues detach from the random bulk distribution, providing a dynamical framework for representation formation in high-dimensional learning dynamics. We demonstrate this in a solvable linear teacher-student model, where spectral
evolution is analytically tractable and a phase diagram of trainability governed by the step size (or learning rate) and initial weight variance is obtained, and subsequently extend our formalism beyond the linear regime to nonlinear and
stochastic settings. Numerical simulations in realistic settings support this picture, showing robust emergence of spectral
alignment during training. Our results suggest that spectral analysis may provide a unified perspective of
stochastic learning dynamics, linking trainability, optimisation hyperparameters, spectral phase transitions, and representation learning in neural networks.
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All authors Chanju Park, Dario Bocchi, Francesco D'Amico, Biagio Lucini, Gert Aarts
Quantum Gases · Cross-listed from hep-th
Geometric pairing of Nambu–Goldstone modes in spacetime symmetry breaking
Aleksander Głódkowski
We identify a
geometric pairing mechanism in systems with spontaneously broken spacetime
symmetries, whereby pairs of Goldstone fields become canonically conjugate and hybridize into a single type-B Nambu–Goldstone mode (NGM). The mechanism originates from deformations of the local spacetime volume element induced by Goldstone fluctuations, which endow the Goldstone
manifold with a Berry
curvature. Integrating this pairing with existing reductions, we propose a general counting formula for the number of gapless NGMs in many-body systems. We demonstrate the mechanism in a microscopic model of a two-component Bose–Einstein condensate, where the dilaton and the $U(1)$ Goldstone field combine into a single NGM with quadratic dispersion.
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Materials Science
A Magnetism-Aware Crystal Graph Neural Network with Explicit Magnetic-Sublattice and Exchange-Geometry Representations
Sourav Mal and Satadeep Bhattacharjee
Magnetic order in
crystals is governed by moment-carrying sublattices and ligand-mediated exchange pathways, yet standard
crystal graph neural networks do not explicitly distinguish
magnetic sublattices and encode bonds primarily through pair distances. We propose mCGCNN, a magnetism-aware
crystal graph neural network that augments the full structural graph with a dedicated
magnetic subgraph. The
magnetic stream performs angle-aware message passing between
magnetic centers using metal–ligand–metal exchange-path descriptors motivated by Goodenough–Kanamori–Anderson physics, while layer-wise cross-coupling transfers structural and ligand-environment information from the full
crystal graph. Separate pooling of the
magnetic sublattice preserves magnetism-specific information alongside the global structural representation. We evaluate mCGCNN for total
magnetic moment prediction on 49,462 crystalline materials with
ferromagnetic spin configurations from the Materials Project and find that the proposed model improves agreement with DFT
magnetic moments over established
crystal-graph approaches without requiring a large increase in model complexity. Material-level analysis shows that the largest gains are concentrated predominantly in complex transition-metal and oxygen-containing
magnetic compounds. Our results show that explicitly incorporating
magnetic sublattices and exchange geometry provides a physically motivated route to improved
crystal-graph representations for
magnetic materials.
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Materials Science
Radiation Damage of TF-1 and PbWO$_4$ Crystals with 20 MeV Electrons
Hamlet G. Mkrtchyan, Arthur H. Mkrtchyan, Vardan H. Tadevosyan et al. (+9 more)
We studied the radiation hardness of two types of
crystals, lead glass TF-1 and lead tungstate PbWO$_4$, using a 20 MeV electron beam from the LUE-75 linear accelerator at AANL. The transmittance of the
crystals in the wavelength range of 200-1000 nm was measured before and after irradiation, and after thermal annealing. % The irradiation was performed in two stages. First, both
crystals were irradiated with beam current of 0.125 $\mu$A, each for a total exposure time of 720 s and absorbing $5.6 \times 10^{14}~e^-$. % Strong degradation of the optical properties of TF-1 caused by this amount of radiation was observed, while the effect on PbWO$_4$ was negligible (it is a few tens of times radiation harder than TF-1). % In the second stage, only the PbWO$_4$
crystal was exposed to radiation, with a beam current of 0.28 $\mu$A and an exposure time of 1200 s, absorbing an additional $2.1 \times 10^{15}e^-$, still no notable effect. % Thermal annealing was performed in the temperature range of 160 to 250$^\circ$C (isochronal) for 10-12 hours. The transmittance of the annealed
crystals increased with the annealing temperature and time.
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All authors Hamlet G. Mkrtchyan, Arthur H. Mkrtchyan, Vardan H. Tadevosyan, Hrachya H. Marukyan, Argine S. Hakobyan, Ashot S. Hakobyan, Arthur A. Hoghmrtsyan, Diana G. Khurshudyan, Nina N. Prazyan, Albert H. Shahinyan, Adelina S. Stepanyan, Lusine R. Vahradyan
Statistical Mechanics · Cross-listed from quant-ph
Diameter truncated operator evolution
Tom Holden-Dye, Max Marvell, Joel Mills et al. (+2 more)
We present a method for simulating operator dynamics in out-of-
equilibrium quantum systems. Due to the rapid growth of complexity in these systems, this is typically speaking an intractable task. However, exceptional progress has been made in recent years to sidestep this barrier, with the introduction of a number of methods that make use of a truncation of the simulation to low-weight (the number of non-trivial terms in a Pauli string basis expansion) observables, which turns out to be a good approximation for many dynamical quantities of interest, e.g., two-point infinite-temperature correlation functions between local operators. In this work, we extend this idea to a leaner truncation protocol, truncating operators based on their diameter - that is, the size of the region on the
lattice on which they are non-trivially supported. Using existing analysis for generic
circuits we argue that this kind of truncation protocol is physically well-motivated, and show via extensive numerical simulations for a number of systems of interest (here, the kicked Ising model and the Heisenberg XXZ model) that it is effective, and allows us to efficiently and accurately extract local correlation functions and transport properties.
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All authors Tom Holden-Dye, Max Marvell, Joel Mills, Christoper J. Turner, Arijeet Pal
Superconductivity
Excitation of Collective Modes in a Chiral Superfluid by Thermal Quench
Noble Gluscevich and J. A. Sauls
Based on time-dependent Ginzburg-Landau field theory we show that rapid cooling through the second-order phase transition into superfluid $^3$He-A excites collective modes of newly formed
chiral domains, in addition to topological defects that are formed via the Kibble-Zurek mechanism. Simulations of temperature quenches in the presence of Gaussian space-time white noise generate a highly excited inhomogeneous condensate. Large-scale simulations exhibit a complex network of domain walls and
vortices. We report results for the excitation of bosonic collective modes by thermal noise as well as nonequilibrium temperature quenches, followed by coarsening dynamics tracked in terms of the
Fourier components of the order parameter amplitudes. For thermal states, the spectrum of bosonic excitations is defined by a power spectral density (PSD) for each mode, which is sensitive to the Langevin damping. For weak damping the PSD onsets sharply at the frequency corresponding to the mass of the bosonic mode, then decays as $1/\omega$. We also track the dynamics of the order parameter following a temperature quench. We report results for the scaling exponents of Kibble-Zurek freeze-out time and correlation length as a function of quench rate for several damping rates. The dynamical exponent $z$ is shown to transition smoothly from $z=1$ to $z=2$ as the damping is increased, while the correlation length exponent, $\nu\approx 1/2$, is independent of damping.
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Disordered Systems and Neural Networks
Stationary point complexity via minimal supersymmetry breaking
Jaron Kent-Dobias
The statistics of stationary points are a powerful way to understand mean-field random landscapes, and the Kac–Rice formula is a general way to compute them. A longstanding technical barrier to these calculations is the presence of the absolute value of the determinant of the Hessian. Neglecting the absolute value produces an elegant 2-index supersymmetric representation of the problem, but is often incorrect. We develop an expanded 4-index supersymmetric representation of the complexity problem which incorporates the absolute value naturally via spontaneous supersymmetry breaking along a particular superspace direction. Positing that no additional
symmetry breaking occurs implies the reduction to five order parameters corresponding to elements of a superspace operator
algebra generated by the spontaneously SUSY-breaking operator. We relate the order parameters to the geometry and spectra of stationary points, showing that the SUSY-breaking order parameter corresponds to the spectral density of the Hessian at zero
eigenvalue. We give examples of this formalism applied to calculate the annealed complexity of several models, including the perceptron and the Sherrington–Kirkpatrick model. The framework is naturally extended to quenched complexity, where each order parameter corresponds to a replica
matrix.
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Statistical Mechanics
Optimal parameterization of nonequilibrium generalized master equations from discrete-time experimental data
Chih-Wei Joshua Liu, Jérémie Klinger and Grant M. Rotskoff
Kinetic analyses of experiments often require coarse-grained descriptions, but complex systems rarely conform to the widely used modeling assumptions of Markovianity and thermodynamic
equilibrium.
Memory is indeed a general and often inevitable consequence of coarse-graining. Markov state models (MSMs) are a popular choice of coarse-grained description, but require microstate assignments – which are rarely experimentally tunable – to macrostates that minimize
memory. Generalized master equations (GMEs) circumvent this limitation of MSMs by explicitly capturing
memory. However, GMEs are difficult to parameterize and usually formally approximate in the experimentally relevant discrete-time setting. Here we introduce a maximum-likelihood-based procedure to parameterize formally exact, physically feasible, discrete-time generalized master equations from experiments and simulations in and out of
equilibrium. By adapting
algorithms typically used in optimal transport, we construct physical-constraint-satisfying conditional-maximum-likelihood
estimators of both exact Nakajima-Zwanzig
memory kernels and time-convolutionless GME propagators in discrete time. Applying these
estimators to three examples – experimental recordings of Förster-resonance energy-transfer in an ion channel, experimental nanoparticle tracking of a processive molecular motor, and simulated folding of a
benchmark protein domain – we recover kinetic parameters including relaxation rates, irreversibilities, dwell times, and first-passage times. These results establish discrete-time GMEs as a physically and statistically principled alternative to MSMs for kinetic analyses of experimental and simulated biomolecular systems.
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Disordered Systems and Neural Networks
Classical versus quantum Anderson localization in disordered systems
Stefano Mossa, Giancarlo Ruocco and Walter Schirmacher
We investigate Anderson localization in three-dimensional disordered systems by comparing scalar classical waves with mass and force-constant disorder to electronic tight-binding models with diagonal and off-diagonal disorder. We show that the commonly employed mapping between classical-wave localization and the electronic Anderson model with diagonal disorder is not mathematically justified. Instead, the correct modulus-type formulation reveals that classical-wave systems constitute a distinct constrained disorder class, in which the acoustic sum rule correlates diagonal and off-diagonal
matrix elements and prevents any direct correspondence with the standard electronic disorder models. Within a unified
eigenvalue framework, we determine localization phase diagrams for all four disorder classes using complementary spectral, eigenvector, and level-statistics diagnostics. We find that classical-wave systems share a key qualitative feature with electronic off-diagonal disorder: localized states occur only near a band edge, while extended states persist in the central part of the spectrum even at strong disorder. At the same time, the acoustic sum rule produces localization
topologies that differ fundamentally from both diagonal- and off-diagonal-disorder electronic systems. In particular, for mass disorder we obtain a phase diagram that differs qualitatively from previous results based on the conventional potential-type approach and reveals an extended localized regime near the upper band edge. Our results establish a unified perspective on localization in
quantum and classical wave systems and provide new insight into the conditions under which Anderson localization may occur in three-dimensional photonic and acoustic media.
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Soft Condensed Matter · Cross-listed from physics.bio-ph
The Allee Effect in Compressible Flows
Jonathan Bauermann, Roberto Benzi, David R. Nelson et al. (+1 more)
Microbes in marine environments are often confined to thin near-surface layers while being advected by turbulent flows. Because such constrained advection generates an effectively compressible flow, reproduction and transport interact in a nontrivial way. Here, we focus on populations whose growth is governed by an Allee effect and show that sinks and sources, generated by the compressible flow, have dramatic consequences for the survival of such species. We derive analytical expressions for the carrying capacity as a function of the Allee strength in the limit of small and large Damköhler number, which measures the product of the large eddy turnover time and the organism growth rate. Numerical simulations reveal how these two limits connect. In the limit of small Damköhler number, we find a maximal Allee strength, set by the statistics of the compressible flow, that leads to species extinction in fully developed
turbulence.
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All authors Jonathan Bauermann, Roberto Benzi, David R. Nelson, Federico Toschi
Disordered Systems and Neural Networks · Cross-listed from cs.LG
How Width and Data Shape Generalization Scaling Laws in Quadratic Neural Networks
Julius Girardin, Emanuele Troiani, Yizhou Xu et al. (+3 more)
Understanding how performance scales jointly with model size and data is a central problem in modern machine learning. Existing theoretical works on scaling laws typically describe generalization as a function of data or compute, often in fixed-feature or infinite-width regimes and for online SGD. Here, we instead study how generalization scales with the number of trainable parameters and the number of samples in a feature-learning model. We analyze $\ell_2$-regularized empirical test error minimization in a quadratic two-layer network in a finite-sample setting with structured data. This setting allows for an explicit characterization of the generalization error as a function of the number of samples, model width, and regularization. Our results reveal a phase diagram with distinct scaling regimes as the number of parameters varies. In particular, the generalization error follows data-dependent power laws controlled by the spectral structure of the target. We further characterize the transitions between regimes, including the onset of interpolation, and their impact on generalization.
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All authors Julius Girardin, Emanuele Troiani, Yizhou Xu, Vittorio Erba, Florent Krzakala, Lenka Zdeborová
Soft Condensed Matter
Entropy functional theory for inhomogeneous fluids
Matthias Schmidt
We present an exact variational scheme for the physics of inhomogeneous classical fluids in thermal
equilibrium. A joint metadensity minimization principle is proven for the one-body density and the global interparticle distance distribution. The theory bypasses the inhomogeneous two-body density and thus remains computationally simple. A universal excess
entropy functional accounts for all many-body correlations in arbitrary pairwise interacting systems. The framework is relevant for neural functional machine learning, for soft matter design, and for predicting hyperobservables, structural correlation functions, and first-principles mechanisms of
entropy-energy competition.
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Quantum Gases
Coexisting Regular and Chaotic Dynamics in the Dysprosium Feshbach Spectrum
Julie Veschambre, Alexandre Journeaux, Maxime Lecomte et al. (+7 more)
Strongly dipolar gases, such as dysprosium, erbium and thulium, exhibit dense Feshbach spectra whose level statistics have been associated with
quantum chaos arising from couplings among many molecular channels. Here, we combine a precise calibration of the Feshbach spectrum of $^{162}$Dy with spectroscopic measurements of the differential
magnetic moments of bound states associated with more than 80 resonances between 0 and 30 G. These
magnetic moments provide an eigenstate-sensitive probe of the molecular states underlying the resonance spectrum. We find that the level statistics are not uniform: resonances associated with states near the center of the
magnetic-moment distribution display enhanced level repulsion, whereas those near the lower edge remain close to Poisson statistics. Our results reveal hidden structure within the chaotic dysprosium Feshbach spectrum and identify molecular-state composition as a key ingredient in the emergence of
quantum chaos in strongly dipolar scattering.
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All authors Julie Veschambre, Alexandre Journeaux, Maxime Lecomte, Alice Belmon, Ethan Uzan, Inès de Verdelhan, Patricia Christina Marques Castilho, Jakub Zakrzewski, Jean Dalibard, Raphael Lopes
Mesoscale and Nanoscale Physics · Cross-listed from hep-th
Higher dimensional quantum Hall effect and the analog of $W_\infty$-algebra
Dimitra Karabali and V.P. Nair
We show that Abelian and nonabelian gauge transformations are the analog of $W_\infty$ transformations for higher dimensional
quantum Hall effect. The commutator anomaly and the extended
algebra of such transformations on the edge modes of a droplet are obtained by purely topological arguments, basically utilizing the two-cocycle in the descent procedure for anomalies and using the fact that there is anomaly cancellation between the bulk and boundary actions. The method relies on the fact that bulk actions are easily constructed in general using the Dolbeault index
theorem. The resulting
algebras are shown to agree with explicit edge mode calculations for cases where they are available. We also comment on the similarities and differences in the nature of these transformations between two and higher dimensions.
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Mesoscale and Nanoscale Physics
Interlayer electric multipole Hall effect in twisted multilayers
Chengxin Xiao, Cong Xiao, Dawei Zhai et al. (+1 more)
Electrons in layered van der Waals materials possess a layer pseudospin characterizing their wave-function distribution among layers. In twisted structures, this pseudospin forms nontrivial textures, leading to intriguing phenomena such as the layer
Hall effect (LHE), where distinct layer
Hall currents flow despite the presence of time-reversal
symmetry. In
chiral bilayers, LHE manifests as an interlayer electric dipole
Hall effect with
Hall counterflows and a concomitant in-plane
magnetic dipole. Multilayers host richer layer-dependent
Hall currents, generating interlayer electric multipole
Hall effects and in-plane
magnetic multipoles. We start from exploring the interlayer electric quadrupole
Hall effect in mirror-symmetric twisted trilayers. At small twist angles, interlayer translation efficiently tunes layer
Hall current magnitudes. At large angles and low doping, the currents can be well accounted for by adding the contributions from the two individual twisted interfaces. This decomposition allows obtaining layer-resolved
Hall currents in large-angle twisted multilayers even without well-defined periodicity.
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All authors Chengxin Xiao, Cong Xiao, Dawei Zhai, Wang Yao
Strongly Correlated Electrons · Cross-listed from quant-ph
Hybrid quantum-classical neural network for sample-efficient recognition of topological phases
Markus K. Hoffmann, Leon C. Sander, Colin Scarato et al. (+4 more)
With increasing maturity of
quantum computers, standard methods for characterizing global properties of their output
quantum states via direct measurements and classical post-processing are becoming increasingly impractical due to large measurement costs. Although
quantum neural networks could directly process
quantum states to identify underlying characteristics with reduced measurement efforts, they often require deep
quantum circuits that cannot be implemented on existing devices. To overcome these challenges, we introduce a hybrid
quantum-classical neural network that consists of a shallow parameterized
quantum circuit, measurements, and a classical neural network. The parameterized
quantum circuit performs a nonlocal transformation of the measurement basis, which is jointly trained with the classical neural network to maximize the statistical distance between data obtained by measuring different
quantum states. Using supervised learning, we demonstrate that the hybrid neural network distinguishes the topological phase of the surface code from a
symmetry-enriched topological phase and random product states. Moreover, this hybrid neural network reduces both inference and training sample complexities of recognizing the topological phase by approximately one order of magnitude compared to a classical neural network trained on randomized Pauli measurements. As this hybrid neural network features a shallow
quantum circuit that can be readily implemented on existing
quantum computers, it enables the efficient characterization of complex
quantum states.
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All authors Markus K. Hoffmann, Leon C. Sander, Colin Scarato, Christoph Hellings, Johannes Knörzer, Michael J. Hartmann, Petr Zapletal
Mesoscale and Nanoscale Physics
Role of the Casimir force in the capacitive radio-frequency microelectromechanical switches
G. L. Klimchitskaya, A. S. Korotkov, V. V. Loboda et al. (+1 more)
We determine the role of the fluctuation-induced Casimir force acting between a membrane of cylindrical shape and a bottom electrode in microelectromechanical capacitive switches. For this purpose, the Casimir force is computed taking into account the real properties of both a membrane and a bottom electrode materials with account of surface roughness. The obtained results are compared with those found for the smooth surfaces using the idealization of ideal metal. It is shown that an account of both the real material properties and surface roughness is crucial for obtaining the correct values of the Casimir force. According to our results, at the shortest separations, when the switch membrane is in contact with the transmission line, the magnitudes of the Casimir force may exceed the magnitudes of the electric one depending on the value of the operating voltage. The obtained values of the Casimir force can be used for determining the thickness of the switch membrane, which ensures the necessary magnitude of the restoring elastic force required for a stable cyclic functioning of the micromechanical switch with no pull-in.
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All authors G. L. Klimchitskaya, A. S. Korotkov, V. V. Loboda, V. M. Mostepanenko
Superconductivity
Imaging geometry- and phase-controlled spectra in a surface-state Andreev cavity
Adrian Greichgauer, Yoichi Ando and Jens Brede
Andreev cavities provide a setting in which superconducting proximity spectra are shaped by phase-coherent electron-hole motion along extended trajectories. While such Andreev physics is well established in transport, local spectra in two-dimensional cavities remain largely unexplored in real space. Here we use scanning tunnelling spectroscopy to study confined Cu(111) surface states coupled to superconducting Nb(110). The in-plane
magnetic-field scale for the collapse of the resolved low-energy spectrum is controlled by the transverse extent available to Andreev trajectories, while the zero-field excitation energy evolves with the characteristic trajectory length. These trends, together with spatial variations within individual islands and the response to
vortex phase textures, are captured by a minimal semiclassical phase-accumulation picture. Our results identify geometry-defined Andreev trajectories as a design principle for phase-coherent superconducting cavities accessible by local spectroscopy.
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Materials Science
Moiré Phonons and Emergent Exciton-Phonon Coupling in a Moiré Heterobilayer
Can B. Uzundal, Woochang Kim, Zhiyuan Cui et al. (+13 more)
Moiré superlattices have emerged as a new platform for engineering electronic and optical properties in van der Waals
heterostructures, enabling control over correlated and excitonic phenomena. Yet the impact of moiré superlattices on
exciton-
phonon coupling remains largely unexplored. Here we demonstrate emergent, layer-selective coupling between moiré
phonons and moiré
excitons in angle-aligned WS2/WSe2 heterobilayers. Using a broadband terahertz
phonon transducer, we coherently launch moiré
phonons that resonantly perturb the excitonic states. We show that the
exciton-
phonon coupling is intrinsically modified by the moiré superlattice in a layer-selective manner. A driven oscillator model captures the dynamics, revealing three moiré
phonon resonances with distinct coupling to the moiré
excitons. First principles calculations show that many moiré
phonon modes can arise with distinct strongly hybridized in-plane and out-of-plane vibrations in the moiré unit
cells. The calculations further identify the three experimentally observed moiré
phonons and their emergent characteristic coupling to the moiré
excitons.
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All authors Can B. Uzundal, Woochang Kim, Zhiyuan Cui, Yuxuan Wei, Zheyu Lu, Qixin Feng, Francis L. Hong, Indrajit Maity, Takashi Taniguchi, Kenji Watanabe, Manish Jain, Mit H. Naik, Yoseob Yoon, Michael F. Crommie, Steven G. Louie, Feng Wang
Soft Condensed Matter
Universality of Bubble Coalescence in Electrolytic Media
Afsal Chakkam Palliyalil, Gaurav Tomar and Susmita Dash
Bubble coalescence phenomenon in electrolytic media finds applications in technologies from mineral flotation to electrochemical energy conversion. However, the underlying governing physics still remains unresolved, with longstanding disagreement over the extent to which Marangoni stresses affect the coalescence time by modulating the interfacial mobility. Here, we show that the thin film morphology governs drainage more strongly than the interfacial boundary conditions. We demonstrate experimentally that thin film drainage during bubble coalescence proceeds through three distinct regimes. An initial visco-capillary stage that exhibits a power-law thinning, followed by an exponential decrease in film thickness with time induced by rim stabilisation. The final regime is governed by disjoining pressure and is marked by an exponential relaxation of the film to the
equilibrium thickness. We show that, irrespective of the electrolyte type and concentration, film
evolution exhibits universal behavior by collapsing onto a single curve when rescaled with the characteristic film thickness and time scale, demonstrating that electrolyte effects act only to renormalize timescales rather than alter the underlying dynamics.
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Materials Science
Uniaxial compression of crystalline HCP titanium: an atomistic modelling study of size effects
Fatemeh Safari and Konstantinos Konstantinou
Understanding the deformation behaviour of titanium is important not only for technological advances associated with industrially-relevant applications, but also essential to achieve a fundamental understanding of the mechanical properties of the relevant
alloys. In this computational study, molecular-dynamics simulations are employed to ascertain the impact of model size on the mechanical response of alpha-titanium under compression. The deformation behaviour of the crystalline models is investigated as a function of different system sizes (varied by four orders of magnitude, up to 32 million atoms), and strain rates (down to 10^8 s^-1). The results show that the elastic properties remain independent of both system size and strain rate, whereas marked size effects emerge during plastic deformation. Increasing the system size of the titanium model reduces stress fluctuations, results in more homogeneous structural
evolution, and stabilizes dislocation activity. Decreasing the applied strain rate requires correspondingly a larger system size to achieve equilibration and to ensure a stable behaviour for the simulated structure. The modelling results demonstrate that system size and strain rate are strongly coupled, and their combined effect governs the simulated deformation behaviour of the compressed crystalline material.
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Materials Science · Cross-listed from physics.ins-det
A single platform with van der Pauw geometry for measurement of Seebeck coefficient, resistivity, and Hall effect of thin films
Niraj Kumar Singh, Martin Falk, Per-Anton Schön Wallander et al. (+3 more)
A modular thermoelectric properties measurement setup in van der Pauw configuration was developed for a straightforward and simultaneous measurement of electrical resistivity and Seebeck coefficient in an extensive temperature range of 25{\deg}C - 600{\deg}C and can also perform
Hall measurements at room temperature. The setup is optimized for accurate measurement of voltages and temperatures gradients by minimizing possible errors from offset voltages, wire contributions and thermal contact resistances which helps getting reliable data. The setup is user friendly, and the measurements are fully automated and controlled using a LabVIEW program. The detachable modules make this setup quite versatile and provide an all-in-one (except thermal conductivity) solution for thermoelectric measurements.
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All authors Niraj Kumar Singh, Martin Falk, Per-Anton Schön Wallander, Per Sandström, Per Eklund, Arnaud le Febvrier
Disordered Systems and Neural Networks
Scaling limit of the Random Language Model
Eric De Giuli
We develop a quantitative theory of the Random
Language Model (RLM), an ensemble of
stochastic context-free grammars, in a scaling limit where the number of hidden symbols $N \to \infty$ while the grammar temperature $\tilde{\epsilon}_d \to 0$ at fixed $x = {\tilde\epsilon}_d \log N$. In this limit, the model admits a controlled description based on a large-deviation principle over rule-usage patterns. A semi-annealed approximation maps the problem to a class of Random Energy Models with nontrivial combinatorics. We show that the RLM exhibits a condensation transition at a critical value $x_c=1/8$, below which rule usage concentrates and
language statistics acquire a nontrivial dependence on corpus length. A second characteristic scale at $x=1/2$ marks the onset of
entropy reduction from its maximal value. Across these regimes, we derive explicit scaling laws for the number of distinct rules,
entropy, and related observables, identifying distinct scaling, saturation, and critical regimes controlled by the interplay of grammar size, corpus length, and temperature. The theory resolves previous ambiguities regarding the existence of a thermodynamic transition and explains the slow approach to the large-$N$ limit as a consequence of the dependence on $\log N$. It further provides a unified framework in which universal statistical properties of
language emerge from typical realizations of generative grammars, with implications for both natural
language statistics and the behavior of large
language models.
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Disordered Systems and Neural Networks
Phase structure of the Random Language Model
Alessio Giorlandino, Eric De Giuli and Sebastian Goldt
Context-free grammars are minimal models of hierarchical structure in human
language, generating structured text from recursive production rules. The Random
Language Model (RLM) [De Giuli, PRL 2019], an ensemble of such grammars with random rule weights, exhibits a cross-over from gibberish-like output to structured text as a function of a "temperature", but the location and nature of this transition remained unclear. Here, we show that the RLM exhibits a hierarchy of phase transitions in a double-scaling limit where the grammar temperature $\tilde{\epsilon}_d \to 0$ and the number of hidden symbols $N \to \infty$ at fixed $x = \tilde{\epsilon}_d \log N$. By identifying the relation between RLM and the Random Energy Model, we identify a series of transitions where correlations between symbols emerge, single-symbol marginals become non-uniform, and rule use freezes in a glassy phase. A semi-annealed approximation yields nontrivial scaling laws for rule usage,
entropy, and energy, consistent with Heaps' law and context-length scaling observed in large
language models.
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Materials Science
Tuning the optoelectronic properties of wide bandgap perovskites: Data-driven insights from combinatorial synthesis and high-throughput experimentation
Alexander Wieczorek, Sergey Tsarev, Nathan Rodkey et al. (+4 more)
The discovery and optimization of wide-bandgap lead halide perovskites (LHPs) is hindered by solution-based workflows with limited scalability. Large compositional parameter spaces present an additional challenge for materials optimization. Here, we establish an integrated, combinatorial workflow based on sequential physical vapor deposition that enables independent tuning of cation (Cs/Pb) and anion (Br/Cl) compositions. Applying automated structural, compositional, and optical characterizations across >500 samples regions of interest are rapidly screened in the quaternary Cs-Pb-Br-Cl space. From the screening, we establish a practical Cs/Pb window of 1.05-1.20 for wide bandgap perovskites, within which elevated PL yields were observed. Through in-depth analysis of the data set, we uncover a high-energy optical transition as a robust determinant for high PL yields. By combining mechanistic insight into the compositional origins of high PL efficiency with a fully integrated, high-throughput screening framework, and by openly releasing the complete multi-modal
dataset, this work provides a broadly accessible
benchmark to accelerate data-driven discovery of wide-bandgap perovskites.
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All authors Alexander Wieczorek, Sergey Tsarev, Nathan Rodkey, Oleksandr Pshyk, Stefanie Frick, Maksym V. Kovalenko, Sebastian Siol
Mesoscale and Nanoscale Physics
Population-Dominated Ergotropy in a Capacitively Coupled Double-Quantum-Dot Battery under 1/f Charge Noise
Khalil Loukhssami, Khadija El Hawary, Sanaa Abaach et al. (+1 more)
We investigate extractable work storage in a capacitively coupled double
quantum dot (DQD)
quantum battery (QB) subjected to experimentally motivated detuning charge noise. The battery is modeled as two interacting charge
qubits with an Ising-type capacitive coupling and is charged by resonant microwave modulation of the tunnel coupling channel. Detuning fluctuations are introduced as classical
stochastic processes generated from a band-limited 1/f noise spectrum. For each noise realization, the
evolution remains
unitary, whereas decoherence and loss of contrast emerge after ensemble averaging. We analyze the total ergotropy, its population and coherent contributions, the energy basis populations, a passive ordering violation diagnostic, and the Jensen-Shannon coherence of the noise-averaged state. The results show that resonant tunnel coupling driving selects a dominant E0 <-> E3 population transfer channel in the interacting DQD spectrum. The dominant extractable work is stored in non-passive population distributions, in agreement with recent population ordering interpretations of ergotropy in QBs, while coherence accompanies and supports the resonant transfer as a transient dynamical resource. Detuning noise reduces the energy basis coherence amplitude and also weakens the population transfer pathway responsible for the dominant population ergotropy. This framework provides a noise-aware description of
semiconductor QB charging based on extractable work rather than on injected energy alone.
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All authors Khalil Loukhssami, Khadija El Hawary, Sanaa Abaach, Morad El Baz