Materials Science
Accelerating Structure-Property Relationship Discovery with Multimodal Machine Learning and Self-Driving Microscopy
Jiawei Gong, Danqing Ma, Ralph Bulanadi et al. (+4 more)
Microscopy combined with local spectroscopy is widely used to correlate nanoscale structure with functional properties in materials, but conventional measurements rely heavily on human-selected sampling locations and predefined targets, limiting
dataset diversity and the potential for discovery. Here, we present a framework that integrates autonomous microscopy with a dual-novelty deep kernel learning (DN-DKL) for adaptive data acquisition and a dual variational autoencoder (VAE) for representation learning. DN-DKL actively guides the microscopy toward structurally and spectroscopically novel regions, enabling efficient collection of large spectral
datasets. Dual-VAE embeds local structure and spectroscopic responses into a shared latent
manifold that serves as a structure-property relationship map. We applied this framework for the investigation of halide perovskite films using conductive atomic force microscopy. The results reveal distinct hysteresis behaviors that are linked to specific nanoscale structural motifs, including grain boundary junction points that show hysteresis under different bias conditions and asymmetric grain boundaries that suppress charge transport. This framework establishes a general strategy that leverages the complementary strengths of self-driving microscopy, machine learning, and human expertise to accelerate scientific discovery in functional materials.
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All authors Jiawei Gong, Danqing Ma, Ralph Bulanadi, Robert Moore, Rama Vasudevan, Lianfeng Zhao, Yongtao Liu
Statistical Mechanics
Resetting in a viscoelastic bath: the bath remembers
Ion Santra and Debankur Das
We study
stochastic resetting of a probe particle in a viscoelastic environment where only the probe is reset while the medium retains
memory of its past dynamics. Using a minimal model with finite correlation time, we analyze the competition between the resetting timescale and the viscoelastic relaxation timescale. This interplay leads to nonequilibrium steady states that differ qualitatively from those of Markovian Brownian motion with resetting. In particular, strong
memory effects produce stationary position distributions with non-exponential tails. For instantaneous resets, we derive the limiting steady-state distributions analytically and compute exactly the time dependent leading non-vanishing moments. We also investigate non-instantaneous resetting via constant-velocity return protocols. In contrast to overdamped Brownian motion, where steady-state fluctuations are independent of the return dynamics, we find that in a viscoelastic medium the fluctuations depend on the reset velocity. This protocol dependence arises from the finite
memory of the environment and highlights the role of environmental correlations in resetting-induced steady states.
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Statistical Mechanics
On deforming and breaking integrability
Ysla F. Adans, Marius de Leeuw and Tristan McLoughlin
In this paper we study nearest-neighbour deformations of integrable models. After expanding in the deformation parameter, we identify four possible types of deformations. First there are deformations that simply break or preserve integrability. Then we find two different subtle cases. The first case is where the deformation is only integrable if all orders of the deformation parameter are taken into account. An example of these are the long-range deformations that appear in
holographic models. The second case is when the deformation is perturbatively integrable to some order in the deformation parameter but can not be extended to an integrable model. In this paper we work this out for the XXZ
spin chain and discuss the level statistics of each of these cases. We find numerical evidence that the onset of chaos occurs differently in each of these models. For the perturbatively integrable models, we find that the deformation strength at which chaos appears demonstrates a volume-scaling intermediate between strong and weak integrability breaking models.
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Strongly Correlated Electrons
Luttinger's Theorem Violation and Green's Function Topological Invariants in a Fractional Chern Insulator
Anton A. Markov, Andrey M. Nikishin, Nigel R. Cooper et al. (+2 more)
Luttinger's
theorem constrains the particle density of interacting
fermions through global properties of the single-particle Green's function, and its violation signals a breakdown of the identification between the quantized
Hall response and the Green-function-based Ishikawa-Matsuyama invariant. This phenomenon becomes especially compelling in strongly correlated topological phases, such as fractional Chern
insulators, where fractionalized quasiparticles lack an adiabatic connection to electrons, raising the question of how Green's-function-based topological invariants manifest in such phases. Using exact diagonalization of the fermionic Harper-Hofstadter-Hubbard model, we compute bulk single-particle Green's functions deep inside a fractional Chern insulating phase and directly evaluate the Luttinger count, its possible correction (the Luttinger integral), and the Ishikawa-Matsuyama invariant $N_3[\mathrm{G}]$. We demonstrate a clear violation of Luttinger's
theorem and show that the fractional nature of the many-body Chern number is encoded in the Středa response of the Luttinger integral, while the integer invariant $N_3[\mathrm{G}]$ arises from the Středa response of the Luttinger count. We also analytically prove that $N_3[\mathrm{G}]$ is fully determined by the Luttinger count together with the Chern number of the occupied Bloch band, upon neglecting Bloch-band mixing. Finally, we propose an experimental protocol to extract all Green-function-based topological invariants from local density-of-states measurements, experimentally accessible in fractional
quantum Hall systems.
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All authors Anton A. Markov, Andrey M. Nikishin, Nigel R. Cooper, Nathan Goldman, Lucila Peralta Gavensky
Strongly Correlated Electrons
Electronic Sound and Diffusion in Disordered Multiband Metals
Miguel-Ángel Sánchez-Martínez, Blaise Goutéraux, Louk Rademaker et al. (+1 more)
Multiband metals can host acoustic plasmons: gapless collective charge excitations involving out-of-phase motion of electrons in different bands, sometimes referred to as 'demons'. Using a hydrodynamic description valid at high temperatures, and a microscopic description with vertex corrections valid at low temperatures, we show, upon including disorder inevitably present in real materials, that the mode frequency becomes purely imaginary, resulting in diffusive behaviour over a finite range of small wave vectors $q\le q_c$. This framework provides a natural, parameter-free explanation for the anomalous nonlinear dispersion recently reported for the demon in Sr$_2$RuO$_4$, which deviates from the gapless behaviour predicted by the random phase approximation. Our results establish demons as fundamentally distinct from previously known acoustic excitations, such as
phonons and
photons, which exhibit inertial dynamics protected by
symmetries or gauge redundancies.
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All authors Miguel-Ángel Sánchez-Martínez, Blaise Goutéraux, Louk Rademaker, Felix Flicker
Mesoscale and Nanoscale Physics
Maxim Trushin
Field emission from metals underpinned early
vacuum-tube technology, and recent nanoscale engineering made field-emission devices compatible with modern silicon platforms. However, the limited tunability of electron transport in metals has restricted their applicability. Here, we show that noble metals coated with
graphene exhibit clean non-monotonic $I-V$ characteristics arising from resonant tunneling through
graphene's electronic states, enabled by
graphene's atomic thinness and weak electronic hybridization with noble metals. Our approach combines ab-initio interface parameters with exact solutions of the Schrödinger equation for electron transmission across the interface. We analyze two experimentally relevant geometries: a vertical configuration with a flat suspended emitter and a coplanar configuration with sharp electrodes allowing for strong field enhancement and gating. These results establish a practical route to tunable electron transport in metal
heterostructures, positioning them as competitive components for air-channel field-emission nanoelectronics.
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Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
Chiral and bond-ordered phases in a triangular-ladder superconducting-qubit quantum simulator
Matthew Molinelli, Joshua C. Wang, Jeronimo G. C. Martinez et al. (+4 more)
Many-body systems with strong interactions often exhibit macroscopic behavior markedly absent in single-particle or noninteracting limits. Such emergent phenomena are well exemplified in
lattice Hubbard models, where the interplay between interactions,
geometric frustration, and
magnetic flux gives rise to rich physics. Superconducting
qubits naturally enable analog
quantum simulation of Bose-Hubbard models, while offering tunable parameters, site-resolved control, and rapid experimental repetition rates. Here, we study a superconducting-
qubit device that realizes the Bose-Hubbard model on a triangular-ladder
lattice. By tuning the magnitude and sign of couplings, we engineer a synthetic
magnetic flux to characterize the resulting half-filling ground state for various parameter regimes. We measure observables analogous to current-current correlators and bond kinetic energies, finding signatures consistent with
chiral superfluids, Meissner superfluids, and bond-ordered
insulators. Our results establish superconducting
circuits as a platform for robustly probing
quantum phases of matter in frustrated Bose-Hubbard systems, even in strongly correlated and gapless regimes.
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All authors Matthew Molinelli, Joshua C. Wang, Jeronimo G. C. Martinez, Sonny Lowe, Andrew Osborne, Rhine Samajdar, Andrew A. Houck
Soft Condensed Matter
Hydrodynamic Modeling of Odd Nematic Elasticity in Liquid Crystals
Zeyang Mou, Haijie Ren, Ding Xu et al. (+2 more)
There is a recent interest in studying odd elasticity in soft solids. Current focus has been on simple solids. However, many soft solids are structured and can exhibit nematic elasticity or viscoelasticity. Here we generalize the concept of odd elasticity to nematic elasticity. By rewriting the governing equation for two-dimensional nematic
liquid crystals (LCs) in terms of complex Ginzburg–Landau equation, we propose an odd nematic elastic term and its stress term in the hydrodynamic model of nematic LCs. The odd nematic elasticity can be physically interpreted as non-reciprocal interactions between neighboring directors. In odd nematics we find that domain walls become self-propelled and are accompanied by a bidirectional flow, and point defects can self-
spin, develop a spiral pattern, and induce a vortical flow. Interactions of a pair of defects show rich dynamics that are distinct from those in active nematics. As such, we have developed an odd general elasticity, which can be further generalized to other viscoelastic materials, and proposed a novel way to manipulate topological defects in nematic LCs.
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All authors Zeyang Mou, Haijie Ren, Ding Xu, Igor S. Aranson, Rui Zhang
Materials Science
From pore collapse to crystal growth: ultrafast laser-induced stishovite formation in nanoporous silica
Aram Yedigaryan, Mohamed Yaseen Noor, Elena Kachan et al. (+4 more)
The crystallization of amorphous solids under ultrafast
laser irradiation represents a paradigm of non-
equilibrium phase transitions, where the interplay between electromagnetic energy localization and atomic-scale dynamics remains largely uncharted. By using a multiscale framework that couples finite-difference time-domain simulations of nonlinear femtosecond
laser pulse propagation with molecular dynamics of the atomic response, we demonstrate that field enhancement around the pores of nanoporous amorphous silica confines
laser energy and drives rapid pore collapse. In nanoporous silica, the enhanced local electromagnetic field leads to stronger energy absorption compared with smaller-pore and homogeneous systems. This heterogeneous energy localization provides preferential nucleation sites within the dense glass network, leading to ultrafast formation of stishovite on a sub-nanosecond timescale, faster than in homogeneous silica. This accelerated crystallization can outpace pressure relaxation making the transition to a high-pressure phase possible. These results are confirmed by experimental observations of femtosecond-
laser-induced crystallization in confined geometries, and show that electromagnetic hotspots in nanoporous glass structures can be tailored to control solid-state transformations.
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All authors Aram Yedigaryan, Mohamed Yaseen Noor, Elena Kachan, Gabriel Calderon, Jinwoo Hwang, Enam Chowdhury, Jean-Philippe Colombier
Materials Science
Data-knowledge dual-driven intelligent framework for full-chain, experiment-efficient synthesis of 2D dendrites
Wenqiang Huang, Xuhang Gu, Susu Fang et al. (+9 more)
Exemplified by the chemical vapor deposition growth of two-dimensional dendrites, which has potential applications in catalysis and presents a parameter-intensive, data-scarce and reaction process-complex model problem, we devise a machine intelligence-empowered framework for the full chain support of material synthesis, encompassing rapid process optimization, accurate customized synthesis, and comprehensive mechanism deciphering.First, active learning is integrated into the experimental workflow, identifying an optimal recipe for the growth of highly-branched, electrocatalytically-active ReSe2 dendrites through 60 experiments (4 iterations), which account for less than 1.3% of the numerous possible parameter combinations.Then, a prediction accuracy-guided data augmentation strategy is developed combined with a tree-based machine learning (ML)
algorithm, unveiling a non-linear correlation between 5 process variables and fractal dimension (DF) of ReSe2 dendrites with only 9 experiment additions, which guides the synthesis of various user-defined DF. Finally, we construct a data-knowledge dual-driven mechanism model by integration of cross-scale characterizations, interpretable ML models, and domain knowledge in thermodynamics and kinetics, unraveling synergistic contributions of multiple process parameters to the product morphology. This work demonstrates the ML potential to transform the research paradigm and is adaptable to broader material synthesis.
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All authors Wenqiang Huang, Xuhang Gu, Susu Fang, Shen'ao Xue, Huanhuan Xing, Junjie Jiang, Junying Zhang, Shen Zhou, Zheng Luo, Jin Zhang, Fangping Ouyang, Shanshan Wang
Statistical Mechanics
Lifting the fog - a case for non-reversible "lifted" Markov chains
Gabriele Tartero, Sora Shiratani and Werner Krauth
Phase transitions appear all over science, and are familiar from everyday life, as water boiling, sugar melting into caramel or as nematic molecules turning smectic in
liquid-
crystal displays. The dynamics of phase transitions can be extremely slow, as for example when fog in winter does not lift, that is when the coarsening takes much time from many tiny water droplets to fewer but larger rain drops that feel the pull of
gravity. The dynamics of phase transitions is relevant also for the performance of computer
algorithms. In the ubiquitous Metropolis Monte Carlo
algorithm, the mixing dynamics towards
equilibrium leads towards the solution of a sampling problem. It is governed by the same reversibility and detailed-balance principles as the overdamped physical dynamics of fog. For the phase-separated Lennard-Jones system, we describe here how the coarsening dynamics of non-reversible "lifted" variants of the Metropolis
algorithm proceeds on much faster time scales, with the microscopic non-reversibility translating into large-scale relative motion of droplets that is impossible under the Ostwald-ripening condition of reversibility. A density-displacement coupling moves droplets relative to each other through a
lensing effect. Efficient implementations of the long-range Metropolis
algorithm and its non-reversible lifting (event-chain Monte Carlo) allow us to show that, in consequence, the coarsening growth exponent is larger under lifting. For large system sizes, the computing problem is thus solved infinitely faster than before, with the outcome strictly unchanged with respect to the Metropolis
algorithm. We also discuss the larger setting of our findings, namely that "lifted" non-reversible
algorithms can be set up for generic reversible sampling methods, with applications going much beyond our example of lifting fog.
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Disordered Systems and Neural Networks · Cross-listed from cs.LG
Stochastic Resetting Accelerates Reinforcement Learning Beyond Random Search
Jello Zhou, David J. Schwab and Vudtiwat Ngampruetikorn
Stochastic resetting – intermittently returning a process to a fixed reference state – has emerged as an effective mechanism for optimizing first-passage properties. Existing theory largely treats processes that search but do not learn: the searcher follows fixed dynamics, accumulating no knowledge between resets. Here we ask how
stochastic resetting interacts with reinforcement learning, where the underlying dynamics adapt through experience. In tabular grid environments, we find that resetting can accelerate learning even when it does not reduce the search time of a diffusive
agent. Our results reveal a distinct additional mechanism through which resetting speeds the propagation of reward information. We show that deterministic, sharp resetting accelerates learning more than the
stochastic protocol but over a narrower range of reset rates. In a continuous-state task with neural-network-based value approximation, we demonstrate that resetting speeds up learning when exploration is hard and rewards are sparse. We argue further that, in the tabular tasks, resetting accelerates learning without altering the solution the
agent ultimately reaches, unlike other techniques such as temporal discounting, which biases the optimal behavior. Our results establish
stochastic resetting as a simple, tunable mechanism for accelerating learning by shaping how experience accumulates, extending a canonical phenomenon of statistical mechanics to adaptive systems.
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Materials Science · Cross-listed from cs.CV
What DINO saw: ALiBi positional encoding reduces positional bias in Vision Transformers
Moritz Pawlowsky, Antonis Vamvakeros, Alexander Weiss et al. (+3 more)
Vision transformers (ViTs) - especially feature foundation models like DINOv2 - learn rich representations useful for many downstream tasks. However, architectural choices (such as positional encoding) can lead to these models displaying positional biases and artefacts independent of semantic content. This makes zero-shot adaption difficult in fields like material science, where images are often cross-sections of homogeneous microstructure (i.e. having no preferred direction). In this work, we investigate the positional bias in ViTs via linear probing, finding it present across a range of objectives and positional encodings, and subsequently reduce it by finetuning models to use ALiBi relative positional encoding. We demonstrate that these models retain desirable general semantics and their unbiased features can be used successfully in trainable
segmentation of complex microscopy images.
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All authors Moritz Pawlowsky, Antonis Vamvakeros, Alexander Weiss, Anja Bielefeld, Samuel J. Cooper, Ronan Docherty
Mesoscale and Nanoscale Physics
Complex Wannier centers and drifting Wannier functions in non-Hermitian Hamiltonians
Pedro Fittipaldi de Castro, Yifan Wang and Wladimir A. Benalcazar
The extension of topological band theory to non-Hermitian
Hamiltonians with line energy gaps remains largely unexplored, despite early indications of rich underlying physics. In these systems, Wilson loops, the objects characterizing polarization, become nonunitary. Yet, the physical consequences of this nonunitarity have remained unclear. Using biorthonormal
quantum mechanics, we introduce the concept of complex Wannier centers, defined from the gauge-invariant
eigenvalues of nonunitary Wilson loops. Complex Wannier centers acquire physical meaning through the breaking of reciprocity in their associated Wannier functions. When the centroid of a Wannier function shifts into the complex plane, it acquires an effective momentum offset that produces directional drift over time. We analyze how
symmetries constrain complex Wannier centers and identify
symmetry-protected Wannier configurations in pseudo-Hermitian
Hamiltonians, where the centers are either real or form complex-conjugate pairs, as determined by conserved "Krein signatures" of the projected metric operator of pseudo-Hermiticity. We further show that the Krein structure of the Wilson loop can establish a bulk-boundary correspondence: in a system with anticommuting pseudo-Hermitian metric and (pseudo) inversion
symmetries, the behavior of complex Wannier centers predicts the existence of a filling anomaly in the occupied bands and whether the resulting edge modes experience gain or loss. Finally, we propose an implementation of this system that enables experimental tests of our predictions.
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Mesoscale and Nanoscale Physics
Chiho Yoon and Fan Zhang
Recent experiments in rhombohedral
graphene report an unusual superconducting phase emerging from a
spin- and valley-polarized quarter-metal state. The prevailing interpretation invokes
chiral topological superconductivity, but the role of the `Fulde-Ferrell' phase factor due to intra-valley pairing has remained largely unexplored. Here we show, via a gauge transformation, that this phase is equivalent to an ordinary
chiral topological
superconductor on the triangular
lattice, while simultaneously forming an extraordinary Majorana
crystal on the dual honeycomb
lattice reminiscent of the Haldane model.
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Soft Condensed Matter
Thermo-Rheological Memory of $\kappa$-Carrageenan Fluid Gels Formed Under Flow
Julien Bauland, Tim J. Wooster, Peter Fischer et al. (+1 more)
Fluid gels are soft materials formed by shearing biopolymer solutions during the sol-gel transition. Their ability to yield and flow beyond a critical stress makes them attractive for designing versatile, biocompatible materials in food, health care and medical applications. Although it is well established that both microstructure and mechanical properties depend on the shear applied during gelation, a unified physical framework linking these features remains lacking. Here, using $\kappa$-carrageenan gels as a model system, we use a combination of rheology and confocal microscopy to tackle their shear-induced structuring in fluid gels. We identify a thermo-rheological
memory in $\kappa$-carrageenan gels formed under flow and show that it arises from a competition between shear and interparticle adhesion, captured by an Adhesion number. The resulting microstructural
evolution is reminiscent of the behavior of attractive particulate dispersions under simple shear flow, thereby bridging gels made of macromolecules and particulate gels. This framework provides a route to tune fluid gel properties without altering their composition.
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All authors Julien Bauland, Tim J. Wooster, Peter Fischer, Jan Vermant
Soft Condensed Matter
Visualizing shear-induced structures in carbon black gels by tomo-rheoscopy
Julien Bauland, Stéphane G. Roux, Stefan Gstöhl et al. (+3 more)
Suspensions of attractive particles form space-spanning networks that endow the suspension with solid-like behavior at rest. The microstructure of these colloidal gels depends sensitively on the shear history and on the path followed across the sol-gel transition, resulting in viscoelastic properties that can be tuned by shear. Here, we report in situ X-ray tomo-rheoscopy experiments on carbon black gels whose elastic properties exhibit a non-monotonic dependence on the shear intensity applied prior to flow cessation. By directly imaging the gel microstructure under a well-controlled rheological protocol, we reveal the emergence of pronounced structural heterogeneities extending from tens to hundreds of microns – length scales far larger than those accessible by conventional scattering techniques such as Ultra-Small Angle X-ray Scattering. In particular, we show that only the low-shear reinforcement of elasticity correlates with a growing mesoscale correlation length, while high-shear strengthening occurs without detectable mesoscale reorganization. These observations demonstrate that flow
memory in colloidal gels is not solely governed by local particle rearrangements, but is also encoded in a mesoscale structural organization extending up to 100 times the particle size. More broadly, this work highlights the power of X-ray tomo-rheoscopy to uncover large-scale structural signatures of flow history in soft materials, opening new perspectives to tailor their mechanical properties.
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All authors Julien Bauland, Stéphane G. Roux, Stefan Gstöhl, Christian M. Schlepütz, Michael Haist, Thibaut Divoux
Statistical Mechanics · Cross-listed from quant-ph
Quantum signal processing in Hilbert space fragmented systems
Naoya Egawa, Kaoru Mizuta and Joji Nasu
Quantum signal processing (QSP), originally developed for composite pulse sequences in
nuclear magnetic resonance systems, has recently attracted
attention as a unified framework for
quantum algorithms. A pioneering study applied QSP to nonequilibrium control in integrable many-body systems, enabling the realization of nonequilibrium dynamics with greater flexibility than Floquet engineering. However, extending QSP to nonintegrable systems faces fundamental obstacles arising from the limited number of conserved quantities and thermalization. In this work, we propose a protocol that leverages QSP in systems exhibiting
Hilbert space fragmentation (HSF). Specifically, we consider a pair-hopping model with four-fold periodic potentials that exhibits an HSF structure, thereby providing integrable and nonintegrable sectors within a single system. We analytically show that nonequilibrium dynamics can be flexibly designed through QSP engineered by these potentials in the integrable sectors. In contrast, we numerically identify signatures of thermalization in the nonintegrable sectors. Remarkably, by inserting domain walls, we achieve parallel control of multiple
quantum dynamics within a single system. This approach sheds light on the control of nonequilibrium dynamics from the perspective of
quantum computation by extending the scope of QSP to nonintegrable systems.
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Mesoscale and Nanoscale Physics
Magnetism Induced by Periodically Driven Non-Magnetic Impurities on Surfaces with Spin-Orbit Coupling
Malen Etxeberria-Etxaniz, Andrés Arnau and Asier Eiguren
We investigate the response of the Rashba
spin-orbit system to a time-periodic scalar potential, in order to determine whether an induced magnetization exists. We approach this by employing the Floquet-Green function method within the Keldysh formalism, computing the non-
equilibrium steady state of the system. We find that, even in the absence of an external
magnetic field, the system evolves into a state with an oscillating magnetization density that is remarkably rich in structure. We provide a detailed physical interpretation of the results by performing a
Fourier decomposition in non-local momentum-space, which helps to uncover the physical origin of the induced
magnetic field in terms of
Fermi surface
spin polarization and the system's dynamical character.
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Soft Condensed Matter
Optimal multi-parameter control of trapped active matter
Luke K. Davis
The realization of efficient micro-machines built from active matter requires precise thermodynamic control far from
equilibrium. Despite theoretical progress, the focus on single-parameter driving, coupled with strict theoretical assumptions, limits efforts to capture modern multi-parameter control experiments. Here, guided by careful theoretical considerations, we develop a transparent computational framework based on exact-gradient descent via automatic differentiation. We derive optimal protocols for a wide range of multi-parameter problems – involving trap stiffness, trap center, and particle activity – to minimize the thermodynamic work or heat. We demonstrate that smoothed, experimentally plausible protocols – obtained by assigning kinetic costs to the controls – achieve near-optimal efficiencies comparable to discontinuous “bang-bang” solutions. By exploring both open- and closed-loop control, we find the dynamical coupling between parameters leads to genuinely new strategies, including
symmetry breaking in optimal activity cycles and non-monotonic trap stiffness controls. Further, we identify regimes where initial measurement and multi-parameter flexibility combine to improve efficiency. Finally, we reveal that the naive simultaneous execution of independently optimized controls incurs only slightly more work than the full multi-parameter solutions. Taken together, our work elucidates the non-
equilibrium physics of multi-parameter control and provides robust, scalable strategies for controlling active matter.
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Quantum Gases · Cross-listed from quant-ph
How compactness curbs entanglement growth in bosonic systems
Stefan Aimet, Philipp Schmoll, Jens Eisert et al. (+2 more)
Zero modes, understood here as degrees of freedom with vanishing confining frequency, play a central role in the nonequilibrium dynamics of bosonic systems. In Gaussian models, however, they lead to an unbounded, logarithmic growth of
entanglement entropy. We show that this divergence is not an intrinsic property of zero modes themselves, but arises specifically for non-compact zero modes. Their non-compact configuration space allows unbounded spreading in position space, while their continuous spectra enable indefinite dephasing in momentum space. By contrast, compact zero modes in compact bosonic systems behave fundamentally differently: Spreading and dephasing are eventually halted, so that compactness caps the
entanglement entropy at a finite value, making its dynamical role most transparent in the presence of a zero mode. We demonstrate this mechanism in a minimal setting by comparing two coupled harmonic oscillators with two coupled
quantum rotors. We then show that the same physics persists in many-body systems by contrasting an N-site compact rotor chain with the non-compact harmonic chain. Finally, we relate these insights to ultra-cold-atom realizations of compact
quantum field theories. In particular, we clarify when a compact free-
boson (Tomonaga-Luttinger
liquid) description is required and when the commonly used non-compact massless Klein-Gordon model breaks down. Even when the initial state is accurately captured by a non-compact Gaussian description, compactness ultimately governs the late-time quench dynamics, curbing
entanglement growth rather than allowing a dynamical divergence.
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All authors Stefan Aimet, Philipp Schmoll, Jens Eisert, Jörg Schmiedmayer, Spyros Sotiriadis
Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
Decoherence and the Reemergence of Coherence From a Superconducting "Horizon"
Eric J. Sung and Charles A. Stafford
In a recent paper [arXiv:2205.06279], Danielson et al. demonstrated that the mere presence of a black hole causes universal decoherence of
quantum superpositions (dubbed the DSW decoherence). We analyze decoherence in a superconducting analogue [arXiv:1709.06154] of the event horizon of a late-stage black hole, where Andreev reflection plays the role of Hawking radiation. We consider a normal metal interferometer threaded by an Aharonov-Bohm flux, where one of the arms of the interferometer is coupled to a
superconductor by a tunnel coupling of varying strength. At absolute zero temperature and for weak coupling, we find that the scattering states of the interferometer are decohered by Andreev reflection, a nontrivial manifestation of the proximity effect analogous to DSW decoherence from the event horizon of a black hole. However, for increasing coupling strength to the
superconductor, we find a reemergence of coherence via resonant tunneling through Andreev bound states. This suggests the existence of an analogue gravitational phenomenon wherein transmission mediated by virtual Hawking radiation leads to a reemergence of coherence in an interferometer placed near a black hole's event horizon.
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Statistical Mechanics · Cross-listed from quant-ph
An asymmetry lower bound on fermionic non-Gaussianity
Filiberto Ares, Michele Mazzoni, Sara Murciano et al. (+3 more)
Fermionic Gaussian states are a fundamental tool in many-body physics, faithfully representing non-interacting
quantum systems and allowing for efficient numerical simulations. Given a many-body wave function, it is therefore interesting to ask how much it differs from that of a Gaussian state, as quantified by the notion of non-Gaussianity. In this work, we relate measures of non-Gaussianity with the Shannon
entropy of the particle-number distribution, coinciding with the particle-number asymmetry for pure states. We derive a lower bound on the relative
entropy of non-Gaussianity in terms of the exponential of the Shannon
entropy, and study numerically its tightness for large system sizes. Our bound is non-trivial for large values of the asymmetry and relies on the concentration of the particle-number distribution of (mixed) fermionic Gaussian states. Since the Shannon
entropy of the particle-number distribution is often efficient to compute or experimentally measure, our results can be viewed as a practical way to lower bound non-Gaussianity, highlighting a non-trivial interplay with particle-number asymmetry.
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All authors Filiberto Ares, Michele Mazzoni, Sara Murciano, Dávid Szász-Schagrin, Pasquale Calabrese, Lorenzo Piroli
Materials Science
Phonon collisional broadening and heat transport beyond the Boltzmann equation
Enrico Di Lucente, Nicola Marzari and Michele Simoncelli
In
crystals, macroscopic technological properties such as thermal conductivity originate from the microscopic drift and scattering of
phonons, commonly described by the Boltzmann Transport Equation (BTE). Despite its widespread use, the most general space-time nonlocal form of the BTE still lacks a rigorous derivation of its collisional part based on
Fermi's Golden Rule (FGR), and becomes inadequate in several regimes, including when the energy-variation scale set by
phonon dispersion approaches that of collisional broadening. A hallmark of this issue is the poor numerical convergence of conductivity with respect to the smearing used to evaluate FGR rates. This is often circumvented using adaptive schemes, which however violate detailed balance and allow unphysical negative
eigenvalues in the collision operator. Here, we overcome these limitations by rigorously deriving the space-time-dependent BTE from the Kadanoff-Baym Equations (KBE), and introduce a linearized generalized BTE (LGBTE) that goes beyond the FGR framework, incorporating self-consistent, physically derived, fully anharmonic, and mode-resolved collisional broadening and energy-nonconserving scattering. More generally, we establish a hierarchy of ansätze on Green's functions, enabling controlled extensions of the semiclassical BTE and a roadmap toward
quantum KBE accuracy. Finally, using first-principles simulations complemented by analytical arguments, we show that this approach addresses two long-standing problems of the FGR-based linearized BTE across
crystal dimensionalities: (i) the lack of conductivity convergence, common to heat conductors like diamond; and (ii) its universal failure in all 2D systems, rooted in FGR predicting an unphysical overdamping for scattering channels involving flexural vibrations, as shown in the insulating {\alpha}-GeSe monolayer.
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Strongly Correlated Electrons
Machine Learning Reconstruction of High-Dimensional Electronic Structure from Angle-Resolved Photoemission Spectroscopy
Yu Zhang, Yong Zhong, Nhat Huy Tran et al. (+7 more)
The emergent behavior of
quantum materials is governed by their electronic structure, which can be experimentally probed by photoemission spectroscopy techniques that generate a four-dimensional
dataset of energy and momentum. However, the quantitative extraction of
Hamiltonian parameters from these high-dimensional spectra remains a significant challenge, currently relying on labor-intensive, expert-dependent analysis rather than standardized workflows. Here, we introduce a deep learning framework based on implicit neural representations to accelerate the
retrieval of
Hamiltonian parameters in two types of transition-metal
oxides: perovskite nickelates and manganites. Our approach outperforms traditional analytical fitting procedures, yielding superior agreement with experimental
Fermi surface
topologies and energy-momentum dispersions. This work highlights the potential of deep learning tools to bridge the gap between theory and experiment, paving the way for high-throughput, autonomous discovery pipelines in
quantum materials.
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All authors Yu Zhang, Yong Zhong, Nhat Huy Tran, Shuyi Li, Kyuho Lee, Yonghun Lee, Tiffany C. Wang, Harold Y. Hwang, Zhi-Xun Shen, Chunjing Jia
Quantum Gases
Fate of a Fractional Chern Insulator under Nonlocal Interactions in Synthetic Dimensions
Patrick Liam Geraghty, Alberto Nardin, Leonardo Mazza et al. (+1 more)
Synthetic dimensions provide a powerful route to engineer topological
lattice models in ultracold atomic systems, but they contain intrinsic nonlocal interactions along the synthetic direction. We investigate an extended Harper-Hofstadter model subject to infinite-range column interactions that mimic this synthetic nonlocality. By tuning this interaction strength, we demonstrate an adiabatic
evolution from a Laughlin-type bosonic fractional Chern
insulator to a charge-ordered Tao-Thouless-like state without closing the many-body gap. Along this path, the many-body Chern number and the topological
entanglement entropy remain unchanged, despite a pronounced restructuring of the
entanglement spectrum and the loss of robustness against local perturbations. This adiabatic connectivity establishes a controlled bridge between topologically ordered and effect- ively one-dimensional charge-ordered regimes, opening potential new avenues for state preparation. Our results also show that conventional topological markers may fail to diagnose the breakdown of locality-protected topological order in synthetic dimensions, and identify nonlocal interactions as a powerful knob to coherently interpolate between distinct many-body regimes.
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All authors Patrick Liam Geraghty, Alberto Nardin, Leonardo Mazza, Matteo Rizzi
Materials Science
Low bending rigidity and large Young's modulus drive strong flexural phonon renormalization in two-dimensional monolayers
Navaneetha K Ravichandran
Many intriguing phenomena such as the wave-like hydrodynamic heat flow, the logarithmic divergence of electrical resistivity at low temperatures and microscale kirigami are driven by flexural acoustic (ZA)
phonons in two-dimensional (2D) materials. Yet, a definitive first-principles description of their dispersion, with explicit consideration of the
crystal anharmonicity and the stability of large 2D monolayers against thermal fluctuations, is lacking in the literature. Using first-principles calculations, we show that the bending
rigidity ($\kappa$) controls the anharmonic renormalization of the ZA
phonons throughout the Brillouin zone in 2D monolayers, with stronger renormalization in low-$\kappa$ materials like germanene and weaker effects in high-$\kappa$ materials like molybdenum disulphide. Furthermore, the ZA
phonons at long wavelengths undergo an additional renormalization to stabilize the flat phase of the 2D monolayers against thermal fluctuations, which is modulated by the competing influence of the bending
rigidity and the in-plane Young's modulus in all materials. The resulting renormalized ZA
phonon dispersions are qualitatively and quantitatively different from those commonly used by the first-principles community, thus motivating a re-examination of the ZA
phonon-driven unconventional thermal and electronic phenomena in 2D as well as lower-dimensional systems. Our work provides new insights into the role of nanoscale
crystal anharmonicity and macroscale elasticity in shaping the vibrational properties of 2D materials and will inform novel engineering applications that are exclusive to low dimensions such as kirigami, with materials beyond
graphene.
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Materials Science · Cross-listed from cs.LG
Novelty-Driven Target-Space Discovery in Automated Electron and Scanning Probe Microscopy
Utkarsh Pratiush, Kamyar Barakati, Boris N. Slautin et al. (+4 more)
Modern automated microscopy faces a fundamental discovery challenge: in many systems, the most important scientific information does not reside in the immediately visible image features, but in the target space of sequentially acquired spectra or functional responses, making it essential to develop strategies that can actively search for new behaviors rather than simply optimize known objectives. Here, we developed a deep-kernel-learning BEACON framework that is explicitly designed to guide discovery in the target space by learning structure-property relationships during the experiment and using that evolving model to seek diverse response regimes. We first established the method through demonstration workflows built on pre-acquired ground-truth
datasets, which enabled direct benchmarking against classical acquisition strategies and allowed us to define a set of monitoring functions for comparing exploration quality, target-space coverage, and surrogate-model behavior in a transparent and reproducible manner. This benchmarking framework provides a practical basis for evaluating discovery-driven
algorithms, not just optimization performance. We then operationalized and deployed the workflow on STEM, showing that the approach can transition from offline validation to real experimental implementation. To support adoption and extension by the broader community, the associated notebooks are available, allowing users to reproduce the workflows, test the
benchmarks, and adapt the method to their own instruments and
datasets.
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All authors Utkarsh Pratiush, Kamyar Barakati, Boris N. Slautin, Catherine C. Bodinger, Christopher D. Lowe, Brandi M. Cossairt, Sergei V. Kalinin
Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
Kibble-Zurek Mechanism in the Open Quantum Rabi Model
T. Pirozzi, G. Di Bello, V. Cataudella et al. (+2 more)
The Kibble-Zurek mechanism provides a universal framework for predicting defect formation in non-
equilibrium phase transitions. While Markovian dissipation typically degrades universal scaling, the impact of non-Markovian
memory remains largely unexplored. We demonstrate that an Ohmic bath induces a Berezinskii-Kosterlitz-Thouless transition in the open
quantum Rabi model. Using simulations based on
Matrix Product States, we show that the excitation energy strictly follows universal Kibble-Zurek power-law scaling when evaluated at the freeze-out time. Crucially, we find that since the environment defines the universality class, dissipation does not inherently compete with adiabatic dynamics, in stark contrast to Markovian regimes. Our results establish the Kibble- Zurek mechanism as a robust witness of universality in open
quantum systems, revealing that non-Markovian
memory preserves the integrity of non-
equilibrium scaling.
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All authors T. Pirozzi, G. Di Bello, V. Cataudella, C. A. Perroni, G. De Filippis
Mesoscale and Nanoscale Physics
Correlated Quantum Phenomena in Confined Two-Dimensional Hexagonal Crystals
Xiang Liua, Zheng Taoa, Wenchen Luoa et al. (+1 more)
Low-energy fermionic excitations in two-dimensional materials deviate from the conventional Schrödinger description and are instead governed by Dirac equations. Such Dirac
fermions give rise to a variety of unconventional
quantum phenomena that have no direct analogues in traditional condensed matter systems. Among these materials,
graphene and transition metal dichalcogenides (TMDs) represent two prototypical platforms, hosting massless and massive Dirac particles, respectively, and exhibiting rich electronic, optical, and valley dependent properties. Here we review the effect of the
quantum confinement in these two-dimensional hexagonal materials that provides a powerful route to enhance Coulomb interactions and stabilizing correlated
quantum states. In
graphene- and TMD-based
quantum dots, externally imposed confinement leads to discrete electronic and excitonic spectra, where interaction effects are strongly amplified. In twisted van der Waals
heterostructures, the moiré superlattices generate emergent confinement and induce nontrivial band
topology, giving rise to a wealth of novel phenomena. More generally, reduced dimensionality and spatial localization in two-dimensional materials promote a diverse range of correlated states. Recent experimental and theoretical advances highlight the central role of confinement in shaping
quantum behavior and reveal new opportunities for applications based on these states. In this review, we provide an overview of recent progress in confinement-induced correlated phenomena in two-dimensional materials from both theoretical and experimental perspectives.
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All authors Xiang Liua, Zheng Taoa, Wenchen Luoa, Tapash Chakraborty