Materials Science
Benchmarking Machine Learning Approaches for Polarization Mapping in Ferroelectrics Using 4D-STEM
Matej Martinc, Goran Dražič, Anton Kokalj et al. (+5 more)
Four-dimensional scanning transmission electron microscopy (4D-STEM) provides rich, atomic-scale insights into materials structures. However, extracting specific physical properties - such as polarization directions essential for understanding functional properties of ferroelectrics - remains a significant challenge. In this study, we systematically
benchmark multiple machine learning models, namely ResNet, VGG, a custom convolutional neural network, and PCA-informed k-Nearest Neighbors, to automate the detection of polarization directions from 4D-STEM diffraction patterns in ferroelectric potassium sodium niobate. While models trained on synthetic data achieve high accuracy on idealized synthetic diffraction patterns of equivalent thickness, the domain gap between simulation and experiment remains a critical barrier to real-world deployment. In this context, a custom made prototype representation training regime and PCA-based methods, combined with data augmentation and filtering, can better bridge this gap. Error analysis reveals periodic missclassification patterns, indicating that not all diffraction patterns carry enough information for a successful classification. Additionally, our qualitative analysis demonstrates that irregularities in the model's prediction patterns correlate with defects in the
crystal structure, suggesting that supervised models could be used for detecting structural defects. These findings guide the development of robust, transferable machine learning tools for electron microscopy analysis.
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All authors Matej Martinc, Goran Dražič, Anton Kokalj, Katarina Žiberna, Janina Roknić, Matic Poberžnik, Sašo Džeroski, Andreja Benčan Golob
Materials Science
Engineering van der Waals heterostructures for dispersion-selective meV-scale quantum sensing
Elizabeth A. Peterson
Quantum sensing of meV-scale scattering and absorption of impinging particles with electrons in solid state detectors is a challenging technological advancement with the potential to enable breakthroughs in
quantum information applications and studies of fundamental physics. However, a key obstacle for current sensing schemes is the difficulty in distinguishing the signals from particles of interest and from intrinsic excitations, like
phonons or
magnons. Here we propose a technique to selectively detect impinging particles based not only on their imparted energy, but specifically by their dispersion relations. By harnessing interfacial orbital hybridization in van der Waals
heterostructures of Dirac materials, interlayer charge transfer may be promoted only for pre-selected impinging particles of interest. Using first-principles density functional theory (DFT) calculations of
heterostructures of the layered Dirac materials ZrTe5 and HfTe5, we examine the effects of strain and layer number for successfully tuning orbital hybridization in their electronic structure. We demonstrate a proof-or-principle feasibility study for using Dirac materials to construct dispersion filters to be leveraged for next-generation meV-scale
quantum sensors.
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Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
Simulating the Open System Dynamics of Multiple Exchange-Only Qubits using Subspace Monte Carlo
Tameem Albash and N. Tobias Jacobson
We propose a Monte Carlo based method for simulating the open system dynamics of multiple exchange-only (EO)
qubits. In the EO encoding, the total
spin projection
quantum number along the $z$-axis of the three constituent
spins remains unchanged under exchange operations, in contrast to the open system (or multi-
qubit miscalibration) setting where coherent and incoherent mixing of states with different
quantum numbers occurs. In our approach, we choose to measure the total
spin component along the $z$-axis of each EO
qubit after every logical
quantum operation, which decoheres coherent mixtures of states with different
spin projection
quantum numbers. Independent simulations thus give different trajectories of the system in the associated subspaces, so we refer to this method as the Subspace Monte Carlo method. With each EO
qubit having a definite
spin projection
quantum number, the density
matrix of $n$
qubits can be represented by a vector of dimension $3^{2n}$, instead of $8^{2n}$, with an additional vector of dimension $n$ to label the
quantum number of each
qubit. We show that this approximation of the dynamics remains faithful to the true dynamics when the simulated
circuits twirl the noise, converting coherent errors to
stochastic errors, which can be achieved using randomized compiling. We use this simulation approach to study how correlations in measurement outcomes of
circuits with reset-if-leaked gadgets, such as a multi-round Bell state stabilization
circuit that uses 6 EO
qubits, are affected by the choice of CNOT implementations.
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Strongly Correlated Electrons
Pseudogapped Fermi liquids from emergent quasiparticles
Andreas Gleis and Gabriel Kotliar
We propose an interacting model that is exactly solvable in any spatial dimension and gives rise to a
Fermi liquid (FL) featuring a pseudogapped (PG) single-particle spectral function and a vanishing quasiparticle (QP) weight at half-filling, without invoking Mott physics. The PG originates from a purely fermionic mechanism through emergent QPs arising from a correlated hopping interaction. By employing an appropriate coherent-state basis, we derive a Gaussian path-integral representation of the partition function, which enables systematic treatments of deviations from the Gaussian limit using standard many-body techniques, such as diagrammatic perturbation theory or mean-field theory. We explicitly demonstrate and discuss several properties of the exactly solvable limit on the square
lattice, including the mechanism for temperature-dependent PG opening, the singular behavior of the self-energy, the violation of the Luttinger sum rule, and the role of Luttinger and
Fermi surfaces. Finally, we explore
quantum phase transitions between PG-FLs and Landau FLs.
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Mesoscale and Nanoscale Physics
Spin-Transfer Torque on Curved Surfaces: A Generalized Thiele Formalism
J. I. Costilla, M. Castro, K. V. Yershov et al. (+3 more)
Curvature is a highly relevant parameter when considering nanostructures, favoring the stability and affecting the dynamics of
magnetic textures. In this work, we address the
spin-transfer torque phenomenon by deriving an expanded Thiele equation with the Zhang-Li term for curved surfaces. Our results show a coupling between current and
curvature, which is perceived as a gyrovector and an additional dissipative tensor associated with this coupling. Using this model, we determine the dynamics of a skyrmion in a nanotube with Gaussian and variable mean
curvature. The new terms included in the Thiele equation are responsible for an additional
Hall effect in the skyrmion dynamics and for the generalization of the Walker limit condition.
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All authors J. I. Costilla, M. Castro, K. V. Yershov, D. Altbir, V. L. Carvalho-Santos, V. P. Kravchuk
Disordered Systems and Neural Networks · Cross-listed from quant-ph
Analog-Digital Quantum Computing with Quantum Annealing Processors
Rahul Deshpande, Majid Kheirkhah, Chris Rich et al. (+12 more)
Quantum annealing processors typically control
qubits in unison, attenuating
quantum fluctuations uniformly until the applied system
Hamiltonian is diagonal in the computational basis. This simplifies control requirements, allowing annealing QPUs to scale to much larger sizes than gate-based systems, but constraining the class of available operations. Here we expand the class by performing analog-digital
quantum computing in a highly-multiplexed, superconducting
quantum annealing processor. This involves
evolution under a fixed many-body
Hamiltonian that, in the weak-coupling regime, is well-described by an effective XY model, together with arbitrary-basis initialization and measurement via auxiliary
qubits. Operationally, this is equivalent to implementing single-
qubit gates at the beginning and end of an analog
quantum evolution. We demonstrate this capability with several foundational applications: single-
qubit and two-
qubit coherent oscillations with varying initialization and measurement bases, a multi-
qubit quantum walk with fermionic dispersion in line with theory, and Anderson localization in a disordered chain. These experiments open the door to a wide range of new possibilities in
quantum computation and simulation, greatly expanding the applications of commercially available
quantum annealing processors.
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All authors Rahul Deshpande, Majid Kheirkhah, Chris Rich, Richard Harris, Jack Raymond, Emile Hoskinson, Pratik Sathe, Andrew J. Berkley, Stefan Paul, Brian Barch, Daniel A. Lidar, Markus Müller, Gabriel Aeppli, Andrew D. King, Mohammad H. Amin
Mesoscale and Nanoscale Physics
Umklapp-Enhanced Interlayer Valley Drag in Moiré Bilayers
Ritajit Kundu, Mandar M. Deshmukh, Herbert A. Fertig et al. (+1 more)
Van der Waals materials may be combined to form moiré patterns that are effectively
crystal lattices. These systems are unique in that their in-plane unit
cell sizes may be orders of magnitude larger than interlayer separations, leading to unique behaviors emerging from interlayer interactions. In this work, we investigate interlayer valley drag in
lattice-matched moiré
bilayers, demonstrating a remarkable enhancement due to umklapp scattering. In contrast to drag phenomena in more conventional two-dimensional systems, interlayer valley drag appears at first order in the interlayer interaction, and remains non-vanishing in the low temperature limit even at this low order in the interlayer coupling. We propose an experimental geometry, feasible with current state-of-the-art fabrication techniques, to detect and characterize this effect in moiré
bilayer systems.
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All authors Ritajit Kundu, Mandar M. Deshmukh, Herbert A. Fertig, Arijit Kundu
Statistical Mechanics
Glass and jamming transitions in a random organization model
Leonardo Galliano and Ludovic Berthier
We study a two-dimensional, off-
lattice particle model introduced to describe absorbing phase transitions in driven non-Brownian suspensions. We numerically explore the $(\phi,\epsilon)$ phase diagram, where $\phi$ is the packing fraction and $\epsilon$ controls the amplitude of particle jumps. We use a binary mixture to suppress crystallization, which allows us to disentangle the model's distinct phase transitions between amorphous states. At large $\phi$, we find that the approach to the absorbing transition is preceded by a non-
equilibrium glass transition to a non-diffusive amorphous state. This dynamic arrest makes the location of the critical absorbing transition protocol-dependent. The $\epsilon \to 0$ end-point of the transition line defines a jamming transition whose location is shown to vary continuously with the preparation protocol, and cannot serve as a unique definition of random close packing. Near jamming, we observe a complex landscape and marginal stability, reminiscent of Gardner phases found in thermal glasses. The critical exponents characterizing packings at the jamming transition numerically agree with alternative approaches based on energy minimization, and with analytic predictions from mean-field replica theory. We analyze hyperuniformity of large-scale density fluctuations in fluid and glass phases, where it emerges with qualitatively distinct signatures, and show that random organization dynamics does not determine the hyperuniformity observed in jammed packings, which is found to be non-universal. Our results show that random organization models share deep physical similarities with thermal soft-particle systems undergoing glass and jamming transitions, with little impact of the non-
equilibrium nature of the microscopic dynamics on emerging physical properties.
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Superconductivity
Effect of pulse duration on current-induced selective oxygen migration in high-Tc superconductors
Fridrich Egyenes, Daniel Stoffels, Stefan Marinkovic et al. (+6 more)
High current densities can induce the directional
diffusion of atoms in metallic films. In YBa$_2$Cu$_3$O$_{7-\delta}$ (YBCO), this electromigration process selectively acts on oxygen atoms lying in the Cu-O chains, permitting to vary the oxygen concentration in a targeted spot of high current density. This approach has proven successful in mapping the phase diagram of the material as a function of carrier concentration or as a way to manufacture memristive devices owing to its reversibility under small bipolar excitations. Thus far, most of the investigations have been limited to pulsed excitation with current/voltage pulses on a millisecond or longer scale, for which thermal effects undeniably influence the process. In the present work, we explore the impact of pulse length $\delta t$ on the onset current of electromigration, $I_{\text{EM}}$, of YBCO bridges, covering the range from 200 ns to 1 ms. As $\delta t$ decreases below $\sim 10~\mu$s, $I_{\text{EM}}$ exhibits a rapid increase. Analytical and numerical estimates of the local temperature show that as pulses shorten, the temperature decreases, making the electromigration process more athermal. These findings are relevant for the operation of memristors and should be taken into account when describing the effects of thermomagnetic instabilities in thin films.
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All authors Fridrich Egyenes, Daniel Stoffels, Stefan Marinkovic, Bernd Aichner, Huidong Li, Anna Palau, Milan Tapajna, Wolfgang Lang, Alejandro V. Silhanek
Materials Science
High-Throughput Computational Exploration of MOFs for Short-Chain PFAS Removal
Mengru Zhang, Satyanarayana Bonakala, Taku Watanabe et al. (+2 more)
Short-chain per- and polyfluoroalkyl substances (PFASs) are increasingly replacing regulated long-chain PFASs, yet they remain challenging to remove from water due to their high persistence, mobility, and weak affinity toward conventional adsorbents. In this work, we developed a hybrid high-throughput computational screening (HTCS) strategy to identify high-performance MOFs for the selective adsorption of perfluorobutanoic acid (PFBA), a representative short-chain PFAS, from water. The workflow begins with a curated MOF
dataset and employs Monte Carlo (MC) simulations based on synergistic use of a classical universal force field (UFF) and a universal machine-learned interatomic potential (u-MLIP), enabling scalable and quantitatively accurate prediction of adsorption across large MOF databases. A set of promising MOFs initially identified using UFF-based HTCS, that combine strong PFBA affinity and high PFBA/H2O selectivity were re-evaluated with u-MLIP to refine adsorption predictions and to assess guest-induced framework flexibility, enabling the exclusion of materials with unfavourable high water-framework interactions. Ultimately, four high-performance MOFs were identified that optimally balance strong PFBA interactions, high PFBA selectivity over water, and practical considerations including sustainability, water stability, and synthetic feasibility. This study demonstrates that combining classical force fields with u-MLIPs enables scalable, quantitatively accurate MOF adsorption screening and establishes transferable principles for the rational design of adsorbents targeting short-chain PFAS.
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All authors Mengru Zhang, Satyanarayana Bonakala, Taku Watanabe, Karim Hamzaoui, Guillaume Maurin
Materials Science
Agentic workflow enables the recovery of critical materials from complex feedstocks via selective precipitation
Andrew Ritchhart, Sarah I. Allec, Pravalika Butreddy et al. (+5 more)
We present a multi-agentic workflow for critical materials recovery that deploys a series of AI
agents and automated instruments to recover critical materials from produced water and magnet leachates. This approach achieves selective precipitation from real-world feedstocks using simple chemicals, accelerating the development of efficient, adaptable, and scalable separations to a timeline of days, rather than months and years.
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All authors Andrew Ritchhart, Sarah I. Allec, Pravalika Butreddy, Krista Kulesa, Qingpu Wang, Dan Thien Nguyen, Maxim Ziatdinov, Elias Nakouzi
Strongly Correlated Electrons
Single-Crystal Growth and Physical Properties of the Antiferromagnetic Double Perovskite Ba_2CoMoO_6
A.R.N. Hanna, M. M. Ferreira-Carvalho, S.H. Chen et al. (+6 more)
This work presents a comprehensive investigation of the structural,
magnetic, and electronic properties of the double perovskite Ba$_2$CoMoO$_6$ (BCMO). Single
crystals were grown via floating-zone and Czochralski growth techniques and characterized using a set of complementary methods. X-ray diffraction analysis confirmed that BCMO crystallizes in a face-centered cubic (FCC) structure with space group $Fm\overline{3}m$.
Magnetic susceptibility measurements exhibit
antiferromagnetic ordering below $T_{\mathrm{N}} = 20.1(1)$~K. A
spin-flop transition is observed at 26.5~kOe. Heat capacity measurements and
entropy analysis are consistent with a $J_{\mathrm{eff}} = 1/2$ ground state for Co$^{2+}$ ions. X-ray absorption spectroscopy provided insight into the local electronic structure, revealing the
spin-orbit and
crystal field effects. The cluster-model analysis yields a $g$-factor of 4.36, consistent with a
spin-orbit-entangled ground state. Surface photovoltage spectroscopy demonstrates a strong near surface optical response with an onset near 1.5~eV and a pronounced feature at 2.65~eV, consistent with visible range Co–O–Mo transitions in line with related Ba-based double perovskites, highlighting its potential for spintronic and energy conversion applications.
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All authors A.R.N. Hanna, M. M. Ferreira-Carvalho, S.H. Chen, C. F. Chang, C. Y. Kuo, A.T.M.N. Islam, R. Feyerherm, L.H. Tjeng, B. Lake
Materials Science
Understanding early stages of low-temperature hydrogen-driven direct co-reduction of Fe-Ni mixed oxide thin films at the near atomic scale
Emmanuel Uwayezu, Shaolou Wei, Yujiao Li et al. (+3 more)
Kinetic understanding of hydrogen co-reduction of multinary and multi-phase
oxides is of interest for enhancing sustainability of
alloy production and transition to a hydrogen-based economy. Benefits include decrease in energy consumption, enhanced kinetics, and conversion of
oxides to
alloys. Thin films provide a platform to study these processes as reactive co-deposition from multiple elemental,
alloy or compound targets and precise oxygen flow control allow atomic mixing into various
oxide phases which are well-defined nanoscale precursor structures for the subsequent reduction study at the near atomic scale. The early stages of hydrogen direct reduction of
oxide thin films are investigated using a Fe50Ni50Ox thin film consisting of NiFe2O4 and NiO phases. After reduction at 280 C in pure H2 for different times, structural, morphological, and nanoscale changes were examined by different characterisation methods including atom probe
tomography (APT). The low-temperature reduction is nucleation-limited marked by grain-boundary nucleation preceded by an incubation time of more than 5 min. APT revealed that the early-stages of the reduction involves phase separation into a Ni-rich FexNiy metallic phase and a transformed remaining
oxide (magnetite, Fe3O4). Further reduction induces magnetite reduction and alloying into a nearly equiatomic FeNi
alloy. The low-temperature reduction and alloying are facilitated by synergetic effects from the nanostructure of the film, and Ni autocatalytic effects through alloying and hydrogen spillover. The results pave the way for low-temperature formation of Fe-Ni
alloy thin films with tunable compositions directly from
oxides, and broaden the scope of hydrogen direct reduction of multinary
oxides to thin-film platforms.
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All authors Emmanuel Uwayezu, Shaolou Wei, Yujiao Li, Johannes D. Bartl, Dierk Raabe, Alfred Ludwig
Mesoscale and Nanoscale Physics
Observation of two-component exciton condensates in an excitonic insulator
Ruishi Qi, Qize Li, Jiahui Nie et al. (+9 more)
Macroscopic
quantum coherence emerges when
bosons condense into a Bose-Einstein condensate (BEC). First observed as a single-component superfluid in helium, BECs later emerged in ultracold atomic gases at nanokelvin temperatures as weakly interacting
quantum fluids, which can also host multicomponent spinor condensates with rich internal degrees of freedom.
Excitons provide a promising solid-state platform for BECs that can combine strong interactions, electrical tunability, high transition temperatures, and multicomponent order. Yet, conclusive evidence for condensation has remained elusive. Here, we report evidence of two-component
exciton BECs in MoSe2/hBN/WSe2 electron-hole
bilayers by directly probing the
spin susceptibility of constituent electrons and holes. This
heterostructure hosts
equilibrium exciton fluids with four
spin-valley
flavors. Using magneto-optical spectroscopy in a dilution refrigerator, we reveal three
exciton condensate phases with distinct
flavor polarizations. At zero
magnetic field, the many-body ground state is a coherent superposition of two simultaneously condensed intravalley
exciton flavors. Under a
magnetic field, the intravalley
exciton condensate first switches to a two-component intervalley
exciton condensate via a first-order
quantum phase transition at a weak critical field, and then turns into a fully-polarized single-component condensate at high fields. The two-component condensates persist up to ~1.8 K. Our results establish van der Waals electron-hole
bilayers as a versatile platform for exploring strongly interacting, multicomponent
exciton BECs.
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All authors Ruishi Qi, Qize Li, Jiahui Nie, Ruichen Xia, Haleem Kim, Hyungbin Lim, Jingxu Xie, Takashi Taniguchi, Kenji Watanabe, Michael F. Crommie, Allan H. MacDonald, Feng Wang
Statistical Mechanics
Exact and limit results for the CTRW in presence of drift and position dependent noise intensity
Marco Bianucci, Mauro Bologna and Riccardo Mannella
Continuous-time random walks (CTRWs) with drift and position-dependent jumps provide a general framework for describing a wide range of natural and engineered systems. We analyze the
stochastic differential equation associated with this class of models, in which the driving noise consists of spike (shot) events, and we derive two exact analytical results. First, we obtain a closed-form expression for the $n$-time correlation functions of The noise, expressed as a sum over all $2^{n-1}$ ordered partitions of the observation times (Proposition 2). Second, using the $G$-cumulant formalism, we derive an exact non-local master equation (ME) for the probability density function of the CTRW variable, valid without invoking diffusive limits, fractional scaling assumptions, or closure hypotheses (Proposition 3). In interaction representation, this ME retains the same structural form as that of the standard CTRW without drift or position-dependent jumps. Our main result is the emergence of a universal local master equation: at long times, the exact non-local ME is universally and accurately approximated by a time-local ME whose only coefficient is the instantaneous renewal rate $R(t)$. From this equation, exact in the well known Poissonian case, both local and global properties of the PDF can be readily inferred. For example, the temporal behavior of the PDF is directly controlled by that of the rate function $R(t)$: if the waiting-time distribution decays as a power law with exponent $\mu>2$, then $R(t)\to const$ and the system converges to the Poissonian
equilibrium. By contrast, for $\mu<2$, the rate decays in time and the effective
diffusion induced by the noise slowly weakens, without leading to a stationary state. Numerical experiments confirm its remarkable accuracy even far beyond regimes where a naive time-scale separation would justify it.
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Materials Science
Microstructural characteristics, atomic-scale features, and growth mechanisms of deuterides (hydrides) in hafnium
Di Wang, Catriona M McGilvery, James O Douglas et al. (+1 more)
Hafnium hydride is a promising material for next-generation
nuclear reactors, particularly as control rods for fast fission and shielding in fusion systems. The material's intrinsic brittleness encourages its use in the form of hydride-metal composites, where the functional and mechanical performance is strongly influenced by the multiscale structure of hydride-
matrix interfaces. In this study, we employ a suite of microscopy techniques, including scanning electron microscopy with electron backscatter diffraction, transmission electron microscopy with electron energy-loss spectroscopy, and atom probe
tomography, to investigate the deuteride-
matrix interfaces in a deuterium-charged Hf
alloy. We characterise their structure and chemistry, extracting key information including the deuteride-
matrix crystallographic orientation relationship, microstructural features, misfit-induced dislocation distributions, electron energy-loss characteristics, and the segregation of oxygen during deuteride growth. These findings help clarify the mechanisms of interface
evolution and may contribute to improved understanding of hydride-metal systems, with potential relevance for their processing, performance, and design in
nuclear applications.
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All authors Di Wang, Catriona M McGilvery, James O Douglas, Siyang Wang
Materials Science
Epitaxial growth of topological insulator $\beta$-Ag2Te thin films
Ayuki Takegawa, Kouya Imoto, Minoru Kawamura et al. (+2 more)
We report epitaxial growth of $\beta$-Ag2Te thin films by molecular beam epitaxy. $\beta$-Ag2Te, recently identified as a topological
insulator, was grown by depositing Ag on InP substrate at room temperature followed by Te supply at elevated temperature. X-ray diffraction measurements and transmission electron microscopy analyses confirmed the (002)
crystal orientation and the epitaxial atomic arrangement of $\beta$-Ag2Te thin films. Electrical transport measurements revealed that the $\beta$-Ag2Te thin film exhibits two-dimensional metallic conduction while the bulk remains insulating. The epitaxial $\beta$-Ag2Te thin films obtained here provide a viable platform for investigating emergent phenomena arising from surface Dirac states and for designing heterojunction-based device structures.
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All authors Ayuki Takegawa, Kouya Imoto, Minoru Kawamura, Moeta Tsukamoto, Ryutaro Yoshimi
Disordered Systems and Neural Networks
Controlled Langevin Dynamics for Sampling of Feedforward Neural Networks Trained with Minibatches
Alessandro Zambon, Francesca Caruso, Riccardo Zecchina et al. (+1 more)
Sampling the parameter space of artificial neural networks according to a Boltzmann distribution provides insight into the geometry of low-loss solutions and offers an alternative to conventional loss minimization for training. However, exact sampling methods such as hybrid Monte Carlo (hMC), while formally correct, become computationally prohibitive for realistic
datasets because they require repeated evaluation of full-batch gradients. We introduce a pseudo-Langevin (pL) dynamics that enables efficient Boltzmann sampling of feed-forward neural networks trained with large
datasets by using minibatches in a controlled manner. The method exploits the statistical properties of minibatch gradient noise and adjusts fictitious masses and friction coefficients to ensure that the induced
stochastic process samples efficiently the desired
equilibrium distribution. We validate numerically the approach by comparing its
equilibrium statistics with those obtained from exact hMC sampling. Performance
benchmarks demonstrate that, while hMC rapidly becomes inefficient as network size increases, the pL scheme maintains high computational
diffusion and scales favorably to networks with over one million parameters. Finally, we show that sampling at intermediate temperatures yields optimal generalization performance, comparable to SGD, without requiring a validation set or early stopping procedure. These results establish controlled minibatch Langevin dynamics as a practical and scalable tool for exploring and exploiting the solution space of large neural networks.
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All authors Alessandro Zambon, Francesca Caruso, Riccardo Zecchina, Guido Tiana
Materials Science
Polar Charge-Ordered States in BiFeO$_3$/CaFeO$_3$ Superlattice
Rajan Gowsalya, Monirul Shaikh, Sathiyamoorthy Buvaneswaran et al. (+1 more)
Oxide superlattices represent a potent avenue for tailoring emergent electronic phases through sophisticated interfacial charge transfer and dynamic
lattice distortions. This study systematically investigates the structural and electronic attributes of the BiFeO$_3$/CaFeO$_3$ superlattice, leveraging a comprehensive approach that integrates first-principles computations with detailed
symmetry-mode analysis. The strategic integration of polar bismuth ferrite alongside charge-transfer calcium ferrite instigates profound
lattice instabilities, notably manifest in octahedral rotations and cooperative FeO$_6$ breathing modes that might not necessarily be soft. However, their synergistic coupling stabilizes a non-centrosymmetric $Pc$ ground state that intrinsically features polar charge ordering of Fe ions. This resultant phase ingeniously unifies C-type antiferromagnetism with robust ferroelectric
semiconductor characteristics, exhibiting a calculated indirect band gap of about 0.6 eV. Our discoveries firmly establish ferrite superlattices as an exceptionally versatile and tunable platform for the rational design of next-generation multifunctional materials, offering precise control over polarization, charge ordering phenomena, and electronic transport behavior via advanced interface and strain engineering techniques.
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All authors Rajan Gowsalya, Monirul Shaikh, Sathiyamoorthy Buvaneswaran, Saurabh Ghosh
Strongly Correlated Electrons
Motivic GUT Part I: Grand Unified Theory of Topological Order
Masahiko G. Yamada
In the series of papers Motivic GUT Part I: Grand Unified Theory of Topological Order, Motivic GUT Part II: Grand Unified Theory of
Symmetry-Protected Topological Order, and Motivic GUT Part III: Grand Unified Theory of
Symmetry-Enriched Topological Order, we propose a unified framework for gapped topological phases based on the Grothendieck-Kitaev-Lurie motivic yoga. In the spirit of Grothendieck's rising sea, we argue that the classification problem can only be properly addressed after identifying the correct higher-categorical ambient space in which its full richness appears. In this first part, we propose a unified definition of gapped topological order in spatial dimension $d$ in terms of
unitary fusion $(\infty,d)$-categorical data, considered up to Morita equivalence. For $d=2$, this framework recovers
unitary modular tensor categories. For $d>2$, it naturally leads to genuinely higher-categorical structures. This suggests a Copernican turn in the theory of topological phases: many existing classification schemes should be reinterpreted as lower-categorical shadow realizations of intrinsically $\infty$-categorical objects.
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Mesoscale and Nanoscale Physics
Low-frequency noise as a probe of microscopic disorder in CVD-grown graphene
Jagadis Prasad Nayak, Smrutirekha Sahoo, Shreya Barman et al. (+1 more)
We report a detailed investigation of low-frequency resistance fluctuations (1/f noise) in chemical vapor deposition (CVD) grown
graphene. Systematic measurements reveal that the magnitude of 1/f noise in CVD-grown
graphene is significantly higher by several orders of magnitude than that typically observed in exfoliated single-
crystal graphene. This enhancement is attributed to structural imperfections such as grain boundaries and defect states within the polycrystalline film. Detailed analysis of the temperature dependence of the noise demonstrates that the resistance fluctuations arise from thermally activated dynamics of localized defects. These results provide key insights into the microscopic mechanism of noise in scalable
graphene films and highlight the role of defect engineering in optimizing
graphene for large-scale electronic applications. Our findings establish low-frequency noise as a sensitive probe of microscopic disorder in CVD
graphene, providing a practical pathway for assessing material quality in scalable electronic technologies.
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All authors Jagadis Prasad Nayak, Smrutirekha Sahoo, Shreya Barman, Gopi Nath Daptary
Materials Science
Will it form a glass? Tackling glass formation using binary classification
Diogo P. L. Carvalho, Ana C. B. Loponi and Daniel R. Cassar
Glass formation is one of the most important and fundamental open problems in glass science. Predicting whether a
liquid can be easily frozen into a glass appears simple but is far from it. In this communication, we address glass formation in inorganic nonmetallic
liquids using binary classification to predict the probability that a given
liquid will form a glass under typical laboratory conditions. Using a
dataset of more than 50,000 examples, we trained random forest classifiers that achieved ROC-AUC values around 0.89 and PR-AUC close to 0.95 on the holdout
dataset (i.e., unseen data). A rigorous model selection routine was employed, including hyperparameter tuning with cross-validation, and four different data treatment routes were evaluated. Using SHAP values, we extracted valuable insights from the trained models that both agree with established knowledge and extend it. For example, we identified that the bandgap energy of the constituent chemical elements is positively correlated with glass formation. When glass stability parameters and Jezica were added to the
dataset, no performance improvement was observed, but model complexity decreased significantly. This result is particularly relevant for composition screening, especially in inverse design problems.
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Superconductivity
First-principles prediction of high-temperature superconductivity in stretched carbon nanotubes
Hua-Zhen Li and Xun-Wang Yan
Superconductivity in quasi-one-dimensional systems is an significant but undervalued research field. In this work, based on the electron-
phonon coupling mechanism, we systematically investigate the superconductivity in quasi-one-dimensional carbon nanotube under uniaxial tensile strain. The calculated superconducting critical temperature attains its peak value of 162 K at a uniaxial tensile strain of 4.5%, being drastically higher than the counterpart in the unstrained carbon nanotube. An overall softening of
phonons, strong electron-
phonon coupling, and an increase of electronic density of states at the
Fermi level, play key roles in achieving high-temperature superconductivity in this system. Our research demonstrates that stretching is an effective approach to modulating the superconductivity one-dimensional materials, and more importantly, indicates that high-temperature superconductivity may occur in carbon nanotubes.
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Disordered Systems and Neural Networks
Extreme-Value Criticality and Gain Decomposition at the Integer Quantum Hall Transition
Wei-Han Li and Abbas Ali Saberi
Extreme-value fluctuations at
quantum critical points remain poorly understood in the presence of strong correlations and openness. At the integer
quantum Hall transition in the open Chalker–Coddington network, we show that the maximal wave-function amplitude separates into a global gain and an intrinsic extreme component, $|\psi|_{\max}=A\,|\tilde{\psi}|_{\max}$. We introduce extreme-moment scaling for $|\psi|_{\max}$ and observe an approximately
parabolic exponent function $\tau_{\max}(q)$ over moderate $q$, while $\ln|\psi|_{\max}$ displays an almost Gaussian bulk over the studied sizes. The gain factor is close to log-normal and largely controls the raw extremes. Gain normalization reorganizes the statistics: $\tilde{\tau}_{\max}(q)$ changes qualitatively and $|\tilde{\psi}|_{\max}$ does not support a single-parameter generalized extreme-value collapse under standard centering/scaling in the accessible size window. Extreme observables thus provide a robust probe of correlated criticality in open
quantum systems.
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Mesoscale and Nanoscale Physics
Anomalous and Topological Hall Effects in Antiferromagnetic EuSn2As2 Nanostructures
Evgeny I. Maltsev, Nicolas Pérez, Romain Giraud et al. (+8 more)
We investigate magnetotransport in exfoliated nanostructures of the candidate
magnetic 3D topological
insulator $\mathrm{EuSn_{2}As_{2}}$. Similar to macroscopic single
crystals, the negative magnetoresistance observed below the Néel temperature ($T_N$ = 24 K) is related to the canted
antiferromagnetic state (CAF) of an easy-plane antiferromagnet (AFM), with an increase of the saturation field when tilting the applied
magnetic field away from the (ab) plane ($\mu_{0} H^{c}_{s}$ = 4.9 T, $\mu_{0} H^{ab}_{s}$ = 3.6 T). Higher-accuracy measurements in nanostructures up to 14 T further evidence a non-linear normal
Hall response due to several electronic bands. Interestingly, the transverse resistance due to magnetism reveals an anomalous
Hall effect in the CAF state, but also a topological
Hall effect due to
chiral spin textures, as found in AFM or helical magnets. The presence of real-space
chiral spin texture, already reported in another
magnetic topological
insulator, $\mathrm{MnBi_{2}Te_{4}}$, could be a characteristic generally appearing in
magnetic 3D topological
insulators.
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All authors Evgeny I. Maltsev, Nicolas Pérez, Romain Giraud, Kranthi Kumar Bestha, Anja U. B. Wolter, Joseph Dufouleur, Kirill S. Pervakov, Vladimir M. Pudalov, Kornelius Nielsch, Bernd Büchner, Louis Veyrat
Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
Thermodynamics of a biophotomimetic nonreciprocal quantum battery
Trishna Kalita, Manash Jyoti Sarmah and Himangshu Prabal Goswami
We propose a theoretical model of a fully functional nonreciprocal
quantum battery inspired by the architecture of bacterial light-harvesting complexes. We assign functional roles to collective
quantum optical subradiant and superradiant states and introduce a unimodal cavity to assist storage. The transition rates are obtained from an effective non-Hermitian
Hamiltonian, tailored to the battery geometry which are fed into a master equation to unravel the time
evolution. We investigate the complete thermodynamic performance including storage, leakage, ergotropy, work extraction, flux, and power. We observe optimization at different ring sizes, each peaking at its specific energetic function. Strong coupling between the ring and central system enhances the battery's ability to store energy but reduces the ability of power output. The ergotropy exceeds capacity and approaches it linearly with increasing system size, with an optimal small-size regime that disappears under strong coupling.
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Superconductivity
Quench Protection in Insulated REBCO Conductors: Design Optimization and Fast Detection via REBCO SQD
Hajar Zgour, Walid Abdel Maksoud, Bertrand Baudouy et al. (+1 more)
This work was conducted within the framework of the exploratory French project PEPR SupraFusion, which aims to advance the field of fusion energy by developing High-Temperature
Superconductor (HTS)-based demonstrators capable of storing significant energy while operating under high
magnetic fields and currents. Ensuring a reliable protection during a quench in Insulated REBCO conductors is challenging\,: slow normal-zone propagation and validation delays allow the hotspot's temperature to reach damaging levels. We compare (i) conductor protection via copper-stabilizer optimization and (ii) a co-wound, REBCO superconducting quench detector (SQD) that is electrically isolated yet thermally coupled and intentionally deoxygenated to lower Tc and Ic for an earlier transition. Onedimensional THEA modeling shows that a good choice of stabilizer cross-section makes the protection possible during quench events by keeping the temperature of the hotspot within a safe limit. The simulations also demonstrate that the use of a REBCO SQD enables the quench detection at lower temperatures.
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All authors Hajar Zgour, Walid Abdel Maksoud, Bertrand Baudouy, Antoine Guinet
Mesoscale and Nanoscale Physics
Spin-valley physics in anomalous thermoelectric responses of the spin-orbit coupled $\alpha$-$T_3$ system with broken time-reversal symmetry
Lakpa Tamang and Tutul Biswas
We extract
spin-valley physics in the anomalous
Hall and Nernst responses of the
spin-orbit coupled $\alpha$-$T_3$ system in the presence of a time-reversal
symmetry breaking staggered magnetization. We show that the interplay between the SOI, magnetization, and a model parameter $\alpha$ for the $\alpha$-$T_3$
lattice enables efficient tuning of
spin- and valley-dependent
Hall and Nernst signals. The
spin-valley physics of the
Hall and Nernst responses in the absence and presence of the magnetization are well explained. The peak-dip features of the Nernst responses are also understood from the corresponding
Hall responses through the Mott relation. We find that the magnetization introduces highly tunable
spin and valley polarizations, which are calculated from the
spin- and valley-resolved Nernst conductivities. It is shown that both the
spin and valley polarizations can attain nearly complete polarization over extended regions of the parameter space.
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Statistical Mechanics
A Formal Physical Framework for the Origin of Life: Dissipation-Driven Selection of Evolving Replicators
Shlomo Segal
The emergence of life from inanimate matter presents a thermodynamic challenge: the Second Law of Thermodynamics dictates a global trend towards disorder, yet life constitutes localized pockets of profound organization. This paper presents a formal physical framework for abiogenesis grounded in the statistical physics of non-
equilibrium systems. We transition from the established connection between dissipation and process probability (e.g., Crooks Fluctuation
Theorem) to a large-deviation framework for the likelihood of system histories. This formalism reveals a probabilistic bias towards histories with greater integrated dissipation. We then demonstrate how this bias leads to the selection of heredity. The core of our argument is a rigorous mathematical proposition showing that while simple autocatalysis leads to an exponential increase in dissipation, template-directed replication, via its capacity for mutation and adaptation (a process from which we derive an effective adaptation rate, alpha), unlocks a super-exponential growth pathway. This translates to a doubly-exponential amplification in the relative probability of its emergence over time, constituting an asymptotically dominant physical bias for its selection. This framework delineates a hierarchical transition from simple dissipative structures to information-bearing replicators, whose stability is contingent upon exceeding critical thresholds of fidelity, kinetic efficiency, and resource supply. We conclude by proposing a refined, quantitative, and falsifiable experiment, defining a precise mathematical signature for identifying the onset of evolutionary processes in synthetic chemical systems.
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Strongly Correlated Electrons
Nanoscale electronic variations in altermagnetic $\alpha$-MnTe
Zeyu Ma, Yidi Wang, Gal Tuvia et al. (+3 more)
Altermagnets exhibit
spin-split electronic bands like ferromagnets, yet they are magnetically compensated like collinear antiferromagnets. Altermagnets thus combine the benefits of ferromagnets and antiferromagnets, opening routes to tailored materials and applications. However, reported bulk signatures such as the anomalous
Hall response in candidate altermagnets have been inconsistent across samples, suggesting that inhomogeneity may affect their functionality in electronic devices. Here, we use low-temperature scanning tunneling microscopy and spectroscopy to map the local electronic landscape of $\alpha$-MnTe on atomically flat cleaved single
crystals. We resolve two distinct electronic regions. In Region A, the chemical potential lies near the valence-band edge and varies by $\sim$100 meV on the nanometer length scale. In Region B, the chemical potential lies near the middle of a wider band gap. We further identify an incommensurate charge modulation with periodicity (2.5$\pm$0.1)$a$, observed exclusively in Region A. Our work establishes that $\alpha$-MnTe can exhibit significant electronic non-uniformity, suggesting that nanoscale characterization is essential for its reliable use in electronic applications.
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All authors Zeyu Ma, Yidi Wang, Gal Tuvia, Kevin Hauser, Jiaqiang Yan, Jennifer E. Hoffman