Superconductivity · Cross-listed from hep-th
Chi-Hsien Tai and Wen-Yu Wen
We investigate the emergence of a time-crystalline phase in a single-band
holographic superconductor, extending the AdS/CFT framework. By incorporating a nonlinear gauge-scalar coupling and external driving, we derive coupled equations of motion for the
plasma and
Higgs modes, analogous to those in high-Tc
superconductors. Multi-scale analysis reveals a sum resonance with subharmonic growth indicating broken time-translation
symmetry. We perform numerical computation of quasinormal mode and demonstrate the transition to the time-crystalline phase. The
holographic model may serve as a robust tool for studying strongly coupled time
crystals.
Read the full abstract ▾
Strongly Correlated Electrons
Giant hysteretic magnetoresistance accompanying the Mott transition and spin-glass state in organic metal
P.D. Grigoriev, S.I. Pesotskii, R.B. Lyubovskii et al. (+3 more)
The
giant magnetoresistance with a huge hysteresis is observed in the organic metal k-(BEDTTTF)2Hg(SCN)2Br at low temperature in a pressure interval around 3 kbar of a width ~1 kbar. The hysteretic magnetoresistance is isotropic with respect to the direction of
magnetic field, which excludes the orbital effect of
magnetic field as its origin. The observed temperature and
magnetic-field dependence of this hysteresis and of its relaxation time indicates the strong influence of
spin-glass state on magnetoresistance. Although a quantitative theory of this effect, originating from strong electronic correlations, requires complex numerical calculations, we suggest its explanation and a simple model which qualitatively describes the observed magnetoresistance behavior and shows a strong charge-
spin entanglement. The proposed effect suggests a new class of extreme magnetoresistance mechanisms.
Read the full abstract ▾
All authors P.D. Grigoriev, S.I. Pesotskii, R.B. Lyubovskii, S.A. Torunova, D.S. Lyubshin, V.N. Zverev
Mesoscale and Nanoscale Physics
Probing ground-state degeneracies of a strongly interacting Fermi-Hubbard model with superconducting correlations
Sebastiaan L. D. ten Haaf, Sebastian Miles, Qingzhen Wang et al. (+6 more)
The
Fermi-Hubbard model and its rich phase diagram naturally emerges as a description for a wide range of electronic systems. Recent advances in
semiconductor-
superconductor hybrid
quantum dot arrays have allowed to realize degenerate
quantum systems in a controllable way, e.g., allowing to observe robust zero-bias peaks in Kitaev chains, indicative for Majorana bound states. In this work, we connect these two domains. Noting the strong on-site Coulomb repulsion within
quantum dots, we study small arrays of spinful hybrid
quantum dots implemented in a two-dimensional electron gas. This system constitutes a
Fermi-Hubbard model with inter-site superconducting correlations. For two electronic sites, we find robust zero-bias peaks indicative of a strongly degenerate spectrum hosting emergent Majorana Kramers pairs or $\mathbb{Z}_3$-parafermions. Extending to three sites, we find that these spinful systems scale very differently compared to spinless Kitaev chains. When the sweet-spot conditions are satisfied pairwise, we find that the ground state degeneracy of the full three-site system is lifted. This degeneracy can be restored by tuning the superconducting phase difference between the hybrid segments. However, these states are not robust to
quantum dot detuning. Our observations are a first step towards studying degeneracies in strongly interacting
Fermi-Hubbard systems with superconducting correlations.
Read the full abstract ▾
All authors Sebastiaan L. D. ten Haaf, Sebastian Miles, Qingzhen Wang, A. Mert Bozkurt, Ivan Kulesh, Yining Zhang, Christian G. Prosko, Michael Wimmer, Srijit Goswami
Statistical Mechanics
Zipfian universality of interaction laws: A statistical-mechanics framework for inverse power scaling
Jerome Baray
Inverse power-law interaction forms, such as the inverse-square law, recur across a wide range of physical, social, and spatial systems. While traditionally derived from specific microscopic mechanisms, the ubiquity of these laws suggests a more general organizing principle. This article proposes a statistical-mechanics framework in which such interaction laws emerge as macroscopic fixed points of aggregation processes involving strongly heterogeneous microscopic contributions. We consider systems where individual interaction sources exhibit heavy-tailed heterogeneity consistent with Zipf-Pareto statistics and where aggregation proceeds without intrinsic length scales. Under minimal assumptions of heterogeneity, multiplicativity, scale invariance, and stability under coarse-graining, we show that the resulting macroscopic interaction field must adopt a scale-free, power-law form. The associated exponent is not imposed a priori but emerges from effective dimensionality,
symmetry, and aggregation structure. Within this framework, the inverse-square law is interpreted as a stable statistical fixed point corresponding to isotropic aggregation in an effective three-dimensional space, while deviations from this regime naturally arise from anisotropy, constrained geometries, or nontrivial effective dimensions. This perspective provides a unified interpretation of interaction laws observed in physics, spatial economics, and human geography, without invoking domain-specific microscopic mechanisms. The proposed framework reframes inverse power-law interactions as robust emergent features of Zipfian aggregation rather than as unique consequences of particular physical forces, thereby offering a common statistical explanation for their cross-disciplinary recurrence.
Read the full abstract ▾
Soft Condensed Matter
Self-assembled filament layers in drying sessile droplets: from morphology to electrical conductivity
Johannes Schöttner, Qingguang Xie, Gaurav Nath et al. (+1 more)
Controlling the deposition of filaments, such as nanowires and nanotubes, from evaporating droplets is critical for the performance of emerging technologies like flexible sensors and printed electronics. The final deposit morphology strongly governs functional properties, such as electrical conductivity, yet remains challenging to control. In this work, we numerically investigate how filament length, stiffness, and concentration affect deposition patterns during the drying process. We compare reaction-limited and
diffusion-limited evaporation regimes, demonstrating that their distinct velocity fields and flow magnitudes fundamentally alter filament arrangement. While
diffusion-limited evaporation drives the “coffee-ring effect", compromising network uniformity, reaction-limited evaporation suppresses edge accumulation, promoting centered conductive deposits. We map out the spatial variation of filament
alignment - tangential at the contact line, radial in the intermediate region, and random near the center. Longer filaments tend to favour more tangential
alignment overall and suppress edge accumulation. We find that by tuning the evaporation regime, filament deposition can lead to significantly lower percolation thresholds and significantly higher conductivity exponents. These results quantify the link between evaporation kinetics and microstructure, providing guidelines for optimizing conductive network formation in printed electronics.
Read the full abstract ▾
All authors Johannes Schöttner, Qingguang Xie, Gaurav Nath, Jens Harting
Soft Condensed Matter
Probing molecular-motor forces driving Chlamydomonas gliding motility by holographic microscopy
Nicolas Fares, Elorri Garcia, Ahmad Badr et al. (+5 more)
The unicellular microalga Chlamydomonas reinhardtii is a widely used model microswimmer for biophysicists. However, the interest around C. reinhardtii goes beyond its swimming capabilities. In fact, light can drastically alter its behavior: under blue illumination, the
cell attaches to a nearby surface and intermittently glides on it. Such a gliding motility is powered by molecular-motor
proteins operating in the
cell's cilia, and the related machinery has established the
cell as a
prime reference for the study of intraciliary-transport mechanisms. In the present work, we track label-free
cells using in-line
holographic microscopy, which allows us to characterize their gliding motility without requiring fluorescent labeling. After benchmarking the experimental technique on swimming
cells, we show that, while gliding, the
cells move mostly along the surface, and exhibit anomalous-diffusive features, including Lorentzian-like distributions of displacements. Furthermore, gliding trajectories, by being intermittent, are relevant candidates to determine forces at the molecular-motor scale. We report a gliding threshold of about 20~pN, which is compatible with the activity of single molecular motors, and on the same order of magnitude as the forces generated during intraciliary cargo transport.
Read the full abstract ▾
All authors Nicolas Fares, Elorri Garcia, Ahmad Badr, Yacine Amarouchene, Alexandros A Fragkopoulos, Oliver Bäumchen, Thomas Salez, Antoine Allard
Statistical Mechanics
Scaling laws for stationary Navier-Stokes-Fourier flows and the unreasonable effectiveness of hydrodynamics at the molecular level
P.I. Hurtado, J.J. del Pozo and P.L. Garrido
Hydrodynamics provides a universal description of the emergent collective dynamics of vastly different many-body systems, based solely on their
symmetries and conservation laws. Here we harness this universality, encoded in the Navier-Stokes-
Fourier (NSF) equations, to find general scaling laws for the stationary uniaxial solutions of the compressible NSF problem far from
equilibrium. We show for general transport coefficients that the steady density and temperature fields are functions of the pressure and a kinetic field that quantifies the quadratic excess velocity relative to the ratio of heat flux and shear stress. This kinetic field obeys in turn a spatial scaling law controlled by pressure and stress, which is inherited by the stationary density and temperature fields. We develop a scaling approach to measure the associated master curves, and confirm our predictions through compelling data collapses in large-scale molecular dynamics simulations of paradigmatic model fluids. Interestingly, the robustness of the scaling laws in the face of significant finite-size effects reveals the surprising accuracy of NSF equations in describing molecular-scale stationary flows. Overall, these scaling laws provide a novel characterization of stationary states in driven fluids.
Read the full abstract ▾
Materials Science
Computational tuning of the elastic properties of low- and high-entropy ultra-high temperature ceramics
Samuel J. Magorrian, Ljiljana Stojanović, Lara Kabalan et al. (+4 more)
Ultra-high temperature ceramics (UHTCs) represent a class of crystalline materials for extreme environments. They can withstand extremely high temperatures but are mechanically difficult to work with due to their inherent brittleness. Mixture compounds, in particular high-
entropy mixtures, offer a pathway to tune the physical properties of UHTCs such as their elastic constants. Here we fine-tune the MACE-MPA-0 universal machine-learning potential on rocksalt carbide UHTCs containing group IV-V metals and demonstrate that not only do the elastic constants deviate from the rule of mixtures approximation in the high-
entropy limit, but also in the low-
entropy limit of binary and ternary mixtures. We find that this is caused by distortion imposed by the
lattice mismatch, enabling the tuning of the physical properties of UHTC mixtures in both low- and high-
entropy compounds. We identify a three-component mixture compound, HfCVCZrC, as the best balance between synthesizability and toughness, and apply our developed MACE-UHTC model to identify a range of non-equimolar candidate compositions of this compound which may enable the synthesis of a mixture UHTC with a Young's modulus up to 40 GPa below that of ZrC.
Read the full abstract ▾
All authors Samuel J. Magorrian, Ljiljana Stojanović, Lara Kabalan, Ardita Shkurti, Richard N. White, Fabian L. Thiemann, Viktor Zólyomi
Mesoscale and Nanoscale Physics
I. G. van Rens, O. O. Zheliuk, M. W. de Dreu et al. (+7 more)
We have measured the
quantum Hall effect in monolayer
graphene samples that were exposed to a cold hydrogen
plasma leading to a hydrogenation level of a few percent. Compared to pristine
graphene, the Landau level distance significantly decreases in the hydrogenated structures, and its field dependence changes from square root type to linear. From this observation we conclude that the band structure in hydrogenated
graphene changes from a linear Dirac-Weyl type dispersion to a quadratic one with an effective electron mass $m_e^* = 0.24~m_e$. This is in good agreement with ab-initio band structure calculations of hydrogen decorated
graphene monolayer.
Read the full abstract ▾
All authors I. G. van Rens, O. O. Zheliuk, M. W. de Dreu, K. Mukhuti, Y. Kreminska, C. S. A. Müller, P. C. M. Christianen, J. T. Ye, N. de Groot, U. Zeitler
Materials Science · Cross-listed from cs.LG
PolySet: Restoring the Statistical Ensemble Nature of Polymers for Machine Learning
Khalid Ferji
Machine-learning (ML) models in
polymer science typically treat a
polymer as a single, perfectly defined molecular graph, even though real materials consist of
stochastic ensembles of chains with distributed lengths. This mismatch between physical reality and digital representation limits the ability of current models to capture
polymer behaviour. Here we introduce PolySet, a framework that represents a
polymer as a finite, weighted ensemble of chains sampled from an assumed molar-mass distribution. This ensemble-based encoding is independent of chemical detail, compatible with any molecular representation and illustrated here in the homopolymer case using a minimal
language model. We show that PolySet retains higher-order distributional moments (such as Mz, Mz+1), enabling ML models to learn tail-sensitive properties with greatly improved stability and accuracy. By explicitly acknowledging the statistical nature of
polymer matter, PolySet establishes a physically grounded foundation for future
polymer machine learning, naturally extensible to copolymers, block architectures, and other complex
topologies.
Read the full abstract ▾
Statistical Mechanics · Cross-listed from quant-ph
Quantum critical dynamics and emergent universality in decoherent digital quantum processors
Brendan Rhyno, Swarnadeep Majumder, Smitha Vishveshwara et al. (+1 more)
Understanding how noise influences nonequilibrium
quantum critical dynamics is essential for both fundamental physics and the development of practical
quantum technologies. While the
quantum Kibble-Zurek (QKZ) mechanism predicts universal scaling during quenches across a critical point, real
quantum systems exhibit complex decoherence that can substantially modify these behaviors, ranging from altering critical scaling to completely suppressing it. By considering a specific case of nondemolishing noise, we first show how decoherence can reshape universal scaling and verify these theoretical predictions using numerical simulations of
spin chains across a wide range of noise strengths. Then, we study linear quenches in the transverse-field Ising model on IBM superconducting processors where the noise model is unknown. Using large system sizes of 80-120
qubits, we measure equal-time connected correlations, defect densities, and excess energies across various quench times. Surprisingly, unlike earlier observations where noise-induced defect production masked universal behavior at long times, we observe clear scaling relations, pointing towards persistent universal structure shaped by decoherence. The extracted scaling exponents differ from both ideal QKZ predictions and analytic results for simplified noise models, suggesting the emergence of a distinct noise-influenced universality regime. Our results, therefore, point toward the possibility of using universal dynamical scaling as a high-level descriptor of
quantum hardware, complementary to conventional gate-level performance metrics.
Read the full abstract ▾
All authors Brendan Rhyno, Swarnadeep Majumder, Smitha Vishveshwara, Khadijeh Najafi
Materials Science · Cross-listed from quant-ph
Intense-Laser Nondipole-Induced Symmetry Breaking in Solids
Asger Weeth and Lars Bojer Madsen
High-harmonic spectroscopy in solids gives insight into the inner workings of solids, such as reconstructing band structures or probing the topological phase of materials. High-harmonic generation (HHG) is a highly non-linear phenomena and simulations guide interpretation of experimental results. These simulations often rely on the electric dipole approximation, even though the driving fields enter regimes that challenge its accuracy. Here, we investigate effects of including nondipole terms in the light-matter coupling in simulations of HHG in materials with both topologically trivial and non-trivial phases. We show how the inclusion of nondipole terms breaks dipole selection rules, allowing for new polarizations of the generated light. Specifically we find that helicity, completely absent in the dipole approximation, is induced by the nondipole extension, and that this helicity is dependent on the topological phase of the material.
Read the full abstract ▾
Materials Science
Hydrothermal synthesis of SnO2 particles for the degradation of Methylene Blue (MB) dye in presence of sunlight
Komal Singh, Jyoti Sindkar, Mrunal Ramdasi et al. (+2 more)
Three distinct samples were proceed through synthesis utilizing the hydrothermal method to develop tin dioxide (SnO2) nanoparticles. Consistency in all other parameters was ensured by maintaining a constant temperature and time throughout the synthesis. X-ray diffraction (XRD) and scanning electron microscopy (SEM) were used to examine how the surfactant affected the structural, morphological, and crystallographic characteristics. A tetragonal rutile SnO2 phase was confirmed to have formed by XRD investigation, with high crystallinity indicated by strong diffraction peaks. Higher precursor concentration samples showed aggregation, indicating that the smaller size of the nanoparticles caused them to interact. These findings show that changing the surfactant has a major impact on the crystallinity, size, and shape of SnO2 nanoparticles, which makes this technique establish for certain uses, including energy storage, gas sensors, and photocatalysis. Additionally, we examined the photocatalytic activity of the aforementioned samples, indicating from the UV-vis characterization results that the sample containing PEG as a surfactant performs better than others.
Read the full abstract ▾
All authors Komal Singh, Jyoti Sindkar, Mrunal Ramdasi, Vrishali Jadhav, Rohidas B. Kale
Disordered Systems and Neural Networks · Cross-listed from quant-ph
Neural quantum states for entanglement depth certification from randomized Pauli measurements
Marcin Płodzień
Entanglement depth quantifies how many
qubits share genuine multipartite
entanglement, but certification typically relies on tailored witnesses or full
tomography, both of which scale poorly with system size. We recast
entanglement-depth and non-$k$-separability certification as likelihood-based model selection among neural
quantum states whose architecture enforces a chosen
entanglement constraint. A hierarchy of separable neural
quantum states is trained on finite-shot local Pauli outcomes and compared against an unconstrained reference model trained on the same data. When all constrained models are statistically disfavored, the data certify
entanglement beyond the imposed limit directly from measurement statistics, without reconstructing the density
matrix. We validate the method on simulated six- and ten-
qubit datasets targeting GHZ, Dicke, and Bell-pair states, and demonstrate robustness for mixed states under local noise. Finally, we discuss lightweight interpretability diagnostics derived from trained parameters that expose coarse
entanglement patterns and
qubit groupings directly from bitstring statistics.
Read the full abstract ▾
Soft Condensed Matter
Vertex Model Mechanics Explain the Emergence of Centroidal Voronoi Tiling in Epithelia
Sulaimaan Lim, Julien Vermot and Chiu Fan Lee
Epithelia are confluent
cell layers that self-organize into polygonal networks whose geometry encodes their mechanical state. A principal driver is the tunable contractility of the actomyosin cortex, which links
cell-junction tension to tissue architecture. Notably, epithelial tilings frequently resemble centroidal Voronoi tessellations (CVTs), yet the physical origin of this resemblance has remained unclear. Here, using a minimal vertex model that relates
cell shape to a mechanical energy, we show that CVT-like patterns arise naturally in the solid (rigid) regime of tissues. Analytical theory reveals that isotropic strain minimization drives
cell centroids toward Voronoi configurations, a result we corroborate with a analytical mean-field formulation of the vertex model. We further demonstrate that physiologically relevant perturbations – such as cyclic stretch – shift tissues into distinct, geometrically disordered CVT states, and that these shifts provide quantitative, image-based readouts of mechanical state. Together, our results identify a mechanical origin for CVT-like organization in epithelia and establish a
geometric framework that infers tissue stresses directly from morphology, offering broadly applicable metrics for assessing
rigidity and remodeling in living tissues.
Read the full abstract ▾
Materials Science
Quantum-inspired Chemical Rule for Discovering Topological Materials
Xinyu Xu, Rajibul Islam, Ghulam Hussain et al. (+5 more)
Topological materials exhibit unique electronic structures that underpin both fundamental
quantum phenomena and next-generation technologies, yet their discovery remains constrained by the high computational cost of first-principles calculations and the slow, resource-intensive nature of experimental synthesis. Recent machine-learning approaches, such as the heuristic topogivity rule, offer a data-driven pre-screening tool by quantifying each element's intrinsic tendency toward topological behavior. Here, we develop a hybrid
quantum-classical neural network (HQCNN) that extends this rule into a
quantum-inspired formulation. Within this framework, the HQCNN maps compositional descriptors to
quantum probability amplitudes, naturally introducing pairwise inter-element correlations inaccessible to classical heuristics. The physical validity of these correlations is substantiated by constructing an equivalent complex-valued neural network (CVNN), confirming both the consistency and interpretability of the formulation. Retaining the simplicity of chemical
reasoning while
embedding quantum-native features, our
quantum-inspired rule enables efficient and generalizable topological classification. High-throughput screening combined with first-principles (DFT) validation reveals five previously unreported topological compounds, demonstrating the enhanced predictive power and physical insight afforded by
quantum-inspired heuristics.
Read the full abstract ▾
All authors Xinyu Xu, Rajibul Islam, Ghulam Hussain, Yangming Huang, Xiaoguang Li, Pavlo O. Dral, Arif Ullah, Ming Yang
Materials Science
Topological descriptor for interpretable thermal transport prediction in amorphous graphene
Kosuke Yamazaki, Takuma Shiga, Kumpei Shiraishi et al. (+1 more)
Understanding and predicting thermal transport in disordered materials remains a significant challenge due to the absence of periodicity and the complex nature of medium-range structural motifs. In this work, we investigate amorphous
graphene and demonstrate that persistent homology, a topological data analysis technique, can serve as a physically interpretable structural descriptor for predicting thermal conductivity. We first show that ridge regression using persistent homology descriptors achieves high prediction accuracy. To gain physical insight into the prediction process, we perform inverse analysis by mapping the regression coefficients back onto the persistence diagrams. This reveals that distorted hexagonal and triangular motifs are strongly correlated with reduced thermal conductivity. A further comparison with the spatial distribution of localized vibrational modes supports the physical interpretation that these motifs suppress thermal transport. Our findings highlight that persistent homology not only enables accurate prediction of physical properties but also uncovers meaningful structure-property relationships in two-dimensional amorphous materials. This approach offers a promising framework for interpretable machine-learning models in materials science.
Read the full abstract ▾
All authors Kosuke Yamazaki, Takuma Shiga, Kumpei Shiraishi, Emi Minamitani
Other Condensed Matter · Cross-listed from quant-ph
Emergence of long-range entanglement and odd-even effect in periodic generalized quantum cluster models
Zhen-Yu Zheng and Shu Chen
We investigate the
entanglement properties in a generalized
quantum cluster model under periodic boundary condition. By evaluating the
quantum conditional mutual information
entropy under four subsystem partitions, we identify clear signatures of long-range
entanglement. Specifically, when both the system size $N$ and the interaction range $m$ are odd, the system exhibits nonzero four-part
quantum conditional mutual information
entropies in infinitesimal but finite field. This nonvanishing four-part
quantum conditional mutual information
entropy directly signals the presence of long-range
entanglement. In contrast, all other combination of $N$ and $m$ yield vanishing four-part
quantum conditional mutual information
entropy. Remarkably, in the case of $N, m \in \text{odd}$, these long-range entangled features persist even in the presence of a large transverse field, demonstrating their robustness against
quantum fluctuations. These results demonstrate how the interplay between system size and interaction range governs the emergence of long-range
entanglement in one-dimensional generalized
quantum cluster model.
Read the full abstract ▾
Strongly Correlated Electrons
Autoregressive Neural Network Extrapolation of Quantum Spin Dynamics Across Time and Space
Hubert Pugzlys, Shreyas Varude, Sam Dillon et al. (+5 more)
Understanding the long-time dynamics of strongly correlated
quantum matter remains a major challenge: as
quantum entanglement grows during time
evolution, conventional numerical methods become increasingly costly, limiting access to the long-range correlations and low-energy excitations that govern gapless systems. Here we show that these dynamical correlations can be extended beyond the accessible numerical window without explicitly evolving the underlying many-body wavefunction. We introduce an autoregressive machine-learning framework that enables the extrapolation of dynamical
spin correlations in both time and space beyond the reach of conventional numerical methods. Trained on time-dependent density
matrix renormalization group simulations of the gapless XXZ model, our approach is benchmarked against exact solutions available for this analytically solvable system. Combined with physics-informed spatial extension, a multi-layer perceptron model using ReLU activation functions has been shown to be superior to convolutional neural networks and linear regressions for longer time extrapolation. A study of error accumulation further demonstrates that our autoregressive neural network extrapolations are highly robust to perturbations, suggesting stable and reliable predictions. This work offers a complementary route to studying the dynamics of gapless
quantum many-body systems, in which machine learning extends and complements the capabilities of state-of-the-art numerical approaches.
Read the full abstract ▾
All authors Hubert Pugzlys, Shreyas Varude, Sam Dillon, Huy Tran, Ta Tang, Brian Moritz, Zhe Jiang, Chunjing Jia
Statistical Mechanics
Theory of the $\beta$-Relaxation Beyond Mode-Coupling Theory: A Microscopic Treatment
Corentin C. L. Laudicina, Liesbeth M. C. Janssen and Grzegorz Szamel
We develop a systematic extension of mode-coupling theory (MCT) that incorporates critical dynamical fluctuations. Starting from a microscopic diagrammatic theory, we identify dominant classes of divergent diagrams near the mode-coupling transition and show that the corresponding asymptotic series dominates the mean-field below an upper critical dimension $d_c=8$. To resum these divergences, we construct a mapping to a
stochastic dynamical process in which the order parameter evolves under random spatiotemporal fields. This reformulation provides a controlled, fully dynamical derivation of an effective theory for the $\beta$-relaxation which remarkably coincides with
stochastic beta-relaxation theory [T. Rizzo, EPL 106, 56003 (2014)]. All coupling constants of the latter theory are expressed microscopically in terms of the
liquid static structure factor and are computed for the paradigmatic hard-sphere system. The analysis demonstrates that fluctuations alone restore ergodicity and replace the putative mean-field transition by a smooth crossover. Our results establish a predictive framework for structural relaxation beyond mean-field.
Read the full abstract ▾
Soft Condensed Matter
Microscopic Theory of a Fluctuation-Induced Dynamical Crossover in Supercooled Liquids
Corentin C. L. Laudicina, Liesbeth M. C. Janssen and Grzegorz Szamel
Mean-field theories of the glass transition predict a phase transition to a dynamically arrested state, yet no such transition is observed in experiments or simulations of finite-dimensional systems. We resolve this long-standing discrepancy by incorporating critical dynamical fluctuations into a microscopic mode-coupling framework. We show that these fluctuations round off the mean-field singularity and restore ergodicity at all finite densities (or temperatures) without invoking activated dynamics or facilitation. The resulting effective theory describes the order parameter as a
stochastic process with self-induced, annealed disorder, determined self-consistently at the mean-field level. In the $\beta$-relaxation regime it reduces to
stochastic beta-relaxation theory, thereby unifying mode-coupling and replica-based approaches beyond mean-field. All parameters of the
stochastic $\beta$-relaxation theory are fixed by the static structure, enabling parameter-free predictions that extend mean-field theory into finite dimensions.
Read the full abstract ▾
Materials Science
3D lattice Monte Carlo modeling of morphology formation of Si/SiOx nanocomposites during phase separation of nonstoichiometric Si oxide films
Ivan Oliinyk and Andrey Sarikov
In this paper, a three-dimensional
lattice model based on the Monte Carlo approach is presented. This model is developed to investigate the kinetics of morphology change during phase separation in nonstoichiometric Si
oxide (SiOx, x < 2) films. The model takes into account the SiOx local atomic structure and probabilistic migration of oxygen atoms driven by the tendency of free energy minimization. The influence of the initial SiOx stoichiometry index x and film thickness on the morphology of the precipitated Si phase in the Si
oxide matrix is analyzed. The morphology of the Si phase is shown to critically depend on the initial SiOx stoichiometry. Namely, isolated Si nanoparticles form at low excess Si content (x >= 1.4), while interconnected Si networks always appear at x <= 0.8. A dimensional effect on the morphology of the Si phase is revealed. Namely, reducing the film thickness imposes
geometric constraints on the Si network formation. The percolation threshold is found to shift from xp ~= 1.35 for the bulk-like SiOx layers to xp ~= 0.85 for the quasi-two-dimensional films. The transition to the bulk material behavior is observed at a SiOx thickness of approximately 4.2 nm.
Read the full abstract ▾
Superconductivity
Non-thermal pairing glue of electrons in the steady state
Michele Pini, Christian H. Johansen and Francesco Piazza
The study of mechanisms for enhancing superconductivity has been a central topic in condensed matter physics due to the combination of fundamental and technological interests. One promising route is to exploit non-
equilibrium effects in the steady state. Efforts in this direction have so far focused on enhancing the pairing mechanism known from thermal
equilibrium through modified distributions for the electrons or the
bosons mediating the electron-electron interaction. In this work, we identify an additional pairing mechanism that is active only outside thermal
equilibrium. By generalizing Eliashberg theory to non-
equilibrium steady states using the Keldysh formalism, we derive a set of Eliashberg equations that capture the effect of this genuinely non-thermal pairing glue even in the weak-coupling regime. We discuss two examples where this mechanism has a major impact. First, in a temperature-bias setup, we find that superconductivity is enhanced when the
boson mediator is colder than the electrons. Second, we find that an incoherent drive of the
boson mediator at energies much greater than the temperature pushes the system far from thermal
equilibrium but leaves the critical coupling essentially unchanged, owing to a competition between electron heating and the enhancement of pairing by the non-thermal glue.
Read the full abstract ▾
Mesoscale and Nanoscale Physics
Unidirectional gliding of a cycloidal spin structure by an AC magnetic field
Dong Hui Han, Kyoung-Woong Moon, Kab-Jin Kim et al. (+1 more)
The dynamics of a cycloidal
spin structure driven by an AC
magnetic field is theoretically studied in the weak-field limit. A specific model
Hamiltonian describing the cycloidal
spin structure in a
ferromagnetic thin film is constructed, and its dynamics is analyzed using the collective-coordinate approach within the Lagrangian formalism. We demonstrate that the cycloidal
spin structure exhibits a unidirectional gliding motion under an AC
magnetic field, and an expression for the average velocity is derived as a function of the magnitude, the direction, and the frequency of the AC
magnetic field. We compare our theoretical predictions with the results of micromagnetic simulations and identify two resonance frequencies determined by the eigenenergies of the excitation modes. Furthermore, evaluating
spin motive forces induced by the dynamics reveals a substantial DC voltage, which may be exploited in energy-harvesting devices utilizing ambient electromagnetic radiation.
Read the full abstract ▾
All authors Dong Hui Han, Kyoung-Woong Moon, Kab-Jin Kim, Se Kwon Kim
Strongly Correlated Electrons · Cross-listed from quant-ph
Imaginary-time-enhanced feedback-based quantum algorithms for universal ground-state preparation
Thanh Nguyen Van Long, Lan Nguyen Tran and Le Bin Ho
Preparing ground states of strongly correlated
quantum systems is a central goal in
quantum simulation and optimization. The feedback-based
quantum algorithm (FALQON) provides an attractive alternative to variational methods with a fully
quantum feedback rule, but it fails in the presence of spectral degeneracies, where the feedback signal collapses and the
evolution cannot reach the ground state. Using the
Fermi-Hubbard model on
lattices up to 3x3, we show that this breakdown appears at half-filling on the 2x2
lattice and extends to both half-filled and doped configurations on the 3x3
lattice. We then introduce an imaginary-time-enhanced FALQON ($i$FALQON) scheme, which inserts short imaginary-time
evolution steps into the feedback loop. This proposed method suppresses excited-state components, escapes degenerate subspaces, restores monotonic energy descent and improves ground-state convergence across the tested fillings. We further
benchmark its performance against existing methods, showing improved results for iFALQON, demonstrating the potential of hybrid real-imaginary-time feedback dynamics for ground-state preparation in strongly correlated
quantum systems.
Read the full abstract ▾
Materials Science
Enhanced THz emission and exciton transfer in monolayer MoS2/GaAs heterostructures
C. Abinash Bhuyan, Anil K. Chaudhary, Kishore K. Madapu et al. (+2 more)
For designing an efficient terahertz (THz) emitter, the defect density of the
semiconductors is smartly increased to reduce carrier lifetime, which subsequently lowers the overall power output of the
semiconductor. To overcome this fundamental trade-off, this study presents a novel approach, by integrating a direct band gap 2D
semiconductor such as monolayer MoS2 (1L-MoS2) with a well-known THz emitter, low-temperature-grown gallium arsenide (GaAs). The fabricated hybrid 2D/3D vertical van der Waals
heterostructure showed a 15% higher THz emission compared to bare GaAs due to phase-coherent addition of second-order non-linear susceptibility, and overall enhancement in the electric field of
laser. The photoluminescence (PL) enhancement factor of 2.38 in
heterostructures at GaAs emission energy of 1.42 eV. However, the substantial quenching of PL emission for 1L-MoS2 at the energy of 1.84 eV, is attributed to the Dexter-type
exciton transfer mechanism at type-I band
alignment. THz time-domain spectroscopy reveals a significant increase in optoelectronic properties, such as optical conductivity becoming doubled, and a 50% reduction in absorption coefficients. The study introduces a new route for fabricating large-area and compact mixed-dimensional van der Waals
heterostructures, which can be used to enhance the efficiency of conventional
semiconductor technologies and THz-based optoelectronic devices.
Read the full abstract ▾
All authors C. Abinash Bhuyan, Anil K. Chaudhary, Kishore K. Madapu, P. Naveen Kumar, Sandip Dhara
Strongly Correlated Electrons
The interplay of magnetic order with the electronic scattering and crystal-field effects in a metallic ferromagnet
Payel Shee, Tanaya Halder, Chia-Jung Yang et al. (+9 more)
The interplay between
magnetic order, charge dynamics, and
crystal field excitations underpins the emergent ground states of rare-earth intermetallics. Using time-domain terahertz spectroscopy, we probe this coupling in PrSi, a metallic ferromagnet. The optical response exhibits pronounced Drude-Smith behavior over a broad temperature range, indicating persistent carrier scattering. A classical Kondo-
lattice model (CKLM) attributes this non-Drude conductivity to scattering of itinerant electrons by localized
magnetic moments, persisting down to temperatures well below the
magnetic ordering scale. At lower temperatures, beyond the scope of CKLM, our experiment reveals that the response is dominated by
crystal-field excitations, with sharp transitions at 0.6 THz and 1.54 THz. The mode at 1.54 THz shows a dynamic correlation with the onset of
ferromagnetic order, marking the onset of a
crystal-field-governed low temperature regime.
Read the full abstract ▾
All authors Payel Shee, Tanaya Halder, Chia-Jung Yang, Nainish Tickoo, Ratiranjan Samal, Ruta Kulkarni, Shishir K. Pandey, Vikas Kashid, Ashis K. Nandy, Arumugam Thamizhavel, Anamitra Mukherjee, Shovon Pal
Mesoscale and Nanoscale Physics
Electric fields induced spin and/or valley polarization in Weiss oscillations of monolayer 1T$^{\prime}$-$\mathrm{MoS}_{2}$
Y. Li, W. Zeng and R. Shen
Monolayer 1T$^{\prime}$-$\mathrm{MoS}_{2}$ exhibits
spin- and valley-dependent massive tilted Dirac cones with two velocity correction terms in low-energy effective
Hamiltonian. We theoretically investigate the longitudinal diffusive magneto-conductivity of monolayer 1T$^{\prime}$-$\mathrm{MoS}_{2}$ by using the linear response theory. It is shown that the Weiss oscillations are polarized in
spin and valley degrees of freedom, under uniform electric fields and a weak one-dimensional spatially-periodic electrostatic potential modulation. The
spin polarization, the valley polarization and the
spin-valley polarization can be switched by flipping the external electric fields. The polarization is found not only in the amplitudes but also in the periods of the Weiss oscillations. It is found that the period polarization in Weiss oscillations originates from the polarized effective
Fermi energies or the polarized Landau level spacing scales. In Weiss oscillations, polarization in amplitude does not imply the presence of polarization in period, whereas polarization in period is accompanied by polarization in amplitude. The superposition of polarization in amplitude and polarization in period enables the appearance of considerable polarization in Weiss oscillations under relatively weak external electric fields.
Read the full abstract ▾
Strongly Correlated Electrons
Non-linear transport in field-induced insulating states of graphite
Masashi Tokunaga, Kazuto Akiba, Hiroshi Yaguchi et al. (+2 more)
Graphite exhibits multi-stage phase transitions in the
quantum-limit states realized by
magnetic fields applied along the c-axis. Despite extensive studies on this phenomenon, the origin remains a matter of debate to this day. We performed high-field magnetotransport measurements on single
crystals of graphite, focusing on the non-linear conductivity in pulsed-
magnetic fields of up to 75 T. The longitudinal magnetoresistance exhibits distinct non-linearity not only in the first but also in the second field-induced phases.
Read the full abstract ▾
All authors Masashi Tokunaga, Kazuto Akiba, Hiroshi Yaguchi, Akira Matsuo, Koichi Kindo
Materials Science
Phase-field simulation of domain switching in ferroelectric trilayer films under bending-induced strain gradient
Changqing Guo, Letao Yang, Jing Wang et al. (+1 more)
Flexible ferroelectrics possess significant potential for wearable electronics and bio-inspired devices, yet their electromechanical coupling mechanisms under dynamic bending remain elusive. This study employs phase-field simulations to investigate the effects of bending deformation on domain structures and macroscopic ferroelectric responses in (SrTiO3)10/(PbTiO3)10/(SrTiO3)10 trilayer films. By constructing computational models for upward-concave (U-shaped) and downward-concave (N-shaped) configurations, we analyze the regulation of polarization patterns by strain distributions under varying
curvature radii. The results demonstrate that the two bending modes generate opposite through-thickness strain gradients: U-shaped bending produces compressive strain in the upper layer and tensile strain in the lower, while N-shaped bending yields the reverse. These inhomogeneous strains drive distinct polarization reconfigurations within the PTO layer. While stable
vortex-antivortex pairs persist at moderate
curvatures, reducing the bending radius triggers divergent topological transitions – U-shaped bending transforms
vortex pairs into zigzag-like domains, whereas N-shaped bending promotes out-of-plane c-domain
evolution. Crucially, bending-induced strain gradients generate transverse flexoelectric fields that markedly modulate hysteresis loops. U-shaped bending introduces a negative flexoelectric field, shifting loops rightward and suppressing maximum polarization Pmax. In contrast, N-shaped bending generates a positive field, shifting loops leftward and enhancing Pmax. Furthermore, analysis of polarization switching reveals that bending mediates domain-
evolution pathways and reversal dynamics.
Read the full abstract ▾
All authors Changqing Guo, Letao Yang, Jing Wang, Houbing Huang