Mesoscale and Nanoscale Physics
Daniel Jirovec, Stefano Reale, Pablo Cova-Fariña et al. (+9 more)
Quantum simulators enable studies of many-body phenomena which are intractable with classical hardware.
Spins in devices based on
semiconductor quantum dots promise precise electrical control and scalability advantages, but accessing many-body phenomena has so far been restricted by challenges in nanofabrication and simultaneous control of multiple interactions. Here, we perform spectroscopy of up to eight interacting
spins using a 2x4 array of gate-defined germanium
quantum dots. The spectroscopy protocol is based on Ramsey interferometry and adiabatic mapping of many-body eigenstates to single-
spin eigenstates, enabling a complete energy spectrum reconstruction. As the interaction strength exceeds
magnetic disorder, we observe signatures of the crossover from localization to a chaotic phase marking a step towards the observation of many-body phenomena in
quantum dot systems.
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All authors Daniel Jirovec, Stefano Reale, Pablo Cova-Fariña, Christian Ventura-Meinersen, Minh T. P. Nguyen, Xin Zhang, Stefan D. Oosterhout, Giordano Scappucci, Menno Veldhorst, Maximilian Rimbach-Russ, Stefano Bosco, Lieven M. K. Vandersypen
Mesoscale and Nanoscale Physics
High luminescence efficiency of multi-valley excitonic complexes in heavily doped WSe2 monolayer
Sébastien Roux, Tilly Guyot, Abraao Cefas Torres-Dias et al. (+9 more)
Monolayers of group-VI transition-metal dichalcogenides (TMDs) are two-dimensional
semiconductors that exhibit exceptionally strong light-matter coupling yet typically suffer from low emission
quantum yields. In this letter, we investigate the heavily n-doped regime of a WSe$_2$ monolayer and show that multi-particle excitonic complexes produce photoluminescence signals up to two orders of magnitude stronger than in the neutral state. Time-resolved photoluminescence and differential reflectivity measurements reveal that the
quantum yield rises with carrier density and exceeds 50% for electron concentrations above 10$^{13}$ cm$^{-2}$. These findings establish TMD monolayers as a platform for exploring excitonic complexes in high-density electron gases and point toward new opportunities for efficient, atomically thin light emitters.
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All authors Sébastien Roux, Tilly Guyot, Abraao Cefas Torres-Dias, Delphine Lagarde, Laurent Lombez, Dinh Van Tuan, Junghwan Kim, Kenji Watanabe, Xavier Marie, Takashi Taniguchi, Hanan Dery, Cedric Robert
Strongly Correlated Electrons
T-square electric resistivity and its thermal counterpart in RuO$_2$
Yu Ling, Florent Pawula, Ramzy Daou et al. (+2 more)
We present a study of low-temperature electric and thermal transport in RuO$_2$, a metallic
oxide which has attracted much recent
attention. Careful scrutiny of electric resistivity reveals a quadratic temperature dependence below $\sim$ 20 K undetected in previous studies of electronic transport in this material. The prefactor of this T$^2$ resistivity, given the electronic specific heat, corresponds to what is expected by the Kadowaki-Woods scaling. The variation of its amplitude across 4 different samples is negligible despite an eightfold variation of residual resistivity. There is also a T$^5$ resistivity due to scattering by
phonons. By measuring thermal conductivity, $\kappa$, at zero field and at 12 T, we separated its electronic and the phononic components and found that the electronic component respects the Wiedemann-Franz law at zero temperature and deviates downward at finite temperature. The latter corresponds to a threefold discrepancy between the prefactors of the two (thermal and electric) T-square resistivities. Our results, establishing RuO$_2$ as a weakly correlated
Fermi liquid, provide new input for the ongoing theoretical attempt to give a quantitative account of electron-electron scattering in metallic
oxides starting from first principles.
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All authors Yu Ling, Florent Pawula, Ramzy Daou, Benoît Fauqué, Kamran Behnia
Materials Science
Revealing the innate sub-nanometer porous structure of carbon nanomembranes with molecular dynamics simulations and highly charged ion spectroscopy
Filip Vuković, Anna Niggas, Levin Mihlan et al. (+8 more)
Carbon nanomembranes (CNMs) are nanometer-thin disordered carbon materials that are suitable for a range of applications, from energy generation and storage, through to water filtration. The structure-property relationships of these nanomembranes are challenging to study using traditional experimental characterization techniques, primarily due to the radiation-sensitivity of the free-standing membrane. Highly charged ion spectroscopy is a novel characterization method that is able to infer structural details of the carbon nanomembrane without concern of induced damage affecting the measurements. Here we employ molecular dynamics simulations to produce candidate structural models of terphenylthiol-based CNMs with varying degrees of nanoscale porosity, and compare predicted ion charge exchange data and tensile
moduli to experiment. The results suggest that the in-
vacuum CNM composition likely comprises a significant fraction of under-coordinated carbon, with an open sub-nanometer porous structure. Such a carbon network would be reactive in atmosphere and would be presumably stabilized by hydrogen and oxygen groups under atmospheric conditions.
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All authors Filip Vuković, Anna Niggas, Levin Mihlan, Zhen Yao, Armin Gölzhäuser, Louise Fréville, Vladislav Stroganov, Andrey Turchanin, Jürgen Schnack, Nigel A. Marks, Richard A. Wilhelm
Strongly Correlated Electrons
Spin responses of a disordered helical superconducting edge under Zeeman field
Zeinab Bakhshipour and Mir Vahid Hosseini
We investigate analytically and numerically the effects of disorder on the helical edge of the 2D topological
insulator in the presence of the Zeeman field and superconductivity. Employing bosonization and a renormalization-group analysis, we study how
impurity potentials modify charge- and
spin-density wave correlations as well as superconducting pair correlations. Our results reveal that the Zeeman field controls the competition: in the attractive regime, it amplifies the superconducting gap, while in the repulsive regime, it stabilizes
impurity effects by keeping the system longer in the relevant regime for disorder. We also find that disorder induces logarithmic suppression of transverse density-wave correlations, while at the same time introducing positive logarithmic corrections that enhance superconducting pair correlations and contribute to their stability. These effects directly modify the scaling of
spin conductance, providing experimentally accessible signatures of the interplay between disorder and superconductivity in topological edge channels.
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Soft Condensed Matter
Directed autonomous motion of active Janus particles induced by wall-particle alignment interactions
Poulami Bag, Tanwi Debnath, Shubhadip Nayak et al. (+1 more)
We propose a highly efficient mechanism to rectify the motion of active particles by exploiting particle-wall
alignment interactions. Through numerical simulations of active particles' dynamics in a narrow channel, we demonstrate that a slight difference in
alignment strength between the top and bottom walls or a small gravitational drag suffices to break upside-down
symmetry, leading to rectifying the motion of
chiral active particles with over 60% efficiency. In contrast, for achiral swimmers to achieve rectified motion using this protocol, an unbiased fluid flow is necessary that can induce orbiting motion in the particle's dynamics. Thus, an achiral particle subject to Couette flow exhibits spontaneous directed motion due to an upside-down asymmetry in particle-wall
alignment interaction. The rectification effects caused by
alignment we report are robust against variations in self-propulsion properties, particle's chirality, and the most stable orientation of self-propulsion velocities relative to the walls. Our findings offer insights into controlled active matter transport and could be useful to sort artificial as well as natural microswimmers (such as bacteria and sperm
cells) based on their chirality and self-propulsion velocities.
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All authors Poulami Bag, Tanwi Debnath, Shubhadip Nayak, Pulak K. Ghosh
Mesoscale and Nanoscale Physics
Revealing the impact of ambient molecular contamination on scanning tunneling microscopy and spectroscopy of layered materials
György Kálvin, Péter Vancsó, Márton Szendrő et al. (+4 more)
Hydrocarbon contamination is an ever-present factor to consider in surface science measurements. In the case of van der Waals material surfaces, the structure of this contamination has become known in recent years as a self-assembled layer of normal-alkanes, resulting from a few days' exposure to ambient air. Knowledge of its composition and structure enables systematic investigation of its influence on surface properties. Here, we investigate the effect of this contamination on scanning tunneling microscopy (STM) and spectroscopy measurements by comparing clean and ambient alkane-contaminated surfaces of graphite. Our results reveal that the ambient alkane layer suppresses the well-known
phonon-induced gap near the
Fermi energy, resolving a long-standing inconsistency in STM studies, where this feature is often absent. Furthermore, we show that the presence of the contamination layer alters the current-distance ($I(z)$) characteristics, flattening its exponential decay by a factor of 1.5 to 5 compared to the clean surface. This change arises from extra conductance channels through the alkane layer alongside the tunnel junction, as the tip penetrates the contaminant overlayer. Finally, based on the $I(z)$ characteristics, we provide a practical guide to detect the presence of surface contamination in STM measurements.
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All authors György Kálvin, Péter Vancsó, Márton Szendrő, Konrád Kandrai, András Pálinkás, Levente Tapasztó, Péter Nemes-Incze
Soft Condensed Matter
Phase behavior and percolation properties of the primitive model of Laponite suspension. TPT of Wertheim with ISM reference system
Yurij V Kalyuzhnyi
Computation of the properties of associative fluids with the particles highly anisotropic in shape, using multi-density perturbation theory of Wertheim, has long been a challenge. We propose a simple and efficient scheme that allow us to perform such computations. The scheme is based on a combination of thermodynamic perturbation theory and the interaction site model approach for molecular fluids due to Chandler and Andersen. Our method is illustrated by its application to calculation of the phase diagram and percolation properties of a primitive model of Laponite suspension proposed recently.
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Mesoscale and Nanoscale Physics
Polariton XY-simulators revisited
Junhui Cao, Denis Novokreschenov and Alexey Kavokin
Arrays of bosonic condensates of
exciton-polaritons have emerged as a promising platform for simulating classical XY models, capable of rapidly reaching phase-locked states that may be mapped to arrays of two-dimensional classical
spins. However, it remains unclear whether these states genuinely minimize the corresponding XY
Hamiltonian and how the convergence time scales with the system size. Here, we develop an analytical model revealing that an array of $N$ condensates possesses $N$ stable phase configurations. The system selectively amplifies a specific configuration dependent on the pump power: at low power, the state with the smallest
eigenvalue of an effective XY
Hamiltonian is favored, while at high power, the state with the largest
eigenvalue prevails. At intermediate pump powers, the system visits all eigenstates of the
Hamiltonian. Crucially, the formation rate for any of these phase-locked states remains on the order of 100 ps, independent of the size of the array, demonstrating the exceptional speed and scalability of polariton-based XY simulators.
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Superconductivity
High-Tc superconductivity above 130 K in cubic MH4 compounds at ambient pressure
Xinxin Li, Weishuo Xu, Zengguang Zhou et al. (+6 more)
Hydrides have long been considered promising candidates for achieving room-temperature superconductivity; however, the extremely high pressures typically required for high critical temperatures remain a major challenge in experiment. Here, we propose a class of high-Tc ambient-pressure
superconductors with MH4 stoichiometry. These hydrogen-based compounds adopt the bcc PtHg4 structure type, in which hydrogen atoms occupy the one-quarter body-diagonal sites of metal
lattices, with the metal atoms acting as chemical templates for hydrogen assembly. Through comprehensive first-principles calculations, we identify three promising
superconductors, PtH4, AuH4 and PdH4, with superconducting critical temperatures of 84 K, 89 K, and 133 K, respectively, all surpassing the
liquid-nitrogen temperature threshold of 77 K. The remarkable superconducting properties originate from strong electron-
phonon coupling associated with hydrogen vibrations, which in turn arise from
phonon softening in the mid-frequency range. Our results provide crucial insights into the design of high-Tc
superconductors suitable for future experiments and applications at ambient pressure.
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All authors Xinxin Li, Weishuo Xu, Zengguang Zhou, Jingming Shi, Hanyu Liu, Yue-Wen Fang, Wenwen Cui, Yinwei Li, Miguel A. L. Marques
Soft Condensed Matter
Multimodal Physical Learning in Brain-Inspired Iontronic Networks
Monica Conte, René van Roij and Marjolein Dijkstra
Inspired by the
brain, we present a physical alternative to traditional digital neural networks – a microfluidic network in which nodes are connected by conical, electrolyte-filled channels acting as memristive iontronic synapses. Their electrical conductance responds not only to electrical signals, but also to chemical, mechanical, and
geometric changes. Leveraging this
multimodal responsiveness, we develop a training
algorithm where learning is achieved by altering either the channel geometry or the applied stimuli. The network performs forward passes physically via ionic relaxation, while learning combines this physical
evolution with numerical gradient descent. We theoretically demonstrate that this system can perform tasks like input-output mapping and linear regression with bias, paving the way for soft, adaptive materials that compute and learn without conventional electronics.
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Superconductivity
Superconducting Properties on Two-dimensional Quasicrystal (Ta$_{0.95}$Cu$_{0.05}$)$_{1.6}$Te Studied with $^{125}$Te-NMR
H. Matsudaira, S. Kitagawa, K. Ishida et al. (+3 more)
Physical properties in the normal and superconducting (SC) state are investigated with $^{125}$Te-
nuclear magnetic resonance (NMR) measurements in a quasicrystal $\mathrm{(Ta_{0.95}Cu_{0.05})_{1.6}Te}$, which was a recently discovered
superconductor with the SC transition temperature $T_{\mathrm{c}}$ = 0.94 K. The
nuclear spin-
lattice relaxation rate $1/T_1$ shows a coherence peak just below $T_{\mathrm{c}}$, followed by an exponential decrease down to 0.1 K. The overall temperature dependence of $1/T_1$ is in good agreement with an $s$-wave SC model with a SC gap slightly smaller than the BCS value. However, the coherence peak is unusually small, which may be attributable to a reduced Bogoliubov peak theoretically predicted for quasicrystals. Furthermore, $^{125}$Te-NMR spectra show almost no broadening nor shift in the SC state, suggesting that an unusual SC state such as parity mixing might be realized in the Ta$_{1.6}$Te
superconductor.
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All authors H. Matsudaira, S. Kitagawa, K. Ishida, Y. Tokumoto, K. Tomiyama, K. Edagawa
Soft Condensed Matter
Feedback-controlled mechanics of tissue vertex model: emergent soft elasticity and active yielding
Pengyu Yu, Fridtjof Brauns and M. Cristina Marchetti
Biological tissues exhibit diverse mechanical and rheological behaviors during morphogenesis. While much is known about tissue phase transitions controlled by structural order and
cell mechanics, key questions regarding how tissue-scale nematic order emerges from
cell-scale processes and influences tissue rheology remain unclear. Here, we develop a minimal vertex model that incorporates a coupling between active forces generated by cytoskeletal fibers and their
alignment with local elastic stress in solid epithelial tissues. Combining theory and simulations, we show that this feedback loop induces an isotropic–nematic transition, leading to an ordered solid state that exhibits soft elasticity. Further increasing activity drives collective self-yielding, that is the ability to spontaneously transition form elastic to plastic deformations, with tissue flows that are correlated across the entire system. We argue that this remarkable state, that we dub plastic nematic solid, is uniquely suited to facilitate active tissue remodeling during morphogenesis. It fundamentally differs from the well-studied fluid regime where macroscopic elastic stresses vanish and the velocity correlations remain short-ranged. Altogether, our theoretical results reveal a rich spectrum of tissue states jointly governed by activity and passive
cell deformability, with important implications for understanding tissue mechanics and morphogenesis.
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Soft Condensed Matter
Nonequilibrium dynamics of membraneless active droplets
Chenxi Liu, Ding Cao, Siyu Liu et al. (+1 more)
Membraneless droplets or
liquid condensates formed via
liquid-
liquid phase separation (LLPS) play a pivotal role in
cell biology and hold potential for biomedical engineering. While membraneless droplets are often studied in the context of interactions between passive components, it is increasingly recognized that active matter inclusions, such as molecular motors and catalytic enzymes in
cells, play important roles in the formation, transport and interaction of membraneless droplets. Here we developed a bacteria-
polymer active phase separation system to study the nonequilibrium effect of active matter inclusions on the LLPS dynamics. We found that the presence of bacterial active matter accelerated the initial condensation of phase-separated
liquid droplets but subsequently arrested the droplet coarsening process, resulting in a stable suspension of membraneless active droplets packed with motile bacterial
cells. The arrested phase separation of the bacterial active droplet system presumably arises from anti-phase entrainment of interface fluctuations between neighboring droplets, which reduces the frequency of inter-droplet contact and suppresses droplet coarsening. In addition, the active stresses generated by
cells within the droplets give rise to an array of nonequilibrium phenomena, such as dominant long-wavelength fluctuations and enhanced droplet transport with short-term persistent motion due to spontaneous
symmetry breaking. Our study reveals a unique mechanism for arrested phase separation and long-term stability in membraneless droplet systems. The bacteria-
polymer active phase separation system opens a new avenue for studying the dynamics of membraneless active droplets relevant to non-
equilibrium LLPS in
cells and in biomedical engineering applications.
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All authors Chenxi Liu, Ding Cao, Siyu Liu, Yilin Wu
Disordered Systems and Neural Networks · Cross-listed from nlin.CD
Energy transport and chaos in a one-dimensional disordered nonlinear stub lattice
Su Ho Cheong, Arnold Ngapasare, Vassos Achilleos et al. (+3 more)
We investigate energy propagation in a one-dimensional stub
lattice in the presence of both disorder and nonlinearity. In the periodic case, the stub
lattice hosts two dispersive bands separated by a flat band; however, we show that sufficiently strong disorder fills all intermediate band gaps. By mapping the two-dimensional parameter space of disorder and nonlinearity, we identify three distinct dynamical regimes (weak chaos, strong chaos, and self-trapping) through numerical simulations of initially localized wave packets. When disorder is strong enough to close the frequency gaps, the results closely resemble those obtained in the one-dimensional disordered discrete nonlinear Schrödinger equation and Klein-Gordon
lattice model. In particular, subdiffusive spreading is observed in both the weak and strong chaos regimes, with the second moment $m_2$ of the norm distribution scaling as $m_2 \propto t^{0.33}$ and $m_2 \propto t^{0.5}$, respectively. The system's chaotic behavior follows a similar trend, with the finite-time maximum Lyapunov exponent $\Lambda$ decaying as $\Lambda \propto t^{-0.25}$ and $\Lambda \propto t^{-0.3}$. For moderate disorder strengths, i.e., near the point of gap closing, we find that the presence of small frequency gaps does not exert any noticeable influence on the spreading behavior. Our findings extend the characterization of nonlinear disordered
lattices in both weak and strong chaos regimes to other network geometries, such as the stub
lattice, which serves as a representative flat-band system.
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All authors Su Ho Cheong, Arnold Ngapasare, Vassos Achilleos, Georgios Theocharis, Olivier Richoux, Charalampos Skokos
Materials Science
Unconventional Thermal Expansion in quasi-one-dimensional monoclinic BaIrO$_3$
Jeong Jinwon, Chang Bin, Noh Han-Jin et al. (+1 more)
We have investigated the temperature dependence of the
crystal structure of quasi-one-dimensional monoclinic BaIrO$_3$ using X-ray diffraction. Diffraction patterns were measured across a temperature range from 13 K to 300 K, with 5-degree steps, and Rietveld refinements were performed to extract the relevant
lattice parameters. The resulting
cell volumes exhibit a significant deviation from the Debye model predictions for
lattice-specific heat within a reasonable range of the Debye temperature, Grüneisen parameter, and bulk modulus. This suggests an invar-like, unconventional thermal expansion behavior. The deviation begins near the weak
ferromagnetic transition temperature, indicating a strong correlation with changes in the electronic and
magnetic structure of monoclinic BaIrO$_3$.
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All authors Jeong Jinwon, Chang Bin, Noh Han-Jin, Lee Seongsu
Strongly Correlated Electrons
Interaction enhanced altermagnet in the Hatsugai-Kohmoto model
Ádám Bácsi and Balázs Dóra
We investigate the interplay between altermagnetic band structures and electronic correlations by focusing on the $d_{x^2-y^2}$ altermagnetic generalization of the Hatsugai-Kohmoto model. We find that with increasing interaction, a many-body Lifshitz transition takes place when doubly occupied regions disappear from the
Fermi surface and almost all momentum states become fully
spin polarized. This is termed interaction enhanced altermagnet. We find that the dynamical susceptibility, which possesses only transverse non-zero components for small wavevectors, develops a gap proportional to the interaction strength, and displays a sharp peak at a frequency increasing with the interaction. Above the Lifshitz transition, this peak moves to the lower gap edge and becomes log-divergent. The signal intensity increases with the interaction up until the Lifshitz transition and saturates afterwards. The static susceptibility remains unaffected by the correlations and altermagnetism reduces the static transverse response.
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Strongly Correlated Electrons
Phase diagrams of S=1/2 bilayer Models of SU(2) symmetric antiferromagnets
Fan Zhang, Nisheeta Desai, Wenan Guo et al. (+1 more)
We study the $T=0$ phase diagrams of models of
bilayers of $S=1/2$ square
lattices antiferromagnets with SU(2) Heisenberg
symmetry that have 2, 4, and 6
spin exchanges. We study two families of
bilayer models with distinct internal
symmetries and, hence, different phase diagram
topologies. A traditional
bilayer model in which the interlayer interaction is Heisenberg so that the two layers can exchange
spin (and energy) with each other, making it possible to achieve a simple dimerized valence bond
liquid-like state. The resulting phase diagram is rich with Néel, valence bond solid and simple dimer phases, and both first-order and continuous transitions, which we demonstrate are consistent with the conventional Landau theory of order parameters. In the second family of models in which the layers can exchange only energy but no
spin (reminiscent of the Ashkin-Teller coupling), the simple dimer state cannot occur. The phase diagrams reveal a number of phase transitions that are accessed for the first time. We find that the phase transition between Néel and VBS is first order in both the
spin-
spin and energy-energy coupled models, although they have strikingly distinct finite-size scaling behavior and that the transition from VBS to dimer in the
spin-
spin coupling model deviates from the expected scenario of an XY model with dangerously irrelevant four-fold anisotropy.
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All authors Fan Zhang, Nisheeta Desai, Wenan Guo, Ribhu K. Kaul
Statistical Mechanics
Statistics of leaves in growing random trees
Harrison Hartle and P. L. Krapivsky
Leaves, i.e., vertices of degree one, can play a significant role in graph structure, especially in sparsely connected settings in which leaves often constitute the largest fraction of vertices. We consider a leaf-based counterpart of the degree, namely, the leaf degree – the number of leaves a vertex is connected to – and the associated leaf degree distribution, analogous to the degree distribution. We determine the leaf degree distribution of random recursive trees (RRTs) and trees grown via a leaf-based preferential attachment mechanism that we introduce. The RRT leaf degree distribution decays factorially, in contrast with its purely
geometric degree distribution. In the one-parameter leaf-based growth model, each new vertex attaches to an existing vertex with rate $\ell$ + a, where $\ell$ is the leaf degree of the existing vertex, and a > 0. The leaf degree distribution has a powerlaw tail when 0 < a < 1 and an exponential tail (with algebraic prefactor) for a > 1. The critical case of a = 1 has a leaf degree distribution with stretched exponential tail. We compute a variety of additional characteristics in these models and
conjecture asymptotic equivalence of degree and leaf degree powerlaw tail exponent in the scale free regime. We highlight several avenues of possible extension for future studies.
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Materials Science
TXL Fusion: A Hybrid Machine Learning Framework Integrating Chemical Heuristics and Large Language Models for Topological Materials Discovery
Arif Ullah, Rajibul Islam, Yangming Huang et al. (+4 more)
Topological materials, including topological
insulators (TIs) and topological semimetals (TSMs), offer promising platforms for
quantum, spintronic, and low-dissipation electronic technologies. Their discovery, however, remains constrained by the high cost of first-principles calculations and the slow, resource-intensive nature of experimental validation. Here, we introduce TXL Fusion, a hybrid machine-learning framework that integrates chemically inspired heuristics, physically interpretable numerical descriptors, and large
language model (LLM)-derived semantic
embeddings for topological-materials classification and discovery. By combining space-group
symmetry, electron-count and orbital descriptors, composition-derived topological heuristics, and physics-aware semantic representations, TXL Fusion classifies materials into trivial, TSM, and TI categories with improved overall performance and enhanced minority-class TI recognition relative to conventional descriptor-based baselines. The model further serves as a high-throughput pre-screening tool for external discovery spaces, rapidly prioritizing candidate TSMs before expensive first-principles or experimental validation. Representative TXL-prioritized candidates were subsequently supported by density functional theory (DFT) calculations, demonstrating the practical value of the framework for reducing discovery cost. By uniting symbolic chemical rules, statistical learning, and
language-based representations, TXL Fusion provides a scalable and interpretable strategy for accelerating the discovery of next-generation topological and
quantum materials.
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All authors Arif Ullah, Rajibul Islam, Yangming Huang, Ghulam Hussain, Zahir Muhammad, Xiaoguang Li, Ming Yang
Quantum Gases
Fast Transport of Trapped Ultracold Atoms Using Shortcuts-to-Adiabaticity by Counterdiabatic Driving
Denuwan Vithanage, Skyler Wright, Edith Luveina-Joseph et al. (+2 more)
We numerically study the fast spatial transport of a trapped Bose-Einstein condensate (BEC) using shortcuts-to-adiabaticity (STA) by counterdiabatic driving (CD). The trapping potential and the required auxiliary potential were simulated as painted potentials. We compared STA transport to transport that follows a constant-acceleration scheme (CA). Experimentally feasible values of trap depth and atom number were used in the 2D Gross-Pitaevskii equation (GPE) simulations. Different transport times, trap depths, and trap lengths were investigated. In all simulations, there exists a minimum amount of time necessary for fast transport, which is consistent with previous results from
quantum speed limit studies.
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All authors Denuwan Vithanage, Skyler Wright, Edith Luveina-Joseph, Christopher Larson, Edward Carlo Samson
Materials Science
KAN-Enhanced Contrastive Learning Accelerating Crystal Structure Identification from XRD Patterns
Chenlei Xu, Tianhao Su, Jie Xiong et al. (+6 more)
Accurate determination of
crystal structures is central to materials science, underpinning the understanding of composition-structure-property relationships and the discovery of new materials. Powder X-ray diffraction is a key technique in this pursuit due to its versatility and reliability. However, current analysis pipelines still rely heavily on expert knowledge and slow iterative fitting, limiting their scalability in high-throughput and autonomous settings. Here, we introduce a physics-guided contrastive learning framework termed as XCCP. It aligns powder diffraction patterns with candidate
crystal structures in a shared
embedding space to enable efficient structure
retrieval and
symmetry recognition. The XRD encoder employs a dual-expert design with a Kolmogorov-Arnold Network projection head, one branch emphasizes low angle reflections reflecting long-range order, while the other captures dense high angle peaks shaped by
symmetry. Coupled with a
crystal graph encoder, contrastive pretraining yields physically grounded representations. XCCP demonstrates strong performance across tasks, with structure
retrieval reaching 0.89 and space group identification attains 0.93 accuracy. The framework further generalizes to compositionally similar multi principal element
alloys and demonstrates zero-shot transfer to experimental patterns. These results establish XCCP as a robust, interpretable, and scalable approach that offers a new paradigm for X-ray diffraction analysis. XCCP facilitates high-throughput screening, rapid structural validation and integration into autonomous laboratories.
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All authors Chenlei Xu, Tianhao Su, Jie Xiong, Yue Wu, Shuya Dong, Tian Jiang, Mengwei He, Shuai Chen, Tong-Yi Zhang
Disordered Systems and Neural Networks
Enhanced stochasticity in irradiated vanadium oxide oscillators
Nareg Ghazikhanian, David J. Alspaugh, Pavel Salev et al. (+3 more)
Insulator-to-metal transition materials are highly sensitive to even minute deviations of stoichiometry,
lattice defects, and disorder, which provides opportunities to engineer their electrical switching characteristics. Using V2O3 as a prototypical metal-
insulator transition resistive switching material, we demonstrate that localized focused ion beam irradiation can induce
stochastic oscillatory dynamics in simple two-terminal switching devices. After irradiating the material, we observed an unusual dynamic regime where the voltage induced metallic state momentarily collapses into an insulating state, which results in a rapid current flickering that is qualitatively different from the conventional current spiking in a Pearson-Anson type oscillatory
circuit implemented using the pristine material. Furthermore, the current flickering timing in the irradiated devices becomes progressively more random and more sparse with increasing input voltage, resulting in nonlinear and nondeterministic oscillatory behavior. The irradiation also leads to a dramatic reduction in switching power required to induce the current oscillations. These results are elucidated through random resistor network simulations which indicate that a small number of local sites can control the electrical metal-
insulator transition switching properties in large devices with high defect concentration. Our results show that selective focused ion beam irradiation provides exciting prospects for engineering and tuning novel
stochastic behaviors in emergent technologies that rely on the intrinsic randomness of physical processes.
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All authors Nareg Ghazikhanian, David J. Alspaugh, Pavel Salev, Lorenzo Fratino, Marcelo J. Rozenberg, Ivan K. Schuller
Strongly Correlated Electrons
Experimental confirmation of the magnetic ordering transition induced by an electronic structure change in the metallic triangular antiferromagnet Co$_{1/3}$TaS$_2$
Han-Jin Noh, En-Jin Cho, Byeong-Gyu Park et al. (+6 more)
We report ARPES studies combined with DFT+DMFT calculations to confirm that the
magnetic ordering vector transition from Q=(1/2,0,0) to Q=(1/3,0,0) in the metallic triangular antiferromagnets Co$_{1/3\pm\epsilon}$TaS$_2$ ($\epsilon\approx$0.007) is induced by the electronic structure change in the system. The ARPES-measured
Fermi surface (FS) maps of Co$_{0.325}$TaS$_2$ show two hexagonal and one circular hole-like FSs around $\Gamma$, which matches well with the triple-Q state by taking into account the contribution of nesting vectors occurring between Co 3$d$ and Ta 5$d$ orbitals. In the case of Co$_{0.340}$TaS$_2$, a new electron pocket around K appears and the FS geometry changes as a result of the correlation effect of Co$_4$S$_{18}$ tripods forming in the system. The
magnetic susceptibility calculations based on the charge-self-consistent DFT+DMFT band structures and the random phase approximation indicate that the most stable
magnetic ordering vector (1/2,0,0) split into (1/6,0,0) and (1/2,0,0), which is consistent with the
magnetic phase transition around $x$=1/3 in Co$_{x}$TaS$_2$.
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All authors Han-Jin Noh, En-Jin Cho, Byeong-Gyu Park, Hyowon Park, Ivar Martin, Cristian D. Batista, Pyeongjae Park, Woonghee Cho, Je-Guen Park
Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
Multi-Directional Periodic Driving of a Two-Level System beyond Floquet Formalism
Michael Warnock, David A. Hague and Vesna F. Mitrovic
In this manuscript, we introduce an exact expression for the response of a semi-classical two-level
quantum system subject to arbitrary periodic driving. Determining the transition probabilities of a two-level system driven by an arbitrary periodic waveform necessitates numerical calculations through methods such as Floquet theory, requiring the truncation of an infinite
matrix. However, such truncation can lead to a loss of significant interference information, hindering
quantum sensors or introducing artifacts in
quantum control. To alleviate this issue, we use the $\star$-resolvent formalism with the path-sum
theorem to determine the exact series solution to Schrödinger's equation, therefore providing the exact transition probability. The resulting series solution is generated from a compact kernel expression containing all of the information of the periodic drive and then expanded in a non-harmonic
Fourier series basis given by the divided difference of complex exponentials with coefficients corresponding to products of generalized Bessel functions. The present method provides an analytical formulation for
quantum sensors and control applications.
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Mesoscale and Nanoscale Physics
Thermal hot-carrier breakdown in metasurface structures based on coplanar arrays of graphene microribbons connected with wide-gap bridges
V. Ryzhii, M. Ryzhii, M. S. Shur et al. (+2 more)
We analyze the thermal and electrical characteristics of the metasurface consisting of the coplanar interdigital array of the
graphene microribbons (GMRs) connected by nanobridges (NBs). These nanobridges could be implemented using
graphene nanoribbons (GNRs), single-wall semiconducting carbon nanotubes (CNTs), or black-arsenic-phosphorus (b-AsP) nanostructures. The bias voltage applied between neighboring GMRs indices electron and hole two-dimensional systems in the GMRs and induces thermionic currents flowing through connecting NBs. The resulting self-heating increases thermionic currents providing an effective positive feadback between the carrier effective temperature and the injected currents. This mechanism may lead to thermal breakdown enabling threshold behavior of current-voltage characteristics and resulting in the S-shape of these characteristics. The devices based on the GMR/GNR, GMR/CNT, and GMR/AsP metasurface structures can be used as fast voltage-controlled current switches, sensors, thermal terahertz and infrared sources, and other devices.
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All authors V. Ryzhii, M. Ryzhii, M. S. Shur, T. Otsuji, C. Tang
Materials Science
All-optical magnetization reversal via x-ray magnetic circular dichroism
Kihiro T. Yamada, Akira Izumi, Tetsuya Ikebuchi et al. (+15 more)
Light polarization is one of the most fundamental features, equivalent to energy and coherence. Magnetism changes light polarization, and vice versa. The irradiation of intense circularly polarized femtosecond pules to
magnetic materials can alter the
magnetic orders and elementary excitations, particularly in the visible to infrared spectral regions. Furthermore, the recent development of x-ray free-electron
laser enables the element-specific trace of the ultrafast dynamics with high time and spatial resolution. However, the light helicity of x-ray
photons has not yet been used to control order parameters in condensed matter materials, not limited to such
magnetic phenomenon. Here, we demonstrate the deterministic magnetization reversal of a
ferromagnetic Pt/Co/Pt multilayer solely by irradiating femtosecond pulses of circularly polarized hard x-rays. The observed all-optical magnetization switching depends on the helicity of incident x-ray pulses and is strongly resonant with the
photon energy at the Pt $L_3$ edge. These results originate in the x-ray
magnetic circular dichroism of Pt, involving helicity-dependent excitation from the 2$p_{3/2}$ core level to the exchange-split 5$d$ valence states owing to the
magnetic proximity effect with Co. These findings mark a new frontier for examining interactions between light and matter in the x-ray region.
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All authors Kihiro T. Yamada, Akira Izumi, Tetsuya Ikebuchi, Sumiyuki Okabe, Masaki Kubo, Ryusei Obata, Rei Kobayashi, Yuya Kubota, Takuo Ohkochi, Naomi Kawamura, Kotaro Higashi, Yoichi Shiota, Takahiro Moriyama, Teruo Ono, Iwao Matsuda, Tadashi Togashi, Yoshihito Tanaka, Motohiro Suzuki
Strongly Correlated Electrons · Cross-listed from quant-ph
Noninvertible Kramers-Wannier duality symmetries for the discrete-time quantum Ising chain
Akash Sinha, Pramod Padmanabhan and Vladimir Korepin
Integrable trotterization} provides a method to evolve a continuous time integrable many-body system in discrete time, such that it retains its conserved quantities. Here we explicitly show that the first order trotterization of the critical transverse field Ising model is integrable. The discrete time conserved quantities are obtained from an inhomogeneous transfer
matrix constructed using the
quantum inverse scattering method. The inhomogeneity parameter determines the discrete time step. We then focus on the non-invertible Kramers-Wannier duality-
symmetry for the trotterized
evolution. We find that the discretization of both space and time leads to a doubling of these duality operators. They account for discrete translations in both space and time. As an interesting application, we find that these operators also provide maps between trotterizations of different orders. This helps us extend our results beyond the trotterization scheme and investigate the Kramers-Wannier duality-
symmetry for finite time Floquet
evolution of the critical transverse field Ising chain. {Finally, we investigate how these non-invertible operators shape the phase diagram of the discrete-time
evolution. This question is particularly interesting in the Floquet setting, which is known to host a richer phase structure than its undriven counterpart. We systematically construct the necessary operators which relate different phases away from criticality for both trotterized and Floquet evolutions.
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Materials Science · Cross-listed from physics.ins-det
Robust electron counting for direct electron detectors with the Back-Propagation Counting method
Joshua Renner, Matthew A. Wright, Kristofer Bouchard et al. (+6 more)
Electron microscopy (EM) is a foundational tool for directly assessing the structure of materials. Recent advances in direct electron detectors have improved signal-to noise ratios via single-electron counting. However, accurately counting electrons at high fluence remains challenging. We developed a new method of electron counting for direct electron detectors, Back-Propagation Counting (BPC). BPC uses machine learning techniques designed for mathematical operations on large tensors but does not require large training
datasets. In synthetic data, we show BPC is able to count multiple electron strikes per pixel and is robust to increasing occupancy. In experimental data, frames counted with BPC are shown to reconstruct diffraction peaks corresponding to individual nanoparticles with relatively higher intensity and produce images with improved contrast when compared to a standard counting method. Together, these results show that BPC excels in experiments where pixels see a high flux of electron irradiation such as in situ TEM movies and diffraction.
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All authors Joshua Renner, Matthew A. Wright, Kristofer Bouchard, Bruce E. Cohen, Peter Ercius, Azriel Goldschmidt, Cassio C.S. Pedroso, Ambarneil Saha, Peter Denes