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Physics Condensed Matter

cond-mat Watch Condensed Matter

Tuesday 9 June

Strongly Correlated Electrons

Supermoiré Chern mosaic in helical trilayer WSe2

Zhenyu Wang, Mingjie Zhang, Hai Meng et al. (+19 more)

Helically twisted multilayers offer access to moiré physics beyond the single-superlattice paradigm, yet their correlated and topological transport properties remain largely unexplored in semiconductor moiré materials. Here we report magnetotransport measurements of helical trilayer WSe2, in which two coupled moiré patterns relax into a supermoiré landscape composed of inequivalent local topological domains with distinct electronic structures and unequal spatial areas. By electrostatic tuning, we identify a trilayer-hybridized regime where interactions and real-space reconstruction combine to generate a plethora of magnetic and topological states absent in the twisted bilayers. At moiré filling factor $\nu$ = -1, we observe a ferromagnetic insulating state that is robust against magnetic field and accompanied by a non-quantized anomalous Hall response ~-4 kOhms. This behaviour is consistent with a time-reversal-symmetry-breaking supermoiré Chern mosaic, in which the Hall response arises from the non-cancelling contributions of local domains with opposite Chern character arranged by the relaxed structure. Under strong magnetic fields, a symmetry-broken Chern insulating state (C = 1) emerges near $\nu$ = -2/3, displaying a much larger positive Hall response together with strongly enhanced longitudinal resistance, suggestive of field-reconstructed topological minibands and domain-boundary scattering. These results establish relaxed supermoiré semiconductor trilayers as a platform for spatially organized magnetism and topology beyond the bilayer limit.
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All authors Zhenyu Wang, Mingjie Zhang, Hai Meng, Xiuzhen Li, Subi Du, Yaotian Liu, Siyu Fan, Xiaofan Shi, Kenji Watanabe, Takashi Taniguchi, Wei Yang, Guangyu Zhang, Bingbing Tong, Guangtong Liu, Li Lu, Jie Shen, Gang Li, Jing Song, Enke Liu, Song Liu, Fengcheng Wu, Yang Xu

Superconductivity

Superheating field of clean superconductors near the type-I–type-II boundary: the low-temperature Meissner stability limit of niobium

Takayuki Kubo

We calculate the low-temperature superheating field $B_{\rm sh}$ of clean superconductors near the boundary between type-I and type-II superconductivity, with particular emphasis on Nb. Ginzburg–Landau theory is not applicable at low temperatures, while previous microscopic calculations have been limited to either the large-$\kappa$ regime or the dirty limit. The clean, low-$\kappa$ regime relevant to Nb has therefore remained unresolved. We solve the self-consistent nonlinear nonlocal Eilenberger problem for the Meissner state and then analyze its stability against small perturbations. For a Nb-like material with $\kappa_{\rm GL}=0.7$, we obtain $B_{\rm sh}\simeq 290\,{\rm mT}$ at $T/T_c=0.2$, using $B_{c0}\simeq 200\,{\rm mT}$. For a TESLA-shaped Nb accelerator cavity, this corresponds to an intrinsic Meissner-stability limit of about $67\,{\rm MV/m}$.
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Strongly Correlated Electrons

Antiferromagnetic order and magnetic polarons in lightly doped Li$_x$CoO$_2$ (x $\sim$ 0.9)

Sudip Pal, Pampa Sadhukhan, Waqar Suleman et al. (+2 more)

We investigate the magnetic properties of Li$_x$CoO$_2$ (x$\sim$0.9) using bulk magnetization, specific heat, nuclear magnetic resonance (NMR) and electron paramagnetic resonance (EPR) spectroscopy measurements. The dc magnetization, specific heat and NMR measurements, which probe the macroscopic response, indeed show that this compound partially undergoes an antiferromagnetic transition below $T_N \sim$ 10 K. In addition, we observed a weak ferromagnetic response, which gives rise to the history dependence in magnetization measurements at low fields and is observed at temperatures above room temperature. We propose that there are ferromagnetic clusters at high temperatures due to the formation of magnetic polarons out of doped holes. In EPR measurements performed at the $X$-band frequency, only a fraction of the total spins contribute and show Curie-like paramagnetic behavior as reflected in the temperature dependence of the EPR intensity. The temperature variation of the EPR spectra can be understood in the framework of the diffusion of magnetic polarons.
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All authors Sudip Pal, Pampa Sadhukhan, Waqar Suleman, Andrej Pustogow, S. B. Roy

Mesoscale and Nanoscale Physics

Higher-winding phases in one-dimensional non-Hermitian topological superconductors

Yung-Yeh Chang, Xiang-Yu Li, Ken Shiozaki et al. (+1 more)

Non-Hermitian topological superconductors provide a setting in which point-gap topology, non-Hermitian skin effects, and Majorana zero modes are strongly intertwined. In this work, we adopt a coefficient-based approach for computing winding numbers and deriving analytical expressions for phase boundaries in one-dimensional non-Hermitian topological superconductors characterized by point-gap topology with $\mathbb{Z}$ invariants. We apply this approach to two non-Hermitian topological superconducting lattice models, with and without sublattice degrees of freedom, including longer-range hoppings, thereby accessing a much broader parameter space. These extensions generate higher-order polynomials and support phases with higher winding numbers, reflecting the underlying $\mathbb{Z}$ topology. We further clarify how a weak perturbation suppresses the non-Hermitian skin effect while preserving the sublattice-symmetry-protected invariant associated with Majorana zero modes. The predicted winding numbers are verified by open-boundary spectra, where one or multiple pairs of zero-energy boundary modes appear consistently with the bulk invariant. We also examine the stability of these modes against onsite disorder by examining the zero-mode energy, the bulk gap, and the inverse participation ratio. Our results provide a systematic and efficient route to constructing topological phase diagrams for higher-winding non-Hermitian topological superconductors.
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All authors Yung-Yeh Chang, Xiang-Yu Li, Ken Shiozaki, Chen-Hsuan Hsu

Strongly Correlated Electrons

Improved selector behavior in ultrathin chromium-doped V$_2$O$_3$ films

Johannes Mohr, Tyler Hennen, Yudi Wang et al. (+6 more)

Devices based on the negative differential resistance effect in chromium doped V$_2$O$_3$ are considered to be promising as selector elements for use in emerging memory technologies, as well as for neuromorphic applications. It is shown by electrical measurements, that the switching effect is maintained for very thin films down to 5 nm, and even improved properties such as a low leakage current and an abrupt transition are observed. For these thicknesses, the behavior of crystalline and amorphous films becomes very similar; most strikingly, a forming step is required in both. Transmission electron microscopy reveals this to be likely due to a thin amorphous layer that forms at the interface to the TiN electrode. Elemental mapping further shows a complex distribution of the chromium dopants, as well as a diffusion of Ti into the layer from the electrode, which might be responsible for the improved properties.
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All authors Johannes Mohr, Tyler Hennen, Yudi Wang, Xiaoyu Xu, Loc Vinh, Dirk J. Wouters, Rainer Waser, Joyeeta Nag, Daniel Bedau

Materials Science

Neural electron backscatter diffraction

I-Tzu Huang and Marat I. Latypov

At the mesoscale, the state of a material is described by continuous fields. In polycrystals, crystallographic orientation and defect content vary continuously within grains, and grain boundaries trace continuous curves. Like other spatially resolved characterization methods, electron backscatter diffraction (EBSD) records this continuum on a discrete grid. Every subsequent analysis inherits the grid, whether it is classical Hough indexing or pattern-based machine learning. We introduce neural EBSD, which treats a scan as a continuous and differentiable field of Kikuchi diffraction intensity over specimen and detector coordinates. Two formulations are explored: a joint network over all four coordinates, and a factorized representation that combines continuous specimen-domain coefficient fields with learned detector-domain basis patterns. The factorized formulation exhibits higher accuracy: for recrystallized and additively manufactured Ni-base superalloys, it reconstructs 900,000 Kikuchi patterns per map with mean errors below 1% of the maximum intensity, while reducing data storage nearly 750-fold relative to the raw patterns. Since the learned field is continuous, patterns can be queried at any specimen position. Trained only on a quarter of the scan points, the model recovers withheld patterns whose indexed orientations fall within 4 deg. of reference at 97% of positions in the recrystallized alloy. Analytical spatial derivatives of the differentiable representation provide a diffraction gradient that localizes grain boundaries continuously, free of indexing, disorientation thresholds, and staircase artifacts. The gradient field also exposes intragranular heterogeneity, including dislocation-cell substructure in the as-built alloy.
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Disordered Systems and Neural Networks

Magnetic HIP-NN for spin dynamics in disordered itinerant magnets

Supriyo Ghosh, Yunhao Fan, Sheng Zhang et al. (+2 more)

We present a magnetic extension of the Hierarchically Interacting Particle Neural Network (HIP-NN) that enables large-scale simulations of electron-mediated spin dynamics in disordered itinerant magnets. The resulting magnetic HIP-NN (mHIP-NN) incorporates rotationally invariant spin correlations directly into hierarchical message-passing layers, enabling the network to learn emergent magnetic energy landscapes and effective local fields from coupled geometric-spin environments while preserving spin-rotation symmetry. As a benchmark application, we consider structurally disordered itinerant $s$-$d$ exchange models in which the effective magnetic forces arise dynamically from the instantaneous electronic structure and are computationally prohibitive to evaluate using conventional exact-diagonalization-based approaches. We show that mHIP-NN accurately reproduces the local torques governing Landau-Lifshitz-Gilbert dynamics and faithfully captures the nonequilibrium evolution of spatial spin correlations following thermal quenches. Our results establish symmetry-aware hierarchical message-passing networks as an efficient and scalable framework for large-scale simulations of frustrated itinerant spin systems and nonequilibrium magnetic dynamics. More broadly, because the learned energy functional remains fully differentiable with respect to both atomic coordinates and spin variables, the framework also provides a natural foundation for spin-dependent interatomic potentials and coupled atom-spin dynamics.
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All authors Supriyo Ghosh, Yunhao Fan, Sheng Zhang, Kipton Barros, Gia-Wei Chern

Statistical Mechanics · Cross-listed from cs.LG

Rank Collapse, Fixed Points, and the Renormalization Group Structure of MLP Residual Networks

Parviz Haggi-Mani and Irina Rish

The analogy between deep neural network forward passes and renormalization group (RG) flows has been repeatedly noted in the literature, but existing treatments remain qualitative: depth is described as a coarse-graining scale, attention is likened to a partition function, and representations are said to flow toward fixed points. No existing work has defined a measurable RG order parameter, tested it under controlled variation of the input distribution, or made quantitative predictions that are empirically verified. We study the simplest architecture for which the analogy is tractable: a pure MLP residual stack trained on masked token prediction over synthetic Markov chain sequences with known spectral properties. We report three findings. (i) The effective rank of the residual stream decreases monotonically with depth after training, consistent with progressive integration of irrelevant degrees of freedom. (ii) This rank collapse is selective: it occurs for chains with short correlation length approximately 1 but is absent for chains with long correlation length approximately 7, measured at the position level to control for mean-pooling artifacts. The network preserves exactly the degrees of freedom relevant to the prediction task, the content of the RG relevance criterion. (iii) Inter-layer kernel drift is concentrated at one or two specific transitions, with the remainder of the network near a fixed point, consistent with a discrete fixed-point plateau. Together these findings constitute the first quantitative, position-level evidence that MLP residual networks implement a selective coarse-graining procedure governed by the spectral structure of the input distribution.
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Superconductivity

Vortex pinning of Ba$_{0.62}$K$_{0.38}$BiO$_3$ investigated by magneto-optical Kerr-effect and magnetization measurements

Soichiro Yamane, Sota Nakamura, Atsutoshi Ikeda et al. (+8 more)

Vortex pinning plays a crucial role in determining properties of type-II superconductors. For example, it governs the irreversible magnetic response as well as dissipation caused by vortex motion. Here, we study vortex pinning in the three-dimensional oxide superconductor Ba1-xKxBiO3 using ultra-high-resolution magneto-optical Kerr effect (MOKE) and detailed magnetization measurements. We find that the zero-field MOKE signal in the superconducting state exhibits a pronounced magnetic-history dependence. This behavior closely resembles the remanent magnetization caused by trapped vortices. Furthermore, we demonstrate that the observed evolution of the MOKE signals is well described by Bean's critical-state model for trapped vortices. Our results establish MOKE as a viable optical and mesoscopic probe of vortex pinning in type-II superconductors, providing a new complementary approach to investigate mixed-state phenomena. We also find that the training-field dependence of the MOKE is linear near zero training field, without any anomalies indicative of spontaneous time-reversal-symmetry breaking in an unconventional superconducting state. Our study defines a clear protocol to distinguish vortex-induced MOKE responses from those associated with a time-reversal-symmetry broken superconducting order parameter.
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All authors Soichiro Yamane, Sota Nakamura, Atsutoshi Ikeda, Dayu Zhai, Siddarth Gorregattu, Xing He, Sudarshan Sharma, Yipeng Cai, Yasutomo J. Uemura, Martin Greven, Shingo Yonezawa

Other Condensed Matter · Cross-listed from physics.optics

Unidirectional-like Edge Transport Induced by Non-Hermitian Skin Effects

Junyi Rao, Jinting Ding, Qinghua Guo et al. (+2 more)

Non-Hermitian skin effects (NHSEs) enable dramatic boundary accumulation of waves, yet their experimental realization typically demands engineered nonreciprocity or spatially patterned loss. Here we demonstrate theoretically and experimentally that uniform loss provides a simple and previously overlooked mechanism for enforcing unidirectional-like edge transport in photonic crystals (PhCs) that breaks time-reversal symmetry in the presence of nonchiral edge states. Using a core cladding geometry where domains share identical Chern numbers but possess distinct bulk polarizations, we show that uniform loss activates NHSEs that reshape the spectral topology of edge bands, giving rise to point gap windings that dictate a one way propagation. Near field measurements confirm that loss converts intrinsically bidirectional interface states into a unidirectional-like circulation around the entire domain wall, showing excellent agreement with theory. Our results establish uniform loss as a universal and structurally simple route for achieving unidirectional-like wave transport.
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All authors Junyi Rao, Jinting Ding, Qinghua Guo, Jun He, Xiang Ni

Materials Science · Cross-listed from physics.app-ph

Filamentary Transport and Thermoelectric Effects in Mushroom Phase Change Memory Cells

Md Samzid Bin Hafiz, Helena Silva and Ali Gokirmak

We performed a 2D finite-element electrothermal computational study of thermoelectric effects and filamentary electronic transport in Ge$_2$Sb$_2$Te$_5$ mushroom phase change memory cells during Reset and Set operations, accounting for spatial activation energy variations in amorphous Ge$_2$Sb$_2$Te$_5$ and phase-change dynamics. Reset operations with current going from the top electrode to the narrow 4 nm bottom electrode require $\sim$3x less energy and power, and $\sim$2x lower current to achieve the same Reset resistance, compared to the opposite polarity, due to thermoelectric effects. Filamentary conduction, electrical breakdown, thermal runaway, and local crystallization of amorphous Ge$_2$Sb$_2$Te$_5$ depend on current polarity and thermal boundary conditions, and determine the location, shape, and volume of the programming region, which may be significantly smaller than the semi-cylindrical mushroom region. The programming volume does not scale with contact dimensions larger than 10 nm. Larger contact areas introduce increased device-to-device and cycle-to-cycle variability due to filamentary conduction but are expected to lead to higher reliability and endurance.
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Monday 8 June

Materials Science · Cross-listed from physics.soc-ph

The Sustainability Paradox of Biodegradable Packaging: A Life Cycle Perspective on Chitosan-Based Food Packaging

Maria Cosic, Milena Cosic, Amy Kim et al. (+9 more)

Chitosan-based nanomaterials are being increasingly explored as sustainable alternatives to petroleum-derived food packaging, yet their environmental performance across the full life cycle remains insufficiently understood. This review critically evaluates these systems from a life cycle perspective and examines how material origin, processing pathways, functional performance, and end-of-life behavior collectively influence sustainability outcomes. Beginning with chitin extraction from crustacean waste, key processing steps, including demineralization, deproteinization, and nanoparticle synthesis, are assessed in terms of chemical intensity, energy demand, and associated emissions. Manufacturing routes, including solvent-based and green synthesis approaches, are compared with those of conventional plastics to identify relative environmental burdens. The use phase is analyzed with respect to antimicrobial functionality, shelf life extension, and potential reductions in food waste. End-of-life pathways, including biodegradation and composting, are evaluated alongside uncertainties related to degradation behavior and nanoparticle fate. By synthesizing these stagewise interactions, this review highlights critical trade-offs that are often overlooked in sustainability narratives and examines whether chitosan-based nanomaterials provide net environmental benefits in food packaging applications.
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All authors Maria Cosic, Milena Cosic, Amy Kim, Siddhartha Pahari, Grace Wu, Rayna Zhou, Trisha Daftari, Shaily Gupta, Reyna Michelle Suneel, Srinivasan Latha, Rashi Sharma, Utkarsh Chadha

Soft Condensed Matter

Inverse Laplace Transform for Dynamic Light Scattering: Impact of Regularization

Pierre Pajuelo, Stéphane G. Roux, Adrien Meynard et al. (+3 more)

Dynamic Light Scattering (DLS) analyzes particle dynamics from the autocorrelation functions of scattered light intensity, yet extracting accurate relaxation time distributions from noisy data is challenging. We develop an inverse problem approach to recover this distribution by inverting the Laplace transform with physics-based regularization, called the CONTIN method. We improve it to use it on noisy data, across a wide range of time scales, with a selection of the regularization strength through a data-driven L-curve criterion. Our approach enhances robustness under high noise and reveals multi-scale dynamics in complex systems. Validation is performed on simulated data, compared to the Cramér-Rao bound and to parametric methods, and on experimental data from Carbopol microgels. It demonstrates superior accuracy over parametric methods, especially for broad time distributions. The algorithm's logarithmic discretization and variance-reduced correlation estimation enhance performance, offering a powerful tool for non-parametric DLS analysis and deeper insights into soft matter dynamics.
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All authors Pierre Pajuelo, Stéphane G. Roux, Adrien Meynard, François Liénard, Éric Freyssingeas, Pierre Borgnat

Statistical Mechanics

Numerical simulations of the spread from the mean of the SLE and Multiple SLE dynamics

Phillip Kim and Vlad Margarint

The Schramm-Loewner Evolution (SLE) describes a family of fractal curves that arise in the study of the scaling limits of many planar Statistical Physics models. These curves are modeled using the Loewner Differential Equation for the conformal maps $g_t(z)$ with a Brownian motion driver. Using Euler's Method, in the current work we performed numerical experiments to study at a fixed time the quantities $|g_t(z) - \overline{g_t(z)}|$ and $Re(g_t(z)) - Re(\overline{g_t(z)})$, where $Re$ denotes the real part and $\overline{g_t(z)}$ refers to the sample average. These random variables measure the 'spread' of the dynamics from the average behavior at fixed time. One of the scopes of this work is to give numerical predictions for future theoretical investigations on these quantities. When investigating these quantities in the SLE case our experiments predict that the distribution is bimodal when the dynamics started close to the origin, and it can become bell-shaped if the dynamics is started further from the origin. In the second part, we performed experiments for a Multiple SLE model whose driver is Dyson Brownian Motion. Due to singularity in the dynamics of the drivers and the many data points needed, this part is challenging from a computational perspective. In the multiple SLE case, our experiments predict that the distribution is bell-shaped in all cases. In addition, we check the changes in the distributions as we vary the parameter $\kappa$ in the SLE case and $\beta$ in the Multiple SLE case.
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2606.11254 · 8 Jun · Note that an updated version of this paper is officially published in the Journal Research in Statistics (2026 Vol 4 Issue 1) that has more updated experiments and discussions. That version is also open access under the Creative Commons Attribution License. It is availabe at https://doi.org/10.1080/27684520.2026.2648957

Abstract PDF $EVO ×1

Strongly Correlated Electrons

Coherent manipulation of Kondo Majoranas in two-channel Kondo setups

Yashar Komijani and C. J. Bolech

We study coherent manipulation of Majorana zero modes emerging in overscreened two-channel Kondo systems. Using compactified lattice models, we show that these interacting Kondo Majoranas support non-local qubits and admit teleportation, fusion, and braiding operations. In particular, we identify a distinction between non-topological and genuinely topological Y-junction geometries, the latter realizing a non-Abelian geometric holonomy. Our results establish a proof-of-principle route toward coherent control of non-Abelian anyons beyond conventional free-fermion platforms.
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Materials Science

Robust AI-Driven Discovery of Electronic Metal Phosphide Semiconductors

Benhao Zhu, Muhammad Faizan, Zewei Li et al. (+4 more)

Metal phosphides have diverse bonding motifs and coordination environments, making them promising for optoelectronic and thermoelectric applications, but their chemical space remains underexplored. Here we report an AI-driven high-throughput discovery workflow that combines generative materials design, machine-learning interatomic potentials, and targeted density functional theory (DFT) calculations. ICSD-derived Wyckoff-site substitution and MatterGen-based conditional structure generation are used to expand the candidate space beyond existing phosphide databases. A domain-finetuned DPA3 machine-learning potential then enables efficient prescreening of thermodynamic and dynamical stability before DFT validation. This workflow identifies 3,574 previously unreported stable phosphide structures, including 196 semiconductors with HSE06 band gaps of 0-3.0 eV. By screening these new semiconductors together with experimentally known phosphide semiconductors, we identify 30 promising optoelectronic candidates and 26 promising thermoelectric candidates, including seven newly discovered optoelectronic materials and eight newly discovered thermoelectric materials. These results provide a candidate pool for experimental synthesis and show that combining generative AI with machine-learning interatomic potentials can accelerate the discovery of functional semiconductor materials.
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All authors Benhao Zhu, Muhammad Faizan, Zewei Li, Wenshuo Li, Feifei Ren, Jiahao Xie, Lijun Zhang

Disordered Systems and Neural Networks · Cross-listed from q-bio.NC

Multifractal Signatures of Ageing and Dementia Development: A Multifractal Space-Filling Curve Analysis

Marta Lotka, Jacek Grela, Zbigniew Drogosz et al. (+2 more)

Multifractality is an effective formalism for quantifying the nonlinear, scale-free properties of complex data. In this study, we propose a novel and efficient methodology, termed Multifractal Space-filling Curve Analysis (MFSCA), for quantifying the correlation structure of multidimensional data. Within this framework, the original multidimensional data - while preserving both local and long-range organisational properties - are projected onto a one-dimensional representation using a fractal space-filling curve. The resulting one-dimensional signal is then analysed using multifractal algorithms. We demonstrate the utility of the method using both artificially generated multifractal structures and real data. In particular, we apply MFSCA to analyse magnetic resonance imaging (MRI) data from Alzheimer patients at different stages of dementia. Based on the results, we estimate the multifractal profiles of the brain for healthy subjects of different ages as well as for dementia patients. The analysis reveals that the spatial organization of brain structures, as measured by the degree of multifractality, progressively weakens with age and the development of dementia. A transition from multifractality to monofractality is observed both in control groups, when comparing the Young Control and Elderly Control groups, and among dementia subjects of similar age but at different stages of the disease, namely early dementia and mild cognitive impairment. Thus, from the perspective of multiscaling properties, the heterogeneous characteristics of spatial brain organization deteriorate under worsening conditions, leading to a homogeneous and weakly correlated structure. These findings not only effectively capture key aspects of brain organisation, but also demonstrate that the multifractality of MRI data can serve as a marker of structural brain changes.
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All authors Marta Lotka, Jacek Grela, Zbigniew Drogosz, Jeremi K. Ochab, Paweł Oświęcimka

Materials Science

Finite-temperature Fe K-edge X-ray absorption simulations reveal local structural dynamics of an iron(II) photosensitizer in solution and the crystalline phase

Patrick Müller, Lorena Fritsch, Matthias Bauer et al. (+1 more)

Interpreting metal K-edge spectra of flexible photosensitizers requires a structural model that separates electronic signatures from thermal motion, solvent disorder, and crystal-packing effects. We combine Fe K-edge X-ray absorption measurements with second-generation Car–Parrinello ab initio molecular dynamics and all-electron Gaussian and augmented-plane-wave simulations for an iron(II) N-heterocyclic carbene photosensitizer in acetonitrile solution and in the crystalline phase. Ensemble-averaged spectra reproduce the main near-edge features in both environments and preserve the experimentally observed similarity of the first Fe coordination shell upon dissolution. Comparison with radial distributions extracted from extended fine-structure measurements validates the Fe–N and Fe–C coordination shells sampled by the trajectories, while element-resolved pair distributions explain why higher-shell experimental contrast is rapidly lost. The same dynamical ensembles reveal a broad out-of-plane distribution of the terpyridine nitrogen atom and a nearly octahedral distribution of the Fe-centered coordination planes. The results show that finite-temperature X-ray absorption simulations can provide a compact structural-dynamics picture of molecular transition metal photosensitizers by linking local spectra, solvent-phase ligand motion, and medium-range structural disorder within one trajectory-based description.
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All authors Patrick Müller, Lorena Fritsch, Matthias Bauer, Thomas D. Kühne

Materials Science

Graphlet Histogram Representation Database of Inorganic Crystals

Aaditya Panigrahi, Yanjun Liu, Omri Lesser et al. (+2 more)

Machine learning models for materials property prediction increasingly rely on representations learned end-to-end from large density-functional-theory databases, limiting their applicability when only scarce experimental data are available. Domain-knowledge-driven representations precomputed from crystal structures alone offer a data-efficient, interpretable alternative, but existing approaches capture at most composition or bonding connectivity and discard local structural geometry. Here, we present Graphlet-MP, a database of graphlet histogram representations for 149,082 inorganic crystals from the Materials Project (MP). Seventy-nine distributions describe each material over three hierarchical graphlet orders: atomic sites, bonded pairs, and bond-angle triplets, extracted via screened Voronoi tessellation from the crystallographic information file. We provide a complete technical specification of the representation, an Earth Mover's Distance metric for comparing materials in this space, and the full precomputed database. An accompanying open-source codebase enables users to generate graphlet histograms for arbitrary crystal structures, including experimentally determined ones, and to extend the database to new materials or target properties.
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All authors Aaditya Panigrahi, Yanjun Liu, Omri Lesser, Krishnanand Mallayya, Eun-Ah Kim

Materials Science

Pressure-Driven Structural Phase Competition and Functional Response in Layered LiInP2S6

Xiaochi Xie, Pegah Mohammadi and Sobhit Singh

Understanding how hydrostatic pressure modifies interlayer interactions and competing ionic configurations is essential for controlling the emergent functional properties of layered quantum materials. Here, using first-principles density-functional theory calculations, we investigate the pressure-dependent structural, mechanical, electronic, and optical properties of three competing LiInP2S6 polymorphs: the monoclinic C2/c phase and the trigonal P-31c phase in both in-layer and in-gap configurations. Our results reveal a pressure-induced structural phase transition from the monoclinic ground-state C2/c phase to a trigonal P-31c in-layer phase at ~0.38 GPa, driven by enhanced interlayer coupling and anisotropic lattice compression. In contrast, the trigonal P-31c in-gap phase remains energetically unfavorable due to its stronger interlayer ionic interactions and reduced compressibility. All phases remain mechanically stable under compression (0-26 GPa) and exhibit enhanced mechanical rigidity, elastic wave velocities, and Debye temperatures with increasing pressure. Remarkably, the electronic and optical properties within each phase remain highly robust under pressure, with only moderate changes in the band gap and optical absorption edge (UV-Visible range) under pressure; however, substantial modifications emerge across the pressure-induced structural phase transition. These findings establish LiInP2S6 as a pressure sensitive ionic-vdW material in which subtle changes in interlayer interactions govern structural stability and functional properties.
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Superconductivity

Microscopic Investigation of the Superconducting State in CuCo$_{2}$S$_{4}$: Evidence for an Intermediate-Coupling Fully Gapped Superconductor

K. Panda, A. Bhattacharyya, Liang-Wen Ji et al. (+4 more)

The thiospinel compound CuCo$_2$S$_4$ provides an attractive platform for exploring superconductivity in transition-metal chalcogenide spinels. Here, we report the first microscopic investigation of the superconducting state in CuCo$_2$S$_4$ using muon spin rotation and relaxation ($\mu$SR) measurements, complemented by magnetization and heat-capacity experiments. The temperature dependence of the superconducting depolarization rate obtained from transverse-field $\mu$SR measurements indicates a fully gapped superconducting order parameter. The extracted gap ratio $2\Delta(0)/(k_{\mathrm{B}}T_\mathrm{SC}) = 3.95(2)$ exceeds the BCS weak-coupling value of 3.53, placing CuCo$_2$S$_4$ in the intermediate electron-phonon coupling regime. Zero-field $\mu$SR measurements were performed to probe possible time-reversal symmetry breaking (TRSB) in the superconducting state. Within the experimental resolution, no additional spontaneous internal magnetic fields are observed below $T_c$. However, due to the presence of a ferromagnetic impurity phase and the associated fast-relaxing signal component, the sensitivity of the present measurements to weak spontaneous fields is reduced. Consequently, while no evidence for TRSB is detected, its existence cannot be definitively ruled out. Overall, our combined thermodynamic and $\mu$SR results demonstrate that CuCo$_2$S$_4$ exhibits a fully gapped superconducting state with intermediate coupling strength, consistent with conventional $s$-wave superconductivity in this cobalt-based thiospinel system.
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All authors K. Panda, A. Bhattacharyya, Liang-Wen Ji, Jing Li, R. Stewart, D. T. Adroja, Guang-Han Cao

Soft Condensed Matter

Beyond the Markovian limit: Exact solutions for active motion in a power-law viscoelastic bath

Mintu Karmakar, Jure Dobnikar and Ignacio Pagonabarraga

Active particles from bacteria to synthetic microswimmers often navigate viscoelastic media with complex relaxation dynamics. The classical active Brownian model that assumes instantaneous friction is clearly not applicable to describe such motility, while the non-Markovian processes combined with viscoelasticity are relatively unexplored. Here, we develop an analytical theory for an active particle in a power-law viscoelastic medium by solving coupled non-Markovian generalized Langevin equations for translational and rotational degrees of freedom. The viscoelastic memory results in novel phenomena such as fractional short-time transport, enhanced long-time persistence, and de-correlation of the instantaneous force and the swimmer orientation. We demonstrate that the memory kernel controls the anomalous scaling exponents, while the activity determines the crossover between sub-diffusive, ballistic and diffusive regimes. Our work provides a framework for theoretical description of biological and synthetic micro swimmers in complex biological and polymeric environments.
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Materials Science

Synthesis and Characterization of Atomically-Sharp Superconductor-Dielectric Interface

Nathan Sitaraman, Zhaslan Baraissov, Alexis Grassl et al. (+4 more)

Modification of superconductor-dielectric interfaces is known to strongly impact coherence times of superconducting quantum devices. This relationship is thought to arise from differences in the concentration of "two-level system" defects in the disordered dielectrics and superconductor-dielectric interfaces; these defects couple to electromagnetic modes in the device and cause dissipation. Zirconium oxide barrier layers on niobium have emerged as a promising pathway to low-loss interfaces in recent years, evidently due to the crystalline nature of these layers in comparison to the amorphous niobium native oxide. We explain the unique ability of zirconium oxide to form a crystalline layer, to maintain a sharp interface with metallic niobium, and to prevent niobium oxide re-growth in terms of the chemical properties of ZrO$_2$ and the Nb-Zr-O ternary system. We demonstrate a new method to grow air-stable zirconium oxide layers on niobium with a higher level of crystallinity and a sharper oxide-metal interface than previously shown, and provide the first comprehensive microscopic analysis of ZrO$_2$ capping layer properties. These developments pave the way toward vital performance advances in superconducting quantum devices.
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All authors Nathan Sitaraman, Zhaslan Baraissov, Alexis Grassl, Hongbin Yang, Daniel Tong, David Muller, Matthias Liepe

Materials Science

Predicting Defect States: A Quick Screening Protocol for Substitutional Point Defect Engineering

Hyosik Kang and Lukas Muechler

Point defects in crystalline materials play a central role in determining electronic, optical, and magnetic properties. However, systematic exploration of defect configurations remains computationally expensive because large supercell calculations are required to approximate isolated defects under periodic boundary conditions. We present a unit-cell-based tight-binding protocol that enables rapid pre-screening of substitutional defects. The protocol extracts Wannier tight-binding Hamiltonians from small, fully relaxed unit cells of the host and defect-like systems, replicates the host Hamiltonian to construct a supercell model, and introduces the defect by modifying only the on-site energies at the substitution site while leaving the hopping parameters unchanged. We validate the protocol across three diverse systems: isostructural substitutional defects in transition-metal dichalcogenides (M$_\mathrm{Mo}$ MoS$_2$, M = Ce, Zr, Nb, Tc, and Ru), symmetry-breaking carbon substitutions in hexagonal boron nitride (C$_\mathrm{B}$C$_\mathrm{N}$ h-BN), and nitrogen-vacancy (NV$^-$) centers in diamond. These case studies span two-dimensional and three-dimensional hosts, simple substitutions, and substitution-vacancy complexes. In all cases, the protocol successfully captures the number of in-gap states, their degeneracies, and their shallow or deep character relative to host band edges, despite some quantitative deviations in absolute energy positions. We further identify limitations for vacancies of highly electronegative atoms and for charge-state or spin-polarization effects, both of which involve self-consistent charge redistribution not captured by the protocol.
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Quantum Gases · Cross-listed from nucl-th

Determining universal spectra from probability distributions

Charles Kacir, Joseph Moscoso, Amy Nicholson et al. (+2 more)

The probability distribution of a two-particle correlation function computed over background auxiliary field configurations, used to generate the interactions, has been shown to inform about the spectra of universal $n$-body clusters [1]. Here, we utilize two approaches, a numerical lattice computation and an analytic expansion in the limit of large numbers of identical species, in an attempt to refine the initial predictions. Exploratory calculations in these directions are presented, and future investigations laid out.
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All authors Charles Kacir, Joseph Moscoso, Amy Nicholson, Thomas R. Richardson, Cade Rodgers

Strongly Correlated Electrons

Correlation-driven phonon renormalisation and the equation of state of $\gamma$-cerium

Yao Wei, Siyu Chen, Evgeny Plekhanov et al. (+3 more)

We investigate the thermodynamic properties of elemental cerium by assessing the crucial role of phonon free energy within the framework of dynamical mean-field theory (DMFT). While conventional density functional theory (DFT) often fails to capture the intricate energy landscape of $f$-electron materials, our approach integrates many-body electronic correlations with lattice dynamics to achieve a more rigorous description of the equation of state. We calculate the total energy as a function of the lattice constant at both the DFT and DFT+DMFT levels, subsequently incorporating the vibrational free energy derived from the phonon density of states. Our findings reveal that electronic renormalisation of the force constants significantly alters the phonon spectra, particularly in the strongly correlated $\gamma$-phase. By applying these phonon corrections to the energy profiles, we observe a substantial refinement in the predicted equilibrium volumes. Using principal-component-based machine learning, we interpolate phonon dispersions continuously from a finite set of first-principles calculations and compare them to experiment, finding significantly closer agreement compared to conventional DFT and DFT+U calculations that neglect dynamical many-body correlations. This study underlines the necessity of accounting for both electronic and vibrational entropy when evaluating the phase stability and structural transitions of lanthanide systems under varying pressures and temperatures.
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All authors Yao Wei, Siyu Chen, Evgeny Plekhanov, Ivan Stich, Cedric Weber, Jan M. Tomczak

Strongly Correlated Electrons

Atomic-scale visualization of the toroidal order in a trimeric Dy(III) single-molecule toroic

Michael J. Jenkins, Madalynn G. Marshall, Jie Xing et al. (+8 more)

Single-molecule toroics (SMTs) offer a unique platform for next-generation quantum devices utilizing head-to-tail spin alignments in the compounds. Presence of toroidal moments in SMTs has been essentially based on magnetometry and ab initio calculations. Here, we report observation and probe of the toroidal moment in [Dy3(OH)(teaH2)3(paa)3]Cl(OMe) [teaH3: triethanolamine; paaH: N-(2-pyridyl)-acetoacetamide] from mapping of Dy3+ magnetic susceptibility tensors by polarized neutron diffraction (PND). Neutron diffraction under variable magnetic fields demonstrates field-induced magnetization along the c-axis with toroidal moments anti-parallelly stacked, providing definite proof of the toroidal moment. Magnetometry studies confirm the toroidal ground state. For the first time, the combined use of PND, variable-field neutron diffraction, ab initio calculations, and magnetometry is introduced as a robust and quantitative methodology to probe molecular-scale toroidal magnetism. This integrated approach overcomes limitations of earlier indirect methods, establishes a benchmark framework for investigating SMTs, and provides valuable insights for the design of molecular quantum materials.
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All authors Michael J. Jenkins, Madalynn G. Marshall, Jie Xing, Muthu Satheeshkumar, Brandon D. Watson-Sanders, Xiaoping Wang, Christina M. Hoffmann, Gopalan Rajaraman, Huibo Cao, Rongying Jin, Zi-Ling Xue

Disordered Systems and Neural Networks

Jittery Quantum Boomerang Effect

Pedro Dornelas and Gerson J. Ferreira

We study the dynamics of a spin-polarized wave packet in a disordered Rashba two-dimensional electron gas and identify a jittery quantum boomerang effect in which longitudinal and transverse motion return to the origin through fundamentally distinct mechanisms. Starting from an initial state with finite momentum along $x$ and spin polarized along $z$, we calculate the time evolution by combining a Chebyshev expansion of the time-evolution operator with a disorder ensemble average. In the weak-scattering regime, equations of motion derived from the quantum kinetic equation reproduce the numerical trends and show that impurity scattering acts as a viscous damping mechanism that suppresses the transient Zitterbewegung and drives the transverse displacement back to $y=0$ at long times. In contrast, the longitudinal dynamics show a Drude-like saturation at weak disorder. These results are consistent with the vanishing intrinsic spin Hall conductivity in the disordered Rashba model and with experimental observations of a transient intrinsic spin Hall effect in the time-domain. As disorder increases, the longitudinal dynamics evolve to a partial return toward the origin, which signals a transition from weak antilocalization to Anderson localization in 2D.
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Materials Science

Dominant in-plane anomalous Hall effect in a monoclinic room-temperature ferromagnet

Guoxin Zheng, Arjyama Bordoloi, Mingjun Fan et al. (+6 more)

Ferromagnetic metals are characterized by enhanced dissipationless transverse transport responses via the anomalous Hall effect, offering a route towards magnetic sensing and spintronic readout functionalities. In most ferromagnets, the anomalous Hall current is constrained to lie in the plane perpendicular to the magnetization (or applied magnetic field). Recently, it has been recognized that selected symmetries can also permit a Hall response in a traditionally forbidden configuration, where the Hall current lies in the same plane as the magnetization, realizing an in-plane anomalous Hall effect. Reported realizations of this effect, however, are typically much weaker than the conventional Hall response in the same material. Here, through engineering specific crystallographic mirror symmetry-breaking, we realize a strongly enhanced in-plane anomalous Hall response in monoclinic Cr3Te4 with room-temperature ferromagnetism. Remarkably, the in-plane anomalous Hall signal exceeds the out-of-plane response by a factor of five, with which we demonstrate a unique in-plane field and current sensing functionality. Combined with density functional theory calculations, our results establish low-crystalline-symmetry ferromagnets with near-Fermi-level Weyl points as a practical platform for symmetry-engineered Hall responses, and point to a route towards room-temperature, geometry-flexible sensing devices.
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All authors Guoxin Zheng, Arjyama Bordoloi, Mingjun Fan, Shunsuke Kitou, Hiraku Saito, Taro Nakajima, Sobhit Singh, Takashi Kurumaji, Linda Ye

Statistical Mechanics · Cross-listed from quant-ph

Scaling law of asymptotic freedom in collective charging of quantum batteries

Gentaro Watanabe, Chunlin Chen and B. Prasanna Venkatesh

We establish a universal scaling law for collective charging of quantum batteries, independent of microscopic details. We prove that the ergotropy-to-energy ratio approaches unity at least as fast as $\sim N^{-1}$ with the number of batteries $N$, implying generic asymptotic freedom. We further show how the universal $1/N$ scaling can be overcome: when the battery state becomes asymptotically pure, the convergence can be substantially faster, including $\sim N^{-b}$ with $b>1$ and even exponential scaling in $N^2$. Rigorous finite-$N$ upper and lower bounds on the ergotropy-to-energy ratio are further derived, providing nonasymptotic guarantees for the universal $1/N$ scaling.
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