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Physics Condensed Matter

cond-mat Watch Condensed Matter

Sunday 4 January

Superconductivity

Common sublattice-pure van Hove singularities in the kagome superconductors $\textit{A}$V$_{3}$Sb$_{5}$ ($\textit{A}$ = K, Rb, Cs)

Yujie Lan, Yuhao Lei, Congcong Le et al. (+7 more)

Kagome materials offer a versatile platform for exploring correlated and topological quantum states, where van Hove singularities (VHSs) play a pivotal role in driving electronic instabilities, exhibiting distinct behaviors depending on electron filling and interaction settings. In the recently discovered kagome superconductors $\textit{A}$V$_{3}$Sb$_{5}$ ($\textit{A}$ = K, Rb, Cs), unconventional charge density wave order, superconductivity, and electronic chirality emerge, yet the nature of VHSs near the Fermi level ($\textit{E}$$_{F}$) and their connection to these exotic orders remain elusive. Here, using high-resolution polarization-dependent angle-resolved photoemission spectroscopy, we uncover a universal electronic structure across $\textit{A}$V$_{3}$Sb$_{5}$ that is distinct from density-functional theory predictions that show noticeable discrepancies. We identify multiple common sublattice-pure VHSs near $\textit{E}$$_{F}$, arising from strong V-$\textit{d}$/Sb-$\textit{p}$ hybridization, which significantly promote bond-order fluctuations and likely drive the observed charge density wave order. These findings provide direct spectroscopic evidence for hybridization-driven VHS formation in kagome metals and establish a unified framework for understanding the intertwined electronic instabilities in $\textit{A}$V$_{3}$Sb$_{5}$.
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All authors Yujie Lan, Yuhao Lei, Congcong Le, Brenden R. Ortiz, Nicholas C. Plumb, Milan Radovic, Xianxin Wu, Ming Shi, Stephen D. Wilson, Yong Hu

Materials Science

Phonon-informed Crystal Structure Classification via Precision-Adaptive ResNet-based Confidence Ensemble

Hongyu Chen, Mengyu Dai, Hongjiang Chen et al. (+7 more)

Accurate description of crystal structures is a prerequisite for predicting the physicochemical properties of materials. However, conventional X-ray diffraction (XRD) characterization often encounters intrinsic bottlenecks when applied to complex multiphase systems, necessitating the integration of complementary optical measurement. In this study, we developed a multi-descriptor framework by integrating key parameters including space groups, Pearson symbols, and Wyckoff sequences, to categorize the dataset of over 19,000 crystals into several dozen structural prototypes. Then, an accuracy-adaptive ensemble network based on residual architectures was implemented to capture structural “fingerprints" within phonon vibration modes and Raman spectra. The ensemble algorithm demonstrates exceptional robustness when processing various crystals of varying lengths and quality. This data-driven classification strategy not only overcomes the reliance of traditional characterization on ideal data but also provides a high-throughput tool for the automated analysis of material structures in large-scale experimental workflows.
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All authors Hongyu Chen, Mengyu Dai, Hongjiang Chen, Ruilin Liu, Xiaole Tian, Ruixiao Lian, Yuqian Zhang, Xia Cai, Wenwu Li, Hao Zhang

Mesoscale and Nanoscale Physics

Alignment-Dependent Gapless Chiral Split Magnons in Altermagnetic Domain Walls

Zhaozhuo Zeng, Zhejunyu Jin and Peng Yan

Altermagnets, an emerging class of magnetic materials, exhibit exotic chiral split magnons that are of great interest for both fundamental physics and spintronic applications. However, detecting and manipulating these magnons is challenging due to their THz frequency response. Here, we report the discovery of gapless chiral split magnons confined within altermagnetic domain walls. Unlike in conventional ferromagnets or antiferromagnets, their spectrum is highly sensitive to the domain wall orientation relative to the crystal axis. These magnons inherit the chiral splitting of their bulk counterparts and are detectable in the microwave regime, offering a distinctive signature for identifying altermagnets. We further show that the interfacial Dzyaloshinskii-Moriya interaction drives hybridization of magnons with opposite chiralities, enabling unidirectional strong magnon-magnon coupling. Moreover, we demonstrate that spin-orbit torque can control the domain wall orientation, providing a practical means to manipulate these chiral magnons. Our findings open pathways for novel magnonic nanocircuitry based on altermagnetic domain walls.
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Superconductivity

Isotropic Superconductivity in Room-temperature Superconductor LaSc$_{2}$H$_{24}$

Zefang Wang, Wenbo Zhao, Yuan Ma et al. (+2 more)

The discovery of LaSc$_{2}$H$_{24}$ represents a milestone in the quest for room-temperature superconductivity, yet the microscopic mechanism underlying its superior performance remains unclear. Through a comprehensive revisit of theoretical calculations, we uncover a pivotal transition from the anisotropic two-gap superconductivity of LaH$_{10}$ to the isotropic single-gap superconductivity in LaSc$_{2}$H$_{24}$ upon the introduction of scandium, thereby enhancing the superconducting critical temperature ($T_\mathrm{c}$). This enhancement is rooted in a critical dual role of Sc $3d$ electrons: i) the Sc-derived Jahn-Teller effect promotes hydrogen metallization via the elongation of specific interlayer H-H bonds and enhances electron-phonon coupling (EPC) through the softening of associated phonon modes; ii) Sc $3d$ electrons reconstruct the electronic structure into an MgB$_{2}$-like configuration, generating novel Sc-H-Sc $\sigma$- and $\pi$-bonding states with EPC strengths comparable to LaH$_{10}$. Crucially, the pronounced hybridization between Sc and the hydrogen cages effectively unifies these two contributions on the Fermi surface. This Sc-induced gap unification bridges the high-EPC H-H states with widespread Sc-H states, establishing an isotropic single-gap nature with a large overall EPC strength. Our findings identify this Sc-induced gap unification as the fundamental mechanism for achieving room-temperature superconductivity in LaSc$_{2}$H$_{24}$, offering a theoretical blueprint for the future design of superior superconducting hydrides.
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All authors Zefang Wang, Wenbo Zhao, Yuan Ma, Hanyu Liu, Yanming Ma

Disordered Systems and Neural Networks

Simulating diffusion and disorder-induced localization in random walks and transmission lines

Jake S. Bobowski

We present two complementary simulations that lead to an exploration of Anderson localization, a phenomenon in which wave diffusion is suppressed in disordered media by interference from multiple scattering. To build intuition, the first models the random walk of classical, non-interacting point-like particles, providing a clear analogy to the way disorder can limit transport. The second examines the propagation of an electromagnetic pulse through a one-dimensional, lossless transmission line with randomly varying propagation constant and characteristic impedance along its length, a system that captures the interference effects essential for true Anderson localization. We evaluate quantitative measures that reveal the transition from normal diffusion to localization of particles in one case, and the exponential confinement of wave energy in the other. Together, these simulations offer a pair of accessible tools for investigating localization phenomena in an instructional setting.
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Materials Science

Recent Progress in Ultrafast Dynamics of Transition-Metal Compounds Studied by Time-Resolved X-ray Techniques

Hiroki Wadati, Kohei Yamamoto and Kohei Yamagami

X-ray absorption spectroscopy and X-ray magnetic circular dichroism have long served as indispensable tools for probing the electronic and magnetic properties of transition-metal compounds with elemental selectivity. In recent years, the emergence of femtosecond lasers has opened a new avenue for studying nonequilibrium dynamics in condensed matter. However, conventional optical techniques lack elemental and orbital specificity, making it difficult to disentangle the coupled charge, spin, and lattice responses in complex materials. The development of X-ray free-electron lasers (XFEL) and laboratory high-harmonic generation (HHG) sources has enabled the extension of X-ray absorption and scattering techniques into the femtosecond time domain. Time-resolved X-ray absorption spectroscopy, X-ray magnetic circular dichroism, and resonant soft X-ray scattering now provide direct, complementary access to element- and momentum-resolved ultrafast dynamics. This review summarizes recent progress in these techniques, focusing on pump-probe measurements of laser-induced demagnetization, spin-state transitions, and valence and structural changes in transition-metal compounds. We also discuss advances in tabletop HHG-based X-ray spectroscopy and its integration with large-scale XFEL facilities. These developments provide powerful routes for visualizing the nonequilibrium evolution of charge, spin, orbital, and lattice degrees of freedom, offering new insights into the ultrafast control of quantum materials.
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Materials Science

Molecular simulation of methane hydrate growth confined into a silica pore

Ángel M. Fernández-Fernández, María M. Conde, Germán Pérez-Sánchez et al. (+2 more)

The growth of a methane hydrate seed within a silica slit pore of fixed width has been studied using AllAtom Molecular Dynamics (AA-MD). An AA force field has been used to describe the molecules of the solid silica substrate, with a-quartz crystalline structure. The crystallisation of hydrates in confined geometries is not well understood yet, and the objective of this work is to study the hydrate growth inside a silica pore using molecular simulation. Both NVT and NpT ensembles were used in the AA-MD simulations to analyse the hydrate growth from an initial seed. Results showed that the boundary conditions imposed by the nanometric slit pore yielded a hydrate with structural defects, filling the accessible space between the silica walls. The water molecules which were not incorporated to the initial seed hydrate formed a high density water layer trapped between the silica walls and the crystallised hydrate. These results provide an interesting insight into the hydrate crystallisation process in confined geometries, resembling those found in natural hydrate deposits.
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All authors Ángel M. Fernández-Fernández, María M. Conde, Germán Pérez-Sánchez, Martín Pérez-Rodríguez, Manuel M. Piñeiro

Superconductivity

Tripling of the Superconducting Critical Current Density in BaFe$_2$(As$_{1-x}$P$_x$)$_2$ Retained After Pressure Release

Jiangteng Liu, Alex Lopez, Daniel Slone et al. (+5 more)

Superconducting performance is tunable not only via chemical modification or defect engineering, but also through external parameters such as pressure, though this method remains less readily accessible. In this work, we study how compression influences vortex dynamics and critical currents in an iron-based superconductor. Specifically, we perform magnetization measurements using an off-the-shelf pressure cell to investigate the effects of hydrostatic pressures up to 1.08 GPa on the magnetic properties of BaFe$_2$(As$_{0.62}$P$_{0.38}$)$_2$ crystals across a range of temperatures $T$ and magnetic fields $H$. Although these pressures minimally affect the superconducting critical temperature, they produce a clear increase in the critical current density $J_c(T,H)$, a pronounced reduction in the rate of thermally activated vortex motion $S(T,H)$, and can change the dominant vortex pinning mechanism. Furthermore, the effects of pressure are irreversible: after pressurization and subsequent release at room temperature, high-density microcracks are observed and the crystals retain their enhanced critical current densities. The second magnetization peak vanishes above 18 K after the pressure cycle, which we attribute to a transition from predominantly $\delta \kappa$ pinning to a mixed mechanism of $\delta T_c$ and surface pinning. Lastly, a threefold increase in $J_c$, a more than 40% reduction in $S$ at 8~K and 0.5~T, and an expanded elastic-creep region were achieved after $1-2$ pressure cycles. These findings demonstrate the potential utility of pressure cycling for improving $J_c$, which may offer a simpler alternative compared to approaches such as chemical doping or the introduction of artificial pinning centers.
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All authors Jiangteng Liu, Alex Lopez, Daniel Slone, Guodong Ren, Zhaoyu Liu, Juan-Carlos Idrobo, Jiun-Haw Chu, Serena Eley

Disordered Systems and Neural Networks · Cross-listed from quant-ph

Bond Additivity and Persistent Geometric Imprints of Entanglement in Quantum Thermalization

Chun-Yue Zhang, Shi-Xin Zhang and Zi-Xiang Li

Characterizing the intricate structure of entanglement in quantum many-body systems remains a central challenge, as standard measures often obscure underlying geometric details. In this Letter, we introduce a powerful framework, termed multi-bipartition entanglement tomography, which probes the fine structure of entanglement across an exhaustive ensemble of distinct bipartitions. Our cornerstone is the discovery of a “bond-additive law”, which reveals that the entanglement entropy can be precisely decomposed into a bulk volume-law baseline plus a geometric correction formed by a sum of local contributions from crossed bonds of varying ranges. This law distills complex entanglement landscapes into a concise set of entanglement bond tensions $\{\omega_j\}$, serving as a quantitative fingerprint of interaction locality. By applying this tomography to Hamiltonian dynamics, random quantum circuits, and Floquet dynamics, we resolve a fundamental distinction between thermalization mechanisms: Hamiltonian thermalized states retain a persistent geometric imprint characterized by a significantly non-zero $\omega_1$, while this structure is completely erased in random quantum circuit and Floquet dynamics. Our work establishes multi-bipartition entanglement tomography as a versatile toolbox for the geometric structure of quantum information in many-body systems.
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Materials Science

Predicting Coherent B2 Stability in Ru-Containing Refractory Alloys Through Thermodynamic Elastic Design Maps

Avik Mahata

Ruthenium-based B2 intermetallics are promising for refractory superalloys but are limited by the trade-off between high thermodynamic stability and elastic precipitation strain. We present a physics-guided machine learning framework integrating high-throughput Density Functional Theory (DFT), Random Forest screening, and Symbolic Regression to navigate this design space. This approach resolves the paradox where stoichiometric compounds like RuHf fail to achieve theoretical solvus temperatures. By deriving a closed-form physical law, we quantify the strain penalty: a 1% lattice misfit reduces the solvus temperature by approximately 200 degrees C. This finding confirms that maximizing thermodynamic driving force alone is insufficient. We demonstrate that multi-component alloying is structurally necessary, identifying ternary additions such as Al and Ti as essential lattice-tuning agents that zero out the elastic penalty. This framework establishes a rigorous, constraint-based protocol for alloy design, enabling the precise engineering of zero-misfit, high-stability microstructures.
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Materials Science

Calorimetric Measurement of the Surface Energy of Enstatite, MgSiO$_3$

Megan A. Householder, Tamilarasan Subramani, Kristina Lilova et al. (+3 more)

Surface thermodynamics of minerals influence their properties and occurrence in both terrestrial and planetary systems. Using high-temperature oxide melt solution calorimetry, we report the first direct measurement of the surface energy of enstatite, MgSiO$_3$. Enstatite nanoparticles of different sizes were synthesized using the sol-gel method, characterized with X-ray diffraction, thermal analysis, infrared spectroscopy, surface area measurements, and electron microscopy. The materials consist of crystallites with sizes of $\sim $10 - 20 nm, which are agglomerated into larger nanoparticles. Thus, both surface and interface terms contribute to the measured enthalpies. Analysis based on calorimetry and calculated surface and interface areas gives the surface enthalpy of enstatite as 4.79 $\pm$ 0.45 J m$^{-2}$. This value is comparable to that of forsterite (Mg$_2$SiO$_4$) and larger than those of many nonsilicate oxide materials. This large surface energy may present a barrier to the nucleation of enstatite in planetary atmospheres and other geochemical and planetary environments. The interfacial energy of enstatite appears to be close to zero. The transition enthalpy from bulk orthoenstatite to bulk clinoenstatite is 0.34 $\pm$ 0.93 kJ mol$^{-1}$, which is in agreement with earlier reports. The methodology developed here can be extended to other materials having complex structures and morphologies to separate surface and interfacial contributions to energetics.
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All authors Megan A. Householder, Tamilarasan Subramani, Kristina Lilova, James R. Lyons, Rhonda M. Stroud, Alexandra Navrotsky

Disordered Systems and Neural Networks · Cross-listed from quant-ph

Multifractal and Glassy Signatures of Non-Ergodic 2D Quantum Dynamics

Aleksey Lunkin, Nicole S. Ticea, Michael T. Solomon et al. (+296 more)

The fate of ergodicity and localization in disordered, interacting quantum systems in two spatial dimensions remains an outstanding open problem in non-equilibrium physics. Theoretical and numerical approaches are severely constrained by exponential Hilbert space growth. Here, we leverage the high data-acquisition rates of superconducting quantum processors to extensively sample Hilbert space configurations, effectively imaging the state as a wavefunction network (WFN). Tracking the bitstring return probability across varied disorder strengths, we find heavy-tailed distributions and power-law typical decay characteristic of glassy relaxation. Furthermore, the distribution of bitstring probabilities transitions from a Porter-Thomas form at low disorder to an eight-decade power law at stronger disorder. In the reconstructed configuration space, WFN connectivity is compatible with a random geometric network at low disorder and becomes scale-free at stronger disorder. Finally, a multifractal analysis based on the binary intrinsic dimension (BID) reveals a non-ergodic regime where the wavefunction support saturates to a finite fraction of the total Hilbert space. Together, these results rule out a direct ergodic-to-localized transition, pointing instead to an extended multifractal regime. By visualizing wavefunction dynamics directly in configuration space, this work complements traditional real-space studies, showing the potential of quantum processors to resolve long-standing questions in non-equilibrium physics.
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All authors Aleksey Lunkin, Nicole S. Ticea, Michael T. Solomon, Riccardo Andreoni, Shashwat Kumar, Connie Miao, Jaehong Choi, Mohammed Alghadeer, Ilya Drozdov, Dmitry Abanin, Amira Abbas, Rajeev Acharya, Laleh Beni, Georg Aigeldinger, Ross Alcaraz, Sayra Alcaraz, Markus Ansmann, Frank Arute, Kunal Arya, Walt Askew, Nikita Astrakhantsev, Juan Atalaya, Ryan Babbush, Brian Ballard, Joseph C. Bardin, Hector Bates, Andreas Bengtsson, Majid Karimi, Alexander Bilmes, Simon Bilodeau, Felix Borjans, Alexandre Bourassa, Jenna Bovaird, Dylan Bowers, Leon Brill, Peter Brooks, Michael Broughton, David A. Browne, Brett Buchea, Bob B. Buckley, Tim Burger, Brian Burkett, Nicholas Bushnell, Jamal Busnaina, Anthony Cabrera, Juan Campero, Hung-Shen Chang, Silas Chen, Zijun Chen, Ben Chiaro, Liang-Ying Chih, Agnetta Y. Cleland, Bryan Cochrane, Matt Cockrell, Josh Cogan, Paul Conner, Harold Cook, Rodrigo G. Cortiñas, William Courtney, Alexander L. Crook, Ben Curtin, Martin Damyanov, Sayan Das, Dripto M. Debroy, Sean Demura, Paul Donohoe, Andrew Dunsworth, Valerie Ehimhen, Alec Eickbusch, Aviv Moshe Elbag, Lior Ella, Mahmoud Elzouka, David Enriquez, Catherine Erickson, Lara Faoro, Vinicius S. Ferreira, Marcos Flores, Leslie Burgos, Sam Fontes, Ebrahim Forati, Jeremiah Ford, Brooks Foxen, Masaya Fukami, Alan Wing Fung, Lenny Fuste, Suhas Ganjam, Gonzalo Garcia, Christopher Garrick, Robert Gasca, Helge Gehring, Robert Geiger, William Giang, Dar Gilboa, James E. Goeders, Edward C. Gonzales, Raja Gosula, Stijn J. Graaf, Alejandro Dau, Dietrich Graumann, Joel Grebel, Alex Greene, Jonathan A. Gross, Jose Guerrero, Loïck Guevel, Tan Ha, Steve Habegger, Tanner Hadick, Ali Hadjikhani, Michael C. Hamilton, Monica Hansen, Matthew P. Harrigan, Sean D. Harrington, Jeanne Hartshorn, Stephen Heslin, Paula Heu, Oscar Higgott, Reno Hiltermann, Jeremy Hilton, Hsin-Yuan Huang, Mike Hucka, Christopher Hudspeth, Ashley Huff, William J. Huggins, Evan Jeffrey, Shaun Jevons, Zhang Jiang, Xiaoxuan Jin, Cody Jones, Chaitali Joshi, Pavol Juhas, Andreas Kabel, Dvir Kafri, Hui Kang, Kiseo Kang, Amir H. Karamlou, Ryan Kaufman, Kostyantyn Kechedzhi, Julian Kelly, Tanuj Khattar, Mostafa Khezri, Seon Kim, Paul V. Klimov, Can M. Knaut, Bryce Kobrin, Alexander N. Korotkov, Fedor Kostritsa, John Mark Kreikebaum, Ryuho Kudo, Ben Kueffler, Arun Kumar, Vladislav D. Kurilovich, Vitali Kutsko, Tiano Lange-Dei, Brandon W. Langley, Pavel Laptev, Kim-Ming Lau, Emma Leavell, Justin Ledford, Joonho Lee, Joy Lee, Kenny Lee, Brian J. Lester, Wendy Leung, Lily Li, Wing Yan Li, Ming Li, Alexander T. Lill, William P. Livingston, Matthew T. Lloyd, Laura Lorenzo, Erik Lucero, Daniel Lundahl, Aaron Lunt, Sid Madhuk, Aniket Maiti, Ashley Maloney, Salvatore Mandrà, Leigh S. Martin, Orion Martin, Eric Mascot, Paul Das, Dmitri Maslov, Melvin Mathews, Cameron Maxfield, Jarrod R. McClean, Matt McEwen, Seneca Meeks, Anthony Megrant, Kevin C. Miao, Zlatko K. Minev, Reza Molavi, Sebastian Molina, Shirin Montazeri, Charles Neill, Michael Newman, Anthony Nguyen, Murray Nguyen, Chia-Hung Ni, Murphy Yuezhen Niu, Logan Oas, William D. Oliver, Raymond Orosco, Kristoffer Ottosson, Alice Pagano, Agustin Paolo, Sherman Peek, David Peterson, Alex Pizzuto, Elias Portoles, Rebecca Potter, Orion Pritchard, Michael Qian, Chris Quintana, Ganesh Ramachandran, Arpit Ranadive, Matthew J. Reagor, Rachel Resnick, David M. Rhodes, Daniel Riley, Gabrielle Roberts, Roberto Rodriguez, Emma Ropes, Lucia B. Rose, Eliott Rosenberg, Emma Rosenfeld, Dario Rosenstock, Elizabeth Rossi, David A. Rower, Robert Salazar, Kannan Sankaragomathi, Murat Can Sarihan, Kevin J. Satzinger, Max Schaefer, Sebastian Schroeder, Henry F. Schurkus, Aria Shahingohar, Michael J. Shearn, Aaron Shorter, Vladimir Shvarts, Volodymyr Sivak, Spencer Small, W. Clarke Smith, David A. Sobel, Barrett Spells, Sofia Springer, George Sterling, Jordan Suchard, Aaron Szasz, Alexander Sztein, Madeline Taylor, Jothi Priyanka Thiruraman, Douglas Thor, Dogan Timucin, Eifu Tomita, Alfredo Torres, M. Mert Torunbalci, Hao Tran, Abeer Vaishnav, Justin Vargas, Sergey Vdovichev, Guifre Vidal, Benjamin Villalonga, Catherine Heidweiller, Meghan Voorhees, Steven Waltman, Jonathan Waltz, Shannon X. Wang, Brayden Ware, James D. Watson, Yonghua Wei, Travis Weidel, Theodore White, Kristi Wong, Bryan W. Woo, Christopher J. Wood, Maddy Woodson, Cheng Xing, Z. Jamie Yao, Ping Yeh, Bicheng Ying, Juhwan Yoo, Noureldin Yosri, Elliot Young, Grayson Young, Adam Zalcman, Ran Zhang, Yaxing Zhang, Ningfeng Zhu, Nicholas Zobrist, Zhenjie Zou, Sergio Boixo, Hartmut Neven, Vadim Smelyanskiy, Trond I. Andersen, Markus Heyl, Marcello Dalmonte, Pedram Roushan, Mikhail V. Feigelman, Lev B. Ioffe

Saturday 3 January

Materials Science · Cross-listed from astro-ph.IM

Exploring Metal Additive Manufacturing in Martian Atmospheric Environments

Zane Mebruer and Wan Shou

In-space manufacturing is essential for achieving long-term planetary colonization, particularly on Mars, where material transport from Earth is both costly and logistically restrictive. Traditional subtractive manufacturing methods are highly equipment-, energy-, and material-intensive, making additive manufacturing (AM) a more practical and sustainable alternative for extraterrestrial production. Among various AM technologies, selective laser melting (SLM) stands out due to its exceptional versatility, precision, and capability to produce dense metallic parts with complex geometries. However, conventional SLM processes rely heavily on inert argon environments to prevent oxidation and ensure high-quality part formation, conditions that are difficult to reproduce on Mars. This study investigates the feasibility of using carbon dioxide (CO2), which makes up over 95% of the Martian atmosphere, as a potential substitute for argon in SLM. Single-track and two-dimensional 316L stainless steel specimens were fabricated under argon, CO2, and ambient air environments with a wide range of laser parameters to evaluate the influence of atmospheric composition on surface morphology, microstructural cohesion, and oxidation behavior. The results reveal that no single parameter controls the overall part quality; rather, a balance of parameters is essential to maintain thermal equilibrium during fabrication. Although parts produced in CO2 exhibited slightly inferior surface finish, cohesion, and oxidation resistance compared to argon, they performed significantly better than those fabricated in ambient air. These findings suggest that CO2-assisted SLM could enable sustainable in situ manufacturing on Mars and may also serve as a cost-effective alternative shielding gas for terrestrial applications.
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Statistical Mechanics

A Unified Computational Framework for Two Dimensional Diffusion Limited Aggregation via Finite-Size Scaling, Multifractality, and Morphological Analysis

Satish Prajapati

Diffusion-Limited Aggregation (DLA), the canonical model for non-equilibrium fractal growth, emerges from the simple rule of irreversible attachment by random walkers. Despite four decades of study, a unified computational framework reconciling its stochastic algorithm, universal fractal dimension, multifractal growth measure, and finite-size effects remains essential for applications from materials science to geomorphology. Through large-scale simulations (clusters up to $N = 10^6$ particles) in two dimensions, we perform a tripartite analysis: (1) We establish a definitive finite-size scaling collapse, extracting the universal fractal dimension $D = 1.712 \pm 0.015$ and identifying the crossover to boundary-dominated growth at a scaled mass $x_0 \approx 0.10 \pm 0.02$. (2) We quantify the full multifractal spectrum of the harmonic measure ($\Delta\alpha \approx 1.13$), directly linking the stochastic algorithm to the deterministic Laplacian growth equation $\nabla^2 p = 0$ and explaining the screening effect via an exponential decay $\eta \sim e^{-r/\xi}$ with screening length $\xi = 22.7 \pm 0.8$ lattice units. (3) We provide a complete morphological characterization, revealing power-law branch length distributions ($\tau \approx 2.1$) and angular branching preferences ($\sim 72^\circ$). This work computationally validates DLA as a robust universality class and provides a scalable methodology for analyzing diffusion-controlled pattern formation across disciplines.
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Superconductivity

Exploring the Thermodynamic, Elastic, and Optical properties of LaRh2X2 (X = Al, Ga, In) low Tc Superconductors through First-Principles Calculations

Md. Hasan Shahriar Rifat, Mirza Humaun Kabir Rubel, Md. Borhan Uddin et al. (+3 more)

LaRh2X2 (X = Al, Ga, In) compounds crystallize in a tetragonal layered ThCr2Si2-type structure and belong to a family of low critical temperature superconductors. Using first-principles density functional theory calculations implemented in the CASTEP code, we systematically investigated their structural, mechanical, elastic, electronic, vibrational, thermophysical, and optical properties for the first time. The optimized structural parameters show good agreement with available experimental data. The Born stability criteria and negative formation energies confirm the mechanical and thermodynamic stability of these materials. Poisson and Pugh ratios indicate a ductile nature, while low Debye and melting temperatures together with low Vickers hardness suggest that the compounds are relatively soft. The electronic band structures and density of states reveal metallic behavior. Charge density distribution and Mulliken population analysis indicate mixed covalent, ionic, and metallic bonding. The calculated Fermi surfaces contain both hole-like and electron-like sheets, suggesting possible multiband characteristics. Phonon dispersion analysis confirms the dynamical stability of LaRh2Al2 and LaRh2Ga2, while LaRh2In2 shows dynamical instability associated with a possible structural phase transition. Optical property analysis indicates that these superconductors may be promising candidates for high-density optical data storage applications. The estimated electron-phonon coupling constant of about 0.56 indicates that LaRh2X2 compounds are weakly coupled low critical temperature superconductors.
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All authors Md. Hasan Shahriar Rifat, Mirza Humaun Kabir Rubel, Md. Borhan Uddin, Apon Kumar Datta, Md. Mijanur Rahaman, Jubair Hossan Abir

Statistical Mechanics

From Random Walks to Thermal Rides: Universal Anomalous Transport in Soaring Flights

Jérémie Vilpellet, Alexandre Darmon and Michael Benzaquen

Cross-country soaring flights rely on intermittent atmospheric updrafts to cover long distances, producing trajectories that alternate between rapid relocation and local exploration. From a large dataset of paraglider, hang glider, and sailplane flights, we uncover a universal transport law: beyond short ballistic times, horizontal motion is persistently sub-ballistic, with a Hurst exponent $\approx 0.88$ largely independent of aircraft type. Phase-resolved analysis using a probabilistic segmentation method shows that this scaling arises from the fundamentally intermittent, two-dimensional, and directionally correlated nature of soaring transport, in which successive ballistic segments do not add coherently. We find that learning, in the sense of experience-driven improvements in exploration and decision-making, manifests primarily in the search phase, enhancing the ability to efficiently probe the air mass and locate the next thermal. Overall, our results suggest that atmospheric structure and the generic organization of the transition-search-climb cycle dominate transport properties, placing human soaring alongside biological and physical systems where anomalous transport emerges from intermittency and persistence.
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Mesoscale and Nanoscale Physics

Breakdown of Ohm's Law by Disorders in Low-Dimensional Transistors

Chang Niu, Adam Charnas, Jian-Yu Lin et al. (+4 more)

Ohm's law provides a fundamental framework for understanding charge transport in conductors and underpins the concept of electrical scaling that has enabled the continuous advancement of modern CMOS technologies. As transistors are scaled to even smaller dimensions, device channels inevitably enter low-dimensional regimes to achieve higher performance. Low-dimensional materials such as atomically thin oxide semiconductors, 2D van der Waals semiconductors, and 1D carbon nanotubes, have thus emerged as key candidates for extending Moore's law. Here, we reveal the fundamental distinction between three-dimensional and low-dimensional conductors arising from disorder-induced electron localization, which leads to the breakdown of Ohm's law and lateral linear scaling. We develop a quantitative model that captures the role of the disordered region, a unique characteristic intrinsically to low-dimensional transistors. Furthermore, the disorder-induced localization framework consistently explains experimental observations in atomically thin In2O3 field-effect transistors across variations in channel length, temperature, thickness, and post-annealing conditions. This work establishes a unified physical picture for understanding and optimizing disorder-driven electronic transport in low-dimensional transistors.
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All authors Chang Niu, Adam Charnas, Jian-Yu Lin, Linjia Long, Zehao Lin, Zhuocheng Zhang, Peide D. Ye

Statistical Mechanics

Cellular Automata: From Structural Principles to Transport and Correlation Methods

Mihir Metkar, Neha Sah and Yichen Zhou

Cellular automata (CA) are discrete-time dynamical systems with local update rules on a lattice. Despite their elementary definition, CA support a wide spectrum of macroscopic phenomena central to statistical physics: equilibrium and nonequilibrium phase transitions, transport and hydrodynamic limits, kinetic roughening, self-organized criticality, and complex spatiotemporal correlations. This survey focuses on three tightly connected themes. (i) We present a structural view of CA as shift-commuting maps on configuration spaces, emphasizing rule complexity, reversibility, and conservation laws (including discrete continuity equations). (ii) We organize transport in CA into ballistic, diffusive, and anomalous regimes, and connect microscopic currents to macroscopic laws through Green–Kubo formulas, scaling theory, and universality classes. (iii) We develop correlation-based methods – from structure factors and response formulas to computational mechanics and data-driven inference – that diagnose regimes and enable coarse-graining.
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Statistical Mechanics

Thermodynamic geometry of friction on graphs: Resistance, commute times, and optimal transport

Jordan R Sawchuk and David A Sivak

We demonstrate that the thermodynamic friction metric governing dissipation in slowly driven continuous-time Markov chains is equivalent to the commute-time embedding and the resistance distance. This equivalence yields complementary insights: The commute-time embedding demonstrates the intrinsic cost of transporting probability across dynamical bottlenecks, while the resistance distance maps thermodynamic dissipation to Joule heating in an electrical network. We further demonstrate that the linear-response thermodynamic distance is a discrete $L^2$-Wasserstein optimal transport cost evaluated along paths of equilibrium distributions, extending a continuous-state correspondence to discrete networks. This conceptual synthesis of linear-response thermodynamics, random walks on graphs, electrical circuits, and optimal-transport theory connects independently developed geometric frameworks, reduces complex metric calculations to simple circuit algebra, and provides a clear physical picture of dissipation as the energetic cost of routing probability through the state space network.
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Statistical Mechanics · Cross-listed from q-fin.MF

Critical volatility threshold for log-normal to power-law transition

Valerii Kremnev

Random walk models with log-normal outcomes fit local market observations remarkably well. Yet interconnected or recursive structures - layered derivatives, leveraged positions, iterative funding rounds - periodically produce power-law distributed events. We show that the transition from log-normal to power-law dynamics requires only three conditions: randomness in the underlying process, rectification of payouts, and iterative feed-forward of expected values. Using an infinite option-on-option chain as an illustrative model, we derive a critical volatility threshold at $\sigma^* = \sqrt{2\pi} \approx 250.66\%$ for the unconditional case. With selective survival - where participants require minimum returns to continue - the critical threshold drops discontinuously to $\sigma_{\text{th}}^{*} = \sqrt{\pi/2} \approx 125.3\%$, and can decrease further with higher survival thresholds. The resulting outcomes follow what we term the Critical Volatility ($V^*$) Distribution - a power-law whose exponent admits closed-form expression in terms of survival pressure and conditional expected growth. The result suggests that fat tails may be an emergent property of iterative log-normal processes with selection rather than an exogenous feature.
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Materials Science · Cross-listed from quant-ph

Simulating Wigner Localisation with the IBM Heron 2 Quantum Processor: A Proof-of-Principle Benchmarking Study

Airat Kiiamov and Dmitrii Tayurskii

We report on a high-fidelity digital quantum simulation of Wigner localisation in a quasi-one-dimensional (quasi-1D) electron system using a 6-qubit segment of the state-of-the-art IBM\,Heron\,2 quantum processor. By mapping the Coulomb interaction Hamiltonian onto a 6-qubit ring lattice, we reconstruct the ground-state energy landscape for a 2-electron Wigner dimer across fifteen interaction regimes in the range $U \in [5, 75]$. This study serves as a rigorous benchmarking exercise, translating foundational experimental models originally developed for electrons on liquid helium into the domain of modern quantum computing. Leveraging the enhanced gate fidelity and tunable coupler architecture of the Heron 2, we demonstrate that the digital simulation accurately captures the energy minimisation trends associated with Wigner dimer formation, achieving a relative error below 7% in the strong-interaction limit. Our results provide a crucial proof-of-principle validation for using superconducting quantum hardware to probe strongly correlated phases of matter with high precision, establishing a baseline for future simulations beyond the classical limit.
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Materials Science

Structural, Bonding, and Optical Properties of B$_{18}$Ca$_2$ Clusters: Double-Ring Forms

P. L. Rodríguez-Kessler

The structural and electronic properties of the doubly calcium-doped boron cluster B$_{18}$Ca$_2$ have been systematically investigated using density functional theory calculations. Basin-hopping searches reveal that B$_{18}$Ca$_2$ adopts a double-ring geometry as its global minimum, consisting of two fused B$_9$ rings symmetrically stabilized by calcium atoms located above and below the boron framework. Vibrational frequency calculations verify the dynamical stability of the low-lying structures, while infrared and UV-Vis spectra highlight strong Ca–B coupling and pronounced electronic delocalization within the boron scaffold. Atomic dipole-corrected Hirshfeld charge analysis indicates substantial charge transfer from Ca to the electron-deficient boron framework, with the donated electrons uniformly delocalized over the B$_{18}$ skeleton. Real-space bonding analyses based on the electron localization function (ELF), Interaction Region Indicator (IRI), and the Laplacian of the electron density reveal an extended multicenter bonding network characterized by global $\sigma$-delocalization and Ca-induced polarization effects rather than localized two-center Ca–B bonds. Together, these results establish B$_{18}$Ca$_2$ as a prototypical boron toroidal cluster and provide fundamental insights into the role of alkaline-earth doping in stabilizing complex boron nanostructures.
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Statistical Mechanics

Stochastic Thermodynamics of Associative Memory

Spencer Rooke, Dmitry Krotov, Vijay Balasubramanian et al. (+1 more)

Dense Associative Memory networks (DenseAMs) unify several popular paradigms in Artificial Intelligence (AI), such as Hopfield Networks, transformers, and diffusion models, while casting their computational properties into the language of dynamical systems and energy landscapes. This formulation provides a natural setting for studying thermodynamics and computation in neural systems, because DenseAMs are simultaneously simple enough to admit analytic treatment and rich enough to implement nontrivial computational function. Aspects of these networks have been studied at equilibrium and at zero temperature, but the thermodynamic costs associated with their operation out of equilibrium are largely unexplored. Here, we define the thermodynamic entropy production associated with the operation of such networks, and study polynomial DenseAMs at intermediate memory load. At large system sizes and intermediate and low load, we use dynamical mean field theory to characterize out-of-equilibrium properties, work requirements, and memory transition times when driving the system with corrupted memories. We characterize a failure mode of higher order networks not observed at zero temperature. Further, we develop a method for calculating work and power costs in the mean field limit. Finally, we find tradeoffs between entropy production, memory retrieval accuracy, and operation speed.
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All authors Spencer Rooke, Dmitry Krotov, Vijay Balasubramanian, David Wolpert

Disordered Systems and Neural Networks

Hopping transport regimes and dimensionality transition: a unified Monte Carlo Random Resistor Network approach

Alejandro Toral-Lopez, Damiano Marian and Gianluca Fiori

Hopping transport, characterized by carrier tunneling between localized states, is a key mechanism in disordered materials such as organic semiconductors, perovskites, nitride alloys, and 2D material-based inks. Two main regimes are typically observed: Variable Range Hopping and Nearest Neighbor Hopping, with a transition between them upon temperature variation. Despite numerous experimental observations, the modeling of this transition remain insufficiently explored and not fully understood. In this work, we present an in-house Monte Carlo Random Resistor Network-based simulator capable of capturing both hopping transport regimes. We demonstrate how material properties that define the network, such as localization length and the spatial and energetic distribution of sites, determine the dominant transport regime. The simulator has been successfully validated against experimental data, showing excellent agreement, reproducing the transition from one regime to the other and accurately capturing 1D, 2D and 3D variable range hopping behavior, providing both a theoretical framework for interpreting experiments and a powerful tool for studying transport mechanisms.
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Strongly Correlated Electrons · Cross-listed from hep-th

Tori, Klein Bottles, and Modulo 8 Parity/Time-reversal Anomalies of 2+1d Staggered Fermions

Nathan Seiberg and Wucheng Zhang

We study the symmetries of lattice staggered fermions in 2+1d. Using the symmetries, we can place the system on any sheared torus or Klein bottle. These different backgrounds provide diagnostics of various 't Hooft anomalies associated with the crystalline symmetries. We then compare the lattice model to its continuum limit. The symmetries of the lattice system are mapped in a nontrivial way to the symmetries of the continuum theories. Using this map, we match the 't Hooft anomalies on the lattice and the continuum. Along the way, we develop a general formalism to study Hamiltonian lattice models on nontrivial, compact, flat spaces.
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Materials Science · Cross-listed from cs.ET

Analog Weight Update Rule in Ferroelectric Hafnia, using pico-Joule Programming Pulses

Alexandre Baigol, Nikhil Garg, Matteo Mazza et al. (+5 more)

In an effort to compete with the brain's efficiency at processing information, neuromorphic hardware combines artificial synapses and neurons using mixed-signal circuits and emerging memories. In ferroelectric resistive weights, the strength of the synaptic connection between two neurons is stored in the device conductance. During learning, programming pulses are applied to the synaptic weight, which reconfigures the ferroelectric domains and adjusts the conductance. One strategy to lower the energy cost during the training phase is to lower the duration of the programming pulses. However, the latter cannot be shorter than the self-loading time of the resistive weights, limited by intrinsic parasitics in the circuits. In this work, ferroelectric resistive weights are fabricated using a process compatible with CMOS Back-End-Of-Line integration, based on hafnia/zirconia nanolaminates. By laterally scaling the device area under 100 $\mu$m$^2$, the self-loading time becomes sufficiently short to enable 20 ns programming, which corresponds to a maximum of 3 picoJoules per pulse. Further, in this work, the weight update rule with 20 ns pulses is experimentally measured not only for different amplitudes but also for different initial conductance states. We find that the final weight is determined by the pulse amplitude, independent of the initial weight value.
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All authors Alexandre Baigol, Nikhil Garg, Matteo Mazza, Yanming Zhang, Elisa Zaccaria, Wooseok Choi, Bert Jan Offrein, Laura Bégon-Lours

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

AutoPot: Automated and massively parallelized construction of Machine-Learning Potentials

Max Hodapp and Guillaume Anciaux

Machine-learning potentials (MLIPs) have been a breakthrough for computational physics in bringing the accuracy of quantum mechanics to atomistic modeling. To achieve near-quantum accuracy, it is necessary that neighborhoods contained in the training set are rather close to the ones encountered during a simulation. Yet, constructing a single training set that works well for all applications is, and likely will remain, infeasible, so, one strategy is to supplement training protocols for MLIPs with additional learning methods, such as active learning, or fine-tuning. This strategy, however, yields very complex training protocols that are difficult to implement efficiently, and cumbersome to interpret, analyze, and reproduce. To address the above difficulties, we propose AutoPot, a software for automating the construction and archiving of MLIPs. AutoPot is based on BlackDynamite, a software operating parametric tasks, e.g., running simulations, or single-point ab initio calculations, in a highly-parallelized fashion, and Motoko, an event-based workflow manager for orchestrating interactions between the tasks. The initial version of AutoPot supports selection of training configurations from large training candidate sets, and on-the-fly selection from molecular dynamics simulations, using Moment Tensor Potentials as implemented in MLIP-2, and single-point calculations of the selected training configurations using VASP. Another strength of AutoPot is its flexibility: BlackDynamite tasks and orchestrators are Python functions to which own existing code can be easily added and manipulated without writing complex parsers. Therefore, it will be straightforward to add other MLIP and ab initio codes, and manipulate the Motoko orchestrators to implement other training protocols.
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Mesoscale and Nanoscale Physics

Topological bound states in the continuum

Dunkan Martinez, Rodrigo P A Lima, Alexander Lopez et al. (+2 more)

Bound states in the continuum, originally proposed within the framework of quantum mechanics, have since been observed in a variety of physical contexts, including electromagnetism, acoustics, and optics. Of particular interest are those bound states in the continuum that are protected by continuous symmetries, as their stability makes them resistant to structural imperfections and material disorder. In this study, we demonstrate the existence of topologically protected bound states in the continuum by coupling a finite Su-Schrieffer-Heeger (SSH) chain to a metallic lead. These states are characterized by distinct features in the electrical response of the system, serving as a direct indication of their topological origin. The inherent robustness of such topologically protected states highlights their potential applications in fault-tolerant quantum information processing as well as in the design of advanced electronic and photonic devices.
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All authors Dunkan Martinez, Rodrigo P A Lima, Alexander Lopez, Francisco Dominguez-Adame, Pedro A Orellana

Soft Condensed Matter

Dilatancy-induced surface deformation in dense cohesive granular media

Huzaif Rahim, Thorsten Poeschel and Sudeshna Roy

When granular materials with interstitial liquid bridges are sheared in a split-bottom cell, a localized shear band develops, accompanied by a surface elevation. Cohesion, governed by the surface tension of the interstitial liquid, enhances dilatancy in dense cohesive packings, leading to expansion within the shear band and the emergence of a surface elevation. Surface deformation is observed not only in cohesive systems with high particle density and large liquid surface tension, but also in those with lower values of these parameters. The equivalent Bond number arises as a key control parameter for the surface deformation, shaping both the evolution of the surface profile and the packing density. At higher shear rates, inertial effects dominate dilatancy, resulting in less pronounced surface deformation.
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Materials Science

Automatic calculation of symmetry-adapted tensors under spin-group symmetry. STENSOR, a new tool of the Bilbao Crystallographic Server

Luis Elcoro, Jesus Etxebarria, J. Manuel Perez-Mato et al. (+1 more)

We present STENSOR, a new computational tool integrated into the Bilbao Crystallographic Server, designed for the automatic calculation of symmetry-adapted tensors under spin group symmetry. The program requires either a file containing the structural data of the magnetic compound or the generators of the oriented spin point group, together with the so-called generalized Jahn symbol associated to the tensor of interest. The user can propose any arbitrary tensor type or select a particular one from a predefined list. The program output returns the symmetry-adapted tensor under the spin point group and also under the magnetic point group, which is also calculated. The comparison of these two tensor forms allows to distinguish the coefficients that are due to spin-orbit coupling effects from those that have a non-relativistic origin and thus are usually more important. A couple of examples are given to illustrate the operation of the program.
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All authors Luis Elcoro, Jesus Etxebarria, J. Manuel Perez-Mato, Emre S. Tasci