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Physics Condensed Matter

cond-mat Watch Condensed Matter

Tuesday 5 May

Mesoscale and Nanoscale Physics · Cross-listed from physics.atm-clus

Reflections on future problems in cluster science

K.Hansen, V.V.Kresin, R.Alhyder et al. (+22 more)

This article is a collection of contributions from speakers at the 2025 DEAMN [Dynamics of Electrons in Atomic and Molecular Nanoclusters] workshop at the Majorana Centre in Erice. Not ordinary contributions to a conference proceeding, this gives a new and different perspective on the work done by the workshop participants.
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All authors K.Hansen, V.V.Kresin, R.Alhyder, M.Lemeshko, M.Fárník, J.Fedor, P.Ferrari, L.X.Worutowicz, R.J.Louwerse, D.Kiawi, L.B.F.M.Waters, S.M.Lang, J.M.Bakker, B. v.Issendorff, W.Kong, J.Mehmel, R.Schäfer, S.Pedalino, B.E.Ramírez-Galindo, R.Ferstl, S.Sindelar, S.Gerlich, M.Arndt, S.G.Sayres, L.-S.Wang

Statistical Mechanics

From Enhanced Sampling to Human-Readable Representations of Protein Dynamics

Souvik Mondal, Michael A. Sauer and Matthias Heyden

Understanding protein conformational dynamics is essential for elucidating biological function but remains challenging due to the wide range of timescales and the complexity of collective motions. Enhanced sampling methods overcome timescale limitations of conventional molecular dynamics, yet their effectiveness depends on the choice of collective variables (CVs), which are often difficult to define and may lack physical interpretability. In particular, collective variables derived from machine learning or collective vibrational modes can efficiently capture slow dynamics but are not easily mapped onto intuitive structural descriptors. Here, we present a fully automated framework that transforms enhanced sampling trajectories into human-readable representations of protein dynamics. Our approach combines enhanced sampling along CVs derived from frequency-selective anharmonic mode analysis with a post hoc analysis of biased trajectories using weighted dynamic cross-correlation matrices. From these, we identify residue pairs and domains exhibiting correlated and anti-correlated motions, yielding simple domain-domain distances that serve as physically interpretable CVs. We apply this method to five proteins, including KRAS and HIV-1 protease, and show that it consistently identifies biologically relevant domains and motions without prior system-specific knowledge. Projection onto these distances produces free energy surfaces that reproduce known conformational states with low statistical uncertainty while maximizing independent dynamical information. This workflow enables systematic recasting of complex CVs into simple geometric descriptors without loss of essential dynamics. Its generality and automation make it broadly applicable for interpreting enhanced sampling simulations and generating interpretable conformational ensembles for integration with emerging machine learning approaches.
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Statistical Mechanics · Cross-listed from quant-ph

Finite-frequency fluctuation-response bounds for open quantum systems

Jie Gu and Kangqiao Liu

We derive a finite-frequency fluctuation-response inequality for Markovian open quantum systems in an input-output setting. For any downstream measurement of the emitted field, the measured lock-in response-to-noise matrix is bounded by the output-field quantum Fisher information rate. For dissipative amplitude modulation with vacuum inputs, this information rate is further bounded by a frequency-independent signal-channel activity, which reduces for kinetic modulation to the stationary channel fluxes. The result is detector-facing but unraveling-independent: it applies after choosing a measurement record, while the information ceiling is set by the quantum field before any detection scheme or trajectory representation is selected. We formulate the bound for multiple signal channels and real finite-frequency quadratures, and illustrate it with a single-sided cavity, resonance fluorescence, and a truncated Kerr-parametric cat resonator.
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Mesoscale and Nanoscale Physics

Time-boundary scattering and topological resonant transmissions

Haiping Hu

Time boundaries (TBs), temporal analogues of spatial interfaces, offer a powerful handle to engineer quantum systems. However, unlike the well-developed stationary scattering theory at spatial interfaces, a unified framework for quantum scattering at TBs has been missing. Here we develop a Bloch-wave scattering theory for TBs by introducing a temporal scattering matrix $S$ between incoming and outgoing Bloch channels. We uncover topological resonant transmissions (RTs) – poles of $S$ that yield perfect interband transmission and dynamical freezing of the quantum state. We establish a bulk-time-boundary correspondence for all integer Altland-Zirnbauer classes: the number of RTs equals the jump of the bulk topological invariant across the TB. In one dimension this gives a time-domain Levinson's theorem. A topological analysis further reveals a striking dimensional dependence. In even dimensions RTs are robust to temporal modulations and disorder, whereas in odd dimensions they can be destroyed by dynamical symmetry breaking. Our work places temporal and spatial scattering on the same footing and opens new avenues for engineering and probing quantum dynamics.
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Soft Condensed Matter · Cross-listed from physics.class-ph

Revisiting the Stress Field Inside an Elastic Sphere Subjected to a Concentrated Load

Yosuke Mori, Kiwamu Yoshii and Satoshi Takada

We present a complete analytical solution for the stress field inside a homogeneous, inside a homogeneous, linearly elastic solid sphere subjected to a concentrated normal load applied on its surface. Starting from the three-dimensional linearized elastodynamic equations, the displacement and stress fields are derived using scalar and vector potential representations combined with spherical harmonic expansions. All expansion coefficients are determined explicitly by enforcing the traction boundary conditions. The static elastic solution is obtained rigorously as the long-time limit of the dynamical formulation. Closed-form expressions for all components of the stress tensor are provided, enabling direct evaluation of the principal stresses and their differences throughout the interior of the sphere. The analytical solution is further generalized to arbitrary loading positions by means of rotational transformations, allowing systematic treatment of multiple concentrated loads through superposition.
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Monday 4 May

Materials Science · Cross-listed from physics.ins-det

Particulate analysis of post-thermal runaway soot of Li-ion battery using X-ray computed tomography

Avtar Singh and Donal P. Finegan

The microstructural characteristics of soot generated during thermal runaway events in lithium-ion batteries have been examined, with a focus on the associated health risks. X-ray computed tomography (Nano-CT) offers advanced 3D imaging for accurate analysis of particle shape, size, and distribution. Its primary benefit is the detection of core-shell structures that contain thin shell of carcinogenic materials. In contrast, traditional techniques like X-ray diffraction can only quantify the mass fraction of these hazardous phases, which is often minimal. Nevertheless, even a small mass fraction of carcinogenic materials on carbonaceous surfaces poses significant health risks when inhaled, potentially compromising internal organ function. This research underscores the need for a deeper understanding of particulate composition to inform safety regulations and respiratory protection measures.
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Soft Condensed Matter

Quantifying the effects of particle clustering in random thermoelastic composites – numerical and mean-field analyses

Pawel Holobut, Michal Majewski and Katarzyna Kowalczyk-Gajewska

The effect of space distribution of randomly-placed particles in a representative composite volume on the thermoelastic effective properties and local stress and strain distribution is analyzed. Quantitative assessment is performed using both the full-field finite element analyses and the mean-field interaction model, known also as a ”cluster” model. The latter model is developed in the multi-family setting enabling one to study the mean stress and strain separately for each inclusion of the representative unit cell. The particles are assumed to be spherical and of equal size, while considered examples differ by the volume fraction of inclusions and mean nearest-neighbour distances.
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Mesoscale and Nanoscale Physics

Nonlinear Coherent Transport in 2D Thermal Metamaterials: From Solitons and Topological Defects to Quantum Computing

R. A. C. Correa, K. N. M. Sharma, P. Lolur et al. (+1 more)

Understanding heat transport in low-dimensional and nano-architectured materials remains a central challenge in nonequilibrium statistical physics due to persistent deviations from Fourier's law. These deviations are driven by anharmonicity, reduced dimensionality, and the emergence of long-lived coherent excitations. In this work, we develop a unified theoretical framework for two-dimensional thermal metamaterials that combines nonlinear lattice dynamics, soliton-based effective field theories, and geometrically organized defect networks as guiding structures for energy flow. We introduce minimal discrete and continuum-inspired models suitable for controlled benchmarking of thermal transport in patterned two-dimensional architectures and identify a two-channel transport mechanism in which coherent nonlinear excitations coexist with incoherent hydrodynamic modes. The interplay between these channels is shown to be highly sensitive to geometry, nonlinearity, and temperature, offering new avenues for thermal management. We establish rigorous connections between microscopic nonlinearity, geometry-driven channeling of heat in two dimensions, and quantum-enabled exploration of both high-occupation classical regimes and genuinely quantum regimes beyond the reach of standard simulation strategies. The theoretical predictions are corroborated by recent experimental and computational results in Stone-Wales-defected PdSSe monolayers and silicon phononic crystal nanostructures, which exhibit ultra-low thermal conductivity coexisting with high carrier mobility and strong anisotropy – direct manifestations of the two-channel mechanism. This synthesis provides actionable guidance for the design of engineered heat-spreading architectures and positions quantum simulation as a transformative tool for advancing the theory of nonlinear heat transport.
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All authors R. A. C. Correa, K. N. M. Sharma, P. Lolur, J. van Velzen

Statistical Mechanics · Cross-listed from hep-ph

Constraining Tsallis Corrections to Photon Reheating from Electron-Positron Annihilation: A Phenomenological Approach

Matias P. Gonzalez

In this work we generalize the entropy transfer from electron-positron annihilation to photons in the early Universe. The generalization is implemented within the Tsallis formalism by using generalized distribution functions derived from Curado-Tsallis constraints. Through this deformation, the entropy density of the electromagnetic sector is modified, while the photon component is kept extensive. Therefore, the nonextensive correction is introduced only in the $e^-e^+$ pairs. This affects the entropic degrees of freedom before electron-positron annihilation and consequently modifies the temperature ratio $T_\nu/T_\gamma$. The resulting correction is then mapped into an effective value of \(N_{\rm eff}\) within the instantaneous decoupling approximation. Comparing this effective thermodynamic estimate with CMB$+$BAO data, and using BBN only as an illustrative Gaussian comparison, we obtain an order-of-magnitude phenomenological interval for the nonextensive parameter. The result should not be interpreted as a precision neutrino decoupling constraint, since a full treatment would require solving the kinetic evolution of the neutrino sector, including non-instantaneous decoupling, finite-temperature QED effects and possible spectral distortions.
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Materials Science

From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

Aritra Roy, Kevin Shen, Andrew MacBride et al. (+350 more)

Large language models (LLMs) are rapidly changing how researchers in materials science and chemistry discover, organize, and act on scientific knowledge. This paper analyzes a broad set of community-developed LLM applications in an effort to identify emerging patterns in how these systems can be used across the scientific research lifecycle. We organize the projects into two complementary categories: Knowledge Infrastructure, systems that structure, retrieve, synthesize, and validate scientific information; and Action Systems, systems that execute, coordinate, or automate scientific work across computational and experimental environments. The submissions reveal a shift from single-purpose LLM tools toward integrated, multi-agent workflows that combine retrieval, reasoning, tool use, and domain-specific validation. Prominent themes include retrieval-augmented generation as grounding infrastructure, persistent structured knowledge representations, multimodal and multilingual scientific inputs, and early progress toward laboratory-integrated closed-loop systems. Together, these results suggest that LLMs are evolving from general-purpose assistants into composable infrastructure for scientific reasoning and action. This work provides a community snapshot of that transition and a practical taxonomy for understanding emerging LLM-enabled workflows in materials science and chemistry.
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All authors Aritra Roy, Kevin Shen, Andrew MacBride, Awwal Oladipupo, Mudassra Taskeen, Wojtek Treyde, Ruaa A. E. A. Abakar, Ahmad D. Abbas, Elsayed Abdelfatah, Abbas A. Abdullahi, Seham S. Abyah, Chahd Rahyl Adjmi, Fariha Agbere, Savyasanchi Aggarwal, Muhammad Ahmed, Tasnim Ahmed, Motasem Ajlouni, Mattias Akke, Hussein AlAdwan, Anwaar S. Alazani, Zahra A. Alharbi, Wajd A. Aljulyhi, Mohammed A. AlKubaish, Fatima A. Almahri, Sayed A. Almohri, David Obeh Alobo, Mohammed Alouni, Azizah S. Alqahtani, Omar Alsaigh, Husain Althagafi, Md. Aqib Aman, Lena Ara, Arifin, Ignacio Arretche, Abdulaziz Ashy, Syeda A. Asim, Amro Aswad, Adeel Atta, Sören Auer, Abdullah al Azmi, Toheeb Balogun, Suvo Banik, Viktoriia Baibakova, Shakira A. Baksh, Neus G. Bastús, Christina J. Bayard, Adib Bazgir, Louis Beal, Lejla Biberić, Wahid Billah, Ankita Biswas, Joshua Bocarsly, Montassar T. Bouzidi, Esma B. Boydas, Youssef Briki, Cailin Buchanan, Mauricio Cafiero, Damien Caliste, Yi Cao, Rafael E. Castañeda, Sruthy K. Chandy, Benjamin Charmes, Shayantan Chaudhuri, Yiming Chen, Alexander Chen, Jieneng Chen, Min-Hsueh Chiu, Defne Circi, Cinthya H. Contreras, Yoann Cure, Nathan Daelman, Roshini Dantuluri, Thomas Davy, William Dawson, Leonid Didukh, Rui Ding, Aminu R. Doguwa, Claudia Draxl, Sathya Edamadaka, Oulaya Elargab, Christina Ertural, Matthew L. Evans, Edvin Fako, Hossam Farag, Nur A. Fathurrahman, Merve Fedai, Rodrigo P. Ferreira, Giuseppe Fisicaro, Thomas Frank, Sasi K. Gaddipati, Abhijeet Gangan, Jennifer Garland, James Garrick, Luigi Genovese, Maryam Ghadrdran, Sandip Giri, Maxime Goulet, Jeremy Goumaz, Sara U. Gracia, Jacob Graham, Gabriel Graves, Kevin P. Greenman, Tim Greitemeier, Cameron Gruich, Sophie Gu, Salomé Guilbert, Hans Gundlach, Muriel F. Gusta, Mourad El Haddaoui, Alexander J. Haibel, Anubhab Haldar, Vehaan Handa, Hassan Harb, Nathan D. Harms, Abdullah Al Hasan, Abir Hassan, Qiyao He, Andrés Henao-Aristizábal, Bram Hoex, Sungil Hong, Alexander J. Horvath, Md. Shaib Hossain, Yanqi Huang, Yuqing Huang, Kostiantyn Hubaiev, Donald Intal, Katherine Inzani, Kevin Ishimwe, Tugba Isik, Gopal R. Iyer, Katharina Jager, Jan Janssen, Hyewon Jeong, Michael Jirasek, Tyler R. Josephson, Nisarg Joshi, Yassir Ben Kacem, Remya A. M. Kalapurakal, Rakesh R. Kamath, Sugan Kanagasenthinathan, Dohun Kang, Jason Kantorow, Kübra Kaygisiz, Murat Keceli, Farhana Keya, Muhammad U. Khan, Sartaaj Takrim Khan, Hyungjun Kim, Alexander Kister, Sascha Klawohn, Collin Kovacs, Pranav Krishnan, Maurycy Kryzanowski, Ritesh Kumar, Suman Kumari, Gourav Kumbhojkar, Ryo Kuroki, Shashank Kushwaha, Magdalena Lederbauer, Jaejun Lee, Seunghan Lee, Jeonghwan Lee, Bingcan Li, Calvin Li, Zhanzhao Li, Shi Li, Shicheng Li, Chengyan Liu, Hao Liu, Tung Yan Liu, Yutong Liu, Lucia Vina-Lopez, Chayaphol Lortaraparsert, Andre K.Y. Low, Saffron Luxford, Carlos Madariaga, Rishikesh Magar, Piyush R. Maharana, Rahul Mallela, Shoaib Mahmud, Natesan Mani, Umair Mansoor, Omar B. Mansour, Cassandra Masschelein, Kinga O. Mastej, Ankit Mathanker, Jeffrey Meng, Omran Mezghani, Yidong Ming, Rishav Mitra, Michail Mitsakis, Matthew Miyagishima, Ravikumar Mohan, Naveen R. Mohanraj, Trupti Mohanty, Bernadette Mohr, Francisco A. Molina-Bakhos, Jeremy Monat, Seyed Mohamad Moosavi, Shayan Mousavi, Arman Moussavi, Rubel Mozumber, Muhammad J. Mufti, Diyana Muhammed, Ram Munde, Mrigi Munjal, José A. Márquez, Shankha Nag, Giacomo Nagaro, Juno Nam, Jose M. Napoles-Duarte, Ry Nduma, Xuan-Vu Nguyen, Ebrahim Norouzi, Oluwatosin Ohiro, Ryotaro Okabe, Viejay Ordillo, Shuichiro Ozawa, Sebastian Pagel, Daniel Palmer, Angela Pan, Akash Pandey, Vivek Pandit, Prakul Pandit, Chiku Parida, Jaehee Park, Hyunsoo Park, Hemangi Patel, Shakul Pathak, Taradutt Pattnaik, Elena Patyukova, Noah Paulson, Deepak S. Pendyala, Erick S. Pepek, Martin H. Petersen, Thang D. Pham, Aniket Phutane, Sabila K. Pinky, Étienne Polack, Alison Polasik, Maria Politi, Tim Pongratz, Akhila Ponugoti, Fabio Priante, Thomas Michael Pruyn, Sai S. Puppala, Mohammad A. Qazi, Heike Quosdorf, Gollam Rabby, Mohammad J. Raei, Md. Habibur Rahman, A.B.M. Ashikur Rahman, Subhashree Rajasekaran, Tawfiqur Rakib, Hemanth N. Ramesh, Vrushali Ranadive, Karnamohit Ranka, Bojana Rankovic, Adwaith Ravichandran, Ilija Rašović, Sergei Rigin, Tatem Rios, Varun Rishi, Victor Naden Robinson, Lucas S. Rodrigues, Oswaldo Rodriguez, Mahule Roy, Diptendu Roy, Subhas Roy, Arokia Anto Royan M, Joseph F. Rudzinski, Muhammad Sabih, Subramanyam Sahoo, Srusti Bheem Sain, Thahira Saliya, Vignesh Sampath, Jesus Diaz Sanchez, Arthur S. S. Santos, Muliady Satria, Hasan M. Sayeed, Jörg Schaarschmidt, Philippe Schwaller, Nofit Segal, Abhishec Senthilvel, Sherjeel Shabih, Devanshu Shah, Faezeh Shahmoradi, Samiha Sharlin, Killian Sheriff, Qiuyu Shi, Abubakar D. Shuaibu, Ayesha Siddiqua, M.A. Shadab Siddiqui, Darian Smalley, Benjamin Smith, Taylor D. Sparks, Daniel T. Speckhard, Elena Stojanovska, Akshay Subramanian, Jiwon Sun, Yunkai Sun, Abdul W. Syed, Souvik Ta, Izumi Takahara, Kelly Tallau, Guannan Tang, Ans B. Tariq, Sui X. Tay, Nurlybek Temirbay, Surya P. Tiwari, Febin Tom, Tajah Trapier, Kasidet J. Trerayapiwat, Samanvya Tripathi, Hawra H. Tuhaifa, Mustafa Unal, Mohammad Uzair, Vallabh Vasudevan, Estefania Vazquez, Victor Venturi, Rahul Verma, Ashwini Verma, Alvaro Vazquez-Mayagoitia, Nicholas Wagner, Araki Wakiuchi, Hao Wan, Liaoyaqi Wang, Wolfgang Wenzel, Alexander Wieczorek, Sze H. Wong, Yue Wu, Tong Xie, Andrew Yi, Ziqi Yin, Jodie A. Yuwono, Nahed A. Zaid, Mohd Zaki, Shehtab Zaman, Maimuna U. Zarewa, Mahtab Zehtab, Baosen Zhang, Wenyu Zhang, Melody Zhang, Yangfan Zhang, Yuwen Zhang, Runze Zhang, Zongmin Zhang, Huanhuan Zhao, Yuanlong Bill Zheng, Ramzi Zidani, Xue Zong, Ian Foster, Ben Blaiszik

Soft Condensed Matter

Equilibrium fluctuations of a quasi-spherical vesicle: role of the membrane dissipation

Petia M. Vlahovska and Rony Granek

We theoretically investigate the thermally-driven curvature and lipid density fluctuations of a quasi-spherical vesicle, accounting for the dissipation due to monolayer viscosity and intermonolayer friction. The theory predicts that membrane curvature makes long-wavelength undulations sensitive to membrane viscosity and speeds up the relaxation of the lipid density fluctuations. Implications for the dynamic roughness and Dynamic Structure Factor measurements of submicron liposomes on nano-second time scales are discussed. Specifically, a clear stretched-exponential relaxation regime may not exist, in contrast to the behavior of planar membranes for which an anomalous diffusion exponent of 2/3 has been predicted [Zilman and Granek, Phys. Rev. Lett. (1996)].
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Other Condensed Matter · Cross-listed from quant-ph

Completely-positive non-signalling non-Markovian dynamics

Serhii Kryhin and Vivishek Sudhir

We define non-Markovian quantum dynamics as evolution in which the current state depends on all past states, and completely characterize its structure under the assumptions of complete positivity and non-signalling. The resulting continuous-time dynamics is an integro-differential equation that augments the Gorini-Kossakowski-Sudarshan-Lindblad equation with a memory integral, and is capable of describing the quantum state of systems exposed to noise with any integrable power spectral density with no further approximations. We then establish a formalism to evaluate multi-time correlations of measurement outcomes in this general setting, obviating the need for a regression theorem. As an application, we derive the emission spectrum of a driven two-level system coupled to a non-Markovian bath: the familiar Mollow triplet acquires a frequency-dependent linewidth that encodes the memory of the bath. Our work provides a rigorous yet transparent description of the quantum state of non-Markovian systems, opening the door for state estimation and state-based quantum control beyond the Markovian regime.
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Statistical Mechanics

Universal criticality of entropy production in chemical reaction networks

Kyota Tamano and Keiji Saito

Stochastic thermodynamics gives universal relations for microscopic entropy production, yet its critical behavior at macroscopic nonequilibrium transitions remains unclassified. We study well-mixed reversible chemical reaction networks in the macroscopic-first limit, where transitions arise as local bifurcations of mass-action dynamics. Using linear-noise formulas, center-manifold normal forms, and Floquet theory, we obtain generic exponents for entropy-production fluctuations and responses at pitchfork, transcritical, saddle-node, and Hopf bifurcations. Beyond this low-order classification, a trajectory-space Cramér-Rao type bound yields the universal scaling inequality $\alpha - 2\beta \geq 0$. Hence divergent responses require divergent fluctuations, but not conversely, making entropy-production fluctuations a sharper probe of nonequilibrium criticality.
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Statistical Mechanics

Non-Markovian entropy production fluctuation theorem driven by a time-dependent electric field

K. S. Rodríguez-Vigil, M. A. Bastarrachea-Magnani and J. I. Jiménez-Aquino

Fluctuation theorems are key to understanding both fundamental and applied aspects of non-equilibrium thermodynamics of small systems. We study the non-Markovian entropy production fluctuation theorem for the diffusion process of charged particles in a gas inside a harmonic potential and under the action of a time-dependent electric field, using a generalized Langevin equation. By considering the influence of the electric field on both the tagged Brownian particle and the bath particles, an "induced" electric force arises. Despite the additional force, we demonstrate that Kubo's second fluctuation-dissipation theorem (FDT) remains unchanged. The FDT allows us to obtain the Gaussian probability density for the position along a single stochastic trajectory, which is the key to demonstrating the validity of the detailed fluctuation theorem (DFT) for the total entropy production. We study the specific result of an Ornstein-Uhlenbeck-type friction memory kernel and an oscillating electric field, and analyze the average work and entropy production in different parameter regimes.
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Mesoscale and Nanoscale Physics · Cross-listed from quant-ph

Operating a bistable qubit

Fabrizio Berritta, Jan A. Krzywda, Tom Dvir et al. (+4 more)

Parasitic two-level-system (TLS) defects limit the stability and performance of solid-state quantum processors. Their interaction with a qubit can cause discrete, stochastic shifts of the qubit frequency, making the qubit bistable. We experimentally demonstrate an adaptive protocol for operating a bistable qubit with high fidelity using a classical controller powered by a field-programmable gate array (FPGA). Our "1-bit feedback" protocol estimates the qubit's bistable frequency from only one single-shot measurement, reaching the information limit set by the qubit's intrinsic entropy. We validate the protocol in a superconducting qubit by suppressing TLS-induced Ramsey beating, and deploy it to stabilize gate fidelities over time with approximately 136 kHz estimation bandwidth and a 77% error reduction. Our approach provides a simple, yet fundamentally efficient strategy for mitigating dephasing errors induced by strongly coupled TLS defects, and may enable the operation of large future qubit arrays suffering from few remaining, discrete instabilities.
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All authors Fabrizio Berritta, Jan A. Krzywda, Tom Dvir, Paul Buttles, Stanislav Eilhart, Jeroen Danon, Ferdinand Kuemmeth

Superconductivity

Nb$_3$Sn Thin Films Using a Cu-Sn Route for Dark Matter Detection

Andre Juliao

Axion dark matter searches require superconducting radio-frequency (SRF) cavities on copper (Cu) substrates with quality factors Q > 10^5 in multi-tesla magnetic fields. Copper reduces thermal noise and allows complex geometries. Nb3Sn is a strong candidate due to its superior superconducting properties. However, uniform high-Tc Nb3Sn thin films on Cu are challenging due to Sn loss and substrate strain. This work uses solid-state diffusion of Sn from high-Sn Cu-Sn alloys into Nb layers to form Nb3Sn at Cu-compatible temperatures (650-750{\deg}C), avoiding the traditional ~1100{\deg}C vapor method. Varying Cu-Sn composition yielded an optimal alloy that maintains high Sn activity. Compositional and thermal expansion analyses showed Tc is suppressed below 18 K by Cu substrate strain. Experiments on Nb and sapphire substrates isolated the strain effects. Two routes were developed: (1) Cu-Sn on Ta-coated Cu with hot Nb sputtering (Tc = 16 K), and (2) Nb on Ta/Cu with Cu-Sn evaporation and ex-situ reaction. Route 2 gave uniform Nb3Sn and was chosen for cavity coating. A hexagonal cavity combining designs from the University of Washington and Center for Axion and Precision Physics was coated using Route 2 and tested to 50 mK and 9 T. At zero field it reached Q = 77,000 (40% above bare Cu's Q = 55,000), but Q dropped sharply in field. Nb3Sn coatings on Cu cavities outperform bare Cu at zero field and provide practical routes for improved axion detectors.
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Strongly Correlated Electrons

Transition Metal Dichalcogenide Excitons in Periodic Electrostatic Potentials: Center-of-Mass Models

Jose M. Torres-Lopez, Sudipta Kundu, Felipe H. da Jornada et al. (+2 more)

Two-dimensional (2D) van-der-Waals materials are a promising platform for exciton state engineering. In this paper, we study the properties of excitons in 2D group VI transition-metal dichalcogenide (TMD) semiconductors that are modified by a periodic electrostatic potential through the quadratic Stark effect. Using a model that retains only center-of-mass and valley degrees-of-freedom, we find that electrostatic potentials can drive optical valley splitting up to 10meVs and induce valley selective exciton dispersion. We explain why both properties are sensitive to the rotational symmetry of the electrostatic trapping potential using a combination of numerical results and analytical approximations. An important consequence of valley-splitting is that the lowest exciton band is non-degenerate and has a linear dispersion around $\gamma$ that is expected to suppress thermal excitations, allowing true Bose condensation and superfluidity of excitons in two space dimensions.
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All authors Jose M. Torres-Lopez, Sudipta Kundu, Felipe H. da Jornada, Tony Heinz, Allan H. MacDonald

Mesoscale and Nanoscale Physics

Thermal bottleneck in a freely suspended superconducting island on InAs nanowire

E.V. Shpagina, E.S. Tikhonov, D. Ruhstorfer et al. (+2 more)

We investigate the heat balance in superconducting islands (S-islands) formed in epitaxial Al/InAs nanowires (NWs) freely suspended above the substrate. We employ a Joule spectroscopy approach, which traces the superconductor-normal transition in the S-island mediated by heating of the neighboring InAs NW segments via transport current. The temperature of the surrounding 3He bath is varied with nearby mesoscopic heaters and controlled with the NW Johnson noise thermometry. The experiment reveals a substantial thermal relaxation bottleneck associated with the cooling via surrounding 3He, which gives rise to phonon heating in the S-island. Our results uncover the role of environmental cooling in non-equilibrium experiments in S-islands in NW devices.
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All authors E.V. Shpagina, E.S. Tikhonov, D. Ruhstorfer, G. Koblmueller, V.S. Khrapai

Superconductivity

Quantum Geometric Quadrupole of Cooper Pairs

Wenqin Chen, Kaijie Yang, Ting Cao et al. (+3 more)

The size of Cooper pairs defines a fundamental length scale of superconductivity, conventionally set by band dispersion and the superconducting gap. This picture breaks down in flat bands, where quenched dispersion makes quantum geometry essential. Here we develop a general framework based on the Cooper pair quadrupole moment, whose trace gives the pair size. The framework holds for both dispersive and flat-band cases, and provides a unified description of the geometric origin of this length scale. In particular, when time-reversal symmetry is broken, Berry curvature enters through the phase structure of the pair wavefunction and gives an essential contribution absent from previous quantum-metric theories. Together, Berry curvature and quantum metric impose a geometric lower bound on the pair size. Applying this framework to rhombohedral graphene, we find that the Berry-curvature-induced contribution can dominate and yields pair sizes comparable to experimentally inferred coherence lengths. These results identify Berry curvature as a central geometric ingredient controlling the microscopic length scale of superconductivity.
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All authors Wenqin Chen, Kaijie Yang, Ting Cao, Shi-Zeng Lin, Jiabin Yu, Di Xiao

Mesoscale and Nanoscale Physics

Bogoliubov mode dynamics and non-adiabatic transitions in time-varying condensed media

A.M. Tishin

This study investigates non-adiabatic wave dynamics in condensed media and the transition from adiabatic stability to spectral chaos. We introduce a dimensionless parameter, as a universal metric to quantify phase-mode redistribution at sub-wavelength inhomogeneities. Our framework treats defects as localized sites of adiabaticity violation triggering non-adiabatic parametric excitation of the ground state. Numerical validation in an expanded 50-level bosonic basis demonstrates that the framework accurately distinguishes between adiabatic regimes in ENZ-metamaterials and non-adiabatic transitions in ultrafast magnetic media. We establish a universal scaling law governed by the non-adiabaticity-to-regulation ratio, proving that the proposed metric remains a robust metrological tool for identifying sub-wavelength inhomogeneities across diverse material classes. Computational singularities observed at extreme loads identify the rigorous operational boundaries for coherent mode-mixing. The robustness of the proposed framework is numerically validated, proving the method's reliability for a wide class of non-linear condensed media satisfying the stability criterion. This result provides a rigorous physical justification for the dynamic Hilbert space truncation (effective fermion-like dynamics), ensuring metrological consistency in complex structural environments. These results provide a theoretical foundation for probing ultrafast collective excitations and latent internal stresses, extending structural analysis beyond the traditional diffraction barrier.
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Materials Science

Building a physics-aware AI ecosystem for solid-state hydrogen storage materials

Seong-Hoon Jang, Yiwen Yao, Chuanyu Liu et al. (+66 more)

Hydrogen storage remains a central bottleneck for scalable hydrogen energy systems due to the multiscale and coupled nature of the thermodynamics, kinetics, and microstructural evolution of hydrogen storage materials (HSMs). Although artificial intelligence (AI) has accelerated materials discovery, current approaches remain constrained by fragmented data, limited physical consistency, and weak integration with experimental validation. Here, we propose a unified framework that integrates coherent data infrastructure, physics-grounded modeling, and AI-driven inverse design within a closed-loop discovery paradigm. By embedding physical constraints and experimental feedback, this approach enables adaptive, physically consistent optimization, thereby establishing a pathway toward autonomous, digital-twin-enabled discovery of HSMs.
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All authors Seong-Hoon Jang, Yiwen Yao, Chuanyu Liu, Linda Zhang, Di Zhang, Xue Jia, Hung Ba Tran, Eric Jianfeng Cheng, Ryuhei Sato, Yusuke Ohashi, Toyoto Sato, Yusuke Hashimoto, Mark Allendorf, Nongnuch Artrith, Marcello Baricco, Andreas Borgschulte, Darren P. Broom, Ang Cao, Benjamin W. J. Chen, Lixin Chen, Ping Chen, Eun Seon Cho, Stefano Deledda, Zhao Ding, Martin Dornheim, Michael Felderhoff, Yaroslav Filinchuk, George E. Froudakis, Mingxia Gao, Thomas Gennett, Zaiping Guo, Ikutaro Hamada, Jason Hattrick-Simpers, Bjørn C. Hauback, Michael Hirscher, Torben R. Jensen, Baohua Jia, Hyoung Seop Kim, Takahiro Kondo, Kentaro Kutsukake, Xiao-Yan Li, Tongliang Liu, Piao Ma, Jianfeng Mao, Rana Mohtadi, Hyunchul Oh, Mark Paskevicius, Chris J. Pickard, Astrid Pundt, Anibal Ramirez-Cuesta, Hiroyuki Saitoh, Kaihang Shi, Aloysius Soon, Chenghua Sun, Chris Wolverton, Hiroshi Yabu, Weijie Yang, Zhenpeng Yao, Xuebin Yu, Jianxin Zou, Shouyi Hu, Panpan Zhou, Xi Lin, Zhigang Hu, Zhenhao Zhou, Pengfei Ou, Jiayu Peng, Shin-ichi Orimo, Hao Li

Soft Condensed Matter

Multistable energy landscapes for adaptive microscopic machines

Melody Xuan Lim, Zexi Liang, Gabriel Alkuino et al. (+5 more)

The past few years have seen great strides in our ability to build synthetic microscopic machines. However, the function of such machines is often controlled directly by externally applied fields that deterministically specify the instantaneous machine dynamics. A crucial step towards machines that can respond adaptively to changes in their environment is the ability to program multiple functions that actuate under the same external driving field, so that their internal state dictates which function is executed. Here, we demonstrate that energy landscapes with designed multistability enable the same externally applied field to drive multiple configurations and dynamic responses in microscopic machines, enabling increasing levels of autonomy. We show three examples. First, we write a bistable energy landscape into a microscopic device, enabling the device to exhibit two stable mechanical configurations under the same external magnetic field. Next, adding a second degree of freedom enables differing dynamic responses to the same external magnetic field, which we direct into net displacement of the environment. Finally, we demonstrate how a microscopic machine with a continuous symmetry autonomously channels a single degree-of-freedom magnetic actuation into locomotion and adaptively responds to forces induced by other machines.
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All authors Melody Xuan Lim, Zexi Liang, Gabriel Alkuino, Jason Z. Kim, Itay Griniasty, Teng Zhang, Paul L. McEuen, Itai Cohen

Soft Condensed Matter · Cross-listed from cs.CV

Approaching human parity in the quality of automated organoid image segmentation

Chase Cartwright, Gongbo Guo, Sai Teja Pusuluri et al. (+3 more)

Organoids are complex, three dimensional, self-organizing cell cultures which manifest organ-like features and represent a powerful platform for studying human disease and developing treatment options. Organoid development is characterized by dynamic morphological and cellular organization, which mimic some aspects of organ development. To study these rapid changes over the course of organoid development, advanced imaging and analytical tools are critical to accurately monitor the trajectory of organoid growth and investigate disease processes. In this work, we focus on computer vision and machine learning techniques to automatically measure the size and shape of developing spheroids derived from pluripotent stem cells (iPSCs), which are typically the starting material for generating organoid cultures. To facilitate this task, we introduce a composite method that combines the Segment Anything Model (SAM), a general-purpose foundation model, with an existing domain-specific tool. This composite method is evaluated together with several existing tools by testing them on organoid image data and comparing with the results of manual image segmentation. We find that no single existing tool is able to segment the test images with sufficient accuracy across all test conditions, but the newly introduced composite method produces consistent and accurate results for all but a very small fraction of the most challenging images. Finally, we compare the accuracy of this method to the variability between manual segmentations by independent annotators (inter-observer variability) and find that by one measure it performs at the level of inter-observer variability and by others it performs very close to it.
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All authors Chase Cartwright, Gongbo Guo, Sai Teja Pusuluri, Christopher N. Mayhew, Mark Hester, Horacio E. Castillo

Mesoscale and Nanoscale Physics

Beam canalization by a non-Abelian gauge field

Olha Bahrova, Jiahao Ren, Feng Jin et al. (+3 more)

Hyperbolic and quasi-flat isofrequency contours (IFCs) are used for beam canalization and can be created by tilted Dirac points in photonic systems. Dirac points in microcavities are generated by the combination of transverse-electric/transverse-magnetic splitting and linear birefringence. We show that the canalization is here strongly assisted by the coupling between the spatial dynamics and polarization pseudospin precession. This dynamics is well described analytically and numerically as the action of a non-Abelian gauge field on emergent charges (spin current). We demonstrate a ten-fold enhancement of the canalization for a Gaussian beam by the gauge field, as compared to a description based solely on the group velocity associated with the IFCs.
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All authors Olha Bahrova, Jiahao Ren, Feng Jin, Rui Su, Guillaume Malpuech, Dmitry Solnyshkov

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

Epistatic strength, modularity, and locus heterogeneity shape the number of local optima in fitness landscapes

Mahan Ghafari, Alejandro Castro Cabrera, Alejandro Lage-Castellanos et al. (+3 more)

Fitness landscapes provide a quantitative framework for understanding how natural selection shapes evolutionary trajectories. A central feature of these landscapes is their number of local optima, which determines whether fitness-increasing evolution can proceed towards a global optimum or become trapped on suboptimal peaks. Although multiple peaks are known to require reciprocal sign epistasis, the quantitative relationship between epistasis and number of peaks remains incompletely understood. Here, we show that for a broad class of unstructured fitness landscapes, i.e. isotropic Gaussian random fields, the expected number of local optima is determined by a single local measure of epistasis: the correlation of fitness effects. This provides a baseline prediction for the number of peaks in typical unstructured landscapes and links peak density directly to the amount of reciprocal sign epistasis. This baseline changes when epistatic interactions are structured. We show that clustering interactions within blocks of loci slightly increases the number of local optima. In contrast, strong heterogeneity between loci, where only a small subset of loci participate in epistatic interactions, causes the number of peaks to collapse. These results show that the number of local optima is governed not only by the overall strength of epistasis, but also by how epistatic interactions are distributed across the genotype space. Our framework therefore reconciles the central role of reciprocal sign epistasis with the observation that landscapes with similar amounts of epistasis can differ substantially in ruggedness, and provides a guide to the range of peak numbers expected in typical landscapes.
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All authors Mahan Ghafari, Alejandro Castro Cabrera, Alejandro Lage-Castellanos, Guillaume Achaz, Joachim Krug, Luca Ferretti

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

Information in Many-body Eigenstates: A Question of Learnability

Maksymilian Kliczkowski, Jarosław Pawłowski and Masudul Haque

To what extent do individual eigenstates encode information about their parent Hamiltonian, and how does this encoding vary across the spectrum? We introduce learnability as a new framework to quantify this information, measured by the precision with which a machine learning model can reconstruct a Hamiltonian from a limited set of eigenstates. For many-body quantum systems, there is a contrast between the eigenstates near the spectral edges (low-entanglement, highly-structured states) and those far from the spectral edges (high-entanglement, near-random states). Using an encoder-decoder neural network for a non-integrable spin chain, we show that this dichotomy results in a stark difference in learnability: spectral-edge eigenstates allow for higher-accuracy Hamiltonian reconstruction using significantly fewer eigenstates, compared to mid-spectrum eigenstates. Our results provide a new lens through which to view the spectral structure of many-body systems.
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Disordered Systems and Neural Networks · Cross-listed from quant-ph

Robust spin-squeezing with random interaction graphs: the lesson from universality

Andrea Solfanelli, Augusto Smerzi, Peter Zoller et al. (+1 more)

We establish the conditions under which scalable spin squeezing can be achieved in interacting spin ensembles embedded in arbitrary, inhomogeneous graph geometries. We identify two different forms of squeezing: OAT-like scalable squeezing is governed solely by the universal properties of the interaction graph and is controlled by its spectral dimension. In critical squeezing, on the other hand, the value of the spectral dimension only furnishes the necessary condition for scalable metrological gain, while the sufficient condition requires the model to lie below the symmetry breaking transition. Therefore, in systems with random interaction graphs, the scaling of the spin-squeezing critical point emerges from a nontrivial interplay between xy-ferromagnetic universality and percolation universality. We apply this general theoretical framework to several experimental scenarios and discuss sharp and experimentally relevant conditions for achieving robust metrological gain on generic inhomogeneous structures, giving a unifying perspective for designing scalable quantum sensors across diverse quantum simulation platforms.
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All authors Andrea Solfanelli, Augusto Smerzi, Peter Zoller, Nicolò Defenu

Mesoscale and Nanoscale Physics

Characterizing electronic scattering rates with transport in multiterminal devices

Jack H. Farrell and Andrew Lucas

Strongly interacting electrons in clean two-dimensional devices are theorized to exhibit many distinct transport regimes, such as ballistic, hydrodynamic, or diffusive. Realistic samples often lie in crossover regimes between these idealized limits. We show how a single experiment on a multiterminal device can distinguish these regimes and constrain the relevant scattering rates without space-resolved imaging. Using a linearized Boltzmann model in a five-terminal geometry, we find that current partition among the drain contacts diagnoses the ballistic-hydrodynamic-Ohmic crossover and allows extraction of momentum-relaxing and momentum-conserving scattering rates in the crossover regime. The same geometry also exhibits clear signatures of the tomographic regime, potentially allowing for a quantitative discrimination between viscous and tomographic flow in experiments. Our results demonstrate that multiterminal devices are a simpler experimental route to characterize transport regimes in electron liquids, relative to space-resolved imaging experiments.
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Strongly Correlated Electrons

Spin-orbital exchange as a route to intertwined dipole-quadrupole orbital order in MnV$_2$O$_4$ under strong trigonal crystal field

Hiroki Nakai and Yusuke Nomura

Orbitally degenerate systems provide a promising platform for realizing novel quantum phases driven by spin-orbital exchange interactions, as described by the Kugel-Khomskii model. Spinel vanadates, in which orbital degrees of freedom remain active, exhibit structural and magnetic transitions accompanied by orbital ordering, but the nature of the orbital state in MnV$_2$O$_4$ remains under debate. Here, we combine first-principles calculations with an effective spin-orbital model to address this problem. We show that a significant trigonal crystal field is present in high-temperature cubic phase and plays an essential role in determining the low-energy degrees of freedom. Based on the resulting parameters, we construct an effective Hamiltonian beyond the conventional dominant-hopping approximation and demonstrate that subdominant hopping processes strongly modify the spin-orbital exchange interactions. As a result, the system stabilizes a two-in/two-out magnetic configuration featuring spin canting and intertwined dipole-quadrupole orbital order.
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Mesoscale and Nanoscale Physics

Tunable Mixed Parity Spin Splittings in Altermagnets

Yue Yu

Momentum-dependent spin splitting and its relation to inversion ($P$) and time-reversal ($T$) symmetries are central to nonrelativistic spintronics. Representative examples include collinear altermagnets with $(P,T)=(+,-)$ and non-collinear odd-parity magnets with $(P,T)=(-,+)$. In this work, we develop a theoretical framework to induce odd-parity spin splittings in the more abundant collinear altermagnets through two mechanisms: driving by a two-color linearly polarized light field or coupling to a $P$-odd loop-current order. Properly phase-locked two-color driving induces a static $(P,T)=(-,-)$ order, symmetry-equivalent to a translationally invariant $P$-odd loop-current order. Coupling this order to an altermagnet produces a controllable mixed-parity spin texture, opening new avenues for the electrical and optical manipulation of spin-polarized currents in spintronics applications. The same mechanism applied to a collinear $PT$-symmetric magnet induces a distinct $(P,T)=(+,+)$ state with a nonrelativistic dissipationless anomalous spin Hall conductivity. We present group-theory and microscopic Floquet theory to highlight the emergent responses.
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