Statistical Mechanics · Cross-listed from math.AP
Phase transitions in Doi-Onsager, Noisy Transformer, and other multimodal models
Kyunghoo Mun and Matthew Rosenzweig
We study phase transitions for repulsive-attractive mean-field free energies on the circle. For a $\frac{1}{n+1}$-periodic interaction whose
Fourier coefficients satisfy a certain decay condition, we prove that the critical coupling strength $K_c$ coincides with the linear stability threshold $K_\#$ of the uniform distribution and that the phase transition is continuous, in the sense that the uniform distribution is the unique global minimizer at criticality. The proof is based on a sharp coercivity estimate for the free energy obtained from the constrained Lebedev–Milin inequality. We apply this result to three motivating models for which the exact value of the phase transition and its (dis)continuity in terms of the model parameters was not fully known. For the two-dimensional Doi–Onsager model $W(\theta)=-|\sin(2\pi\theta)|$, we prove that the phase transition is continuous at $K_c=K_\#=3\pi/4$. For the noisy
transformer model $W_\beta(\theta)=(e^{\beta\cos(2\pi\theta)}-1)/\beta$, we identify the sharp threshold $\beta_*$ such that $K_c(\beta) = K_\#(\beta)$ and the phase transition is continuous for $\beta \leq \beta_*$, while $K_c(\beta)<K_\#(\beta)$ and the phase transition is discontinuous for $\beta > \beta_*$. We also obtain the corresponding sharp dichotomy for the noisy Hegselmann–Krause model $W_{R}(\theta) = (R-2\pi|\theta|)_{+}^2$ .
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Statistical Mechanics · Cross-listed from quant-ph
Boson correlations are spurious for classical states
Daniel E. Salazar and Fabrice P. Laussy
We show that
boson correlations from
quantum states with a Glauber-Sudarshan representation of their density
matrix which provides a well-behaved probability distribution – including coherent states, thermal states, and all states that can be deemed classical – are a manifestation of the Simpson paradox: they are spurious correlations from statistical (ensemble) averages over uncorrelated measurements made in varying geometries, due to a process of
symmetry-breaking as a confounding factor. Bosonic correlations encoded by the wavefunction appear to be formed in the geometry assumed, which however is not that of the statistical ensemble but varies from realization to realization. This calls to distinguish between
quantum and statistical averages and sheds new understandings on the fundamental problems of nonclassicality and
quantum advantage.
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Mesoscale and Nanoscale Physics
Benchmarking Current-to-Voltage Amplifiers for Quantum Transport Measurements
J. Escorza, G. Pellicer, T. de Ara et al. (+4 more)
Accurate electrical amplification is essential in molecular electronics for measuring conductance through atomic and molecular junctions, where currents often span several orders of magnitude. In this work, we present a systematic design and comparative analysis of four current-to-voltage ($I\text{--}V$) amplifier architectures: single-stage linear, series-linear, logarithmic, and multi-stage cascaded, specifically optimized for break junction (BJ) techniques, including scanning tunneling microscopy (STM-BJ) and mechanically controllable break junctions (MCBJ). Each configuration is evaluated based on sensitivity, noise performance, and dynamic range. Our results characterize the trade-offs between
circuit complexity and noise, providing a robust framework and practical guidelines for selecting amplification schemes in
quantum transport experiments.
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All authors J. Escorza, G. Pellicer, T. de Ara, J. Hurtado-Gallego, E. Scheer, C. Untiedt, C. Sabater
Soft Condensed Matter
Improved Desalination by Polymer Grafting
Mamta Yadav, Clifford E. Woodward and Jan Forsman
Freshwater scarcity demands desalination technologies that are efficient, scalable, and sustainable. Capacitive deionisation (CDI) is promising but remains limited by inefficient ion adsorption and poor charge utilisation. Here, we show that suitably chosen polyampholytic block copolymer grafting can substantially enhance CDI performance, via a combination of dipolar response and steric effects. Using mean-field classical density functional theory and grand-canonical Monte Carlo simulations, we demonstrate that such
polymer grafted electrodes enable strongly improved desalination performance, without altering the pore architecture. Even an electrode grafting by simple neutral
polymers can generate an improvement, although a suitably designed block
polymer architecture offers an additional performance gain. These results establish interfacial block copolymer grafting as a powerful route toward high-performance, membrane-free desalination.
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Materials Science
Atomistic Mechanisms of Stress-Dependent Molten Salt Corrosion in NiCr Alloys
Hamdy Arkoub, Jia-Hong Ke and Miaomiao Jin
Ni-based structural
alloys in molten salt environments often experience simultaneous mechanical loading and corrosive attack, yet the mechanisms governing stress-corrosion interactions remain unclear. Prior studies largely emphasize tensile stress, while the role of compressive stress has received limited
attention. Here, reactive molecular dynamics simulations are used to investigate the coupled effects of applied strain and corrosion in Ni$_{0.75}$Cr$_{0.25}$ exposed to molten FLiNaK at 800$^\circ$C. A $\Sigma5(210)$ grain boundary model is subjected to tensile (+4%) to compressive (-4%) uniaxial strains, and corrosion behavior is evaluated through fluorine adsorption, charge redistribution, and grain boundary
evolution. Tensile strain accelerates intergranular corrosion by reducing local atomic packing through elastic dilation and increasing excess free volume at the grain boundary, which enhances atomic mobility and salt infiltration. In contrast, compressive strain suppresses corrosion by promoting the formation of a ridge-like surface layer along the grain boundary, limiting salt access to the underlying
alloy. These results provide atomistic insight into how stress states influence grain boundary corrosion in molten salts.
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Statistical Mechanics
MF-toolkit: A High-Performance Python Library for Multifractal Analysis with Automated Crossover Detection, Source Identification and Application to Gravitational Waves Data
Nahuel Mendez, Maria Cristina Mariani Maria Pia Beccar-Varela, Osei Tweneboah et al. (+1 more)
Multifractal Detrended Fluctuation Analysis (MFDFA) is a powerful and widely used technique for characterizing the scaling properties and long-range correlations of complex time series. However, its application often involves significant practical challenges, such as the subjective identification of scaling regions (crossovers) and the disambiguation of the physical origins of multifractality. We introduce MF-toolkit, a high-performance, parallelized Python library designed to address these challenges. It integrates three key innovations: (1) fully automatic crossover detection
algorithms (CDV-A and SPIC), which remove operator bias and enhance reproducibility; (2) a built-in implementation of the Iterative Amplitude Adjusted
Fourier Transform (IAAFT) for generating surrogate data, enabling the robust identification of the source of multifractality; and (3) a comprehensive suite for generating synthetic time series for rigorous validation. We demonstrate the rigor and utility of MF-toolkit through its application to characterize the multifractal properties of non-stationary noise in gravitational wave (LIGO) data. The MF-toolkit library offers a robust, efficient, and user-friendly tool for advanced time series analysis, facilitating more rigorous and reproducible research across physics and other data-intensive fields.
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All authors Nahuel Mendez, Maria Cristina Mariani Maria Pia Beccar-Varela, Osei Tweneboah, Sebastian Jaroszewicz
Materials Science
Bridging Atomistic and Continuum Descriptions of Nanoscale Dislocation Loops in Tungsten
Joseph Duque Lopez, Sergei Dudarev, James Kermode et al. (+1 more)
In order to predict the long-term effects of irradiation on the material properties of tungsten, a continuum approach to simulating the interactions of dislocation loops, which arise from radiation damage, is proposed. Continuum models of the displacement, strain and stress fields produced by dislocation loops exhibit unphysical singularities near the defect core, but are thought to accurately capture atomistic displacements in the far-field. A linear elastic model of nanoscale dislocation loops in tungsten is developed, and the model is verified using atomistic simulations to ensure that the model is informed by lower-length scale phenomena such that the physics of the problem is correctly captured. We discuss the model and its advantages, and show that predictions produced by atomistic simulations do indeed agree well with the far-field behaviour of the continuum model when dislocation loops are far from material boundaries. In particular, we robustly demonstrate that the decay rate of atomistic results and continuum results coincide with one another, and show that the results converge as the size of the atomistic simulations approach the far-field limit.
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All authors Joseph Duque Lopez, Sergei Dudarev, James Kermode, Thomas Hudson
Materials Science
ChemGraph-XANES: An Agentic Framework for XANES Simulation and Curation
Vitor F. Grizzi, Thang Duc Pham, Luke N. Pretzie et al. (+3 more)
Computational X-ray absorption near-edge structure (XANES) is widely used to interpret local coordination environments, oxidation states, and electronic structure, but large computational campaigns are often limited by workflow complexity. We present ChemGraph-XANES, a large
language model (LLM)-based agentic framework that combines documentation-grounded parameter
retrieval via
retrieval-augmented generation (RAG), schema-constrained tool execution, deterministic FDMNES input generation, Parsl-backed execution, and provenance-aware data curation. Scripted and natural-
language interfaces share a common scientific backend for structure handling, parameterization, execution, spectral extraction, and optional post-processing. We evaluate three workflow modes: documentation-grounded parameter propagation, structure-file-based execution, and composition-based execution from a chemistry-level request. Repeated trials yielded end-to-end completion in 10/10 composition-based runs, 10/10 structure-file-based runs, and 9/10 documentation-grounded RAG runs. In every RAG run, the energy-grid specification retrieved from the FDMNES manual was correctly propagated, with the single end-to-end failure occurring downstream during multi-structure handling. In a separate task-parallel demonstration, the framework retrieved 21 TiO$_2$ structures from the Materials Project and submitted one FDMNES calculation per structure. All calculations completed successfully, with Parsl distributing the independent tasks across the user-configured worker pool. Together, these results show that ChemGraph-XANES provides a constrained and reproducible orchestration layer for computational spectroscopy, supporting consistent execution of representative tasks, documentation-linked parameter selection, and task-parallel generation of structure-linked XANES collections.
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All authors Vitor F. Grizzi, Thang Duc Pham, Luke N. Pretzie, Jiayi Xu, Murat Keceli, Cong Liu
Soft Condensed Matter
Geometry-Induced Transport of Self-Aligning Chiral Bristlebots
Timo Wagner, Michael Himpel, Thomas Ihle et al. (+1 more)
Active matter systems characterized by the interplay of chirality and self-
alignment offer a rich landscape for non-
equilibrium collective behaviors and the development of autonomous materials. We present a versatile experimental platform for studying these dynamics using augmented commercial bristlebots, where custom-designed housings and elastic couplings induce a self-aligning torque and stable
chiral drift. By mapping experimental trajectories to a Langevin-type model, we characterize the single-particle dynamics. In circular geometries, we show that the stability of edge currents is governed by the interaction between intrinsic particle chirality and handedness of the edge current. Furthermore, we demonstrate that transport can be geometrically rectified using a nautilus-shaped obstacle acting as a doubly chirality-sensitive ratchet. Finally, we explore the collective dynamics of rigidly linked assemblies, observing spontaneous mode-switching between translational and rotational states in active solids. Our results provide a robust framework for experimental studies in active gases and illustrate how
geometric constraints can be used to program complex transport properties in active systems.
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All authors Timo Wagner, Michael Himpel, Thomas Ihle, Horst-Holger Boltz
Soft Condensed Matter
Spinning Living Crystals of Run-and-Tumble Particles with Environmental Feedback
Maks Pečnik Bambič, Nuno A. M. Araújo and Giorgio Volpe
Collective rotations are common in active matter, enhancing cohesion, transport, and mixing. They are typically attributed to
chiral non-reciprocal dynamics due to intrinsic particle chirality, torque-generating interactions among units, or
geometric confinement. Here, we uncover a different mechanism for rotational order in active matter where a dynamic environment coordinates the self-organization of non-
chiral active particles into living
crystals exhibiting sustained collective solid-like rotations. At intermediate densities, feedback from a fluctuating landscape of passive Brownian particles stabilizes large living
crystals of obstacle-avoiding run-and-tumble
agents. Strikingly, this environmental feedback also produces living
crystals with qualitatively distinct dynamics: collective solid-like spinning emerges for particles with long persistence times approaching ballistic motion, rather than for particles moving by conventional enhanced
diffusion. Beyond revealing a new route to collective rotational order in active matter, these findings highlight the integral role of a dynamic environment in self-organization and suggest environment-mediated design principles for active materials with unconventional dynamical responses.
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Mesoscale and Nanoscale Physics
Hopping-Mediated Charge Transport in Graphene Beyond the Ballistic Regime
J. P. Dadario Pereira, Raphael Tromer, Luiz A. Ribeiro Junior et al. (+1 more)
We present a trajectory-resolved framework for charge transport in
graphene and related two-dimensional carbon systems beyond the ideal ballistic and fully coherent limits. Transport is described by kinetic Monte Carlo hopping on a predefined atomic
lattice, allowing the combined treatment of disorder, thermal activation, and external fields. Current and effective transmittance are extracted directly from
stochastic carrier trajectories, without phenomenological transport coefficients. We apply the method to
graphene under bias voltage (0-0.10 V), temperature (300-900 K),
magnetic field (0-10 T), in-plane strain (2-10%, uniaxial and biaxial), and vacancy concentration (0-10%). Pristine
graphene shows an almost ohmic response, with currents of about 7-8 uA, effective transmittance near 0.98-1.00, and conductance of about (5.8-7.8) x 10^-5 S at 0.10 V, depending on direction. Vacancies strongly suppress transport, reducing transmittance to about 0.45-0.75 at 10% vacancy. Higher temperature accelerates hopping and partly restores transport, but cannot overcome severe connectivity loss.
Magnetic fields further reduce transport, especially in disordered networks. The framework provides a unified computational scheme for realistic two-dimensional carbon materials and also yields
diffusion coefficients and effective mobilities from carrier displacements and transit times.
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All authors J. P. Dadario Pereira, Raphael Tromer, Luiz A. Ribeiro Junior, Douglas S. Galvao
Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
Gravitationally induced wave-function collapse from dynamical bifurcation
C. A. S. Almeida
We propose an effective non-relativistic framework in which wave-function collapse emerges as a deterministic dynamical instability induced by gravitational self-interaction and regulated by short-distance repulsion. The dynamics is described by a nonlinear Schrödinger equation supplemented by a phenomenological repulsive sector ensuring regularity at high densities. Using a variational Gaussian ansatz, we derive an explicit effective energy functional and show that extended
quantum states lose stability beyond a critical mass scale. This loss of stability is associated with a bifurcation in the reduced dynamical system governing the wave-function width, leading to the emergence of stable localized configurations. Within this picture, collapse corresponds to the dynamical selection of one of these localized attractors, driven by infinitesimal asymmetries in the initial state and occurring without
stochastic noise or environmental coupling. The mechanism provides a controlled and quantitative realization of
gravity-induced localization, extending Schrödinger–Newton-type models while avoiding their pathological short-distance behavior. Possible implications for mesoscopic systems probing the
quantum-to-classical transition are briefly discussed.
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Quantum Gases
Observation of Strong-to-Weak Spontaneous Symmetry Breaking in a Dephased Fermi Gas
Si Wang, Thomas G. Kiely, Dorothee Tell et al. (+9 more)
Symmetry-based classification of
quantum phases of matter is one of the most foundational organizing principles in physics; however, an analogous framework for mixed, decohered
quantum states has only begun to emerge. A central new concept is strong-to-weak spontaneous
symmetry breaking (SW-SSB), a sharp transition in mixed
quantum states that is invisible to any observable linear in the density
matrix and that has since been predicted across a broad class of open and monitored
quantum systems. It also provides a unifying
language for phenomena as disparate as the decodability of topological
quantum memories and the emergence of classical hydrodynamics from decohered
quantum dynamics. Here we report the first experimental observation of SW-SSB, in dephased single-component fermionic matter imaged by a
quantum gas microscope. A
quantum-classical
estimator built on a machine-learned Gaussian reference state gives direct access to the nonlinear Rényi-1 and Rényi-2 correlators that diagnose SW-SSB, and reveals long-range Rényi order in the dephased
Fermi liquid. Adding a commensurate superlattice drives the underlying
fermions through a metal-to-
insulator transition that, after full dephasing, manifests as a sharp SW-SSB phase transition. Our results uncover the
symmetry principle behind information-theoretic transitions in open
quantum systems, and extend Landau's
symmetry paradigm into the regime of real, decohering
quantum devices.
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All authors Si Wang, Thomas G. Kiely, Dorothee Tell, Johannes Obermeyer, Marnix Barendregt, Petar Bojović, Philipp M. Preiss, Abhijat Sarma, Titus Franz, Matthew P. A. Fisher, Cenke Xu, Immanuel Bloch
Materials Science
Laser-written reconfigurable energy landscapes and programmable Moiré spin textures
Matteo Panzeri, Piero Florio, Davide Girardi et al. (+18 more)
Magnetic textures are central to emerging spintronic and unconventional computing technologies due to their rich dynamics, topological properties and nanoscale dimensions. A major challenge remains achieving tunable, reversible, and spatially resolved control over these textures and their
evolution as a function of external stimuli, by spatially reprogramming the
magnetic energy landscape that governs their nucleation and stability. Here, we exploit a focused
laser-assisted local field cooling technique that establishes a fast, non-contact and scalable platform for grayscale
spin texture engineering. By non-destructively controlling the exchange-bias anisotropy with nanoscale resolution in thin-film
heterostructures, this approach enables grayscale, reprogrammable control of the local energy profile, which we use to create
magnetic patterns with highly controlled hysteresis, field-dependent readability and tunable switching thresholds. Leveraging this capability, we demonstrate information encoding with
magnetic field-gated readability, and artificial
spin metamaterials, stabilizing
spin lattices with field-reconfigurable
symmetries and creating artificial Moiré
spin textures via the
geometric superposition of twisted
magnetic potentials. These results establish a versatile, reprogrammable platform that bridges the gap between application-oriented
magnetic memory and fundamental studies of emergent order in artificial
lattices.
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All authors Matteo Panzeri, Piero Florio, Davide Girardi, Joseba Urrestarazu, Giacomo Sala, Nicola Pellizzi, Matteo Vitali, Marco Madami, Luca Ciaccarini Mavilla, Silvia Tacchi, Elisa Riedo, Andrea Meo, Vito Puliafito, Mario Carpentieri, Riccardo Tomasello, Efe Ersoy, Kai Wagner, Patrick Maletinsky, Olivier Boulle, Edoardo Albisetti, Daniela Petti
Statistical Mechanics
Exact Steady State of a One-end Driven XXZ Spin Chain with Boundary Field
V. Popkov and T. Prosen
We find an exact nonequilibrium steady state of an open dissipatively driven XXZ
spin-1/2 chain with source or sink
spin bath at one end and an arbitrary boundary field at the other end.
Strongly Correlated Electrons
Spinon shift current in a noncentrosymmetric quantum spin chain
Ryosuke Yamashita, Shintaro Takayoshi and Takahiro Morimoto
We theoretically study direct current generation in a
quantum spin chain induced by spinon excitations by light irradiation. We consider a $S=1/2$ one-dimensional (1D)
antiferromagnetic XXZ model with magnetoelectric coupling that describes multiferroics with broken inversion
symmetry. We perform the real-time simulation using infinite time-evolving block decimation, and demonstrate the direct current generation under light irradiation. By comparing the second order nonlinear conductivity and the two-spinon excitation spectra of a 1D XXZ model, we confirm that the spinon excitations are the origin for the direct current generation in the
quantum spin chain. We find that the bulk photovoltaic effect is driven by electric polarization carried by the spinons through the shift current mechanism, and thus is regarded as “the spinon shift current.”
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Materials Science
Formation of photoinduced space-charge field during in-bulk domain creation by femtosecond NIR laser irradiation in MgO:LN crystals
I. A. Kipenko, D. A. Zorikhin, A. R. Akhmatkhanov et al. (+1 more)
We have studied the domain switching under NIR fs-
laser irradiation in MgO:LN single
crystals with special
attention to the relative positions of the light-induced domains, microtracks and regions with modified refractive index in the vicinity of the focusing point. The optical imaging along X direction of the irradiated sample demonstrated the narrow microtracks and the lens-shaped regions ("lenses") located in the vicinity of the microtracks. The relative positions of light-induced microtracks, domains and lenses were revealed by overlapping of their images. We have found that the domain envelops the microtrack and partially intersects with the lens. The temperature stability of all light-induced objects during annealing was studied. It was shown that the local modification of the refractive index disappeared irreversibly while the microtrack and domain remain unchanged. The obtained local modification of the refractive index has been considered as a result of the photorefractive effect. The disappearance of the lens after annealing is caused by bulk screening of the photoinduced space-charge field by increased bulk conductivity. The generation of photovoltaic field by tightly focused NIR fs-
laser irradiation close to the focusing point is reported for the first time to the authors' knowledge. It should be noted that in LN the photovoltaic field is codirectional with spontaneous polarization and thus cannot switch the polarization. However, it is possible in ferroelectrics with the opposite direction of the photovoltaic field and low value of threshold field. The revealed effect can be utilized for creation of 3D nonlinear photonic
crystals by in-bulk domain engineering.
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All authors I. A. Kipenko, D. A. Zorikhin, A. R. Akhmatkhanov, V. Ya. Shur
Soft Condensed Matter
Discharge at the Microscale: Using Optical Tweezers to Observe Muon-Induced Discharges of a Levitated Microparticle in Air
Andrea Stoellner, Isaac C.D. Lenton, Caroline Muller et al. (+1 more)
Electrical discharge at the smallest possible length and charge scales is not well understood. Using optical tweezers, we investigate spontaneous discharges of a single micron-scale particle levitated in air. These “microdischarges” have a typical size of $\sim$40 $|e|$, but can be as small as a few $|e|$ and as large as several hundred. The absence of a well-defined trigger charge and the weak dependence on particle size suggest events are not classical gaseous breakdown. Instead, we show that microdischarge events arise from the rapid capture of ions left in the tracks of nearby passing ionizing radiation. Our results highlight the role of natural ionizing radiation in initiating micron-scale discharges and provide a platform for studying discharge physics in electrode-free environments and at the smallest scales.
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All authors Andrea Stoellner, Isaac C.D. Lenton, Caroline Muller, Scott Waitukaitis
Materials Science
Micromechanical insights into unconstrained grain boundary sliding
Divya Sri Bandla, Subin Lee and Christoph Kirchlechner
Grain boundary sliding is a key deformation mechanism at high homologous temperatures in polycrystalline materials, however, its intrinsic behavior is often obscured by strain accommodation processes. In this study, dislocation-mediated unconstrained GBS was investigated using Ni bicrystal micropillars containing a high-angle grain boundary. Micropillar compression tests were performed from room temperature to $600\,^{\circ}\mathrm{C}$ and strain rates between $5\times10^{-4}$ and $10^{-1}\,\mathrm{s}^{-1}$. By comparing bicrystal and single-
crystal responses, intrinsic contribution of grain boundary sliding was isolated. The strain-rate sensitivity remained low ($0.034 \pm 0.017$), comparable to room temperature values, indicating the absence of
diffusion-controlled accommodation mechanisms. The activation energy for grain boundary sliding was determined to be $284 \pm 47\,\mathrm{kJ\,mol^{-1}}$, consistent with
lattice diffusion-assisted dissociation of
lattice dislocations into grain boundary dislocations. These results demonstrate that the high strain-rate sensitivity associated with grain boundary sliding in polycrystals originates primarily from accommodation processes rather than the intrinsic sliding mechanism.
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Statistical Mechanics · Cross-listed from quant-ph
Discovering quantum phenomena with Interpretable Machine Learning
Paulin de Schoulepnikoff, Hendrik Poulsen Nautrup, Hans J. Briegel et al. (+1 more)
Interpretable machine learning techniques are becoming essential tools for extracting physical insights from complex
quantum data. We build on recent advances in variational autoencoders to demonstrate that such models can learn physically meaningful and interpretable representations from a broad class of unlabeled
quantum datasets. From raw measurement data alone, the learned representation reveals rich information about the underlying structure of
quantum phase diagrams. We further augment the learning pipeline with symbolic methods, enabling the discovery of compact analytical descriptors that serve as order parameters for the distinct regimes emerging in the learned representations. We demonstrate the framework on experimental Rydberg-atom snapshots, classical shadows of the cluster Ising model, and hybrid discrete-continuous fermionic data, revealing previously unreported phenomena such as a corner-ordering pattern in the Rydberg arrays. These results establish a general framework, which constitutes an important step toward the autonomous discovery of physical descriptors from diverse
quantum datasets. All methods are available through qdisc, an open-source Python library designed to make these tools accessible to the broader community.
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All authors Paulin de Schoulepnikoff, Hendrik Poulsen Nautrup, Hans J. Briegel, Gorka Muñoz-Gil
Strongly Correlated Electrons · Cross-listed from physics.chem-ph
A Diagrammatic Route to Multi-Reference GW for Strongly Correlated Molecules
Yuqi Wang, Wei-Hai Fang and Zhendong Li
The GW approximation is a cornerstone of many-body perturbation theory for computing single-particle excitations, yet it can fail qualitatively in strongly correlated systems where the single-reference picture becomes inadequate. To overcome this limitation, we develop a diagrammatic route to multi-reference GW (MR-GW) from an interacting active-space reference, treating strong correlation nonperturbatively and the residual interaction through dynamical screening at the multi-reference random phase approximation level. Because the conventional diagrammatic self-energy expansion no longer applies, we define a practical one-shot MR-GW approximation within a generalized diagrammatic framework, recovering standard GW as a special case. Applications to prototypical correlated atoms and molecules show that the interacting active-space reference captures multiconfigurational satellite structures poorly described by single-reference GW, while dynamical screening generally improves the satellite energies as well as the leading ionization and electron-attachment energies. This work opens a diagrammatic route to Green's-function methods that combine nonperturbative strong correlation with dynamical screening.
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Mesoscale and Nanoscale Physics
Disambiguating electrical detection of magnetization dynamics in magnetic insulators
Hanchen Wang, William Legrand, Shangyuan Wang et al. (+6 more)
Electrical detection of magnetization dynamics in
magnetic insulators underpins both fundamental studies of
magnon transport and the development of low-loss magnonic devices. In heavy-metal/
magnetic-
insulator heterostructures,
spin pumping and
spin-torque
ferromagnetic resonance (ST-FMR) are widely used for this purpose and are often treated separately in different measurement geometries. In practice, the competition between these two effects gives rise to electrical voltage signals of opposite signs, which can lead to ambiguous interpretations of the underlying physics. Here, we show how to disambiguate their respective contributions and provide a framework for interpreting experiments involving microwave excitation of
magnetic insulators and detection of magnetization dynamics via
spin-charge conversion in heavy metals. We systematically investigate
spin pumping and ST-FMR in nonlocal and local devices using Pt-capped thin films of thulium and bismuth-yttrium iron garnets. We show how
spin-wave character,
magnetic dissipation,
magnetic field orientation and device geometry govern the sign and magnitude of the resulting signals. In several cases, the voltage generated by microwave excitation changes sign between an out-of-plane or in-plane
magnetic configuration. We disentangle a contribution due to
spin pumping, induced by exponentially decaying propagating
spin waves, and a weakly distance-dependent contribution from ST-FMR, remotely induced by inductive coupling. We show that both the
spin wave excitation profile across the film thickness and
magnetic damping largely determine which of the two contributions dominates. Hence, the sign of the electrical signal cannot be uniquely assigned to the chirality of the
magnon modes.
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All authors Hanchen Wang, William Legrand, Shangyuan Wang, Davit Petrosyan, Hiroki Matsumoto, Alexander E. Kossak, Richard Schlitz, Ka Shen, Pietro Gambardella
Mesoscale and Nanoscale Physics
Machine Learning and Deep Learning in Quantum Materials: Symmetry, Topology, and the Rise of Altermagnets
Mahyar Hassani-Vasmejani, Hosein Alavi-Rad and Meysam Bagheri Tagani
The landscape of condensed matter physics is facing an unprecedented data surge driven by high-throughput ab initio workflows and rapidly expanding experimental
datasets. Traditional first-principles methods such as Density Functional Theory (DFT), despite their foundational role, suffer from cubic scaling, creating a major bottleneck when exploring the vast chemical space of
quantum materials. This review analyzes how Machine Learning (ML) and Deep Learning (DL) are overcoming these limitations and accelerating the discovery of exotic phases of matter. We examine the shift from rigid descriptor-based models to flexible,
symmetry-aware architectures, particularly E(3)-equivariant Graph Neural Networks (GNNs) that respect rotational and translational invariance. A central focus is the automated identification of topological phases, where ML models exploit
symmetry indicators and elementary band representations to diagnose non-trivial
topology without costly band structure integrations. The discussion culminates in a case study of the Altermagnet, a recently identified third class of magnetism beyond the
ferromagnetic,
antiferromagnetic dichotomy. We highlight how specialized AI search engines, combining graph theory with crystallographic
symmetry analysis, have uncovered d-wave, g-wave, and even i-wave altermagnets, expanding the known landscape of
magnetic order. The review concludes by addressing the interpretability gap and advocates for symbolic regression and active-learning frameworks to connect black-box predictions with experimentally verifiable mechanisms.
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Mesoscale and Nanoscale Physics
Observation of ring states in a delicate topological insulator
Caroline Tornow, Julia Rupprecht, Pascal Engeler et al. (+4 more)
Topological
insulators are typically characterized by particularly stable properties, such as global invariants, and can be identified by probing their robust surface states. A recently discovered novel form of band
topology, delicate
topology, challenges this paradigm: its defining property, multicellularity, can be removed by introducing a coupling to local orbitals anywhere in the spectrum, even far above the relevant band gap. This makes it hard to diagnose delicate
topology with conventional probes that access only low-energy degrees of freedom. Here, we introduce strong local
impurities as a spectroscopic probe of a delicate topological
insulator which we realize in a phononic metamaterial. By tuning the
impurity strength and performing orbital-resolved readout, we observe recently proposed indicators of
topology: ring states, in-gap bound states whose frequencies remain pinned in the strong-
impurity limit while their real-space profiles form a pronounced ring around the
impurity site. We find that these ring states persist even when the multicellularity in our system is removed by a weakly hybridizing additional orbital. Our results establish
impurity-induced ring states as probes of complex multiband physics, including delicate topological phases.
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All authors Caroline Tornow, Julia Rupprecht, Pascal Engeler, Ute Drechsler, Kukka-Emilia Huhtinen, Chiara Devescovi, Sebastian D. Huber
Materials Science
Laser induced surface nitriding of niobium: phase evolution and superconducting behaviour
J. Frechilla, A. Frechilla, G.F. de la Fuente et al. (+3 more)
Laser nitriding represents a versatile approach for tailoring the surface properties of metals. Up to now, its effect on the superconducting response of niobium nitrides remains largely unexplored. In this work, the nitriding process of niobium by
laser irradiation under a controlled nitrogen atmosphere up to 2.50 bar, using a nanosecond pulsed
laser with wavelength of 1064 nm has been investigated. By independently tuning the nitrogen pressure, the two-dimensional accumulated fluence ($F_{2D}$) and the
laser irradiance, a
laser-processing map for the formation of either a combination of $\beta$-Nb$_2$N (hexagonal) and $\gamma$-Nb$_4$N$_{3\pm x}$ (tetragonal) phases or only the $\beta$-phase has been established. Systematic analysis by X-ray diffraction, scanning electron microscopy and electron backscatter diffraction revealed that the nitrogen-rich $\gamma$-phase forms in the near-surface layer through melting when $F_{2D}$ exceeds a certain value ($> 50 \,\mathrm{kJ/cm^2}$ at 2.50 bar). A $\beta$-layer is observed underneath, and further inside, there is a band of embedded $\beta$-grains in the Nb
matrix. Their size gradually decreases with increasing distance to surface, suggesting thermal gradients and a
diffusion formation mechanism. When the $\gamma$-phase becomes predominant, a significant increase in the superconducting critical temperature is observed, up to $T_c \approx 15\,\mathrm{K}$, and
magnetic irreversibility. For low $F_{2D}$ values ($\approx 7.5 \,\mathrm{kJ/cm^2}$ at 1.50-2.50 bar), the formation of a uniform nitride layer composed of sub-micron-sized $\beta$-Nb$_2$N grains results in a ca. fourfold enhancement in surface microhardness. These findings provide fundamental insights into
laser-induced nitriding of niobium to engineer mechanically robust and superconducting Nb-N layers.
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All authors J. Frechilla, A. Frechilla, G.F. de la Fuente, A. Larrea, L.A. Angurel, E. Martínez
Superconductivity
Charge Density Wave Driven Topological Phase Transition in Vortices
Zhenhua Zhu, Ziqiang Wang and Dong E. Liu
The interplay between charge density waves (CDWs) and superconductivity is a central theme in
quantum materials, yet how CDW phase textures govern
vortex topology remains poorly understood. We develop a theoretical framework showing that the phase of a stripe CDW can switch a
magnetic vortex between topological and trivial regimes. Motivated by recent experiments, we propose two candidate mechanisms enabling phase-controlled switching of
vortex topology. In a direct-modulation scenario, the CDW acts as a periodic potential that locally renormalizes band parameters and can induce topological transitions, but it generally cannot reproduce the symmetric node/antinode trend without fine tuning. In contrast, in an inversion-
symmetry-breaking (ISB) scenario, a CDW node pinned to the
vortex center breaks local inversion and allows for the mixture of
spin-triplet pairing of Cooper pairs, producing a robust topological transition when this component dominates. Our results suggests CDW phase as a possible local handle to tune and test
vortex topology.
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Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
A Modular Cryogenic Link for Microwave Quantum Communication Over Distances of Tens of Meters
Josua D. Schär, Simon Storz, Paul Magnard et al. (+6 more)
Quantum technologies promise a radically new way to solve classically intractable computing problems. Superconducting
circuits as a platform are at the forefront of this field. The cryogenic operation temperatures of superconducting
circuits however impose challenges for the further scaling to many connected
quantum information processing units into a local area or global network. In this work, we present a hardware solution for connecting
quantum devices operating at microwave frequencies into local area networks, which enable the exchange of
quantum information between spatially separated parties. Specifically, we demonstrate a modular system spanning distances of 5, 10 and 30 meters operated at cryogenic temperatures and connecting two superconducting
circuit systems, located in individual dilution refrigerators, through a
quantum communication channel. We develop a thermal model to evaluate the heat transfer processes in the setup, optimize the design and select appropriate materials for its construction. The assembled 30-meter-long system achieves operating temperatures of below 50 mK after a cooldown time of about six and a half days. This link enables the execution of distributed
quantum computing and communication
algorithms. It also adds the resource of non-locality, certified by a loophole-free Bell test, to the field of
quantum science and technology with superconducting
circuits.
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All authors Josua D. Schär, Simon Storz, Paul Magnard, Philipp Kurpiers, Janis Lütolf, Melvin Gehrig, Jean-Claude Besse, Anatoly Kulikov, Andreas Wallraff
Soft Condensed Matter
Flash temperature in sliding contacts: comparing theory with experiments
B.N.J. Persson
The temperature increase in the contact regions between solids in sliding contact has a huge influence on friction and wear. Here we test an analytical theory for the flash temperature, valid for randomly rough surface with multiscale roughness, by comparing the theory predictions with the experimental results of Sutter et al \cite{Sutter} for steel sliding on steel. The theory, which is based on the study of stress and temperature correlation functions, is valid for randomly rough surfaces with roughness on arbitrary many decades in length scale. Within the uncertainty of the experimental data (mainly the surface roughness power spectrum and the steel penetration hardness), there is good agreements between the theory and the experimental results.
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Materials Science
Identification and Structural Characterization of Twisted Atomically Thin Bilayer Materials by Deep Learning
Haitao Yang, Ruiqi Hu, Heng Wu et al. (+11 more)
Two-dimensional materials are expected to play an important role in next-generation electronics and optoelectronic devices. Recently, twisted
bilayer graphene and transition metal dichalcogenides have attracted significant
attention due to their unique physical properties and potential applications. In this study we describe the use of optical microscopy to collect the color space of chemical vapor deposition (CVD) molybdenum disulfide ($\mbox{MoS}_2$), and the application of a semantic
segmentation convolutional neural network (CNN) to accurately and rapidly identify thicknesses of $\mbox{MoS}_2$ flakes. A second CNN model is trained to provide precise predictions on the twist angle of CVD-grown
bilayer flakes. This model harnessed a
dataset comprising over 10,000 synthetic images, encompassing geometries spanning from hexagonal to triangular shapes. Subsequent validation of the deep learning predictions on twist angles was executed through the second harmonic generation and Raman spectroscopy. Our results introduce a scalable methodology for automated inspection of twisted atomically thin CVD-grown
bilayer.
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All authors Haitao Yang, Ruiqi Hu, Heng Wu, Xiaolong He, Yan Zhou, Yizhe Xue, Kexin He, Wenshuai Hu, Haosen Chen, Mingming Gong, Xin Zhang, Ping-Heng Tan, Eduardo R Hernández, Yong Xie
Statistical Mechanics · Cross-listed from quant-ph
Finite-Time Thermodynamics of an Autonomous Information Machine
Wanyan Chen, Miao Chen and Yu-Han Ma
While externally driven information engines are well understood, the thermodynamic constraints of their autonomous counterparts remain an open question. Here, we investigate the finite-time operation of an autonomous machine functioning as both an information eraser and a refrigerator, revealing that its irreversibility is bounded by the transient information geometry. Beyond steady-state boundaries, we map the landscape of optimal operation times across both functional modes, uncovering a unique synergistic regime where erasure power $P$ and efficiency $\eta$ increase simultaneously. Fundamentally, this performance is governed by a trade-off relation, $v(1-\eta)P/\eta \le D$, where $v$ is the operational speed and $D$ denotes an information-
geometric distance. Our findings pave the way for optimizing fast autonomous information-energy conversion.
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