Materials Science · Cross-listed from physics.ins-det
Accurate simulations of magnetic excitations in the neutron simulation package McStas
Silas B. Schack, Kristine M. L. Krighaar, Emma Y. Lenander et al. (+1 more)
A new component for the accurate simulation of
neutron scattering from
magnetic excitations has been developed for the
neutron ray-tracing software McStas. The component SpinWave_BCO simulates inelastic
neutron scattering from ferro-, antiferro-, and altermagnetic excitations in a body-centered orthorhombic
crystal structure, where the dispersion relation and scattered
neutron intensities are derived using linear
spin wave theory. Data from a simulated Triple-Axis Spectrometer with an extremely high resolution have been verified by direct comparison with theory and by comparison to data simulated using the package SpinW. The component serves as a proof-of-concept for the implementation of a more general linear
spin wave component in McStas.
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All authors Silas B. Schack, Kristine M. L. Krighaar, Emma Y. Lenander, Kim Lefmann
Soft Condensed Matter · Cross-listed from physics.comp-ph
Efficient Pseudo-spectral Algorithms for Statistical Field Theories
Martin Kjøllesdal Johnsrud and Navdeep Rana
We present
stochastic variants of the exponential time differencing schemes for stiff
stochastic differential equations. We derive three explicit schemes that offer better stability compared to Euler-Maruyama and Milstein's method, and achieve strong convergence up to order O(h) in the time step h. We combine these schemes with a pseudo-spectral approach to outline efficient
algorithms for simulating
stochastic field theories with additive noise. To illustrate the effectiveness of this approach, we study several systems in and out of
equilibrium, including Model A, Model B, the Kardar-Parisi-Zhang equation, and the Complex Ginzburg-Landau equation. We outline procedures for computing physical observables such as the critical exponents, correlation functions, and dynamic linear response, and provide our implementation as open source code.
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Disordered Systems and Neural Networks · Cross-listed from quant-ph
Replica Field Theory of Quantum Jumps Monitoring: Application to the Ising Chain
Youenn Le Gal and Marco Schirò
In this work we derive the replica field theory for monitored
quantum many-body systems evolving under the
quantum jumps protocol, corresponding to a non-Hermitian
evolution interspersed with random
quantum jumps whose distribution is state-dependent. We show that the density
matrix of $R$ replicas evolves according to a master equation where the non-Hermitian term is replica-diagonal while coupling among replicas are due to
quantum jumps. We write down the associated Keldysh action and study its behavior for the specific case of the Ising Chain with monitoring of particle density and tunable anisotropy, interpolating between free
fermions with strong U(1)
symmetry and the Ising chain with Z$_2$
symmetry. We derive the effective field theory in terms of slowly varying fields and obtain the replica-diagonal saddle point, which we show to describe the average state. We then go beyond saddle point and derive the effective field theory describing the replica off-diagonal sector, which takes the form of a Non-Linear Sigma Model. The
symmetry class is either DIII or D, depending on the parameters of the Ising chain, except at a special symmetric point, where we recover the results for free
fermions. We discuss the implications of these findings for the entangling phase observed numerically for the monitored Ising chain.
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Materials Science
Screening novel cathode materials from the Energy-GNoME database using MACE machine learning force field and DFT
Nada Alghamdi, Paolo de Angelis, Pietro Asinari et al. (+1 more)
The development of new battery materials, particularly novel cathode chemistries, is essential for enabling next generation energy storage technologies. In this work, we employ a multi-fidelity screening protocol combining the Energy-GNoME confident criteria, foundational MACE machine-learning force fields (MLFF), and physically motivated heuristic filters to identify novel intercalation cathodes for post-lithium batteries, namely: Na-, K-, Mg-, and Ca-ion batteries. Foundational MACE models are used to efficiently asses dynamical stability, thermodynamical stability, average voltage, and theoretical specific energy, enabling a rapid screening of candidates. For the most promising cathodes, voltage predictions are refined using DFT+U calculations. This work delivers three key outcomes: i) establishing and validating a robust high-throughput screening approach for cathode materials with foundational MLFF models; ii) suggestions for cathode candidates for the development of next-generation of batteries; iii) a fair comparison between the MACE predictions and the readily available figures of merit reported in the Energy-GNoME database on the examined materials.
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All authors Nada Alghamdi, Paolo de Angelis, Pietro Asinari, Eliodoro Chiavazzo
Soft Condensed Matter
The Second Gibbs Paradox
Daan Frenkel
In his
Equilibrium of Heterogeneous Substances Gibbs seems to suggest that the chemical potential of a
crystal nucleus need not be equal to that of the coexisting fluid. In the field, Gibbs's statement has been something of a hot potato. I argue that a consistent treatment of point defects in the critical
nucleus is essential for clarifying the meaning of the chemical potential of the
nucleus. In the end – as always – Gibbs was right.
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Materials Science
Reststrahlen band and optical bandgaps in semiconducting CrN films
Duc V. Dinh, Xiang Lü, Oliver Brandt et al. (+8 more)
We present a comprehensive optical characterization of 200-nm-thick CrN(111) films grown simultaneously on Al$_2$O$_3$(0001) and AlN/Al$_2$O$_3$(0001) using
plasma-assisted molecular beam epitaxy. Spectroscopic ellipsometry, spanning the far-infrared to ultraviolet range (0.04 - 5.5 eV), is conducted at room temperature to determine the optical constants $n$ and $k$ of the films. Spectral fits reveal two interband transitions at approximately 0.35 and 0.60 eV. In the infrared range, the ellipsometry data also reveals a pronounced Reststrahlen band stemming from transversal and longitudinal optical
phonons at approximately 403 and 629 cm$^{-1}$, respectively. The relative static and high-frequency permittivities are estimated to be about 39 and 15, respectively. A Born effective charge of approximately 2.7, extracted from the far-infrared region, indicates that CrN is partially ionic.
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All authors Duc V. Dinh, Xiang Lü, Oliver Brandt, Dilara Sen, Olivia Fairlamb, Frank Peiris, Farihatun Lima, Alexander Bordovalos, Suresh Chaulagain, Ambalanath Shan, Nikolas J. Podraza
Statistical Mechanics
Equivalence of residual entropy of hexagonal and cubic ices from tensor network methods
Xia-Ze Xu, Tong-Yu Lin and Guang-Ming Zhang
The long-standing question of whether the residual
entropy of hexagonal ice ($S_h$) equals that of cubic ice ($S_c$) remains unresolved despite decades of research on ice-type models. While analytical studies have established the inequality $S_h \geq S_c$, numerical investigations suggest that the two values are very close. In this work, we revisit this problem using high-precision tensor-network methods. In Monte Carlo approaches the residual
entropy cannot be directly obtained by sampling the ground-state degeneracy space, however, the tensor-network framework enables an explicit encoding of the "ice rule” into local tensors, and then the residual
entropy is transformed into finding the largest
eigenvalue of a transfer operator in the form of a projected entangled-pair operator, which allows high-accuracy numerical evaluation. Meanwhile, we propose a new perspective based on analyzing the normality of the transfer operator, and demonstrate that if the operator is normal, the equality $S_h = S_c$ follows directly. Then the variational tensor network methods are employed to numerically verify this normality. Finally both residual
entropies are directly computed by using our recently developed split corner transfer
matrix renormalization group
algorithm, providing a rigorous evidence supporting the equality between $S_h$ and $S_c$.
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Other Condensed Matter
Impact of a Fano resonance on the measured transition time scale in solid state photoemission
Fei Guo, Dmitry Usanov, Eduardo B. Guedes et al. (+3 more)
Fundamental
quantum transition time scales are accessible through the
spin polarization of photoelectrons coming from initially
spin-degenerate states for solid-state materials . In this work we investigate the modification of this time scale in the vicinity of a Fano resonance in photoemission from a solid. We employ
spin- and angle-resolved photoemission spectroscopy (SARPES) to study the valence band of 1T-TiSe$_2$ and 1T-TiTe$_2$, with an excitation
photon energy coinciding with the Ti 3p-3d autoionization state. The energy derivative of the measured
spin polarization, which is in the off-resonance case proportional to the transition time, reveals a sign reversal and significant magnitude decrease compared to off-resonance measurements. We show that this effect goes beyond conventional semi-analytical models used to translate
spin polarization to the EWS time delay. At the Fano resonance, the underlying interference assumption of the model breaks down, and additional information about resonance strength is needed to extract the transition time delays.
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All authors Fei Guo, Dmitry Usanov, Eduardo B. Guedes, Arnaud Magrez, Michele Puppin, J. Hugo Dil
Mesoscale and Nanoscale Physics · Cross-listed from cs.CV
From Simulation to Experiment: Benchmarking Machine-Learning Models for Quantum-Dot State Recognition
Valeria Díaz Moreno, Ryan P Khalili, Daniel Schug et al. (+3 more)
Machine-learning models for
quantum-dot state recognition are commonly trained using synthetic data, where large labeled
datasets can be generated efficiently. However, strong performance on simulated data does not guarantee equally strong performance in experiments. Here, we
benchmark five neural network architectures for
quantum-dot state recognition using a shared synthetic training
dataset and independent synthetic and experimental test sets. We compare convolutional and fully connected neural networks, a mixture density network, a
vision transformer, and a U-Net across multiple training set sizes and two input normalization schemes. We find that model performance and rankings are closely preserved when moving from held-out synthetic patches to previously unseen simulated devices, but change substantially when the same models are evaluated on experimental data. In particular, the architecture achieving the highest synthetic performance is not the one that performs best experimentally. Input normalization further affects training behavior and, for some architectures, synthetic-to-experimental transfer. These results show that synthetic
benchmark performance alone is insufficient to select models for experimental deployment and highlight the need to jointly evaluate architecture, preprocessing, data efficiency, model complexity, and experimental transfer when developing machine-learning tools for automated
quantum-dot characterization and control.
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All authors Valeria Díaz Moreno, Ryan P Khalili, Daniel Schug, Patrick J. Walsh, Donovan L. Buterakos, Justyna P. Zwolak
Mesoscale and Nanoscale Physics
Photoionization current spectroscopy of individual silicon vacancies in silicon carbide
Kazuki Okajima, Tetsuri Nishikawa, Hiroshi Abe et al. (+5 more)
Defect charge-state dynamics are central to both
spin-
photon interfaces and photoelectrical
spin readout. Despite the significance of silicon vacancies (V1/V2) in silicon carbide (4H-SiC) for both applications, their ionization behavior has remained unclear because their lack of optical blinking prevents conventional charge-state analysis. Here, we employ photocurrent spectroscopy of individual defects to measure the wavelength dependence of their excitation and ionization cross-sections. We reveal that V1 and V2 exhibit similar ionization cross-sections that increase toward shorter wavelengths, while carbon vacancies dominate the more steeply increasing background photocurrent. These results indicate that V2 and its surrounding environment appear more robust than V1 under resonant excitation. We also identify wavelength regimes that optimize defect-origin photocurrent for photoelectrical
spin readout relative to background contributions, which differ between single-defect and ensemble measurements. Our results establish photocurrent spectroscopy as a powerful complement to optical methods, advancing the development of defect-based
quantum devices.
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All authors Kazuki Okajima, Tetsuri Nishikawa, Hiroshi Abe, Koichi Murata, Takeshi Ohshima, Hidekazu Tsuchida, Naoya Morioka, Norikazu Mizuochi
Statistical Mechanics
Exact four-vector work distribution and covariant fluctuation theorems of work for a relativistic particle in an expanding piston
Tingzhang Shi, Chentong Qi and H. T. Quan
We investigate the non-
equilibrium four-vector work in an expanding relativistic piston. We derive the exact work distribution in this pedagogical model and find that the joint distribution of four-vector work $(W^0, W^1)$ concentrates on the origin and some curves in the $(W^0, W^1)$ space, rather than being smoothly distributed. In the non-relativistic limit, our model consistently recovers the non-relativistic dynamics. We further demonstrate that the momentum component of four-vector work remains significant in both the Lorentz-relativistic and Galilean-relativistic frameworks. On top of the work distribution, we verify a family of covariant fluctuation
theorems of work. In addition, we introduce a novel geometrical technique for analyzing the dynamics of relativistic collision processes, which can be straightforwardly extended to multi-dimensional piston models.
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Soft Condensed Matter
Bubble-Driven Flow Transitions in Evaporating Active Droplets on Structured Surfaces
Meneka Banik and Ranjini Bandyopadhyay
The evaporation of particle-laden droplets on engineered surfaces underpins a wide range of technologies, from printed electronics to biosensing. While the influence of substrate topography on passive particle deposition is well established, the combined effects of active matter dynamics, catalytic gas generation, and surface structuring remain unexplored. Here, we investigate the drying of aqueous droplets containing Janus particles (polystyrene-platinum, PS-Pt) on topographically patterned substrates in the presence of hydrogen peroxide (H2O2) fuel. The catalytic decomposition of H2O2 produces oxygen bubbles within the droplet, introducing strong, transient hydrodynamic perturbations that compete with evaporation driven capillary flows and contact line interactions. We show that bubble activity alters particle transport, leading to distinct and tunable final morphologies not achievable with passive suspensions. This study demonstrates how bubble-induced flow coupled with substrate topography determines deposition patterns during droplet evaporation. Our findings open a route to harnessing active matter and reaction driven flows for directed particle assembly.
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Mesoscale and Nanoscale Physics · Cross-listed from physics.optics
Integration of 2D Materials in Radial van der Waals Heterostructure Metasurfaces
Connor Heimig, Jonas Biechteler, Cristina Cruciano et al. (+12 more)
Two-dimensional
semiconductors, such as monolayer transition metal dichalcogenides (TMDC), exhibit strong excitonic transitions at room temperature and offer a unique platform for exploring light-matter interactions in nanoscale photonic systems. In this work, we demonstrate a compact and polarization-invariant photonic metasurface, fabricated from hexagonal boron-nitride (hBN) and based on radial bound states in the continuum (BIC), which are formed by radially distributed pairs of structurally asymmetric resonators. The metasurface employs multiple
symmetry-breaking perturbations to support high quality-(Q-)factor resonances within a footprint smaller than 8 x 8 $\mu m^2$ - one-sixth of the area of previous approaches. Compared to established hBN metasurface designs, the radial geometry furthermore achieves significantly higher Q-factors with a reduced footprint. By integrating the hBN photonic structure with a WS$_2$ monolayer, we observe enhanced photoluminescence when its resonance is spectrally aligned with the
exciton resonance, accompanied by signatures of discrete momentum-space patterns that identify the orbital-angular-momentum-carrying ring eigenmodes. These features persist over a wide range of excitation powers and show minimal linewidth broadening, indicating robust and spatially modulated
exciton-
photon coupling. This work establishes a scalable approach for generating hybrid photonic-excitonic states with momentum-space structure, offering new opportunities for
exciton localization, valley emission, spatially programmable light-matter interaction in two-dimensional material platforms and compact luminescent devices based on 2D material-integrated metasurfaces.
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All authors Connor Heimig, Jonas Biechteler, Cristina Cruciano, Armando Genco, Thomas Weber, Michael Hirler, Dmytro Gryb, Alexander A. Antonov, Leonardo de S. Menezes, Gianluca Valentini, Cristian Manzoni, Giulio Cerullo, Stefan A. Maier, Luca Sortino, Andreas Tittl
Mesoscale and Nanoscale Physics
Asymmetric quantum Hall effect and diminished $\nu=0$ longitudinal resistance in graphene/InSe heterostructures
Wenxue He, Shijin Li, Jinhao Cheng et al. (+9 more)
We investigate
quantum transport in
graphene/InSe
heterostructures and find major asymmetries in the longitudinal resistance ($R_{xx}$) and vanishing $R_{xx}$ peaks at high
magnetic fields, particularly at the charge-neutrality point. Our Landauer-Buttiker analysis and numerical simulations show that a monotonically varying density gradient combined with a full equilibration mechanism can explain these phenomena. Our results also suggest the presence of trivial long-range
chiral edge current and offer a broadly applicable way to engineer transport properties in
quantum Hall systems.
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All authors Wenxue He, Shijin Li, Jinhao Cheng, Yingpeng Zhang, Kaixuan Fan, Jiabo Liu, Shuaishuai Ding, Wenping Hu, Fan Yang, Chen Wang, Qing-Feng Sun, Hechen Ren
Soft Condensed Matter
Simulations of inertial liquid-lens coalescence with the pseudopotential lattice Boltzmann method
Qingguang Xie and Jens Harting
The coalescence of
liquid lenses is relevant in various applications, including inkjet printing and fog harvesting. However, the dynamics of
liquid-lens coalescence have been relatively underexplored, particularly in the case of
liquid lenses with larger contact angles. We numerically investigate the coalescence of low-viscosity
liquid lenses by means of the pseudopotential multi-component
lattice Boltzmann method over a wide range of contact angles. In two-dimensional simulations, our numerical results on the growth of the bridge height are in quantitative agreement with experimental measurements for small contact angles. In addition, by comparing our simulation results with a theoretical approach based on the thin-sheet equations for
liquid lenses, we find that the thin-sheet equations accurately capture the bridge-growth dynamics up to contact angles of approximately $\theta < 40^{\circ}$. For the three-dimensional case, the growth of the bridge radius is independent of the
equilibrium contact angle of the
liquid lenses at the initial stage of growth. The dependency between the growth of the bridge height and the bridge radius exhibits a non-linear to linear transition.
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Superconductivity
Thermally-controlled flux avalanche dynamics in bulk NbTi superconductor
Irina Abaloszewa, Viktor V. Chabanenko and Aleksander Abaloszew
We report the first direct visualization of flux avalanche propagation dynamics in bulk superconducting NbTi, tracking individual events and measuring their velocities using high-speed magneto-optical imaging. Unlike thin films with electromagnetic avalanches at km/s speeds, we observe velocities of 15–25 m/s, which are orders of magnitude slower. Analysis of characteristic timescales reveals that these avalanches are governed by local heating and limited heat dissipation through the adhesive layer, establishing a fundamentally different, thermally limited propagation regime. The threshold field for avalanche nucleation decreases with temperature, contrary to the increasing trend in thin films with efficient cooling - a behavior consistent with slow heat removal and thermal runaway in our system. All observed avalanches exhibit universal normalized velocity-distance scaling despite varying morphologies, confirming the robustness of thermal control. These findings reveal that bulk
superconductors with poor thermal coupling operate in a previously uncharacterized avalanche regime, with direct implications for flux stability and quench protection in NbTi-based magnets, as well as a broader understanding of thermomagnetic instabilities in technological
superconductors.
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Mesoscale and Nanoscale Physics
Is the atomic quadrupole moment of a carbon atom in graphene zero?: The case for a rational definition of the properties of atoms in a molecule
Devin M. Mulvey, Kenneth D. Jordan and Alston J. Misquitta
It is generally assumed that the carbon atoms of graphitic samples and their finite analogs have sizable quadrupole moments, with the out-of-plane component ($Q^{\rm C}_{20}$ in traceless spherical coordinates) being the dominate contribution. However, there is no consensus on what the quantity is for such carbon-based systems and values reported in the literature range from $Q^{\rm C}_{20} \sim -1.14$ to $+0.79$ a.u. In this work we propose a theoretical framework in which well-defined statements can be made about properties of atoms-in-a-molecule (AIMs) even when these properties are not experimentally observable. Using this framework and the distributed multipole method basis-space iterated Stockholder atoms (BS-ISA), we show that the atomic quadrupole moment of a carbon atom in
graphene is essentially zero within the limits of precision of the numerical method used. We explain how the experimentally measured atomic quadrupole moment of a graphite sample determined by Whitehouse & Buckingham likely originated almost entirely from edge dipoles, and we propose a more realistic electrostatic model for finite
graphene nanoflakes.
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Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
Ultrafast Single Qubit Gates through Multi-Photon Transition Removal
Y. Gao, A. Galicia, J. D. Da Costa Jesus et al. (+12 more)
One of the main enablers in
quantum computing is having
qubit control that is precise and fast. However,
qubits typically have multilevel structures making them prone to unwanted transitions from fast gates. This leakage out of the computational subspace is especially detrimental to
algorithms as it has been observed to cause long-lived errors, such as in
quantum error correction. This forces a choice between either achieving fast gates or having low leakage. Previous works focus on suppressing leakage by mitigating the first to second excited state transition, overlooking multi-
photon transitions, and achieving faster gates with further reductions in leakage has remained elusive. Here, we demonstrate single
qubit gates with a total leakage error consistently below $2.0\times10^{-5}$, and obtain fidelities above $99.98\%$ for pulse durations down to 6.8 ns for both $X$ and $X/2$ gates. This is achieved by removing direct transitions beyond nearest-neighbor levels using a double recursive implementation of the Derivative Removal by Adiabatic Gate (DRAG) method, which we name the R2D method. Moreover, we find that at such short gate durations and strong driving strengths the main error source is from these higher order transitions. This is all shown in the widely-used superconducting transmon
qubit, which has a weakly anharmonic level structure and suffers from higher order transitions significantly. We also introduce an approach for amplifying leakage error that can precisely quantify leakage rates below $10^{-6}$. The presented approach can be readily applied to other
qubit types as well.
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All authors Y. Gao, A. Galicia, J. D. Da Costa Jesus, Y. Liu, Y. Haddad, D. A. Volkov, J. R. Guimarães, H. Bhardwaj, M. Jerger, M. Neis, B. Li, F. A. Cárdenas-López, F. Motzoi, P. A. Bushev, R. Barends
Statistical Mechanics · Cross-listed from quant-ph
Sunburst quantum Ising battery under periodic delta-kick charging
Ankita Mazumdar, Akash Mitra and Shashi C. L. Srivastava
Most
quantum batteries studied so far with notable exception of Sachdev-Ye-Kitaev (SYK) batteries are based on integrable models, where superlinear scaling of charging power and hence a
quantum advantage can be achieved, but at the cost of unstable stored energy due to integrability. Here, by considering the sunburst
quantum Ising battery driven by periodic delta-kicks, we show that in the
quantum chaotic regime a
quantum advantage is achieved for number of batteries $n_b\leq 4$, together with excellent stability of energy storage. In the integrable regime optimal energy storage and extraction are possible irrespective of the initial state of the charger. Finally, we show that the observed advantage does not originate from multipartite
entanglement within the battery subsystem and is therefore classical in nature.
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Soft Condensed Matter
Transfer of Energy and Momentum between Magnetoactive Surface Microstructure and a Solid Object
Arne Geldof, Jan Kopačin, Izidor Straus et al. (+7 more)
We investigated the physical mechanisms driving directional transport of solid objects by micro-lamellar structures
laser-inscribed on the surface of a magnetoactive elastomer (MAE). When subjected to a rotating
magnetic field with magnitude of 175 mT and a time period of 0.4 s, the lamellas reorient within a few milliseconds, reaching angular velocities up to 1100 rad/s. This rapid motion is crucial for efficient momentum and energy transfer to objects in contact with the lamellas. The analysis of collisions of a single lamella with a lead ball with a 2.2 mm diameter shows that the lamella can transfer around 50 nJ of energy, propelling the ball to a speed of around 35 mm/s. We show how this value sets the upper limit for the transport speed of the ball on multi-lamellar MAE arrays. We also explain the background of three distinct transport regimes (kicking, pushing, and bouncing modes) observed on these magnetically driven conveyor belts.
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All authors Arne Geldof, Jan Kopačin, Izidor Straus, Raphael Kriegl, Gaia Kravanja, Luka Hribar, Matija Jezeršek, Mikhail Shamonin, Gašper Kokot, Irena Drevenšek-Olenik
Mesoscale and Nanoscale Physics · Cross-listed from quant-ph
Superradiant decay in non-Markovian Waveguide Quantum Electrodynamics
Rosa Lucia Capurso, Giuseppe Calajó, Simone Montangero et al. (+5 more)
An array of initially excited emitters coupled to a one-dimensional waveguide exhibits superradiant decay under the Born-Markov approximation, manifested as a coherent burst of
photons in the output field. In this work, we employ tensor-network methods to investigate its non-Markovian dynamics induced by finite time delays in
photon exchange among the emitters. We find that the superradiant burst breaks into a structured train of correlated
photons, each intensity peak corresponding to a specific
photon number. We quantify the emitter-
photon and emitter-emitter
entanglement generated during this process and show that the latter emerges in the long-time limit, as part of the excitation becomes trapped within the emitters' singlet subspace. We finally consider the decay of the system's most radiant state, the symmetric Dicke state, and show that time delay can lead to decay rates exceeding those predicted by the Markovian approximation.
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All authors Rosa Lucia Capurso, Giuseppe Calajó, Simone Montangero, Saverio Pascazio, Francesco V. Pepe, Maria Maffei, Giuseppe Magnifico, Paolo Facchi
Mesoscale and Nanoscale Physics
Incommensurate-Stabilized Fractional Chern Insulator in Alternating Twisted Trilayer Graphene
Moru Song and Kai Chang
Fractional Chern
insulators (FCIs) typically emerge in topological flat bands and are regarded as
lattice analogs of fractional
quantum Hall states. Conventionally, the flat-band wavefunctions that support FCIs are expected to mimic the lowest Landau level, a condition that can be quantified by the
quantum-
geometric indicators. In realistic systems, however, FCIs often compete with
lattice symmetry-breaking orders, especially when the hosting flat bands not ideal. In this work, we propose stabilizing FCIs by exploiting the intrinsic incommensurability of alternating twisted trilayer
graphene, which naturally suppresses competing charge-density-wave (CDW) phase while FCIs are less effected. Within an adiabatic approximation at the supermoiré scale, the effect of incommensuration on local physics can be quantified as phase shifts of interlayer coupling. Using exact diagonalization, we compute ground states in different local patches and uncover a strikingly counterintuitive result: the FCI gap increases as the
quantum-
geometric indicators worsen. Within certain parameter ranges, we further identify mixed phases where FCIs coexist with CDWs, but with CDWs confined only to patches of weak incommensurability. Finally, we provide experimental protocols and discuss how incommensuration enrich the system's
topology and
quantum geometry. Not only do our results establish incommensuration as a robust stabilizer of FCIs, but also provide a general paradigm for exploring strong-correlation physics in incommensurate systems.
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Mesoscale and Nanoscale Physics · Cross-listed from cs.AI
Swarms of Large Language Model Agents for Protein Sequence Design with Experimental Validation
Fiona Y. Wang, Di Sheng Lee, David L. Kaplan et al. (+1 more)
Designing
proteins de novo with tailored structural, physicochemical, and functional properties remains a grand challenge in biotechnology, medicine, and materials science, due to the vastness of sequence space and the complex coupling between sequence, structure, and function. Current state-of-the-art generative methods, such as
protein language models (PLMs) and
diffusion-based architectures, often require extensive fine-tuning, task-specific data, or model reconfiguration to support objective-directed design, thereby limiting their flexibility and scalability. To overcome these limitations, we present a decentralized,
agent-based framework inspired by swarm intelligence for de novo
protein design. In this approach, multiple large
language model (LLM)
agents operate in parallel, each assigned to a specific residue position. These
agents iteratively propose context-aware mutations by integrating design objectives, local neighborhood interactions, and
memory and feedback from previous iterations. This position-wise, decentralized coordination enables emergent design of diverse, well-defined sequences without reliance on motif scaffolds or multiple sequence
alignments, validated with experiments on
proteins with alpha helix and coil structures. Through analyses of residue conservation, structure-based metrics, and sequence convergence and
embeddings, we demonstrate that the framework exhibits emergent behaviors and effective
navigation of the
protein fitness landscape. Our method achieves efficient, objective-directed designs within a few GPU-hours and operates entirely without fine-tuning or specialized training, offering a generalizable and adaptable solution for
protein design. Beyond
proteins, the approach lays the groundwork for collective LLM-driven design across biomolecular systems and other scientific discovery tasks.
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All authors Fiona Y. Wang, Di Sheng Lee, David L. Kaplan, Markus J. Buehler
Mesoscale and Nanoscale Physics
Twisted (co)homology of non-orientable Weyl semimetals
Thijs Douwes and Marcus Stålhammar
The quasi-particle excitations in Weyl semimetals, known as Weyl
fermions, are usually forced to emerge in charge-conjugate pairs by the Nielsen–Ninomiya
theorem. When the Brillouin zone is non-orientable, this constraint is replaced by a $\mathbb{Z}_2$ charge cancellation, as a result of the chirality becoming ill-defined on such
manifolds; this results in configurations with seemingly non-zero total chirality. Here, we set out to explain this behaviour from a purely topological perspective, and provide a classification of non-orientable Weyl semimetal
topology in terms of exact sequences of twisted (co)homology groups. This leads to several discoveries of direct physical importance: in particular, we recover the $\mathbb{Z}_2$ charge cancellation in a coordinate-independent way, allowing meaningful limits to be set on its physical interpretation. A detailed discussion is provided on a specific Klein bottle-like
topology induced by a momentum-space glide
symmetry, including a full review of the insulating and semimetallic invariants of the system and a classification of the surface states on the non-orientable boundary. Beyond this, we provide a complete survey of all possible non-orientable Brillouin zones and their associated invariants, and extend our formalism into the realm of non-Hermitian topological physics and inversion-symmetric Weyl semimetals. Our work exemplifies the vast potential of fundamental mathematical descriptions to not only aid the corresponding physical intuition, but also predict novel and hitherto overlooked phenomena of great relevance throughout the physics research forefront.
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Soft Condensed Matter
Molecular simulations of phase separation in elastic polymer networks
Takahiro Yokoyama, Yicheng Qiang, David Zwicker et al. (+1 more)
Phase separation within
polymer networks plays a central role in shaping the structure and mechanics of both synthetic materials and living
cells, including the formation of biomolecular condensates within cytoskeletal networks. Previous experiments and theoretical studies indicate that network elasticity can regulate demixing and stabilize finite-sized domains, yet the microscopic origin of this size selection remains elusive. Here, we use coarse-grained molecular dynamics simulations with implicit solvent to investigate how network architecture controls phase separation and limits domain growth. By systematically varying chain contour length, chain
rigidity, and network
topology, we uncover that finite domains emerge when intrinsic chain- or network-level length scales, such as persistence length or
entanglement length, impose local constraints on coarsening. Further, the size of these finite domains is highly correlated with these microscopic network properties, but depends surprisingly little on bulk elasticity. Taken together, our findings establish a molecular basis for understanding droplet formation in
polymer networks, and provide guiding principles for engineering materials and interpreting condensate behavior in
cells.
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All authors Takahiro Yokoyama, Yicheng Qiang, David Zwicker, Arash Nikoubashman
Mesoscale and Nanoscale Physics
Deep-Cryogenic Modeling of 22-nm FDSOI MOSFETs based on BSIM-IMG
Debargha Dutta, Kerim Ture, Fabio Olivieri et al. (+2 more)
We present a modeling approach based on the BSIM-IMG compact model to capture the deep-cryogenic behavior of MOSFET devices in a 22-nm FDSOI technology. The modeling flow is based on DC measurements to extract static parameters including variability and RF measurements to extract dynamic parameters. Modifications to the mobility equations are introduced to enable the modeling of intersubband scattering effect. The extracted models are used to enable deep-cryogenic simulations of a digital-to-analog converter (DAC), showing close agreement with measurement results.
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All authors Debargha Dutta, Kerim Ture, Fabio Olivieri, Alberto Gomez-Saiz, Grayson M. Noah
Mesoscale and Nanoscale Physics
Extended Multi-Temperature Model for Electron–Phonon Coupling and Ultrafast Thermal Transport in Graphene
Houssem Rezgui, Chuang Zhang and Clivia Sotomayor-Torres
Ultrafast thermal transport in low-dimensional materials challenges traditional diffusive models due to reduced scattering, strong electron-
phonon coupling, and pronounced non-
equilibrium effects. To address these complexities, we extend the macroscopic multi-temperature model by incorporating non-diffusive and non-local phenomena, treating electrons, optical
phonons, and acoustic
phonons as coupled but thermally distinct subsystems. We
benchmark this enhanced framework against the multi-temperature Boltzmann transport equation, enabling detailed resolution of branch-dependent energy relaxation and identifying bottlenecks in thermalization. This approach provides a more accurate and comprehensive description of heat flow in emerging materials, offering novel insights into
phonon dynamics and electron-
phonon interactions. These theoretical advances pave the way for the improved design and optimization of next-generation nanoelectronic and photothermal devices.
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Mesoscale and Nanoscale Physics
Hybrid structure with a ferromagnetic film and an array of magnetic molecules for deep-nanoscale reprogrammable magnonics
Oleksandr Pastukh, Piotr Graczyk, Mateusz Zelent et al. (+2 more)
Miniaturization is an essential element in the development of information processing technologies and is also one of the main determinants of the usability of the tested artificial neural networks. It is also a key element and one of the main challenges in the development of magnonic neuromorphic systems. In this work, we propose a new platform for the development of these new
spin-wave-based technologies. Using micromagnetic simulations, we demonstrate that
magnetic molecules regularly arranged on the surface of a thin
ferromagnetic layer enable resonant coupling of propagating
spin waves with the dynamics of the molecules'
magnetic moments, opening a gap in the transmission spectrum up to 150 MHz. The gap, its width, and frequency can be controlled by an external
magnetic field or the arrangement of molecules on the
ferromagnetic surface. Furthermore, the
antiferromagnetic arrangement of the
magnetic moments of molecules or clusters of molecules allows for control of the gap's position and width. Thus, the proposed hybrid structure offers reprogrammability and miniaturization down to the deep nanoscale, operating frequencies in the range of several GHz, key properties for the implementation of artificial neural networks.
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All authors Oleksandr Pastukh, Piotr Graczyk, Mateusz Zelent, Lukasz Laskowski, Maciej Krawczyk
Statistical Mechanics
Inferring Tree Structure with Hidden Traps from First Passage Times
Fabian H. Kreten, Ludger Santen and Reza Shaebani
Tracking the movement of tracer particles has long been a strategy for uncovering complex structures. Here, we study discrete-time random walks on finite Cayley trees to infer key parameters such as tree depth and
geometric bias toward the root or leaves. By analyzing first passage properties, we show that the first two first-passage-time factorial moments (FPTFMs) uniquely determine the tree structure. However, if the random walker experiences waiting phases – due to sticky branch walls or presence of traps – this identification becomes nontrivial. We demonstrate that the generating function of the first passage time (FPT) distribution decomposes into contributions from the waiting time distribution and the random walk without waiting, leading to a nonlinear system of equations relating the factorial moments of the waiting time distribution and the FPTFMs of random walks with and without waiting. For geometrically distributed waiting times, additional moment measurements do not suffice, but unique determination of the structure is achieved by varying initial conditions or fitting the
Fourier transform of the FPT distribution to measured data. The latter method remains effective also for power-law waiting time distributions, where higher-order FPTFMs are undefined. These results provide a framework for reconstructing tree-like networks from FPT data, with applications in biological transport and spatial networks.
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Soft Condensed Matter
Classical density functional treatment of polydisperse polarisable clusters
Clifford E. Woodward, David Ribar and Jan Forsman
Ion clustering has been proposed as a mechanism leading to the peculiar 'anomalous underscreening' phenomenon seen for electrostatic interactions between charge surfaces immersed in concentrated electrolytes. These interactions have been measured using the Surface Force Apparatus, according to which there are strong repulsive interactions between like-charged surfaces, with a range that increases upon further addition of salt, above some threshold concentration. A common suggestion is that ionic aggregates, if they form in sufficient numbers, will reduce the concentration of free ions and thereby increase the nominal Debye length. In previous work, we investigated a cluster model using classical Density Functional Theory (cDFT) and a
polymer-like description of the ion clusters. These clusters were monodisperse and of either a linear or branched architecture, and a fixed charge sequence along the chains. In this work, we generalise the cDFT to treat 'living
polymers' with variable chain lengths and charge arrangements along the chain. This approach allows clusters to become polarised by the presence of charged surfaces, manifested by like-charged bonding. We find that even with a small degree of like-charged bonding a full
equilibrium treatment of our model predicts only weak repulsion between like-charged surfaces. When a global constraint is applied so that the charged surfaces are neutralised only by the dissociated ions, while the clusters contribute overall zero charge, even a very small fraction of clustering ions generate strong and long-ranged forces. Moreover, if the cluster fraction increase substantially upon the addition of further salt, then the strength of the surface forces will also increase, although the range remains roughly constant.
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