Optics
Kerr rotation signature of nonlinear Maxwell electrodynamics under a uniform electromagnetic background
M. J. Neves and Pedro D. S. Silva
Nonlinear electrodynamics naturally arises in
quantum field theory, where the electromagnetic
vacuum behaves as an effective nonlinear optical medium, leading to phenomena such as
vacuum birefringence and dichroism. Among the recently proposed models, modified Maxwell electrodynamics (ModMax) stands out as a conformally invariant nonlinear extension of Maxwell theory that preserves the fundamental
symmetries of classical electrodynamics while predicting nontrivial optical effects. In this work, we investigate optical effects in ModMax electrodynamics in the presence of an external electromagnetic field. Considering uniform and constant
magnetic and electric backgrounds, the solutions for the refractive indices are revisited. Using these results, we obtain the propagating modes and the phase shift (birefringence) for plane wave solutions in the presence of a pure
magnetic background field. Afterwards, we investigate the Goos-Hänchen effect considering the interface between a simple dielectric and a medium whose electromagnetic response tensors are ruled by the ModMax electrodynamics. Further, based on the general reflection problem, we discuss the complex Kerr rotation with both the electric (E) and
magnetic (B) background fields, considering two main cases: i) $B > E$ and ii) $E > B$. Our findings indicate that the $\gamma$ parameter and the ratios (B/E) and (E/B) play a central role in describing the Kerr signals (rotation and ellipticity) of systems with optical effects induced by nonlinear electromagnetic interactions.
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Chemical Physics
Capacity gain in Li-ion cells with silicon-containing electrodes
Marco-Tulio F. Rodrigues, Charles McDaniel, Stephen E. Trask et al. (+1 more)
Silicon-containing lithium-ion batteries can exhibit capacity gain early in life, which makes
forecasting future
cell behavior difficult. We have observed these anomalous trends even in conditions where known mechanisms, such as overhang equalization and excessive electrolyte oxidation, are unlikely to be significant. Here, we combine simulations and experiments to analyze four cases that can produce increased capacity in Si
cells. Three of these pathways relate to break-in processes, where improved mass and charge transport can lead to increased access to active electrode domains and decreased
cell impedance. The fourth case occurs at high levels of prelithiation, when the positive electrode (PE) is completely replenished with Li+ at the end of
cell discharge. We show that the commonality among these mechanisms is that the underlying transformations change the potentials experienced by electrodes at the end of half-cycles, increasing the Li+ inventory available to the
cell. A quantitative framework to describe these effects is presented, enabling these ideas to be extended to other battery systems.
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All authors Marco-Tulio F. Rodrigues, Charles McDaniel, Stephen E. Trask, Daniel P. Abraham
Applied Physics · Cross-listed from cond-mat.soft
A Minimal Nonlocal Theory of Thixotropic Flow
Saghar Zolfaghari and Safa Jamali
Dense amorphous materials exhibit both nonlocal flow cooperativity and pronounced history dependence, yet existing continuum models capture only one of these features at a time. Nonlocal rheologies are intrinsically memoryless, while thixotropic models remain local. Here we introduce a coupling between structural
memory and nonlocal fluidity to include aging and rejuvenation in nonlocal granular fluidity. The resulting model reproduces hysteresis in shear-rate sweeps and delayed yielding in creep, while preserving nonlocal flow profiles. By introducing
memory augmented non local granular fluidity, MNGF, we show that nonlocality alone cannot encode history, and
memory alone cannot encode spatial cooperativity, but their coupling is essential and minimal. These results demonstrate that
memory and nonlocality must be treated jointly to describe history dependent flows, and provide a unified framework for modeling time-dependent rheology in dense amorphous materials.
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Computational Physics · Cross-listed from quant-ph
Quantum Algorithm Framework for Phase-Contrast Transmission Electron Microscopy Image Simulation
Sean D. Lam and Roberto dos Reis
We present a
quantum algorithmic framework for simulating phase-contrast transmission electron microscopy (CTEM) image formation using a fault-tolerant, gate-based
quantum circuit model. The electron wavefield on an $N\times N$ grid is amplitude-encoded into a $2\log_2 N$-
qubit register. Free-space propagation and objective-lens aberrations are implemented via two-dimensional
quantum Fourier transforms (QFTs) and diagonal phase operators in reciprocal space, while specimen interaction is modeled under the weak phase object approximation (WPOA) as a position-dependent phase grating. We validate projected potentials, contrast transfer function (CTF) behavior, and image contrast trends against classical multislice simulations for MoS$_2$ over experimentally relevant parameters, and provide resource estimates and key assumptions that determine end-to-end runtime. While extracting complete $N\times N$ intensity images requires $O(N^2/\epsilon^2)$ measurements that preclude advantage for full-image reconstruction, the framework enables
quantum advantage for tasks requiring
Fourier-space queries, global image statistics, or phase-coherent observables inaccessible to classical intensity-only detection. This framework provides a physics-grounded mapping from CTEM theory to
quantum circuits and establishes a baseline for extending toward full multislice and inelastic scattering models.
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Plasma Physics
Measurement of the laser pulse phase velocity in plasma channel for DLA optimization
E.M. Starodubtseva, I.N. Tsymbalov, D.A. Gorlova et al. (+3 more)
We demonstrate a novel, direct method for measuring the phase velocity $v_{\phi}$ of an intense
laser pulse within a
plasma channel - the crucial parameter that controls the resonance condition in direct
laser acceleration (DLA). The technique exploits the second harmonic (SH) radiation generated at the channel sheath - a phenomenon previously observed in
laser-wakefield acceleration experiments. The SH emission angle is governed by a phase-matching condition that directly depends on $v_{\phi}$. Experimental measurements performed using a 1 TW, 10 Hz Ti:Sa
laser system yield phase velocities in the range $v_{\phi}=(1.010-1.030)c$ for
plasma electron densities in the range $n_e=(0.01-0.06)n_{cr}$. The diagnostic is validated through quasi-3D particle-in-
cell (PIC) simulations that reproduce the experimental conditions. This work provides a way to optimize DLA schemes by enabling in-situ measurement of the
laser pulse phase velocity in
plasma channels.
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All authors E.M. Starodubtseva, I.N. Tsymbalov, D.A. Gorlova, K.A. Ivanov, R.V. Volkov, A.B. Savel'ev
Popular Physics · Cross-listed from astro-ph.EP
The Interplanetary Habitable Zone
Caleb Scharf
The concept of a system-wide measure of the sustainment of life (habitability) for space-faring interplanetary species is introduced and explored. Although largely agnostic to the details of how interplanetary life might operate (e.g., via technology or by utilizing organism traits that are, as of now, unknown to us), some assumptions must be made about energy harvesting, orbital mobility costs, radiation risks, and resource requirements. A multi-modal figure of merit is developed for evaluating an interplanetary habitable zone (IHZ). An
agent-based model is also developed to simulate the dispersal of interplanetary life in a planetary system and characterize the IHZ. For the
solar system, resource weightings between planetary bodies dictate many overall behaviors, including the sequence of migration from Earth to the Moon, Mars, and asteroid belt. Comparisons with the Trappist-1 exoplanetary system also point to critical sensitivities in the balance between resource availability and risk or cost factors (e.g., radiation risks and orbital Delta-v costs) that determine the structure of an IHZ. Results suggest that our
solar system may have an inherent, and significant, advantage for a space-faring species over a system like Trappist-1. This modeling approach may also have application to emerging space economies in our own
solar system.
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Chemical Physics
Nuclear gradients from auxiliary-field quantum Monte Carlo and their application in geometry optimization and transition state search
Jo S. Kurian, Ankit Mahajan and Sandeep Sharma
In this article, we present a method for computing accurate and scalable
nuclear forces within the phaseless auxiliary-field
quantum Monte Carlo (AFQMC) framework. Our approach leverages automatic differentiation of the energy functional to obtain
nuclear gradients at a computational cost comparable to that of energy evaluation. The accuracy of the method is validated against finite difference calculations, showing excellent agreement. We then explore several machine learning (ML) strategies for learning noisy AFQMC data. These ML potentials are subsequently used to perform geometry optimizations and nudged elastic band (NEB) calculations, successfully identifying the transition state of the formamide-formimidic acid tautomerization. The resulting transition state geometry and barrier heights are in close agreement with coupled-cluster reference values. This work paves the way for highly accurate geometry optimization, molecular dynamics, or reaction path calculations.
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Data Analysis and Statistics · Cross-listed from hep-ph
Profiling systematic uncertainties in Simulation-Based Inference with Factorizable Normalizing Flows
Davide Valsecchi, Mauro Donegà and Rainer Wallny
Unbinned likelihood fits maximize the information extracted from experimental data, yet their application in realistic high-dimensional analyses has been fundamentally bottlenecked by the prohibitive computational cost of profiling systematic uncertainties. Furthermore, current machine learning-based inference methods typically estimate scalar parameters, discarding complex high-dimensional correlations. To address this, we propose a general Simulation-Based Inference (SBI) framework that elevates the fit target from scalar parameters to a multivariate Distribution of Interest (DoI), a learnable, invertible transformation of the feature space. We employ Factorizable Normalizing Flows to model systematic variations as parametric deformations, preserving tractability without combinatorial explosion. Crucially, we develop an amortized training strategy that learns the conditional dependence of the DoI on nuisance parameters in a single optimization process, bypassing repetitive training during likelihood scans. To capture the finite-sample statistical variance of the neural network DoI, we introduce a Poisson-bootstrap ensemble, which we marginalize through an averaged likelihood to deliver a complete statistical-plus-systematic uncertainty budget within a single unbinned likelihood. Validated on a synthetic
dataset emulating a high-energy physics measurement, our method demonstrates that rigorous, fully profiled unbinned measurements can now be extended to complete differential distributions. By turning the fit into a functional measurement, this approach offers a powerful, unifying framework for a broad range of tasks conventionally treated as distinct problems, from detector calibration and differential cross-sections to unfolding and continuous parameter estimation.
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Atmospheric and Oceanic Physics
Selection of CMIP6 Models for Regional Precipitation Projection and Climate Change Assessment in the Jhelum and Chenab River Basins
Saad Ahmed Jamal, Ammara Nusrat, Muhammad Azmat et al. (+1 more)
Effective water resource management depends on accurate projections of flows in water channels. For projected
climate data, use of different General Circulation Models (GCM) simulates contrasting results. This study shows selection of GCM for the latest generation CMIP6 for hydroclimate change impact studies. Envelope based method was used for the selection, which includes components based on machine learning techniques, allowing the selection of GCMs without the need for in-situ reference data. According to our knowledge, for the first time, such a comparison was performed for the CMIP6 Shared Socioeconomic Pathway (SSP) scenarios data. In addition, the effect of
climate change under SSP scenarios was studied, along with the calculation of extreme indices. Finally, GCMs were compared to quantify spatiotemporal differences between CMIP5 and CMIP6 data. Results provide NorESM2 LM, FGOALS g3 as selected models for the Jhelum and Chenab River. Highly vulnerable regions under the effect of
climate change were highlighted through spatial maps, which included parts of Punjab, Jammu, and Kashmir. Upon comparison of CMIP5 and CMIP6, no discernible difference was found between the RCP and SSP scenarios precipitation projections. In the future, more detailed statistical comparisons could further reinforce the proposition.
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All authors Saad Ahmed Jamal, Ammara Nusrat, Muhammad Azmat, Muhammad Osama Nusrat
Plasma Physics
Exact moment methods for conservation laws in phase space
Tileuzhan Mukhamet and Katharina Kormann
We construct exact moment models for a class of conservation laws based on a parametrization of the distribution functions by its moments as proposed in [Burby, Sci. Rep. 13 (2023)]. In particular, we derive moment models for the Vlasov–Maxwell and the relativistic Vlasov–Maxwell systems. The new models can be viewed as a higher degree extension of the Direct Quadrature Method of Moments (DQMOM). We propose slicing moment method for the representation of the distribution function. For simulations with strong kinetic effects, we utilize a hybrid formulation that transforms adaptively a fraction of fluid nodes into particles in order to capture multi-streaming. We demonstrate convergence and performance of our strategies on the weak and strong Landau damping and two-stream instability experiments in non-relativistic and relativistic limits.
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Applied Physics · Cross-listed from cond-mat.quant-gas
Absorption imaging of quantum gases near surfaces using incoherent light
Julia Fekete, Poppy Joshi, Peter Krüger et al. (+1 more)
We introduce an absorption imaging technique for ultracold gases that suppresses interference fringes and coherence-induced artifacts by reducing the transverse spatial coherence of the imaging light. The method preserves the narrow spectral bandwidth required for resonant absorption imaging and is implemented as a modular extension to standard imaging setups using a rotating diffuser. We demonstrate tunability of the illumination light's coherence without modifying the imaging optics. Using this approach, we achieve reliable imaging of ultracold atomic clouds in micron-scale proximity to complex surfaces, where standing waves, edge diffraction, and speckle severely limit conventional absorption imaging.
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All authors Julia Fekete, Poppy Joshi, Peter Krüger, Fedja Oručević
Chemical Physics
Early-warning the compact-to-dendritic transition via spatiotemporal learning of two-dimensional growth images
Hyunjun Jang, Chung Bin Park, Jeonghoon Kim et al. (+1 more)
Transitions between distinct dynamical regimes are ubiquitous in nonequilibrium systems. As a prototypical example, deposition growth is often accompanied by irreversible morphological instabilities.
Forecasting such transitions from pre-transition configurations remains fundamentally challenging, as early precursors are weak, spatially heterogeneous, and masked by inherent fluctuations. Here, we investigate compact-to-dendritic transitions (CDTs) in a two-dimensional particle-based electrodeposition model and formulate a horizon-based early-warning task using trajectory-resolved transition points. We demonstrate that anticipating the CDT is intrinsically a spatiotemporal problem: neither static morphological descriptors nor temporal learning applied to predefined features alone yields reliable predictive signals. In contrast, end-to-end learning of jointly optimized spatial and temporal representations from growth images enables robust anticipation across a wide range of prediction horizons. Analysis of the learned latent dynamics reveals the emergence of a low-dimensional surrogate variable that tracks progressive morphological destabilization and undergoes reorganization near the transition. We further show that the learned spatiotemporal representation exhibits limited but systematic transferability across reaction-rate conditions, with predictive performance degrading as the inference condition departs from the training condition, consistent with changes in the latent-state dynamics. Overall, our results establish a general formulation for
forecasting incipient instabilities in nonequilibrium interfacial growth, with implications for the predictive monitoring and control of pattern-forming driven systems.
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All authors Hyunjun Jang, Chung Bin Park, Jeonghoon Kim, Jeongmin Kim
Optics · Cross-listed from nlin.PS
Optical Thermodynamics Beyond the Weak Nonlinearity Limit
Emily Kabat, Shrohan Mohapatra, P.G. Kevrekidis et al. (+1 more)
Optical thermodynamics has recently emerged as a theoretical framework describing a Rayleigh-Jeans (RJ) modal power distribution of multimoded nonlinear photonic
circuits. However, its applicability is constrained to systems exhibiting weak nonlinear mode-mode interactions. Here, by employing a Transfer Integral Operator, we circumvent this limitation and establish a steady-state interacting RJ modal distribution – referred to as non-ideal RJ (NIRJ) – with renormalized temperature and optical chemical potential. This also builds a natural bridge with earlier work on grand-canonical statistical-mechanical formulations of discrete nonlinear systems. The theory derives the optical analogue of the compressibility factor, which controls the transition from an ideal, non-interacting equation of state (EoS) to a van der Waals-like interacting EoS.
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All authors Emily Kabat, Shrohan Mohapatra, P.G. Kevrekidis, Tsampikos Kottos
Computational Physics
An Always-Accepting Algorithm for Transition Path Sampling
Magdalena Häupl, Sebastian Falkner, Peter G. Bolhuis et al. (+2 more)
We present a one-way shooting
algorithm for transition path sampling that accepts every proposed trajectory, yet samples the correct transition path ensemble for systems with overdamped
stochastic dynamics. The method is based on two key elements: a procedure to propose trajectories that are always reactive, and a reweighting scheme that corrects for the bias introduced by always accepting the proposed paths. This approach significantly improves the efficiency of transition path sampling by eliminating the cost associated with generating trajectories that are then rejected. We demonstrate the performances of the
algorithm by investigating the formation of CO$_2$ clathrate hydrates along different reaction mechanisms, showing that the increased efficiency allows proper sampling of the formation of crystalline hydrates at temperatures and pressures that are difficult to access with conventional schemes.
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All authors Magdalena Häupl, Sebastian Falkner, Peter G. Bolhuis, Christoph Dellago, Alessandro Coretti
Optics
Hybrid Femtosecond Laser and Ion-Implantation Processing for Controlled, Deep, High-Efficiency Ablation in Fused Silica
Mario Garcia-Lechuga, Yoann Levy, Irene Solana et al. (+3 more)
Femtosecond
laser modification of fused silica enables precise surface tailoring for the fabrication of micro-optical components such as microlenses and diffractive elements. However, the process is governed by
laser-matter interactions where the local fluence determines the processing depth, often limiting control over feature geometry and efficiency. Here, we present a hybrid approach combining localized Au implantation (1.8 MeV Au2+ ions) into SiO2 samples with femtosecond
laser irradiation (250 fs), effectively tuning the
laser-matter interaction and resulting morphology. At both 515 nm and 1030 nm irradiation wavelengths, single-shot femtosecond pulses produce cylindrical craters with sharp edges and flat-bottom profiles. Independently of the fluence, these craters exhibit a constant depth of 550 nm, corresponding to the region of maximum Au concentration. The effect manifests already at moderate fluence (app. 4 J/sq.cm) and yields high ablation efficiency, up to 15 cubic micrometers per microjoule. The hybrid method also works effectively at lower implantation doses that preserve the excellent transmission of fused silica, offering a promising pathway for the high-quality fabrication of flat optical components such as binary phase masks, phase lenses, or fused-silica micromolds.
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All authors Mario Garcia-Lechuga, Yoann Levy, Irene Solana, Fatima Cabello, Maria Dolores Ynsa, Nadezhda M. Bulgakova
Data Analysis and Statistics · Cross-listed from quant-ph
Wendy Otieno, Alexandre Zagoskin, Alexander G. Balanov et al. (+2 more)
We present a
quantum reservoir computing (QRC) framework based on a small-scale
quantum system comprising at most six interacting
qubits, designed for nonlinear financial time-series
forecasting. We apply the model to predict future daily closing trading volumes of 20
quantum-sector publicly traded companies over the period from April 11, 2020, to April 11, 2025, as well as minute-by-minute trading volumes during out-of-
market hours on July 7, 2025. Our analysis identifies optimal reservoir parameters that yield stock trend (up/down) classification accuracies exceeding $86 \%$. Importantly, the QRC model is platform-agnostic and can be realized across diverse physical implementations of
qubits, including superconducting
circuits and trapped ions. These results demonstrate the expressive power and robustness of small-scale
quantum reservoirs for modeling complex temporal correlations in financial data, highlighting their potential applicability to real-world
forecasting tasks on near-term
quantum hardware.
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All authors Wendy Otieno, Alexandre Zagoskin, Alexander G. Balanov, Juan Totero Gongora, Sergey E. Savel'ev
Computational Physics
Tensor Network Compression for Fully Spectral Vlasov-Poisson Simulation
Erik M. Åsgrim, Luca Pennati, Marco Pasquale et al. (+1 more)
We propose a numerical method for kinetic
plasma simulation in which the phase-space distribution is represented by a low-rank tensor network with an adaptive level of compression. The Vlasov-Poisson system is advanced using a second-order Strang splitting scheme, with the advection and acceleration steps treated spectrally in position and velocity, respectively. By representing both the state and the operators required for time
evolution as compressed tensor objects, the propagation can be carried out directly in tensor form without reconstructing the full phase-space grid. The self-consistent electric field is likewise obtained entirely within the tensor formalism through a tensor-based Poisson solver. We validate the approach on Landau damping and the two-stream instability, and find near-indistinguishable agreement with the corresponding full-grid reference while achieving substantial compression of the state representation. Additionally, we examine how varying the degree of compression influences conservation properties, positivity behavior, and computational cost, and show that compressibility varies strongly across the considered dynamical regimes. More broadly, the results point toward a promising class of spectral Eulerian
plasma solvers that operate directly on compressed tensor representations.
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All authors Erik M. Åsgrim, Luca Pennati, Marco Pasquale, Stefano Markidis
Fluid Dynamics
Enhanced numerical approaches for modeling insoluble surfactants in two-phase flows with the diffuse-interface method
Shu Yamashita, Shintaro Matsushita and Tetsuya Suekane
Surfactants reside at the interface of two-phase flows and significantly influence the flow dynamics. Numerical simulations are essential for a comprehensive understanding of such surfactant-laden flows and require a method that can accurately simulate surfactant transport along the interface. In this study, we focus on interfacial transport models for insoluble surfactants based on the diffuse-interface method and propose two approaches to improve their accuracy: (a) adopting a formulation that avoids the spatial derivatives of variables with sharp gradients and (b) allowing the width of the delta function to be specified independently of the interface width. These approaches are simple and practical in that they do not lead to significant increases in computational cost, implementation complexity, or degradation of interface-capturing accuracy. Moreover, they preserve the discrete conservation of both fluid and surfactant mass. We conduct a series of numerical tests to demonstrate the effectiveness of the proposed approaches. Finally, we present a challenging test case that is difficult to solve accurately and has not been previously discussed. We expect this case to serve as a valuable
benchmark for evaluating and comparing the performances of various methods proposed in the literature.
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Plasma Physics
Structure preservation using discrete gradients in the Vlasov-Poisson-Landau system
Daniel S. Finn, Joseph V. Pusztay, Matthew G. Knepley et al. (+1 more)
We present a novel structure-preserving framework for solving the Vlasov-Poisson-Landau system of equations using a particle in
cell (PIC) discretization combined with discrete gradient time integrators. The Vlasov-Poisson-Landau system is an accurate model for studying hot
plasma dynamics at a kinetic scale where small-angle Coulomb collisions dominate. Our scheme guarantees conservation of mass, momentum and energy as well as preservation of the monotonicity of
entropy production in both the time-continuous and discrete systems. We employ the conservative integrator for both the
Hamiltonian Vlasov-Poisson equations and the dissipative Landau equation using the PETSc library (www.mcs.anl.gov/petsc) to showcase structure-preserving properties.
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All authors Daniel S. Finn, Joseph V. Pusztay, Matthew G. Knepley, Mark F. Adams
Accelerator Physics
Improving the performance of mid-T baked niobium cavities through post-bake surface treatment
V. Chouhan, D. Bice, A. Cravatta et al. (+7 more)
The Medium temperature (mid-T) baking of niobium superconducting
radio-frequency cavities at 300 350  C in a
vacuum furnace is known to enhance the quality factor (Q₀). However, despite this improvement, cavities treated with this process often exhibit premature quench at relatively low accelerating fields. This limitation is suspected to arise from the formation of surface contaminants, such as niobium carbides, during the furnace bake at 350 C for 3 h. To investigate the influence of potential surface contamination, this study applied an ultralight chemical removal to 1.3 GHz and 650 MHz single-
cell cavities that had undergone medium-temperature baking. The removal of the top RF surface layer led to a notable improvement in the quench field and Q₀, indicating a beneficial effect of eliminating possible surface residues introduced during the bake.
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All authors V. Chouhan, D. Bice, A. Cravatta, B. Guilfoyle, A. Murthy, A. Netepenko, T. Reid, T. Ring, D. Smith, G. Wu
Instrumentation and Detectors · Cross-listed from cond-mat.supr-con
Quantitative imaging of Abrikosov vortices by scanning quantum magnetometry
Clemens Schäfermeier, Ankit Sharma, Christopher Kelvin von Grundherr et al. (+5 more)
Understanding
vortex matter in type-II
superconductors is central to controlling dissipation and flux pinning in superconducting materials and devices. Here, we use cryogenic scanning nitrogen vacancy magnetometry (NVM) to image Abrikosov
vortices in the cuprate
superconductors BSCCO-2212 and YBCO under controlled field-cooled conditions. Measurements, which are performed using continuous-wave optically detected
magnetic resonance (cw-ODMR) in a closed-cycle cryostat, yield quantitative
magnetic-field maps with nanoscale spatial resolution. In BSCCO-2212 at 71 K, we resolve a well-ordered triangular
vortex lattice, whose
symmetry and spacing are confirmed through 2D
Fourier analysis and are consistent with flux quantization. YBCO thin films imaged at 3 K exhibit a more disordered
vortex arrangement reflecting stronger pinning, while maintaining quantitative agreement between measured
vortex density and the applied
magnetic field. These results render our cryogenic scanning NVM a reliable quantitative tool for real-space studies of
vortices in high-$T_c$
superconductors, in particular since such a remarkable
magnetic resolution has been achieved within relatively short acquisition times of 2 to 4 h.
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All authors Clemens Schäfermeier, Ankit Sharma, Christopher Kelvin von Grundherr, Dieter Andres, Andrea Morales, Jan Rhensius, Gabriel Puebla-Hellmann, Mirko Bacani
Optics
Polariton-mediated binding of anti-aligned dipolar excitons
Haifeng Kang, Quanbing Guo, Tianyi Zhou et al. (+7 more)
Interacting bosonic quasiparticles are the cornerstone for exploring many-body physics and nonlinear
quantum phenomena in correlated light-matter systems. Strongly interacting dipolar
excitons in van der Waals
heterostructures have attracted significant interest due to their out-of-plane electric dipole moments and high tunability via the
quantum-confined Stark effect (QCSE). However, leveraging these tunable dipolar
excitons in strongly coupled
exciton-
photon systems to explore exotic many-body physics and macroscopic
quantum phenomena remains experimentally elusive. Here, we report the strong coupling of dipolar
excitons in a gated
bilayer MoS2 device integrated with a one-dimensional photonic
crystal hosting bound-states-in-continuum (BIC). The resulting polaritons hybridize cavity
photons with a coherent superposition of two electrically tunable anti-aligned dipolar
excitons, effectively binding them into composite quasiparticle states. By tuning the dipolar
excitons into non-degenerate states via the QCSE, we realize in situ reconfiguration of the polariton wavefunction and observe an emergent polariton branch exhibiting non-monotonic Stark shifts. Notably, these tunable polaritons allow for customized control over nonlinear interactions through distinct excitonic hybridization and dipolar configurations. This in situ tunability offers a scalable pathway toward electrically programmable
quantum fluids of light and correlated polariton phases in on-chip photonic integrated
circuits.
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All authors Haifeng Kang, Quanbing Guo, Tianyi Zhou, Shun Feng, Wei Dai, Kenji Watanabe, Takashi Taniguchi, Hongxing Xu, Ting Yu, Xiaoze Liu
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Negative thermal expansion in ice I polytypes
Leonardo del Rosso, A. Dominic Fortes, Daniele Colognesi et al. (+4 more)
The fundamental properties of ice have always attracted a lot of interest due to omnipresence of ice in many different natural contexts. Since cubic ice recently become experimentally accessible from a low-density gas hydrate precursor [1, 2], it has been possible to measure its density as a function of temperature in the whole thermodynamic range of metastability. We found strong analogies with respect to the other ice I polytype, i.e., hexagonal ice Ih [3], including the presence of a negative thermal expansion behavior at low temperature. Based on these results, a new enthalpy calculation quantifies the metastable nature of the cubic form and, consequently its inaccessibility from a "normal" ice Ih precursor.
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All authors Leonardo del Rosso, A. Dominic Fortes, Daniele Colognesi, Alberto Santonocito, Francesco Grazzi, Selene Berni, Milva Celli
Biological Physics
Viscous vertex model for active epithelial tissues
Shao-Zhen Lin, Sham Tlili and Jean-François Rupprecht
We present a rotationally invariant viscous vertex model that accounts for both cortical and bulk dissipation of
cells. The vanishing substrate-friction limit is enforced via Lagrange multipliers, which also provides a framework for implementing various boundary conditions, such as fixed boundaries and prescribed tractions. Building on this formulation, we introduce a slab-shear rheology protocol to extract an effective, coarse-grained tissue shear viscosity. Under polar or nematic activity, viscosity regulates the formation of elongated, spatially correlated
cell-shape textures and stabilizes well-defined topological defects. Because the model remains well-posed at zero substrate friction, it is naturally suited to describing free-floating epithelia and organoids.
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Physics and Society
Modelling human activities in a system of cities
Guo-Shiuan Lin, Denise Hertwig, Megan McGrory et al. (+5 more)
Cities host most of the world population with diverse services and activities. One key challenge in urban modelling is the quantification of intra- and inter-city mobility patterns and the associated space-time dynamics of population density and anthropogenic activities. To address this, we apply the novel
agent-based urban model DAVE (Dynamic Anthropogenic actiVities and feedback to Emissions) to simulate population behaviour and mobility in the Vaud and Geneva Cantons, a system of small- to medium-size cities in Switzerland. Simulation results provide detailed temporal (10 min) and spatial (500 m) population dynamics for different age groups and day types. DAVE further models the time-varying population distribution in 11 different microenvironments (e.g., home, work, leisure, outdoor) and the travel flows by different modes. Simulation results align with observations, confirming the possibility of driving urban system modelling with statistical information on residents' behaviour. Sustainability and health indicators like daily driving distance and walking time for each neighbourhood are also reflected by the model with urban-rural gradients displayed. This work serves as a foundation for future applications of DAVE to study bottom-up human-built environment interactions, from anthropogenic emissions and building energy to urban
climate, exposure, and health in cities around the world.
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All authors Guo-Shiuan Lin, Denise Hertwig, Megan McGrory, Tiancheng Ma, Stefán Thor Smith, Maider Llaguno-Munitxa, Sue Grimmond, Gabriele Manoli
Optics
Polarization-Multiplexed Bloch Surface Wave Sensing of Single-Strand DNA Growth
Jonathan Barolak, Erika Mogni, Giovanni Pellegrini et al. (+8 more)
Refractometric biosensing is a vital label-free tool for the real time detection and interaction analysis of biological and chemical substances. Nanophotonic platforms like Surface Plasmon Resonance (SPR) have played a critical role in providing refractometric sensing capabilities for clinical diagnostics and environmental monitoring. However, traditional systems operating in a single-polarization state cannot fully characterize complex optical properties such as birefringence, which is crucial to resolve many complex biological interactions. Although Bloch Surface Wave (BSW) sensors can support both TE and TM modes, a key capability SPR lacks, they have historically been implemented in single-mode configurations. In this paper, we present a polarization multiplexed BSW refractometric sensing system, simultaneously tracking the resonant wavelength shifts of both TE and TM BSW modes through time. Our technique was applied to investigate single-strand DNA growth during rolling circle amplification (RCA). To accurately recover the time-dependent birefringence, capturing dynamics of the DNA growth and orientation of its chains, we implemented a two-stage modeling approach based on the TMM. First, we utilized a wavelength-dependent surface sensitivity model, confining refractive index changes to the immediate layer above the
crystal, to distinguish isotropic background dynamics from birefringent signals. Following the onset of RCA, we transitioned to a model that accounted for the vertical growth of the DNA layers in time. By fitting this model to the TE and TM resonant shifts, we monitor the growth rate of the single-strand DNA layer as well as the refractive index along the two polarization components. Our findings demonstrate the platform's ability to resolve the structural
evolution of complex bimolecular interactions associated with conformational changes.
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All authors Jonathan Barolak, Erika Mogni, Giovanni Pellegrini, Jorge Gil-Rostra, Francisco Yubero, Michele Celebrano, Marco Finazzi, Katharina Schmidt, Stefan Fossati, Jakub Dostálek, Paolo Biagioni
Chemical Physics · Cross-listed from quant-ph
Effective classical potential for quantum statistical averages
Vijay Ganesh Sadhasivam, Stuart C. Althorpe and Venkat Kapil
We present an effective potential that allows
quantum thermal expectation values of a position-dependent observable to be estimated as a classical ensemble average of the corresponding function. We follow the approach of Feynman and Hibbs, but perform the mean-field treatment of
quantum fluctuations about the path starting point rather than the path centroid. Furthermore, rather than performing a full variational optimization of the potential, we explore approximate functional forms that yield a numerical robustness. The resulting closed-form potential is exact in the classical and harmonic limits;
benchmarks against exact position distributions for one-dimensional quartic, Morse, and double-well potentials, show good agreement for potentials with harmonic support.
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Fluid Dynamics
On multiple stable states in Taylor-Couette flow with realistic end-wall boundary conditions
Marvin Kriening, Zhongzhi Yao, Mohammad S. Emran et al. (+3 more)
We investigate Taylor-Couette flow with realistic no-slip boundary conditions at all surfaces through direct numerical simulations (DNS) and theoretical analysis. Imposing physically consistent end-wall conditions at the top and bottom lids significantly alters the flow dynamics compared to that for periodic boundary conditions. We extend the classical angular-momentum-flux framework to account for axial transport, which leads to a significantly improved agreement with the Eckhardt-Grossmann-Lohse model (Eckhardt et al. 2007). A systematic exploration of the parameter space $(Re, n) $ uncovers multiple long-lived states with different roll number $n$ configurations at identical Reynolds numbers $Re$, giving rise to pronounced hysteresis loops occurring under realistic boundary conditions. Our DNS for no-slip axial end caps reveal a sequence of structural transitions: as the inner-cylinder Reynolds number increases, the flow evolves from Taylor
vortex flow through chaotic wavy
vortex flow and turbulent wavy
vortex flow to an axisymmetric turbulent Taylor
vortex flow. Using modal energy budgets we identify transition mechanisms and quantify how the accessible phase-space volume and associated roll-specific angular momentum flux depend on control parameters and the specific flow state. Our findings demonstrate the impact of realistic boundary conditions on the dynamics in Taylor-Couette flow, and how they change the stability landscape of multiple states. The coexistence of distinct flow patterns and their stability analysis offers promising insights into transition dynamics between laminar and turbulent regimes in closed sheared flows.
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All authors Marvin Kriening, Zhongzhi Yao, Mohammad S. Emran, Jiaxing Song, Andrei Teimurazov, Olga Shishkina
Chemical Physics
Neural Quantum States Based on Selected Configurations
Marco Julian Solanki, Lexin Ding and Markus Reiher
Neural
quantum states (NQS) provide a flexible and highly expressive parameterization of wave functions for strongly correlated problems in
quantum chemistry. Despite rapid advances in network architectures, the evaluation of electronic energies remains almost exclusively based on variational Monte Carlo (VMC). While VMC is effective for structured systems such as
spin chains, its accuracy and efficiency for electronic
Hamiltonians are hindered by sharply peaked distributions,
stochastic gradient noise, and slow convergence with sample size. In this letter, we assess the capability of NQS-VMC to efficiently capture correlation in electronic ground states by comparing it to a recently developed NQS-based selected configuration (NQS-SC) approach. We set up a systematic comparison of the ground-state optimizations obtained with NQS-VMC and NQS-SC for molecular systems dominated by either static or dynamical correlation. The comparison demonstrates a clear advantage of NQS-SC over NQS-VMC in both energy accuracy and wave-function coefficients, particularly for statically correlated molecules. Moreover, NQS-SC exhibits robust systematic improvability, whereas NQS-VMC does not. These findings position NQS-SC as the new default approach over NQS-VMC for electronic structure calculations. We further observe that neither NQS-SC nor NQS-VMC can efficiently capture dynamical correlation, highlighting the need for future hybrid methods, such as multiconfigurational perturbation theories built on top of NQS solutions.
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Plasma Physics
Role of the radial electric field in the confinement of energetic ions in the Wendelstein 7-X stellarator
M. Arranz, J. L. Velasco, I. Calvo et al. (+1 more)
Good fast-ion confinement is an essential requirement for a fusion reactor. The
magnetic configuration of the Wendelstein 7-X (W7-X) stellarator is partially optimized in this regard in a reactor-relevant scenario: it is expected to show improved fast-ion confinement when $\beta$ is high and the effect of the radial electric field is negligible. The experimental validation of this optimization is difficult since, with the available power, achieving high $\beta$ under appropriate conditions for the validation is challenging and the effect of the radial electric field is inevitable. In this work, the confinement of fast ions in W7-X has been studied numerically for a variety of scenarios via the ASCOT5 code. The effect of the radial electric field on fast-ion losses is confirmed to be equivalent to the one produced by $\beta$, and this is characterized by means of scans on both parameters. Through a preliminary study with experimentally-based profiles, a viable scenario is identified that takes advantage of this effect for the experimental validation of the optimization strategy of W7-X.
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All authors M. Arranz, J. L. Velasco, I. Calvo, D. Carralero