Chemical Physics
cuSOAP: a GPU-accelerated Generator of Smooth Overlap of Atomic Positions Descriptor
Hongyu Yan, Yuqing Xia, Yong Wei et al. (+2 more)
The Smooth Overlap of Atomic Positions (SOAP) descriptor is one of the most widely adopted representations of atomic environments in molecular machine learning, but the cost of evaluating it and its derivatives remains a principal bottleneck of SOAP-based interatomic potentials, particularly at the large radial and angular basis sizes demanded by complex, multi-species condensed-phase environments. We present cuSOAP, a GPU-accelerated generator of atom-wise SOAP vectors and their analytic derivatives. Built on PyTorch, cuSOAP evaluates closed-form expressions or quadratures for the projection coefficients and their Cartesian gradients for Gaussian-type-orbital and
polynomial radial bases, through fused CUDA and Triton kernels that eliminate the multi-gigabyte intermediates of a naive tensor formulation. The package is a drop-in replacement for the CPU-based reference DScribe, reproducing its constructor signature, feature ordering, and output to within ${\sim}10^{-6}$, and accepts structures directly as Atomistic Simulation Environment (ASE) Atoms objects. On an NVIDIA Grace–Blackwell (GB200) node, a single Blackwell GPU generates the full descriptor-plus-Jacobian workload for a 1000-molecule water cluster up to two orders of magnitude faster than DScribe, i.e., from $13\times$ to $227\times$ across the entire $(n_{\max}, l_{\max})$ hyperparameter map, with the speedup growing with the angular band limit $l_{\max}$. Descriptor-only generation scales as $t \propto n^{1.34}$, close to linear, up to a million-atom water cluster, which is processed in 19.5s on one GPU and, through a shared-
memory multiprocessing driver, in 5.7s on the four GPUs of the node, demonstrating $\sim$90% parallel efficiency with no sign of saturation as devices are added. These results bring on-the-fly SOAP evaluation for large-scale condensed-phase simulation within reach.
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All authors Hongyu Yan, Yuqing Xia, Yong Wei, Minghan Chen, Hanning Chen
Medical Physics
A unified dielectric-tensor model of macular form birefringence and dichroism
Gary P. Misson, Dusan Sarenac, Dmitry. A. Pushin et al. (+1 more)
Optical anisotropy of the Henle fiber layer (HFL) underlies two macular polarization phenomena, form birefringence (the macular cross) and dichroism (Haidinger's brushes), which have conventionally been treated as unrelated. We model the HFL as a radial diattenuating retarder and derive a single complex dielectric tensor: effective-medium theory for parallel cylinders gives the real part, and cylindrical averaging of the measured transmembrane xanthophyll tilt gives the imaginary part. The birefringent slow axis is radial and the absorption axis tangential, perpendicular by structural necessity. The model reproduces measured dichroic ratios of 1.04–1.14 for a single calibrated oriented-pigment fraction, and supplies the input parameters for full electromagnetic treatments.
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All authors Gary P. Misson, Dusan Sarenac, Dmitry. A. Pushin, Shelby E. Temple
Plasma Physics
A Minimal Self-Consistent Model for the Nonlinear Dynamics of Asymmetric Capacitively Coupled Radio-Frequency Plasmas
Thomas Mussenbrock
We develop a minimal self-consistent lumped-element model for the nonlinear
radio-frequency dynamics of geometrically asymmetric capacitively coupled
plasmas. The fast electrical response is described by three dynamical variables: the powered-sheath charge, the blocking-capacitor voltage, and the discharge current. The periodic RF solution is coupled to stationary particle and energy balances, which determine the electron temperature and
plasma density from the operating conditions and the absorbed power. For an argon discharge, the model produces nonlinear current oscillations and a broad higher-harmonic response associated with the
plasma series resonance. Variation of the RF voltage leads to correlated changes in the harmonic spectrum, absorbed power, and
plasma density. Linearization about the periodic state relates the high-frequency response to the time-dependent differential sheath elastance. A moment-based effective elastance provides a compact estimate of the corresponding characteristic PSR frequency. The model thereby connects nonlinear RF dynamics and
plasma sustainment within a minimal self-consistent description.
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Applied Physics · Cross-listed from cond-mat.mes-hall
Spectroscopy With Intelligent Feature Tracking for automated characterization of excited-state structure in semiconductor quantum dot devices
A. R. Huffman, Daniel Schug, Merritt Losert et al. (+6 more)
The characterization of excited-state structure in
semiconductor quantum dot (QD) devices is an important component of tuning them for
spin-
qubit operation. We present Spectroscopy With Intelligent Feature Tracking (SWIFT), a framework that combines machine-learning (ML)-assisted feature identification with physics-informed
geometric processing to extract energy-level splittings from pulsed-gate spectroscopy data. SWIFT isolates the relevant spectral features and exploits their characteristic geometry to reduce the two-dimensional spectroscopy analysis to a one-dimensional peak-detection problem. It further combines an ensemble-based confidence metric with sequential accumulation of rapid, low-SNR scans, allowing the inferred spectrum to be reevaluated as experimental evidence accumulates. Using Si/SiGe QD devices, we demonstrate SWIFT both offline and in real time, including automated tracking of QD excited states and lead resonances. Benchmarking on 255 manually labeled scans shows that SWIFT reduces the median splitting error to 0.05 mV from 0.11 mV for a classical baseline, with the largest improvement on lower-quality measurements. These results provide a path toward incorporating excited-state spectroscopy into autonomous QD characterization, tuning, and optimization, which will be essential in large-scale
quantum dot devices.
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All authors A. R. Huffman, Daniel Schug, Merritt Losert, Sanghyeok Park, Daniel King, Yuna Chun, Giordano Scappucci, M. A. Eriksson, Justyna P. Zwolak
Instrumentation and Detectors
The DarkLight Experiment at TRIUMF
R. Alarcon, D. Almonte, M.I. Alstaty et al. (+60 more)
This paper reports on the commissioning of the DarkLight experiment at the ARIEL superconducting electron linear accelerator located at TRIUMF in Vancouver, Canada. DarkLight was designed to utilize the ARIEL electron beam to search for a new
boson, $A^\prime$, which preferentially couples to
leptons, with a mass in the range 13-17 MeV/$c^2$. Such a
boson could be produced via the $e^-~X\rightarrow e^-~X~A^\prime$ process, and the resulting $A^\prime\rightarrow e^+~e^-$ decay used to reconstruct the invariant mass of the $A^\prime$. The $e^+e^-$ pair is detected using a pair of
magnetic spectrometers. Each spectrometer is instrumented with two triple GEM detectors and a scintillating strip hodoscope to trigger the event readout. Electron beam energies between 10 and 30 MeV were used to commission the experiment with a 1$~\mu$m thick carbon target. With both spectrometer polarities set to select electrons, elastic and Møller scattering were used to examine detector performance and compare with predicted distributions from Monte Carlo simulations. Planned upgrades to the e-linac will allow searches to be made with beam energies up to 50 MeV using a 1$~\mu$m thick tantalum target.
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All authors R. Alarcon, D. Almonte, M.I. Alstaty, J. Azzi, R. Baartman, J.C. Bernauer, X. Braun, D. Ciarniello, C. Clabeaux, E.W. Cline, E. Corey, R. Corliss, W. Deconinck, A. Deshpande, J. Dilling, J. Dodge, D.H. Dongwi, C. Ekeman, E.A. Fielding, S. Frantzen, I. Friščić, G. Gelinas, S. Gelinas, K. Gill, A. Sabzevari Gonzalez, S. Gupte, D.K. Hasell, M. Hasinoff, B. Humphries, E. Ihloff, N. Jackson, D. Jayakodige, R. Kanungo J.E. Kelsey, O. Kester, M. Kohl, H.W. Koay, R. Laxdal, L. Levack, X. Li, W. Lin, C. Ma, A. Mahon, H. Merkel, J.W. Martin, L. Miller, R. Milner, K. Olchanski, K. Pachal, T. Planche, D. Preddy, S.D. Rädel, G. Randall, J. Redinger, D.A. Reiter, R. Richards, B. Scully, S. Shapiro, M. Suresh, C. Vidal, S. Wang, H. Witte, H. Yang, S. Yen
Geophysics
The tetragonal-cubic transition of davemaoite: Implications for lower mantle seismic anomalies
Yoshiyuki Okuda, Bin Chen, Juliana Peckenpaugh et al. (+5 more)
Davemaoite (CaSiO3 perovskite) is the third most abundant mineral in Earth's lower mantle and a dominant phase in subducted oceanic crust. Its
crystal structure is distorted (tetragonal or orthorhombic) at ambient conditions but is considered to transform to cubic at high temperatures. Previous experiments reported low, nearly pressure-independent transition temperatures (approximately 600 K), demonstrating a long-standing discrepancy with theoretical predictions that mostly exceed 1000 K. Here, we determine the phase stability and thermal equation of state of CaSiO3 davemaoite and its titanium-bearing solid solution [Ca(Si0.75,Ti0.25)O3] under simultaneous high-pressure and high-temperature conditions using a
laser-heated diamond anvil
cell combined with synchrotron X-ray diffraction. We find that the tetragonal-to-cubic transition occurs at substantially higher temperatures than previously reported, with the titanium substitution further stabilizing the tetragonal phase and shifting the transition boundary to even higher temperatures. These findings indicate that CaSiO3 davemaoite in subducted oceanic crust likely undergoes its ferroelastic transition in the mid-lower mantle, whereas Ti-rich davemaoite may remain tetragonal throughout most of the lower mantle, transforming to cubic near the core-mantle boundary. Our results demonstrate that the compositionally dependent phase behaviour of davemaoite can account for the seismic anomalies observed in both the mid-lower mantle and the lowermost mantle.
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All authors Yoshiyuki Okuda, Bin Chen, Juliana Peckenpaugh, Keng-Hsien Chao, Saori Kawaguchi-Imada, Hirokazu Kadobayashi, Zhenxian Liu, Dongzhou Zhang
Chemical Physics
Differentiable Solvation Shell Model for Rational Electrolyte Design
Hancheng Zhao, Hongyi Lin, Celia Kelly et al. (+1 more)
Tailoring Li+ solvation structures has emerged as a promising design principle across multiple Li metal battery (LMB) electrolytes, with localized high concentration electrolytes (LHCE) emerging as a leading candidate. However, rational design of these electrolytes remains limited by a poor quantitative understanding of how molecular properties govern Li+ solvation shell composition. Here we introduce a mean field modeling framework, built on an Ising model, that predicts solvation shell composition from donor number (DN), acceptor number (AN), molar ratio, and molecular size. This framework is end-to-end differentiable, which enables parameterization directly from molecular dynamics (MD) solvation structures via gradient-based optimization. Focusing on LHCE, the model achieves 10.7% RMSE and R2=0.87 for shell composition, 2.3% RMSE on free solvent ratio, and further reproduces solvation trends in real LHCE electrolytes, at a fraction of MD's cost. Our model also shows good generalizability on other electrolyte systems in addition to LHCE. Analysis of its interaction terms shows that DN dominates Li+ solvation energetics, providing a thermodynamic basis for empirical DN-based design rules. We further demonstrate the model's design utility on the LiTFSI/tetraglyme (G4) system absent from training. The model identifies fluorobenzene (FB) as a promising diluent and predicts a salt-concentration window with anion-rich solvation shells and low free solvent, favorable for stable anion-derived SEIs and high oxidative stability, respectively. This prediction is validated by higher-fidelity MD. This work establishes an interpretable differentiable framework for predicting Li+ solvation shell composition, with potential to extend to other electrolyte classes.
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All authors Hancheng Zhao, Hongyi Lin, Celia Kelly, Venkatasubramanian Viswanathan
Fluid Dynamics
Direct Numerical Simulation of Thermoacoustically Unstable Flames Via Non-Drifting Acoustic Delay Characteristic Boundary Conditions
Benjamin L. Cookman, Jack R. C. King, Raphaël C. Assier et al. (+1 more)
Thermoacoustic instability in premixed flames results from the coupling between the flame's heat release, as determined by combustion parameters, and surrounding acoustics, as determined by combustor geometry. A primary instability results in flame flattening as intrinsic flame instability modes are stabilised. Secondary thermoacoustic instability results in a parametric flame instability and drastic growth of acoustic amplitudes. Due to their relative expense, numerical simulations of these phenomena remain scarce. In this work, Direct Numerical Simulations (DNS) of thermoacoustically unstable idealised premixed flames in a tube with acoustically closed upstream and open downstream ends are presented. Results herein demonstrate nonlinear saturation of the primary instability as the flame flattens as well as an oscillating flame fingering characteristic of the unsteady Rayleigh-Taylor effect. To reduce computational cost, we perform DNS only on the region surrounding the flame. Acoustics at in- and
outflows are described using the Navier-Stokes Characteristic Boundary Condition (NSCBC) method to model their delayed reentry into the domain in a formulation referred to as the Acoustic Delay Characteristic Boundary Condition (ADCBC) method. A new Averaged Proportional and Integral Linear Relaxation (APILR) method is also introduced, which modifies the Classic Linear Relaxation (CLR) method to maintain time-averaged values of inflow velocity and
outflow pressure. Here, an integral control term is used to remove non-zero
equilibrium time-averaged inflow velocities which impinge control over flame position. Both new methods demonstrate their capability in inert and counterflow flames test cases. These methods enable the numerical simulation of combustion instabilities at significantly reduced computational expense.
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All authors Benjamin L. Cookman, Jack R. C. King, Raphaël C. Assier, Steven J. Lind
Biological Physics · Cross-listed from cond-mat.soft
From agent-based dynamics to a kinetic theory of jellyfish swarms
Nicolas Perez, Erik Gengel, Zafrir Kuplik et al. (+1 more)
Massive jellyfish swarms observed at sea can extend over tens of kilometres and contain millions of individuals, yet the mechanisms governing their formation and large-scale dynamics remain poorly understood.
Agent-based models provide a framework for describing this dynamics based on jellyfish responses to ocean currents and environmental cues, but become computationally prohibitive when extended to large populations and spatial scales relevant to ocean circulation. Here we derive a continuous kinetic theory from an active-particle model of jellyfish motion. The resulting Fokker-Planck framework incorporates transport by prescribed currents,
stochastic reorientation, direct interactions and stimulated steering, allowing chemical signalling to be represented through a coupled field. We further derive a hydrodynamic closure for large swarms by exploiting the separation between fast orientational and slow spatial dynamics, yielding a reduced density equation suitable for implementation in ocean-current models. This framework provides a route from individual behavioural mechanisms to continuum descriptions of jellyfish populations and establishes a basis for constraining model parameters using observations and in-situ measurements. This approach offers a theoretical foundation for future numerical prediction of large jellyfish swarm formation and
evolution in realistic ocean flows.
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All authors Nicolas Perez, Erik Gengel, Zafrir Kuplik, Eyal Heifetz
Atomic Physics · Cross-listed from hep-th
Robin Löwenberg and Julian Sonner
We propose an analog
quantum-simulation protocol based on a
lattice of atomic ensembles and time-averaged Floquet dynamics to construct the four-body potentials that typically appear in bosonic BFSS-like
matrix quantum mechanics. In contrast to gate-based digital implementations requiring deep
circuits, our approach generates the target model through a fixed set of control stages per Floquet cycle, keeping the number of consecutive
unitaries constant with respect to the
matrix size $N$. The principal scaling cost in our construction is given by the frequency range required to control the growing
lattice. We show that this cost grows at most as $\mathcal{O}(N^3)$, giving a
polynomial scaling route to large$-N$, attractive to experimental implementation. Additionally, we demonstrate that the coupling parameter can be tuned beyond $\mathcal{O}(1)$, enabling the simulation of strong-coupling physics necessary for
holographic phases.
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Computational Physics · Cross-listed from quant-ph
Matrix Product Belief Propagation
Gabriel Woolls, Shahin Jahanbani, Adarsh Pashikanti et al. (+3 more)
We introduce "
matrix product belief propagation" (MP-BP) as a controlled method for the approximate contraction of two-dimensional tensor networks and graphical models, which generically leads to a quadratic reduction of errors relative to existing methods: at similar computational effort, the number of accurate digits is asymptotically doubled. For infinite systems, MP-BP can be understood as a practical implementation of Baxter's corner-transfer-
matrix method; for reflection-symmetric networks, it further coincides with the boundary
matrix-product-state and corner-transfer-
matrix renormalization group
algorithms as conventionally implemented. In the limit of unit
matrix-product rank, MP-BP is equivalent to belief propagation, and more generally, can be understood as a generalization of BP in which the "messages" live on surfaces and are assumed to have a
matrix-product factorization. We further extend the quadratic improvement to the computation of expectation values, and numerically demonstrate the qualitatively improved convergence for a variety of classical and
quantum 2D tensor network problems.
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All authors Gabriel Woolls, Shahin Jahanbani, Adarsh Pashikanti, Matthew T. Fishman, Joseph Tindall, Michael P. Zaletel
Fluid Dynamics · Cross-listed from gr-qc
End state of the experimental black-hole bomb
Patrik Švančara, Leonardo Solidoro, Pietro Smaniotto et al. (+10 more)
Rotating black holes can amplify incident waves through superradiant scattering. When these waves are confined, repeated amplification gives rise to the black-hole bomb instability, whose nonlinear
evolution remains poorly understood despite its central role in models of bosonic clouds around astrophysical black holes. Here, we reproduce the black-hole bomb mechanism in a laboratory setting using a
gravity simulator based on a draining
vortex in superfluid helium. Surface waves propagating on the superfluid interface experience an effective rotating spacetime and undergo repeated superradiant amplification within a cylindrical cavity. By tuning the temperature and flow parameters, we achieve exponential growth of a low-frequency resonant mode, followed by the arrest of the instability and the formation of a long-lived non-
equilibrium steady state. Using spatially and temporally resolved measurements, we identify nonlinear frequency shifts, harmonic generation, and coherent three- and four-wave mixing that redistribute energy among interacting modes. This novel end state of the experimental black-hole bomb highlights the role of nonlinear wave interactions in quenching the runaway growth expected from linear theory and governing the system's late-time dynamics. Our results establish a laboratory framework for investigating the nonlinear
evolution of black-hole bombs, with implications for analogous phenomena involving ultralight bosonic fields around rotating black holes.
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All authors Patrik Švančara, Leonardo Solidoro, Pietro Smaniotto, Sam Patrick, Silvia Schiattarella, Maciej T. Jarema, Sean M. D. Gregory, Vitor S. Barroso, Maurício Richartz, Anastasios Avgoustidis, Carlo F. Barenghi, Ruth Gregory, Silke Weinfurtner
Physics and Society
WolfSociety: Understanding Collective Risk from Harmful-Agent Scaling in Financial Agent Societies
Lejun Zhang, Sarah Lu-Liang, Xin Jiang et al. (+3 more)
Safety evaluations typically focus on individual
agents, but interacting
agents can spread harmful information and influence the environment in which later decisions are made. We study how collective failure changes with harmful-
agent fraction and society size in a controlled financial
agent society, where
agents communicate over a social network and trade in a shared
market. In the primary financial scenario, collective failure requires broad harmful
diffusion together with severe price dislocation or liquidity stress. Across all tested society sizes, failure remains rare at low harmful fractions but rises sharply over a narrow range. As society size grows from N=100 to N=2000, the harmful fraction associated with a 50% failure probability decreases from 4.7% to 2.2%, while the corresponding number of harmful
agents increases from approximately 5 to 44. In contrast, when the number of harmful
agents is held fixed, their impact becomes weaker as the society grows. Controlled interventions further show that broader network reach shifts the collapse boundary toward lower harmful fractions, whereas stronger conformity alone has little effect. To characterize these effects, we introduce
Agent Society Dynamics, a finite-size framework for relating harmful-
agent fraction, society size, and interaction structure to collective failure. Overall, our results reveal a nonlinear, size-dependent collapse transition in financial
agent societies, showing that collective failure depends not only on the prevalence of harmful
agents but also on the size and interaction structure of the surrounding society. Code is available at https://github.com/SAIL-Research-Lab/WolfSociety.
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All authors Lejun Zhang, Sarah Lu-Liang, Xin Jiang, Muning Wen, Weinan Zhang, Shangding Gu
Physics and Society
One equation allocates playing time in competitive team sports: the rulebook sets the arithmetic and the league sets the habit
Gustavo Pedro Ricou
Every team sport that lets a team replace players rations the replacements, and the ration settles who plays and for how long. Across eight codes, three in both sexes, we measure how playing time is allocated and find one equation behind it, complete in the one-way codes, its terms separating what the rulebook fixes from what a competition chooses. Under scarcity every league behaves alike: loaded starters are kept on at the same rate on four continents. Under freedom each expresses a preference, and the size of a league's departure is priced near one-for-one by what its own withdrawal minute prices (lambda = 0.87, 95% interval 0.54 to 1.21, twelve leagues), a law confirmed in four out-of-sample predictions and refused in one. The ordering of leagues by appetite persists across a rule change, and club wealth does not price it. Rules are the geometry of a competition; culture is its material.
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Instrumentation and Detectors
Nanoscale NMR of DNA-Functionalized Diamond Using Individual NV Centers
Erika Janitz, Konstantin Herb, Laura A. Völker et al. (+2 more)
Nuclear magnetic resonance (NMR) spectroscopy is a powerful probe of molecular structure and dynamics but typically requires large
spin ensembles. Here, we demonstrate nanoscale NMR detection of fluorinated DNA using individual near-surface nitrogen-vacancy (NV) centers in diamond nanopillar waveguides under ambient conditions. We covalently tether $^{19}$F-labeled oligonucleotides to mixed nitrogen- and oxygen-terminated surfaces, localizing target
spins within the nanoscale sensing volume. Probabilistic
spin simulations suggest that the measured signals are consistent with those expected from a few molecules and depend strongly on NV-molecule separation, configuration, and local surface heterogeneity. These results establish a framework for NMR of surface-tethered biomolecules and identify key challenges for single-molecule structural elucidation.
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All authors Erika Janitz, Konstantin Herb, Laura A. Völker, Christian L. Degen, John M. Abendroth
Optics · Cross-listed from quant-ph
Squeezed light and coherent feedback enhanced multiparameter quantum estimation in a double-cavity optomechanics: steady and dynamical states
Hamza Harraf, Mohamed Amazioug, Amjad Sohail et al. (+2 more)
Multiparameter
quantum estimation in open optomechanical systems is fundamentally constrained by dissipation, thermal fluctuations, and measurement incompatibility. In this work, we investigate a coupled cavity optomechanical platform in which two mechanical modes interact with driven optical cavities, two mode squeezed
vacuum, intracavity degenerate parametric amplification, and coherent optical feedback. Using the continuous variable Gaussian state formalism, we derive the linearized
quantum Langevin dynamics and steady state covariance
matrix and evaluate the
quantum Fisher information
matrices associated with simultaneous estimation of the optomechanical coupling strength and cavity dissipation rate. We characterize the precision bounds using the symmetric and right logarithmic derivative formalisms and employ $\mathcal{B}_{\rm MI}=\max\{\mathcal{B}_S,\mathcal{B}_R\}$ as a comparative figure of merit within the SLD/RLD framework. We find that parametric amplification can substantially reduce the most informative bound, $\mathcal{B}_{\rm MI}$, thereby enhancing multiparameter estimation precision over a broad range of operating conditions. Coherent feedback can further reduce $\mathcal{B}_{\rm MI}$ and improve the estimation precision, particularly in the strong feedback regime. Moreover, the simultaneous presence of coherent feedback, parametric amplification, and squeezed light injection provides a combined mechanism for controlling
quantum fluctuations and parameter dependent correlations, leading to enhanced and more robust multiparameter estimation. We further analyze the dynamical and steady state regimes to identify the parameter regions in which these
quantum resources provide the largest metrological gain. Our results establish coupled cavity optomechanics as a flexible platform for
quantum-noise engineering in multiparameter sensing.
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All authors Hamza Harraf, Mohamed Amazioug, Amjad Sohail, Mojtaba Mazaheri, Rachid Ahl Laamara
Biological Physics · Cross-listed from cond-mat.soft
Molecular interfacial rheology: Lipid membrane shear viscosity
Zhi-Xun Xu and Amaresh Sahu
We develop a method to extract the shear viscosity of a lipid membrane from
equilibrium molecular dynamics simulations. The method characterizes the rheology of general interfacial systems embedded in three-dimensional media; we term it molecular interfacial rheology. In our simulations the planar
bilayer and surrounding water are confined between solid, parallel walls. Following Onsager's regression hypothesis, membrane and water fluctuations are assumed to relax according to the coupled continuum-mechanical equations governing the confined system—which predict that the membrane transverse velocity autocorrelation function (TVACF) decays exponentially, at a rate set by the membrane and water viscosities. The measured TVACF, however, exhibits damped oscillations followed by a slowly decaying tail. We reconcile these behaviors using the Mori–Zwanzig formalism, and extract the wavevector-dependent membrane viscosity from the time-integral of the TVACF. Results from theory and simulations agree over a decade of wavevectors, and extrapolating to long wavelengths yields shear viscosities ranging from 0.064 to 0.18 pN*us/nm across two representative single-component, fluid-phase
bilayers. Our results are corroborated by nonequilibrium simulations where a spatially varying in-plane body force is applied to lipid molecules, thus validating the framework of molecular interfacial rheology.
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Atmospheric and Oceanic Physics
Disentangling Internal and Forced Climate Variability with Convolutional Neural Networks using Multivariate Fields
Guillaume Gastineau, Elena Provenzano, Constantin Bône et al. (+2 more)
Long-term
climate data exhibit variations composed of internal and forced components. Internal variability arises from natural processes that could occur within a stable
climate. Forced variability, on the other hand, reflects
climate changes induced, for example, by anthropogenic greenhouse gas and aerosol emissions. Accurately distinguishing between these types of variability is crucial for attributing
climate fluctuations and understanding internal variability processes and impacts. In this study, we apply a U-Net convolutional network, a model commonly used in computer
vision, to separate forced and internal
climate variability from 1950 to 2022 using a multi-model
dataset. The
dataset includes multiple fields from five single-model initial-condition large ensembles. Cross-validation is conducted by training the U-Net using the data from the ensembles of four models, leaving out the data from one model to assess performance. Validation results yield errors ranging from 0.1{\deg}C to 0.4{\deg}C for the forced variability of local-scale monthly surface air temperature, which is no more than half the magnitude of external forcing. The U-Net achieves better performance than a simple approach based on a fourth-order
polynomial trend for estimating forced variability. The error is mainly due to insufficient sampling and poor agreement among the models, as the U-Net underestimates the warming for the model with the highest transient
climate sensitivity during validation. Performance is lower for variables like sea-level pressure and precipitation because of their low ratio of forced to internal variability. This framework might be enhanced by incorporating a larger multi-model
dataset in the training and validation.
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All authors Guillaume Gastineau, Elena Provenzano, Constantin Bône, Nicolas Lebas, Robert C. J. Wills
Physics and Society
Mitigating Disease Spread by Design in Refugee and IDP Camps
Giulia Zarpellon, Joseph Aylett-Bullock, Frank Krauss et al. (+1 more)
Disease spread represents an increasing challenge in refugee and internally displaced person (IDP) settlements. The movement and interaction of people within camps is influenced by their layout, which therefore has the potential to significantly affect disease spread. This work aims at creating a methodology to explore the potential effects of different camp layouts as mitigating factors in the spread of diseases within settlements. We showcase proof-of-concept experiments by leveraging the JUNE
agent-based epidemic model, discuss the kind of operational insights this methodology can facilitate, and provide a framework for future investigations.
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All authors Giulia Zarpellon, Joseph Aylett-Bullock, Frank Krauss, Miguel Luengo-Oroz
Classical Physics · Cross-listed from cs.LG
Variational Continuation for Double Pendulum Periodic Orbits
Leo Yao, Ziming Liu and Max Tegmark
We present a Hessian-based approach to numerically continue periodic orbits in dynamical systems. A loop (periodic orbit candidate) is parametrized as a
Fourier series; a loss function is defined based on the deviation of the loop from the physical differential equations. Unlike previous work relying on hand-derived Jacobians, our method automates the process by leveraging automatic differentiation, a common machine learning technique. The continuation direction can be determined by the flat directions of the loss landscapes (directions with zero
eigenvalues), making the search of periodic orbits efficient and guided. Our method is integrator-free, precisely initializes oscillations around unstable fixed points, and efficiently detects orbit family intersections and subharmonic bifurcations. As a demonstration, we present full continuations of periodic double pendulum oscillations from fixed points, showing bifurcations along orbit families and categorizing branches of periodic orbits. In particular, we find periodic orbits where both pendulum masses are never simultaneously at rest, which to our knowledge has been missing in the literature.
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Applied Physics
Thermoelectric properties of metal-semiconductor percolation composites
Oleksandr Porubaniyi, Sergii Tomko, Mihailo Cherkez et al. (+2 more)
We analyze thermoelectric response of composite materials comprising homogeneous
semiconductor hosts with randomly distributed metallic inclusions. We demonstrate that the properties of such materials are strongly affected by the percolation transition (with background conductivity). We show that in vicinity of percolation threshold, the power factor and the thermoelectric figure of merit strongly depend on both the concentration and arrangement of inclusions. Finally, we identify promising regimes for enhancing the power factor in realistic composites.
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All authors Oleksandr Porubaniyi, Sergii Tomko, Mihailo Cherkez, Viktor Podolskiy, Radion Cherkez
Chemical Physics · Cross-listed from cond-mat.stat-mech
Diffusion under competing bulk and surface stopping mechanisms
Yilin Ye
We investigate reflected
diffusion in a bounded domain subject to two independent, competing stopping mechanisms: an exponentially distributed bulk lifetime of rate $p$ and a surface reaction triggered when the boundary local time exceeds an independent exponential threshold of rate $q$. Denoting by $T$ the stopping time and by $L$ the acquired boundary local time at stopping, we derive their marginal distributions, joint Laplace transform, and complete hierarchy of mixed moments. These statistics are determined by the splitting probability $\phi$ that surface reaction occurs before bulk decay. In particular, we establish the identity $p\expect{T}+q\expect{L}=1$ and show that the cumulative risk $pT+qL$ is exponentially distributed with unit rate. We further obtain equivalent representations of $\phi$ in terms of the Robin-
Laplacian and the generalized Steklov spectra. Explicit results for a three-dimensional ball reveal how competing rates $p,q$ control $\phi$ and the $(T,L)$ statistics. Monte Carlo simulations test the universal cumulative-risk law.
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Fluid Dynamics
An Aeroelastic Solver Integrating Reformulated-Vortex-Particle and Finite-Element Methods across Non-Conforming Interfaces
Neeraj Balachandar, A. Padmaprabhan and Vishnu R. Unni
We present $\texttt{VarFlExI}$ (Variable Fidelity Unsteady Flow-FEniCS Exchange Interface), a modular aeroelastic solver for modeling two-way fluid-structure interaction (FSI) of flexible lifting surfaces. The framework employs a reformulated
Vortex Particle Method (rVPM) to solve the incompressible Navier-Stokes equations without the need for computationally expensive volumetric meshing, while supporting variable-fidelity aerodynamic modeling using the $\texttt{FLOWUnsteady}$ framework. On the structural side, a Reissner-Mindlin plate formulation is discretized using the finite element method and integrated in time through the generalized-$\alpha$ method, with the nonlinear
equilibrium equations solved using a Gauss-Newton procedure within the $\texttt{FEniCS}$ framework. Fluid and structural solvers are coupled through an explicit staggered partitioned scheme, ensuring conservation of virtual work for load and displacement transfer across the non-matching interface. To accommodate the multi-representative nature of the aerodynamic loads and geometry, the interface coupling employs separate work-conservative force and reverse-geometry transfer operators via a common intermediate interface. The framework is validated against water-tunnel experiments, demonstrating accurate prediction of the coupled aeroelastic response rather than independent validation of the constituent solvers. The computational efficiency of the meshless aerodynamic solver enables simulations at significantly lower computational cost while maintaining accuracy. The solver is further evaluated through sensitivity analyses and parameter studies spanning different flow conditions, structural properties, and coupling parameters.
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Chemical Physics · Cross-listed from cs.LG
Hessian-Informed Conformation Augmentation for Potential Energy Surface Curvature in Machine Learning Interatomic Potentials
Bumju Kwak and Jeonghee Jo
While machine-learning interatomic potentials (MLIPs) have successfully learned potential energy surfaces (PES) and atomic forces, many practical applications, such as vibrational analysis and transition state search, rely heavily on the PES Hessian. Yet standard MLIPs are trained on energy and forces only, and using the Hessian as an additional training objective requires backpropagation whose
memory cost grows quadratically with the number of atoms. To address these limitations, we propose two Hessian-derived data augmentation schemes: isotropic Gaussian displacement (UniAug) and normal mode-weighted displacement (ModeAug). Both methods utilize simple Taylor expansions, generating physically grounded molecular structures with highly accurate energy and force labels. By preserving the underlying MLIP architecture and training procedure, this approach contributes to improving energy and force predictions in various
benchmarks. Comprehensive evaluations across non-
equilibrium and
equilibrium datasets demonstrate that our approach enhances model accuracy where reference forces are large and training data are limited.
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Optics
Screening bolt loosening in a four-bolt plate with global FRF correlation and local FRAC maps from full-field laser Doppler vibrometry
Berkay Kullukcu, Robin Pianowski, Mehmet Sait Özer et al. (+2 more)
Full-field
laser Doppler vibrometry (LDV) can reveal how bolt torque loss redistributes a frequency response function (FRF) over an entire structure rather than only at a few sensor positions. This work presents a screening procedure for a four-bolt aluminum plate using pointwise amplitude and phase exports of scanned H1 FRFs. Candidate resonances were selected from the all-tight spatial RMS spectrum and tracked in four single-bolt 0 Nm cases. Seven baseline responses remained trackable within prescribed group-specific search windows and were retained as experimental resonance groups RG1-RG7; a dimensionless plate-frequency coefficient was reported alongside each measured frequency. Global changes were quantified using amplitude-only and complex, phase-retaining modal-assurance dissimilarities, and local changes were evaluated using matched-window FRAC-deficit maps and a normalized hotspot-area fraction. The retained groups separate into low-, intermediate-, and high-distortion responses, while the local maps distinguish compact joint-centered changes from distributed FRF redistribution. The workflow therefore links global FRF distortion with spatially resolved interpretation without relying on a trained classifier or specimen-specific node labels.
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All authors Berkay Kullukcu, Robin Pianowski, Mehmet Sait Özer, Ercan Altinsoy, Dina Hannebauer
Data Analysis and Statistics · Cross-listed from stat.ML
FluxDisco: Symbolic Regression for Stoichiometric Dynamical Systems via Monte Carlo Graph Search
Cassandra Durr, Alvaro Köhn-Luque, Chris Jewell et al. (+1 more)
Dynamical symbolic regression methods identify governing differential equations from noisy data, balancing interpretability and predictive accuracy. However, standard methods often produce expressions that violate known physical laws. To address this, we propose FluxDisco, a physics-informed framework tailored for flux-based, stoichiometric ODE systems. By leveraging a known stoichiometry, we reduce the expression search space and ensure physical adherence. Our framework adapts the Monte Carlo Graph Search
algorithm for the unique challenges associated with joint flux discovery of stoichiometric systems. We evaluate our method across a range of physical and biological systems, demonstrating its ability to accurately recover governing dynamics through interpretable equations.
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All authors Cassandra Durr, Alvaro Köhn-Luque, Chris Jewell, Lloyd A. C. Chapman
Accelerator Physics
Indirect Integration of Longitudinal and Transverse Wake Potentials for Unequal Beam Pipes and Arbitrary Beam Velocity
Igor Zagorodnov and Dmitry Bazyl
Indirect integration replaces the long uniform beam-pipe parts of a wakefield calculation by field problems in the pipe cross sections. Earlier ultrarelativistic methods were developed mainly for the longitudinal wake, whereas the transverse wake was usually obtained from the Panofsky–Wenzel
theorem. We derive indirect formulas that complete a transverse Lorentz-force integral already accumulated in a time-domain calculation. At $\beta=1$, each semi-infinite tail is found from a Dirichlet Poisson problem driven by $E_z$ and a Neumann Poisson problem driven by $cB_z$, describing the TM and TE contributions, respectively. We obtain both a fixed-time moving-window representation and a fixed-plane time-history representation for equal or unequal input and output pipes. The method is then extended to a rigid bunch moving with constant velocity $0<\beta c<c$. The longitudinal correction satisfies an anisotropic
elliptic equation in $(x,y,s)$ and provides an additional source for the transverse TM problem. In a two-port finite-reference convention, the complete fields, including space charge, are integrated directly between two fixed planes, while the semi-infinite tails are calculated after subtraction of the stationary field in each pipe. The resulting Panofsky–Wenzel relation contains the difference of the stationary transverse electric fields at the two ports. Numerical tests for an unequal rectangular step-out at $\beta=1$ and $\beta=0.8$ confirm the transverse indirect integration and the unequal-pipe boundary term.
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Applied Physics
What Photocurrent Versus Effective Voltage Tells Us About Charge Generation in Organic Solar Cells
Ardalan Armin, Austin M. Kay, Drew B. Riley et al. (+2 more)
The photocurrent of an organic
solar cell is routinely plotted against an effective voltage and used to extract an
exciton dissociation probability, and through it a free-charge generation efficiency. The photocurrent measures neither. Using a drift-
diffusion model in which free-charge generation is field independent and losses occur only by bimolecular recombination, we show that the apparent dissociation probability returned by this procedure lies well below unity even for complete dissociation. Across wide variations of carrier mobility and recombination strength it is a single-valued function of the fill factor and coincides with the short-
circuit charge collection efficiency, reporting neither the generation yield nor anything about collection beyond what the fill factor already shows. Even for ideal transport the normalised photocurrent saturates below unity at an intensity-independent first-order limit set by recombination of photogenerated carriers with injected
equilibrium charge. Applied to four organic
solar cells whose generation efficiencies are known independently, the apparent dissociation probabilities track the short-
circuit collection efficiency rather than the generation yield. We therefore suggest this construction not be used, particularly in the high-efficiency non-fullerene acceptor systems that are now state of the art.
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All authors Ardalan Armin, Austin M. Kay, Drew B. Riley, Oskar J. Sandberg, Paul Meredith
Chemical Physics
Polarizable Embedding for Photoelectron Spectroscopy and Photoelectron Circular Dichroism in Solution: Core-Level Ionization of Aqueous Alanine
Giovanni Nottoli and Piero Decleva. Chiara Cappelli
We present a polarizable
quantum-mechanics/molecular-mechanics formulation for the calculation of molecular photoionization observables in solution. The approach couples the static-exchange density-functional-theory treatment of bound and continuum electronic states with a fully atomistic polarizable
embedding described with the fluctuating-charge force-field. The fluctuating charges are determined self-consistently with the ground-state
quantum-mechanical density and are subsequently included in the static-exchange
Hamiltonian to account for the outgoing electron. The numerical behavior of the coupled scheme is validated and applied to the X-ray photoelectron spectrum and photoelectron circular dichroism of zwitterionic L-alanine in aqueous solution, using an ensemble of configurations extracted from molecular dynamics. Calculated spectra reproduce experimental profiles remarkably well, demonstrating that atomistic solvent structure and environmental polarization must be treated together to reliably model photoelectron observables in aqueous solution.
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Computational Physics · Cross-listed from cond-mat.mtrl-sci
Symmetry-protected triplet Weyl complexes
Yun-Yun Bai, Ke-Xin Pang, Yan Gao et al. (+2 more)
The Nielsen-Ninomiya
theorem dictates that Weyl nodes must appear in pairs of opposite chirality to preserve global charge neutrality. However, in
crystals, specific crystalline
symmetries can stabilize multi-Weyl nodes, circumventing this pairwise constraint and enabling compensated Weyl complexes with mixed
chiral charges. The minimal configuration of this type is a triplet Weyl complex (TWC), comprising exactly three Weyl nodes. Here, we systematically investigate the
symmetry conditions required to realize TWCs. By screening all 1651
magnetic space groups (MSGs) in both spinless and spinful systems, we establish that: (i) Only TWCs with charge magnitudes of $\{1,1,2\}$ and $\{1,2,3\}$ are permitted; (ii) the $\{1,1,2\}$ configuration can be realized in 166 spinless MSGs and 70 spinful MSGs; and (iii) the $\{1,2,3\}$-TWCs, which has not been reported before, can occur in 10 MSGs for both spinless and spinful cases. We explicitly demonstrate the existence of $\{1,2,3\}$-TWC in a tight-binding model. Furthermore, we present the first electronic realization of $\{1,1,2\}$-TWC topological semimetal state in the
chiral carbon allotrope DZQH-C$_{36}$, in which the three Weyl nodes form a collinear configuration, leading to a characteristic “S”-shaped surface
Fermi arc pattern. Our findings uncover novel topological states featuring mixed
chiral charges and provide guidance for exploring their physics in concrete material systems.
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All authors Yun-Yun Bai, Ke-Xin Pang, Yan Gao, Weikang Wu, Shengyuan A. Yang