Optics · Cross-listed from math.NA
Blind source separation for imaging
Randy Bartels and Olivier Pinaud
This work is concerned with the problem of blind source separation and its applications to imaging. We first establish a theoretical result that we stated in our previous article on imaging in diffusive environments. This result is a generalization of separability criteria found in the literature to arbitrary correlated complex-valued sources with additive noise. In a second step, we verify these separability conditions in two propagation regimes frequently encountered in imaging: the speckle regime and the random geometrical optics regime. Finally, we propose a new imaging method based on the blind source separation problem that improves on images obtained with the classical decomposition of the time reversal operator method.
Read the full abstract ▾
Space Physics · Cross-listed from astro-ph.SR
Solar Wind Heating Near the Sun: A Radial Evolution Approach
Yogesh, Leon Ofman, Kristopher Klein et al. (+19 more)
Characterizing the
plasma state in the near-Sun environment is essential to constrain the mechanisms that heat and accelerate the
solar wind. In this study, we use Parker
Solar Probe (PSP) observations from Encounters 1 through 24 to investigate the radial
evolution of
solar wind
plasma and
magnetic field properties in this region. Using intervals with high field-of-view ($>85\%$) coverage, we derive the radial profiles of
magnetic field strength ($|B|$),
proton density ($N$), bulk speed ($V$), total
proton temperature ($T$), parallel ($T_\parallel$) and perpendicular ($T_\perp$) temperatures, temperature anisotropy ($T_\perp/T_\parallel$),
plasma beta ($\beta$), Alfvén Mach number ($M_A$), and
magnetic field fluctuations ($\delta B/B$) for sub and super-Alfvénic regions. In super-Alfvénic regions, power-law of $|B|$, $N$, $V$, and $T$ as a function of heliocentric distance are broadly consistent with previous Helios results at $>0.3$ AU. The radial
evolution of the components of the temperature tensor reveals distinct behavior: $T_\perp$ decreases monotonically with distance, whereas $T_\parallel$ exhibits a non-monotonic trend – decreasing in the sub-Alfvénic region, increasing just beyond the Alfvén surface. We interpret the increase in $T_\parallel$ as a proxy for
proton beam occurrence. We further examine the
evolution of
magnetic field fluctuations, finding decreasing radial/parallel fluctuations but enhanced tangential/normal/perpendicular fluctuations in sunward direction. These fluctuations may provide free energy for beam generation and particle heating via wave-particle interactions.
Read the full abstract ▾
All authors Yogesh, Leon Ofman, Kristopher Klein, Niranjana Shankarappa, Mihailo M. Martinović, Gregory G. Howes, Parisa Mostafavi, Scott A Boardsen, Viacheslav M Sadykov, Sanchita Pal, Lan K Jian, Aakash Gupta, D. Chakrabarty, B. L. Alterman, Jaye L Verniero, K. W. Paulson, Jia Huang, Roberto Livi, Davin E. Larson, Christian Möstl, Emma E. Davies, Eva Weiler
Chemical Physics
Constrained nuclear-electronic orbital second-order Moller-Plesset perturbation theory
Gabrielle B. Tucker and Kurt R. Brorsen
A multicomponent second-order Møller-Plesset perturbation theory (MP2) method is derived and implemented within the constrained
nuclear-electronic orbital (CNEO) framework from a multicomponent generalization of the Hylleraas functional. The CNEO-MP2 method includes electronic-
nuclear and
nuclear correlation in the calculation of vibrationally averaged molecular properties.
Nuclear quantum effects like vibrational averaging, isotopic effects, and zero-point energy can be captured in a single calculation or geometry optimization with CNEO-MP2, eliminating the need to perform costly subsequent calculations to determine higher order force constants as required with many existing methods used to determine vibrational effects upon molecular properties. The CNEO-MP2 method is benchmarked on a test set of diatomic and small polyatomic molecules and ions. Herein, we present internuclear distances, bond angles, potential energy surfaces, and vibrational frequencies calculated with the CNEO-MP2 method to demonstrate that it correctly captures the effects of
nuclear vibrational motion upon molecular properties.
Read the full abstract ▾
Chemical Physics
Field-driven Ion Pairing Dynamics in Concentrated Electrolytes
Seokjin Moon and David T. Limmer
We investigate ion pairing dynamics in electrolytes driven far from
equilibrium using molecular simulations and nonequilibrium rate theory. Focusing on 0.5 M $\mathrm{LiPF_6}$ in water and acetonitrile under uniform electric fields, we compute transition path theory observables including reactive fluxes and mean first-passage times of ion pairing. Moreover, we introduce a dynamical proxy of free-ion population, where its field-induced change is strongly correlated with the nonlinear enhancement of conductivity, yielding an increase of $40 \ \%$ at 50 mV/Å in acetonitrile, compared to less than $10 \ \%$ in aqueous electrolytes. Further kinetic analysis elucidates that Onsager's classical theory substantially overestimates field-induced enhancement of ion pair dissociation in molecular electrolytes. This discrepancy arises from solvent-mediated dynamical pathways and field-induced dielectric decrement that suppress ion pair dissociation within explicit solvents, highlighting that a faithful description of molecular details is essential. Our results provide a molecular interpretation of nonlinear electrolyte transport beyond continuum theories and establish a general framework for quantifying nonequilibrium reaction kinetics in condensed phase systems.
Read the full abstract ▾
Physics and Society
Two phase transitions in modular multiplex networks
Yael Kfir-Cohen, Dana Ben Porath, Bnaya Gross et al. (+2 more)
Modular networks, such as critical infrastructures, are often built from distinct, densely connected modules (e.g., cities) that are sparsely interconnected. When such networks are gradually and randomly disrupted under a percolation process, they undergo two critical phase transitions. The first transition occurs when modules become isolated from one another, while the second corresponds to the collapse of the entire network, including the internal connectivity of the modules. Here, we study these phase transitions in modular multiplex networks and compare them with those observed in single-layer modular networks. We focus on models in which the modules are arranged and connected either as a Random Regular network or as a two-dimensional square
lattice. We show here that these systems exhibit diverse transition behaviors, with some transitions occurring continuously and others abruptly; notably, one realistic model could display two distinct first-order transitions in the same system. For the modular Random Regular multiplex, we further characterize the spatial transition through its scaling behavior, revealing signatures of a mixed-order phase transitions. In addition, we analytically determine the critical threshold at which modules become disconnected. Our results highlight the crucial role of modular organization and the critical role of interdependence in shaping network vulnerabilities under failures.
Read the full abstract ▾
All authors Yael Kfir-Cohen, Dana Ben Porath, Bnaya Gross, Sergey Buldyrev, Shlomo Havlin
Space Physics · Cross-listed from astro-ph.SR
Linking Solar Magnetism, Extreme Solar Particle Events and Stellar Superflares
Valeriy Vasilyev, Natalie Krivova and Ilya Usoskin
The
magnetic field of the Sun drives a wide range of eruptive phenomena, from small-scale nanoflares to large
flares and coronal mass ejections (CMEs). While direct observations of
solar activity cover only the past few decades, indirect evidence indicates that the Sun can occasionally produce events orders of magnitude stronger than any recorded ones in the modern era. Two complementary lines of evidence exist. First, extreme
solar particle events (ESPEs) have been inferred from prominent spikes in cosmogenic isotope concentrations preserved in precisely dated natural archives such as tree rings and ice cores over the past 15 millennia. Second, high-precision space-borne photometry has revealed superflares on thousands of
stars similar to the Sun. Whether these
solar and
stellar extremes are physically related remains an open question. We summarise the present state of understanding and discuss physical mechanisms that may link them. Although superflares and ESPEs are both extremely energetic manifestations of
magnetic energy storage and release, their relationship does not appear to be one-to-one. Their occurrence and energetics likely depend on how
magnetic flux and
topology govern the partitioning of released energy between radiation, mass ejection, and particle acceleration.
Read the full abstract ▾
Biological Physics · Cross-listed from cond-mat.stat-mech
Whodunnit? The case of midge swarms
L. L. Bonilla and R. González-Albaladejo
As collective states of animal groups go, swarms of midge insects pose a number of puzzling questions. Their ordering polarization parameter is quite small and the insects are weakly coupled among themselves but strongly coupled to the swarm. In laboratory studies (free of external perturbations), the correlation length is small, whereas midge swarms exhibit strong correlations, scale free behavior and power laws for correlation length, susceptibility and correlation time in field studies. Data for the dynamic correlation function versus time collapse to a single curve only for small values of time scaled with the correlation time. Is there a theory that explains these disparate observations? Among the existing theories, whodunnit? Here we review and discuss several models proposed in the literature and extend our own one, the harmonically confined Vicsek model, to anisotropic confinement. Numerical simulations of the latter produce elongated swarm shapes and values of the static critical exponents between those of the two dimensional and isotropic three dimensional models. The new values agree better with those measured in natural swarms.
Read the full abstract ▾
Physics and Society
Transforming Police-Car Swerving for Mitigating Isolated Stop-and-Go Traffic Waves: A Practice-Oriented Jam-Absorption Driving Strategy
Zhengbing He
Stop-and-go traffic waves, a major form of freeway congestion, impose severe and persistent adverse impacts, including reduced traffic efficiency, increased safety risks, and elevated vehicle emissions. Among various freeway traffic management strategies, jam-absorption driving (JAD), in which a dedicated vehicle performs "slow-in" and "fast-out" maneuvers before being captured by a stop-and-go wave, has been proposed as a promising approach to suppressing the propagation of such waves. However, most existing JAD strategies remain impractical, primarily due to the lack of consideration of implementation vehicles and operational conditions. Inspired by real-world observations of police-car swerving behavior, this paper first introduces the Single-Vehicle Double-Detector Jam-Absorption Driving (SD-JAD) problem and then proposes a practical JAD strategy based on a definition of the JAD Triangle, transforming such behavior into a traffic control strategy capable of suppressing the propagation of an isolated stop-and-go wave. Five key parameters that significantly affect the proposed strategy, namely JAD speed, inflow traffic speed, wave width, wave speed, and in-wave speed, are identified and systematically analyzed. Using a SUMO-based simulation as an illustrative example, we further demonstrate how these parameters can be measured in practice using only two stationary roadside traffic detectors. The results show that the proposed JAD strategy successfully suppresses the propagation of a stop-and-go wave without triggering secondary waves. This paper is expected to take a significant step toward the practical implementation of JAD, advancing it from a theoretical concept to a feasible and deployable traffic management strategy.
Read the full abstract ▾
History and Philosophy of Physics · Cross-listed from astro-ph.IM
Why do we do astrophysics?
David W. Hogg
At time of writing, large
language models (LLMs) are beginning to obtain the ability to design, execute, write up, and referee scientific projects on the data-science side of astrophysics. What implications does this have for our profession? In this white paper, I list - and argue for - a set of facts or "points of agreement" about what astrophysics is, or should be; these include considerations of novelty, people-centrism, trust, and (the lack of) clinical value. I then list and discuss every possible benefit that astrophysics can be seen as bringing to us, and to science, and to universities, and to the world; these include considerations of love, weaponry, and personal (and personnel) development. I conclude with a discussion of two possible (extreme and bad) policy recommendations related to the use of LLMs in astrophysics, dubbed "let-them-cook" and "ban-and-punish." I argue strongly against both of these; it is not going to be easy to develop or adopt good moderate policies.
Read the full abstract ▾
Medical Physics
Prediction on total inventory of radioisotopes produced by the interaction of 20Ne beams on 181Ta (110-170 MeV)
Sumana Mukherjee, Susanta Lahiri, Rajarshi Raut et al. (+1 more)
This study aims to model the evaporation residues produced by the interaction of 108-170 MeV of 20Ne with the 181Ta target using Monte-Carlo PACE4 simulation code. Reaction mechanisms taking place in these interactions along with production cross sections have been discussed. Possibility of the production of clinically important exotic
neutron deficient radioisotopes from these interactions have been assessed, but the result is not encouraging for production of radioisotopes useful in
nuclear medicine.
Read the full abstract ▾
All authors Sumana Mukherjee, Susanta Lahiri, Rajarshi Raut, Chiranjib Barman
Physics and Society
Detecting Network Instability via Multiscale Detrended Cross-Correlations and MST Topology
Jose De Leon Miranda, Marina Dolfin, George Kapetanios et al. (+1 more)
We introduce a multiscale measure of network instability based on the joint use of Detrended Cross-Correlation Analysis (DCCA) and Minimum Spanning Tree (MST) filtering. The proposed metric, the Elastic Detrended Cross-Correlation Ratio (Elastic DCCR), is defined as a finite-difference measure of the logarithmic sensitivity of the average MST length to the observation scale. It captures how the structure of cross-correlation networks deforms across different investment horizons. When applied to a network of global equity indices, the Elastic DCCR rises sharply during episodes of financial stress, reflecting increased short-term coordination among investors and a contraction of correlation distances. The measure reveals scale-dependent reconfigurations in network
topology that are not visible in single-scale analyses, and highlights clear differences between stressed and stable
market regimes. The approach does not assume covariance stationarity and relies only on scale-dependent detrended correlations; as a result, it is broadly applicable to other complex systems in which interaction strength varies with scale.
Read the full abstract ▾
All authors Jose De Leon Miranda, Marina Dolfin, George Kapetanios, Leone Leonida
Space Physics · Cross-listed from astro-ph.IM
Observing solar vortices with existing and future instrumentation. Solar Physics International Network for Swirls (SPINS) white paper (Helio)
Suzana S.A. Silva, Viktor Fedun, Gary Verth et al. (+13 more)
Solar vortices are fundamental components of
solar atmospheric dynamics, serving as natural laboratories for
magnetic field twisting, energy concentration and transport, wave guidance, and
plasma coupling across atmospheric layers. Numerical and observational studies show that
solar vortices are intimately connected to key physical processes including
magnetic reconnection, atmospheric heating,
turbulence, and wave generation. This white paper, prepared for the UK Space Frontiers 2035 call, outline five high-priority scientific questions addressing
vortex generation mechanisms, cross-layer coupling,
magnetic restructuring, collective wave-guidance structures, and their role in triggering explosive events and modulating the
solar wind. Key observations and capabilities required to make significant advancements over the coming decade are identified. The UK
solar physics community has established world-leading expertise in
vortex dynamics, combining strengths in high-resolution observations, MHD
turbulence theory, numerical modelling, and space instrumentation. UK researchers have made foundational contributions to
Solar Orbiter, delivered critical systems for DKIST, and maintain active involvement in MUSE and
SOLAR-C EUVST missions. Our technical approach centres on developing next-generation instrumentation: a multi-band, space-qualified system employing four tunable Fabry-Pérot Interferometers providing diffraction-limited, high-cadence spectropolarimetric coverage from the deep photosphere to the low corona. This capability will be validated through a staged mission architecture beginning with balloon-borne demonstrators. Continuing this effort over the coming decade is vital to maintain UK leadership in this field and achieve the goals of roadmap for
solar system research.
Read the full abstract ▾
All authors Suzana S.A. Silva, Viktor Fedun, Gary Verth, Istvan Ballai, Eamon Scullion, Malcolm Druett, Kostas Tziotziou, Alex Pietrow, Nitin Yadav, Ioannis Dakanalis, Elena Khomenko, Hidetaka Kuniyoshi, Shivdev Turkay, Matias Koll Pistarini, Robertus Erdelyi, Luiz Augusto Camargo Aranha Schiavo
Chemical Physics
NMRTrans: Structure Elucidation from Experimental NMR Spectra via Set Transformers
Liujia Yang, Zhuo Yang, Jiaqing Xie et al. (+9 more)
Nuclear Magnetic Resonance (NMR) spectroscopy is fundamental for molecular structure elucidation, yet interpreting spectra at scale remains time-consuming and highly expertise-dependent. While recent spectrum-as-
language modeling and
retrieval-based methods have shown promise, they rely heavily on large corpora of computed spectra and exhibit notable performance drops when applied to experimental measurements. To address these issues, we build NMRSpec, a large-scale corpus of experimental $^1$H and $^{13}$C spectra mined from chemical literature, and propose NMRTrans, which models spectra as unordered peak sets and aligns the model's inductive bias with the physical nature of NMR. To our best knowledge, NMRTrans is the first NMR
Transformer trained solely on large-scale experimental spectra and achieves state-of-the-art performance on experimental
benchmarks, improving Top-10 Accuracy over the strongest baseline by +17.82 points (61.15% vs. 43.33%), and underscoring the importance of experimental data and structure-aware architectures for reliable NMR structure elucidation.
Read the full abstract ▾
All authors Liujia Yang, Zhuo Yang, Jiaqing Xie, Yubin Wang, Ben Gao, Tianfan Fu, Xingjian Wei, Jiaxing Sun, Jiang Wu, Conghui He, Yuqiang Li, Qinying Gu
Chemical Physics
Theory for enzymatic degradation of semi-crystalline polymer particles
Michael Schindler, Hernan Garate and Ludwik Leibler
In enzymatic recycling or biodegradation of semi-crystalline plastic waste, crystalline spherulites embedded into an amorphous
matrix hinder and slow down depolymerisation. When the enzymatic depolymerisation temperature exceeds the glass transition temperature, these spherulites tend to grow. The depolymerisation process is thus controlled by a competition between erosion of the amorphous
matrix from the particle surface and the growth of recalcitrant spherulites within the particle bulk and at its surface. We present a
geometric model that captures this competition, together with an
algorithm to solve the equations numerically. Our
algorithm introduces a new extension of Voronoi/Delaunay tessellation in space. We extract the parameters for the model from experimental data on the enzymatic depolymerization by hydrolase LCC-ICCG of PET bottle flakes and textile waste, in order to make a prediction of the observed degradation yield as a function of time. Both the final yield and the degradation kinetics are correctly predicted. Most importantly, the model clarifies how and to which extent nucleating
agents,
impurities, additives, and/or rapid
crystal growth present in the waste can undermine pretreatment efforts aiming to initiate depolymerisation from a material with a low initial crystallinity.
Read the full abstract ▾
Optics
Programmable and nonvolatile computing with composition tuning in thin film lithium niobate
Abhiram Devata, Axel Magaña Ponce and David Barton
Matrix-vector multiplications are fundamental operations in artificial intelligence and high-throughput computations, and are executed repeatedly during training and inference. Their high energy cost in electronic processors motivate scalable photonic computing approaches that reduce the energy required per operation. Thin film lithium niobate is a dominant photonic platform due to its large electro-optic effect. However, it lacks nonvolatile index tuning mechanisms, which promise to pave the way for energy-efficient photonic computing. Here, we explore electrochemical lithiation as a route to nonvolatile
matrix-vector multiplications in thin film lithium niobate. The lithium niobate phase is stable at room temperature over a 2% Li composition window with an associated composition-dependent refractive index. We computationally demonstrate this as a programmable, low-loss approach to perform
matrix-vector multiplications by using composition to control
matrix weights. We design Mach-Zehnder interferometers to perform image processing tasks under realistic material loss constraints. We also design microring resonators for iterative weight updates, using gradient descent training to program target
matrix operations with
matrix-vector multiplication accuracy validated at 1.6% average relative error. These demonstrations show a facile route towards nonvolatile photonic computing in thin film lithium niobate, addressing a critical requirement for energy-efficient photonic
matrix operations at scale.
Read the full abstract ▾
Computational Physics · Cross-listed from cond-mat.mtrl-sci
PySlice: Routine Vibrational Electron Energy Loss Spectroscopy Prediction with Universal Interatomic Potentials
Harrison A. Walker, Thomas W. Pfeifer, Paul M. Zeiger et al. (+3 more)
Vibrational spectroscopy in the electron microscope can reveal
phonon excitations with nanometer spatial resolution, yet routine prediction remains out of reach due to fragmented workflows requiring specialized expertise. Here we introduce PySlice, the first publicly available implementation of the Time Autocorrelation of Auxiliary Wavefunction (TACAW) method, providing an automated framework that produces momentum- and energy-resolved vibrational electron energy-loss spectra directly from atomic structures. By integrating universal machine learning interatomic potentials with TACAW, PySlice eliminates the bottleneck of per-system potential development. Users input atomic structures and obtain
phonon dispersions, spectral diffraction patterns, and spectrum images through a unified workflow spanning molecular dynamics, GPU-accelerated electron scattering, and frequency-domain analysis. We outline the formulation behind the code, demonstrate its application to canonical systems in materials science, and discuss its use for advanced analysis and materials exploration. The modular Python architecture additionally supports conventional electron microscopy simulations, providing a general-purpose platform for imaging and diffraction calculations. PySlice makes vibrational spectroscopy prediction routine rather than specialized, enabling computational screening for experimental design, systematic exploration of
phonon physics across materials families, and high-throughput generation of simulated data for training of future machine learning models.
Read the full abstract ▾
All authors Harrison A. Walker, Thomas W. Pfeifer, Paul M. Zeiger, Jordan A. Hachtel, Sokrates T. Pantelides, Eric R. Hoglund
Atmospheric and Oceanic Physics · Cross-listed from math.AP
Confinement results near point vortices on the rotating sphere
Martin Donati and Emeric Roulley
We study the Euler equation on the rotating sphere in the case where the absolute vorticity is initially sharply concentrated around several points. We follow the literature already concerning vorticity confinement for the planar Euler equations, and obtain similar results on the rotating sphere, with new challenges due to the geometry. More precisely, we show the improbability of collisions for point-
vortices, logarithmic in time absolute vorticity confinement for general configurations, the optimality of this last result in general, and the existence of configurations with power-law long confinement. We take this opportunity to write a unified, self-contained, and improved version of all the proofs, previously scattered across multiple papers on the planar case, with detailed exposition for pedagogical clarity.
Read the full abstract ▾
Plasma Physics
Design of experiments characterising heat conduction in magnetised, weakly collisional plasma
T. A. Vincent, P. Ariyathilaka, L. Creaser et al. (+15 more)
Heat conduction in weakly collisional, magnetised
plasma is challenging to model accurately due to multifaceted physics governing heat-carrying electrons, including microinstabilities that scatter electrons and modify heat transport. Capturing these effects requires multidimensional kinetic theory simulations, which are computationally expensive. Experimental constraints overcome this issue, resulting in improved understanding of thermal transport in systems such as the intra-cluster medium of
galaxy clusters, and the hot-spot in inertial confinement fusion. In this paper, we present a new experimental platform that produces a weakly collisional high-e̱ta}
plasma expected to be susceptible to the whistler heat-flux instability. This platform, to be fielded on the Orion
laser, enables characterisation of whistler-regulated thermal conductivity. The platform design is assessed using radiation-magnetohydrodynamics simulations with the code FLASH. Simulations using three thermal conduction models predict conductivity suppression by over an order of magnitude relative to the Spitzer value at whistler saturation, demonstrating the efficacy of the platform.
Read the full abstract ▾
All authors T. A. Vincent, P. Ariyathilaka, L. Creaser, C. Danson, D. Lamb, J. Meinecke, C. A. J. Palmer, S. Pitt, H. Poole, C. Spindloe, P. Thomas, E. Tubman, L. Wilson, W. J. Garbett, G. Gregori, P. Tzeferacos, T. Hodge, A. F. A. Bott
Optics
Nonreciprocal lensing and backscattering suppression via magneto-optical nonlocality
Dmitry Vagin and Maxim A. Gorlach
We introduce a special kind of nonreciprocal electromagnetic response which gives rise to backscattering suppression in the bulk, a long-sought feature in topological photonics, as well as nonreciprocal
lensing - an effect when the same structure focuses light incident from one direction and defocuses light propagating in the opposite way. We predict this response in
spin spirals and in specially designed metamaterials, validating the key predictions.
Read the full abstract ▾
Medical Physics
Towards a topological view of blood pressure regulation
Arturo Tozzi
Blood pressure regulation is commonly addressed in terms of local mechanisms such as vascular resistance, compliance and neurohumoral control. However, the human vasculature encompasses multiple quasi-closed flow loops under both physiological and pathological conditions. To test whether these loops could influence pressure dynamics beyond local control, we address the role of vascular
topology in blood pressure regulation. Using one dimensional flow simulation models, we compared pressure dynamics in open vascular segments and closed vascular loops. We found that in open segments pressure fades away and remains spatially localized, whereas in closed loops pressure can keep circulating around the loop even if resistance in one spot is modified. Since parallel pathways within loops are dynamically coupled rather than independent, pressure changes in one place can affect the entire closed loop, allowing system level pressure patterns to emerge. Also, we assessed the temporal
evolution of pressure fluctuations within closed vascular loops in normotensive and hypertensive parameter regimes, before and after loop breaking intervention. This topological approach helps clarifying why drugs or local interventions may fail to lower blood pressure in looped vascular architectures, providing a theoretical interpretation of some forms of resistant hypertension. Because disrupting a loop restores pressure relaxation, it may also help explain the disproportionate pressure changes observed after
topology altering events like thrombosis, vascular surgery or embolization of arteriovenous malformations and shunts. Therefore, vascular
topology can influence cardiovascular physiology by coupling local pressure flow relations to global constraints on blood pressure regulation, with physiological, pathological and clinical implications.
Read the full abstract ▾
Computational Physics · Cross-listed from cs.LG
Empirical Stability Analysis of Kolmogorov-Arnold Networks in Hard-Constrained Recurrent Physics-Informed Discovery
Enzo Nicolas Spotorno, Josafat Leal Filho and Antonio Augusto Medeiros Frohlich
We investigate the integration of Kolmogorov-Arnold Networks (KANs) into hard-constrained recurrent physics-informed architectures (HRPINN) to evaluate the fidelity of learned residual
manifolds in oscillatory systems. Motivated by the Kolmogorov-Arnold representation
theorem and preliminary gray-box results, we hypothesized that KANs would enable efficient recovery of unknown terms compared to MLPs. Through initial sensitivity analysis on configuration sensitivity, parameter scale, and training paradigm, we found that while small KANs are competitive on univariate
polynomial residuals (Duffing), they exhibit severe hyperparameter fragility, instability in deeper configurations, and consistent failure on multiplicative terms (Van der Pol), generally outperformed by standard MLPs. These empirical challenges highlight limitations of the additive inductive bias in the original KAN formulation for state coupling and provide preliminary empirical evidence of inductive bias limitations for future hybrid modeling.
Read the full abstract ▾
Chemical Physics · Cross-listed from quant-ph
Universal Foundations of Thermodynamics: Entropy and Energy Beyond Equilibrium and Without Extensivity
Gian Paolo Beretta
Thermodynamics is commonly presented as a theory of macroscopic systems in stable
equilibrium, built upon assumptions of extensivity and scaling with system size. In this paper, we present a universal formulation of the elementary foundations of thermodynamics, in which
entropy and energy are defined and employed beyond
equilibrium and without assuming extensivity. The formulation applies to all systems – large and small, with many or few particles – and to all states, whether
equilibrium or nonequilibrium, by relying on carefully stated operational definitions and existence principles rather than macroscopic idealizations. Key thermodynamic concepts, including adiabatic availability and available energy, are developed and illustrated using the energy-
entropy diagram representation of nonequilibrium states, which provides
geometric insight into irreversibility and the limits of work extraction for systems of any size. A substantial part of the paper is devoted to the analysis of
entropy transfer in non-work interactions, leading to precise definitions of heat interactions and heat-and-
diffusion interactions of central importance in mesoscopic continuum theories of nonequilibrium behavior in simple and complex solids and fluids. As a direct consequence of this analysis, Clausius inequalities and the Clausius statement of the second law are derived in forms explicitly extended to nonequilibrium processes. The resulting framework presents thermodynamics as a universal theory whose concepts apply uniformly to all systems, large and small, and provides a coherent foundation for both teaching and modern applications.
Read the full abstract ▾
Applied Physics
Thin-Film-Engineered Self-Assembly of 3D Coaxial Microfluidics with a Tunable Polyimide Membrane for Bioelectronic Power
Aleksandr I. Egunov, Hongmei Tang, Pablo E. Saenz et al. (+11 more)
Thin-film self-assembly of three-dimensional (3D) microsystems presents a compelling route to integrate complex functionalities into ultra-compact volumes, yet strategies for incorporating tunable ion-conducting elements remain limited. Here, we introduce a strain-induced self assembly platform that transforms lithographically patterned multilayer thin films into functional 3D coaxial Swiss-roll microtubes with total active volumes below 1 uL. A key innovation is the monolithic integration of a chemically tunable polyimide
proton-exchange membrane, enabling post-fabrication optimization of ionic transport that balances
proton transport with mediator blocking. We further implement a dual-mode operational scheme that decouples microbial metabolism from electrochemical power generation, revealing biofouling, not chemical fouling or membrane degradation, as the dominant failure mechanism in conventional architectures. Critically, optimally treated polyimide membranes exhibit excellent recoverability after fouling, while
cell-free mode operation maintains stable performance by physically excluding microorganisms from the microelectronic environment. This integrated bio-electronic microsystem achieves a volumetric power density of ~3.1 mW cm-3 within an ultra-compact footprint of 4.16 mm2. Our work establishes a scalable thin-film engineering approach to create tunable, 3D bioelectronic power sources for autonomous microsystems.
Read the full abstract ▾
All authors Aleksandr I. Egunov, Hongmei Tang, Pablo E. Saenz, Dmitriy D. Karnaushenko, Yumin Luo, Chao Zhong, Xinyu Wang, Yang Huang, Pavel Fedorov, Leandro Merces, Minshen Zhu, Daniil Karnaushenko, Oliver, G. Schmidt
Computational Physics · Cross-listed from cs.LG
Supervised Metric Regularization Through Alternating Optimization for Multi-Regime Physics-Informed Neural Networks
Enzo Nicolas Spotorno, Josafat Ribeiro Leal and Antonio Augusto Frohlich
Standard Physics-Informed Neural Networks (PINNs) often face challenges when modeling parameterized dynamical systems with sharp regime transitions, such as bifurcations. In these scenarios, the continuous mapping from parameters to solutions can result in spectral bias or "mode collapse", where the network averages distinct physical behaviors. We propose a
Topology-Aware PINN (TAPINN) that aims to mitigate this challenge by structuring the latent space via Supervised Metric Regularization. Unlike standard parametric PINNs that map physical parameters directly to solutions, our method conditions the solver on a latent state optimized to reflect the metric-based separation between regimes, showing ~49% lower physics residual (0.082 vs. 0.160). We train this architecture using a phase-based Alternating Optimization (AO) schedule to manage gradient conflicts between the metric and physics objectives. Preliminary experiments on the Duffing Oscillator demonstrate that while standard baselines suffer from spectral bias and high-capacity Hypernetworks overfit (memorizing data while violating physics), our approach achieves stable convergence with 2.18x lower gradient variance than a multi-output Sobolev Error baseline, and 5x fewer parameters than a hypernetwork-based alternative.
Read the full abstract ▾
Chemical Physics
Cavity Quantum Electrodynamics Ring Coupled Cluster and the Random Phase Approximation
A. Eugene DePrince III, Stephen H. Yuwono and Henk Eshuis
It is well known that the ground-state correlation energy from the particle-hole channel of the random phase approximation (RPA) is formally equivalent to that from a simplified coupled cluster doubles (CCD) model that includes only ring diagram contraction contributions in the residual equations [J. Chem. Phys. 129, 231101 (2008)]. We generalize this analytic result to the cavity
quantum electrodynamics (QED) case and demonstrate the numerical equivalence of QED-RPA and a QED ring-CCD model that accounts for double electron excitations, coupled single electron excitations / single
photon creation, and double
photon creation.
Read the full abstract ▾
Atmospheric and Oceanic Physics
Failure to track a stable AMOC state under rapid climate change
René M. van Westen, Reyk Börner and Henk A. Dijkstra
The Atlantic Meridional Overturning Circulation (AMOC) is a tipping element of the
climate system. The current estimate of the global warming threshold for the onset of an AMOC collapse is +4.0C (uncertainty range 1.4-8C). However, such a threshold may not be meaningful because AMOC stability rather depends on the rate of radiative forcing change. Here, we identify an AMOC stabilising mechanism that operates on timescales longer than present-day radiative forcing increase. Slow forcing permits coherent adjustment of surface and interior ocean properties, supported by enhanced evaporation and reduced sea-ice extent, counteracting destabilising feedbacks. We explicitly demonstrate this mechanism in a slow CO2 ramp (+0.5 ppm/yr)
climate model simulation, in which the AMOC remains stable up to +5.5C of global warming. By contrast, under faster CO2 ramps, the AMOC collapses at substantially lower warming levels (+2C). Our findings demonstrate rate-induced AMOC tipping and imply that limiting the rate of greenhouse gas emissions is critical for reducing the near-term risk of an AMOC collapse.
Read the full abstract ▾
Plasma Physics
Deflation Techniques for Stellarator Equilibrium and Optimization
Dario Panici, Byoungchan Jang, Rory Conlin et al. (+3 more)
Stellarator optimization is a multi-objective, non-convex problem characterized by a complex objective landscape containing many local minima. The solution resulting from a single optimization is highly sensitive to factors such as the initial guess, objective weights, and the optimization method employed. However, merely varying these factors does not guarantee that a physically distinct minimum will be found; optimizations often fail to converge to good minima or simply return to the same or very similar local minima despite large-scale parameter scans. This paper presents a novel application of deflation methods to effectively explore this landscape. By modifying the objective function to penalize and "deflate" away already-found solutions, this technique encourages the optimizer towards attractive, distinct new minima while using a single initial guess and optimization setup. We provide a primer on deflation for nonlinear systems and non-convex optimization before applying it to non-axisymmetric
equilibrium and stellarator optimization problems. Key results include the discovery of families of global
equilibria with similar core characteristics and the convergence to helical core
equilibria without prescient initial guesses. Furthermore, we demonstrate that augmenting stage-one stellarator and stage-two coil optimization with deflation constraints readily produces multiple high-quality, distinct solutions, establishing the method's efficacy and ease of use.
Read the full abstract ▾
All authors Dario Panici, Byoungchan Jang, Rory Conlin, Daniel Dudt, Yigit Gunsur Elmacioglu, Egemen Kolemen
Optics
Probing Internal Dynamics of Spatiotemporal Optical Vortex Strings: Spatiotemporal Attraction and Filament Stretching
Xiuyu Yao, Xuechen Gao, Ping Zhu et al. (+13 more)
Vortex dynamics are intriguing and challenging across multiple physics fields. In optics, customized spatiotemporally structured optical fields, especially spatiotemporal optical
vortices (STOV), offer the potential to tailor light via coupled space-time degrees of freedom. However, the interaction mechanisms between multiple transverse orbital angular momentum singularities within a single wave packet remain elusive. This study explores the intrinsic dynamics of a STOV with three phase singularities, observing a pronounced
vortex singularity oscillation phenomena by tuning the temporal dispersion. We show that these phenomena originate from the counterintuitive spatiotemporal attractive effect between
vortices, which is closely related to the singularity distance. Furthermore, the stretching into filaments and annihilation behaviors is observed by introducing antivortex in the center of the wavepacket. Experimentally, we propose a Full Interferometric
Retrieval of Spatiotemporal
Tomography (FIRST) method that enables the complete, single-shot capture of wave packets, with excellent agreement between theoretical predictions and experimental results. To the best of our knowledge, the dynamics of transverse spatiotemporal singularities within a single wave packet are reported here for the first time. These findings confirm the existence of interesting interactions between STOV singularities, deepen our understanding of photonics and open a new direction for investigating the complex dynamics of
vortex singularities in the spatiotemporal domain.
Read the full abstract ▾
All authors Xiuyu Yao, Xuechen Gao, Ping Zhu, Jintao Fan, Jingwen Ran, Zezhao Gong, Dongjun Zhang, Xiao Liang, Xuejie Zhang, Meizhi Sun, Qiang Zhang, Lijie Cui, Hailun Zeng, Minglie Hu, Xinglong Xie, Jianqiang Zhu
Chemical Physics · Cross-listed from cond-mat.mtrl-sci
Long-Range Machine Learning of Electron Density for Twisted Bilayer Moiré Materials
Zekun Lou, Alan M. Lewis and Mariana Rossi
Moiré superlattices in two-dimensional (2D) materials exhibit rich
quantum phenomena, but ab initio modelling of these systems remains computationally prohibitive. Existing machine learning methods for accelerating density-functional theory (DFT) can target the prediction of different quantities and often rely on the locality assumption. Here we train a Gaussian process regression SALTED model exclusively on the electron densities of small displaced
bilayer structures and then extrapolate electron density prediction to the large supercells required to describe small twist angles between these
bilayers. We show the necessity of long-range descriptors to yield reliable band structures and electrostatic properties of large twisted
bilayer structures, when these are derived from predicted densities. We demonstrate that the choice of descriptor determines the distribution of residual density errors, which in turn affects the downstream electronic properties. We apply our models to twisted
bilayer graphene, hexagonal boron nitride, and transition metal dichalcogenides, focusing on the model's capacity to predict complex phenomena, including flat band formation, bandwidth narrowing, domain-wall electric fields, and
spin-orbit coupling effects. Beyond moiré materials, this approach provides a general methodology for electronic structure prediction in large-scale systems with substantial long-range phenomena related to non-local
geometric information.
Read the full abstract ▾
Fluid Dynamics
Linear Stability and Structural Sensitivity of a Swirling Jet in a Francis Turbine Draft Tube
Lester Corpin Toledo, Artur Gesla and Eunok Yim
Motivated by the need to better understand flow unsteadiness in hydraulic turbines, we perform a local linear stability and adjoint-based sensitivity analysis of the turbulent swirling jet at the outlet of a Francis turbine. We use measured mean flow and
turbulence profiles at several operating conditions (below, at, and above the best efficiency point (BEP) flow rate) and perform a stability analysis. Incorporating eddy viscosity $\nu_t$ into the analysis strongly damps inviscid growth rates and restricts instability to low azimuthal modes $m\in [-1,2]$, in better agreement with experiments. Three turbulent viscosity closures (constant, mixing-length and measured $k-\varepsilon$ based) yield similar spectra, with close agreement between mixing length and measured models, all identify partial load (0.92 BEP) as the most unstable regime. Sensitivity results show that axial velocity modifications primarily control growth rates, whereas azimuthal velocity changes mainly shift frequencies. We also derive the sensitivity kernel of the spectrum to turbulent viscosity modifications and find that spatial variations of eddy viscosity are essential for predicting the unstable mode range. The predictions accurately estimate stability changes for small variations in operating point. We further analyze the flow using classical inviscid swirling jet instability criteria (the generalized Rayleigh discriminant) and WKB analysis to predict the stability to broader operating points and reconcile these results to the stability and sensitivity analyses. The approach used in this study is fast and simple to model, but it neglects draft tube geometry (non-parallel effects), motivating future global stability and sensitivity analyses.
Read the full abstract ▾