Medical Physics
The choice of viscous or viscoelastic models affects attenuation and velocity determination in simplified skull-mimicking digital phantoms
Samuel Clinard, Taylor Webb, Henrik Odéen et al. (+2 more)
Simulation-guided transcranial focused ultrasound therapies rely on estimating skull acoustic properties from pretreatment imaging. Typical clinical resolution (0.5 mm isotropic) cannot resolve bone microstructure, making the acoustic properties underdetermined and sensitive to modeling assumptions. Here, we examine how viscous and viscoelastic models predict changes in attenuation and phase velocity due to microstructure. Using viscous and viscoelastic k-Wave implementations, we simulated transmission of a broadband 625 kHz tone burst (250 kHz-1 MHz) through skull-mimicking digital phantoms. The phantoms contained spherical pores (0.1-1.0 mm diameter) randomly embedded within cortical bone (2.5%-90% porosity). Virtual sensors measured attenuation and phase velocity using a time-distance
matrix approach. Both models predict increased attenuation with increasing pore size at a fixed porosity, but differ in the strength and porosity dependence of this relationship. The viscoelastic model generally predicts attenuation peaks at higher porosities than the viscous model. For 1.0 mm pores, the viscous peak (1.98 Np/cm) occurs at 20% porosity, while the viscoelastic peak (2.98 Np/cm) occurs at 70%. Phase velocity decreases with pore size for both models, though the viscoelastic predictions are less sensitive to pore size. These results demonstrate that viscous and viscoelastic models exhibit distinct attenuation and phase-velocity behavior for idealized bone microstructures. While both indicate that microstructure has a strong impact on attenuation, it has a lesser effect on phase velocity for the viscoelastic model compared to the viscous model. This work highlights the importance of acoustic model choice when estimating skull acoustic properties from computed
tomography images. Future work will identify which acoustic model best represents ultrasound propagation through skull microstructure.
Read the full abstract ▾
All authors Samuel Clinard, Taylor Webb, Henrik Odéen, Dennis L. Parker, Douglas A. Christensen
Plasma Physics
The skin effect in anomalous transport of charged particles in plasma with a microturbulent magnetic field. I. Isotropic plasma
N.A. Emelyanov and Vl.V. Kocharovsky
The influence of electromagnetic skin effect on anomalous charged particle transport in dense, non-relativistic, collisionless
plasma with a small-scale turbulent
magnetic field was investigated using quasi-linear kinetic equations, through both analytical and numerical methods. Analytical expressions for the
diffusion tensor components in the Fokker-Planck equation that take this effect into account have been found. The equation was solved numerically in the case of magnetostatic
turbulence. It has been demonstrated that the skin effect increases the mean free path of particles in turbulent
plasma, thereby reducing its anomalous resistance. It also leads to anisotropy in particle scattering, resulting in anisotropy in their stationary velocity distribution, which increases as the screening parameter grows. Approximate analytical formulas for the effective mobility of charged particles and the electric conductivity of
plasma with isotropic magnetostatic
turbulence have been obtained.
Read the full abstract ▾
Optics
Freely controllable single-optical-frequency comb for highly sensitive cavity ring-down spectroscopy
Norihiko Nishizawa, Shotaro Kitajima, Ningwu Liu et al. (+4 more)
Direct comb spectroscopy is a useful tool for obtaining highly accurate spectroscopic information. However, as the number of comb modes is very large and the optical energy is dispersed over them, the optical energy per each comb mode is ultrasmall, limiting the sensitivity of highly sensitive spectroscopy. If we can concentrate the optical energy into the comb modes that only overlap with the absorption spectra, we can demonstrate drastic improvements in its measurement sensitivity. In this study, we developed a freely controllable optical frequency comb source based on the spectral peak phenomenon. The comb modes overlapping the CH4 absorption spectra were transformed into background-suppressed spectral peaks at the nonlinear loop mirror using a CH4 gas
cell. Coherence-preserving power scaling of the generated comb was demonstrated using a fiber Raman amplifier. Subsequently, only the single-comb mode was filtered using a newly developed spectral filter with an ultrahigh resolution. The maximum optical power of a single comb was estimated to be more than 10 mW. The ring-down decay signal from the high-finesse optical cavity was measured using a single selected mode of the generated controllable comb. As a demonstration, the 2v_3 bands of the CH4 absorption spectra were accurately measured by comb-mode-resolved, cavity ring-down spectroscopy (CRDS) with high sensitivity up to 4.2 x 10^(-11) cm^(-1). This sensitivity is two orders of magnitude higher than that of previously reported comb-based CRDS. The residual was only 0.29 %, indicating the high accuracy of the proposed spectrometer for molecular spectral analysis. This approach can be extended to other wavelength ranges and is useful for highly sensitive, high-resolution, comb-resolved spectroscopy.
Read the full abstract ▾
All authors Norihiko Nishizawa, Shotaro Kitajima, Ningwu Liu, Ryohei Terabayashi, Daiki Hashimoto, Hisashi Abe, Hideki Tomita
Fluid Dynamics
Predictive Compressibility Transformation for Hypersonic Turbulent Boundary Layers with Cold Walls
Engin Danis
Compressibility transformations are used to relate hypersonic zero-pressure-gradient (ZPG) turbulent boundary layers (TBLs) to incompressible reference states, but their assessment has largely focused on the collapse of transformed mean velocity profiles, without enforcing a unique, Mach-independent representation of the mean shear. In this work, a stricter consistency condition is proposed, requiring that a single incompressible inner-outer model for the mean velocity gradient reproduce all transformed compressible profiles when expressed in terms of a transformed wall-normal coordinate. This implies collapse not only of the transformed mean velocity but also of semilocal eddy viscosity and TKE production. Existing compressibility transformations are shown, using hypersonic DNS, to incur velocity errors of 1-25% relative to the incompressible inner-outer model, particularly for strongly cooled cases. A new forward compressible-to-incompressible transformation is developed that constructs the transformed coordinate as a convex combination of semilocal and integral-type basis functions with coefficients modeled as functions of friction Mach number and wall heat transfer rate. Casewise optimization yields consistency errors of 1-4% across the available hypersonic DNS set, and this performance is retained using multi-linear and multi-quadratic regressions. The forward transformation is embedded in an inverse incompressible-to-compressible transformation framework, which reconstructs the compressible state from freestream and wall conditions at a prescribed BL thickness. The inverse solver recovers key BL parameters, velocity profiles, and skin friction distributions with good accuracy, and generally improves upon existing models for cold-wall hypersonic TBLs, thereby providing a physically constrained basis for near-wall modeling in hypersonic TBLs with strong wall cooling.
Read the full abstract ▾
Biological Physics
Binding Kinetics Oppositely Regulates type II Topoisomerase Relaxation and Decatenation Activities
Cleis Battaglia, Filippo Conforto, Yair Augusto Gutierrez Fosado et al. (+4 more)
Type II Topoisomerases (topo II) are critical to simplify genome
topology during transcription and replication. They identify topological problems and resolve them by passing a double-stranded DNA segment through a transient break in another segment. The precise mechanisms underpinning topo IIs ability to maintain a topologically simple genome are not fully understood. Here, we investigate how binding kinetics affects the resolution of two distinct forms of topological
entanglement: decatenation and torsional relaxation. First, by single-molecule measurements, we quantify how monovalent cation concentration affects the dissociation rate of topo II from DNA. Second, we discover that increasing dissociation rates accelerate decatenation while slowing down relaxation catalytic activities. Finally, by using molecular dynamics simulations, we uncover that this opposite behaviour is due to a trade-off between search of target through facilitated
diffusion and processivity of the enzyme in catenated versus supercoiled DNA. Thus, our findings reveal that a modulation of topo II binding kinetics can oppositely regulate its topological simplification activity, and in turn can have a significant impact in vivo.
Read the full abstract ▾
All authors Cleis Battaglia, Filippo Conforto, Yair Augusto Gutierrez Fosado, Matt Newton, Erin Cutts, Davide Michieletto, Antonio Valdes
Fluid Dynamics
Simulating surfactant effects in phase-transforming fluids
Keyu Feng, Saikat Mukherjee, Tianyi Hu et al. (+1 more)
Surfactants are critical in natural processes and engineering, but measuring their concentrations in non-
equilibrium conditions and in the presence of flow is difficult. Therefore, computational methods are a key tool for improving our understanding. Predicting the effect of surfactants on
liquid-vapor transformations is particularly challenging due to (1) simultaneous mass transfer, non-
equilibrium thermodynamics and Marangoni stresses, and (2) the phenomenological assumptions underlying many
liquid-vapor phase-change models. Starting from the Navier-Stokes-Korteweg equations, a first-principles approach to
liquid-vapor phase transformations, we developed a model of
liquid-vapor flows with surfactants. We performed simulations of bubbles under
equilibrium and
liquid-vapor interface oscillations to demonstrate that the model successfully reproduces surfactant-mediated reductions in surface tension. We also investigated the mechanisms whereby surfactant affects bubble coalescence and condensation. Overall, this work provides a new framework for studying the effect of surfactants on
liquid-vapor transformations and suggests multiple areas for future research, including the impact of complex surface chemistries on flow around bubbles and the acoustic response of bubbles with surfactants.
Read the full abstract ▾
All authors Keyu Feng, Saikat Mukherjee, Tianyi Hu, Hector Gomez
Fluid Dynamics
Accelerating high-order energy-stable discontinous Galerkin solver using auto-differentiation and neural networks
Xukun Wang, Oscar A. Marino and Esteban Ferrer
High-order Discontinuous Galerkin Spectral Element Methods (DGSEM) provide excellent accuracy for complex flow simulations, but their computational cost increases sharply with higher
polynomial orders. %that provide very accurate solutions. To alleviate these limitations, this work presents a differentiable DG solver coupled with neural networks (NNs) that learn corrective forcing terms to correct low-order simulations and provide high-order accuracy. The solver's full differentiability enables gradient-based optimization and interactive (solver-in-the-loop) training, mitigating the data-shift problem typically encountered in static, offline learning. Two representative test cases are considered: the one-dimensional viscous Burgers' equation and two-dimensional decaying homogeneous isotropic
turbulence (DHIT). The results demonstrate that interactive training with extended unrolling horizons substantially improves the precision and long-term stability of the simulation compared to static training. For the Burgers' equation, a $\mathbb{P}_2$ simulation corrected using a NN-correction achieves the accuracy of a $\mathbb{P}_4$ solution with eight times reduction in computational cost. For the DHIT case, the NN-corrected low-order simulations successfully achieve high-order accuracy while reduce the error beyond the training interval. These results highlight the potential of differentiable solvers combined with neural networks as a robust and efficient framework for accelerating high-fidelity DG-based fluid simulations.
Read the full abstract ▾
Plasma Physics
Bayesian Optimization of Laser-Wakefield Acceleration via Spectral Pulse Shaping
B. Z. Djordjević, C. Benedetti, A. D. McNaughton et al. (+7 more)
In this paper, we investigate the effect of spectral pulse shaping of the
laser driver on the performance of channel-guided,
laser-
plasma accelerators. The study was carried out with the assistance of
Bayesian optimization using particle-in-
cell simulations. We used a realistic
plasma profile based on a novel optical-field-ionized channel technique with ionization injection and low on-axis
plasma densities to maximize the energy gain of the electron bunch trailing the
laser. Spectral shaping allows us to modify the temporal profile of the
laser driver while keeping the
laser energy constant, affecting the acceleration and injection processes. Given the complexity and breadth of the parameter space in question, we used numerical optimization to identify high performers. In particular, we found
laser profiles with additional spectral content that, when used with optimal
plasma channel parameters, result in charge content an order of magnitude higher than the baseline Gaussian case while also increasing the mean energy of the electron bunch.
Read the full abstract ▾
All authors B. Z. Djordjević, C. Benedetti, A. D. McNaughton, R. Lehe, H.-E. Tsai, S. C. Wilks, B. A. Reagan, G. J. Williams, J. van Tilborg, C. B. Schroeder
Computational Physics · Cross-listed from math.NA
A Hybrid Neural Network-Finite Element Method for the Viscous-Plastic Sea-Ice Model
Nils Margenberg and Carolin Mehlmann
We present an efficient hybrid Neural Network-Finite Element Method (NN-FEM) for solving the viscous-plastic (VP) sea-ice model. The VP model is widely used in
climate simulations to represent large-scale sea-ice dynamics. However, the strong nonlinearity introduced by the material law makes VP solvers computationally expensive, with the cost per degree of freedom increasing rapidly under mesh refinement. High spatial resolution is particularly required to capture narrow deformation bands known as linear kinematic features in viscous-plastic models. To improve computational efficiency in simulating such fine-scale deformation features, we propose to enrich coarse-mesh finite element approximations with fine-scale corrections predicted by neural networks trained with high-resolution simulations. The neural network operates locally on small patches of grid elements, which is efficient due to its relatively small size and parallel applicability across grid patches. An advantage of this local approach is that it generalizes well to different right-hand sides and computational domains, since the network operates on small subregions rather than learning details tied to a specific choice of boundary conditions, forcing, or geometry. The numerical examples quantify the runtime and evaluate the error for this hybrid approach with respect to the simulation of sea-ice deformations. Applying the learned network correction enables coarser-grid simulations to achieve qualitatively similar accuracy at approximately 11 times lower computational cost relative to the high-resolution reference simulations. Moreover, the learned correction accelerates the Newton solver by up to 10% compared to runs without the correction at the same mesh resolution.
Read the full abstract ▾
Computational Physics · Cross-listed from math.NA
High Order Numerical Methods Preserving Invariant Domain for Hyperbolic and Related Systems
Kailiang Wu, Xiangxiong Zhang and Chi-Wang Shu
Admissible states in
hyperbolic systems and related equations often form a convex invariant domain. Numerical violations of this domain can lead to loss of hyperbolicity, resulting in illposedness and severe numerical instabilities. It is therefore crucial for numerical schemes to preserve the invariant domain to ensure both physically meaningful solutions and robust computations. For complex systems, constructing invariant-domain-preserving (IDP) schemes is highly nontrivial and particularly challenging for high-order accurate methods. This paper presents a comprehensive survey of IDP schemes for
hyperbolic and related systems, with a focus on the most popular approaches for constructing provable IDP schemes. We first give a systematic review of the fundamental approaches for establishing the IDP property in first-order accurate schemes, covering finite difference, finite volume, finite element, and residual distribution methods. Then we focus on two widely used and actively developed classes of high order IDP schemes as well as their recent developments, most of which have emerged in the past decade. The first class of methods seeks an intrinsic weak IDP property in high-order schemes and then designs
polynomial limiters to enforce a strong IDP property at the points of interest. This generic approach applies to high-order finite volume and discontinuousGalerkin schemes. The second class is based on the flux limiting approaches, which originated from the flux-corrected transport method and can be adapted to a broader range of spatial discretizations, including finite difference and continuous finite element methods. In this survey, we elucidate the main ideas in the construction of IDP schemes, provide some new perspectives and insights, with extensive examples, and numerical experiments in gas dynamics and magnetohydrodynamics.
Read the full abstract ▾
General Physics
Unsupervised Kinematic Dissection of the Solar Neighborhood: Identifying Stellar Moving Groups with Gaia DR3
Anmay Raj
We present a comprehensive kinematic analysis of the
solar neighborhood (d < 50 pc) using high-precision astrometric data from the third
Gaia Data Release (DR3). By leveraging the full six dimensional phase space information (positions and velocities), we apply the Density-Based Spatial Clustering of Applications with Noise (DBSCAN)
algorithm to blindly identify
stellar overdensities in the Galactocentric Cartesian velocity space (U, V, W ). Our unsupervised machine learning approach successfully recovers the kinematic cores of major local moving groups, including the Hyades and Pleiades streams, without prior assumptions regarding their membership or spatial distribution. We analyze the velocity dispersion and structural properties of these associations, demonstrating that automated clustering
algorithms are robust tools for mapping the complex dynamical history of the local Milky Way disk. These results confirm the hierarchical nature of
stellar kinematic substructures and provide a catalog of high-probability members for future spectroscopic follow-up.
Read the full abstract ▾
Applied Physics
Solvent-Directed Femtosecond Laser Ablation: Tuning Phase and Defect Engineering in Hybrid CdPS3/CdS Nanostructures
Andrei Ushkov, Nadezhda Belozerova, Gleb Tikhonowski et al. (+8 more)
The limited visible-light absorption of wide-bandgap van der Waals
crystals fundamentally restricts their utility in
solar energy conversion. Here, we report a surfactant-free, solvent-directed
laser synthesis strategy to engineer the phase and optoelectronic properties of Cadmium Phosphorus Trisulfide (CdPS3). By exploiting the non-
equilibrium thermodynamics of femtosecond pulsed
laser ablation in
liquid (fs-PLAL), we demonstrate a tunable transition from the stoichiometric ternary phase to a highly active binary-rich
heterostructure. While ablation in water preserves the monoclinic CdPS3
lattice, the reducing environment of isopropanol triggers the formation of CdS
quantum dots and metallic cadmium defect sites. This solvent-induced phase engineering transforms the ultraviolet-active host into a robust visible-light photocatalyst. The resulting hybrid CdPS3/CdS nanocolloids exhibit superior charge separation efficiency, driven by Schottky-like metal-
semiconductor junctions, achieving ~ 90% degradation of Methylene Blue under 532 nm irradiation within 30 minutes. This work establishes fs-PLAL as a scalable defect-engineering tool for complex ternary layered materials, offering a new design of high-performance metal-thiophosphate-based photocatalysts.
Read the full abstract ▾
All authors Andrei Ushkov, Nadezhda Belozerova, Gleb Tikhonowski, Stepan Klimov, Alexander Syuy, Sergey V. Bazhenov, Sergey Novikov, Vladimir G. Leiman, Aleksey Arsenin, Gleb I. Tselikov, Valentyn Volkov
Fluid Dynamics
Conserved Pseudomomenta in Linear Quasigeostrophic Fluid Flows From Noether's Theorem
Dusan Begus, Chenyu Zhang and J.B. Marston
Hamiltonian and Lagrangian formulations for the two-dimensional quasi-geostrophic equations linearized about a zonally-symmetric basic flow are presented. The Lagrangian and
Hamiltonian exhibit an infinite U(1)
symmetry due to the absence of wave + wave -> wave interactions in the linearized approximation. By Noether's
theorem the
symmetry has a corresponding infinite set of conservation laws which are the well-known pseudomomenta. There exist separately conserved pseudomomenta at each zonal wavenumber, a point that has sometimes been obscured in past treatments.
Read the full abstract ▾
Atomic Physics · Cross-listed from quant-ph
Subradiant collective states for precision sensing via transmission spectra
Diego Zafra-Bono, Oriol Rubies-Bigorda and Susanne F. Yelin
When an ensemble of
quantum emitters interacts with a common radiation field, their emission becomes collective, giving rise to superradiant and subradiant states, characterized by broadened and narrowed linewidths. In this work, we propose to harness subradiant states for
quantum metrology; such states naturally arise in subwavelength-spaced atomic arrays in free space and in small ensembles of emitters coupled to one-dimensional waveguides. We demonstrate that their collective optical response yields sharp, narrow features in the transmittance spectrum, which can be used to enhance sensitivity to external perturbations. This improved sensitivity can be applied to atomic clock operation, spatially resolved imaging of emitter positions, and enables precise detection of both global and spatially varying detunings (such as those induced by electromagnetic fields or gravitational gradients).
Read the full abstract ▾
Space Physics
Tether-Based Architecture for Solar-Powered Orbital AI Data Centers
Igor Bargatin, Dengge Jin, Zaini Alansari et al. (+1 more)
We propose a tether-based structural architecture for orbital data centers operating in Dawn-Dusk Sun-Synchronous (DDSS) orbits under continuous sunlight. These space-based data centers, powered solely by
solar energy, could provide multi-megawatt computing for artificial intelligence (AI) inference with minimal latency to Earth. The proposed design uses a tethered chain of computing nodes with photovoltaic panels to achieve uninterrupted 2-20 MW of computing power, and employs radiative cooling and integrated shielding to manage heat and radiation. We detail the system architecture, including mass budgets, passive attitude control, and the dynamics induced by micrometeoroid collisions.
Read the full abstract ▾
All authors Igor Bargatin, Dengge Jin, Zaini Alansari, Jordan R. Raney
Fluid Dynamics · Cross-listed from astro-ph.HE
Non-Equilibrium Thermodynamics of Black-Hole Coronae: QPOs, Turbulence, and Jets
Vanessa López-Barquero, Alejandro Jenkins, Christopher S. Reynolds et al. (+1 more)
The variability of X-rays observed from accreting black hole systems, including quasi-periodic oscillations (QPOs), suggests a complex nonlinear dynamics in the corona. Here, we propose a new theoretical framework for this variability, based on non-
equilibrium thermodynamics. In this model, coronal variability arises from feedback between a macroscopic oscillation of the
plasma and the rate at which it is cooled by the inverse Compton scattering of soft
photons from the disc. The "pair thermostat” mechanism then allows the corona to act as a heat engine that extracts work cyclically from the underlying thermal disequilibrium between the low-
entropy heating from the black hole and the high-
entropy cooling by soft
photons from the disk, in close analogy to the well-known $\kappa$-mechanism for pulsating
stars. This coronal self-oscillation may explain QPOs without invoking an external periodic driving. Moreover, we argue that this mechanism can generate coronal
turbulence and jets.
Read the full abstract ▾
All authors Vanessa López-Barquero, Alejandro Jenkins, Christopher S. Reynolds, Andrew Fabian
Fluid Dynamics · Cross-listed from cs.LG
Graph Deep Learning for Intracranial Aneurysm Blood Flow Simulation and Risk Assessment
Paul Garnier, Pablo Jeken-Rico, Vincent Lannelongue et al. (+11 more)
Intracranial aneurysms remain a major cause of neurological morbidity and mortality worldwide, where rupture risk is tightly coupled to local hemodynamics particularly wall shear stress and oscillatory shear index. Conventional computational fluid dynamics simulations provide accurate insights but are prohibitively slow and require specialized expertise. Clinical imaging alternatives such as 4D Flow MRI offer direct in-vivo measurements, yet their spatial resolution remains insufficient to capture the fine-scale shear patterns that drive endothelial remodeling and rupture risk while being extremely impractical and expensive. We present a graph neural network surrogate model that bridges this gap by reproducing full-field hemodynamics directly from vascular geometries in less than one minute per cardiac cycle. Trained on a comprehensive
dataset of high-fidelity simulations of patient-specific aneurysms, our architecture combines graph
transformers with autoregressive predictions to accurately simulate blood flow, wall shear stress, and oscillatory shear index. The model generalizes across unseen patient geometries and inflow conditions without mesh-specific calibration. Beyond accelerating simulation, our framework establishes the foundation for clinically interpretable hemodynamic prediction. By enabling near real-time inference integrated with existing imaging pipelines, it allows direct comparison with hospital phase-diagram assessments and extends them with physically grounded, high-resolution flow fields. This work transforms high-fidelity simulations from an expert-only research tool into a deployable, data-driven decision support system. Our full pipeline delivers high-resolution hemodynamic predictions within minutes of patient imaging, without requiring computational specialists, marking a step-change toward real-time, bedside aneurysm analysis.
Read the full abstract ▾
All authors Paul Garnier, Pablo Jeken-Rico, Vincent Lannelongue, Chiara Faitini, Aurèle Goetz, Lea Chanvillard, Ramy Nemer, Jonathan Viquerat, Ugo Pelissier, Philippe Meliga, Jacques Sédat, Thomas Liebig, Yves Chau, Elie Hachem
Optics
Strong Mode Coupling via Quasi-Bound States in the Continuum in Bianisotropic Metasurfaces
Luis Manuel Máñez-Espina, Bahman Amrahi, Viktar Asadchy et al. (+1 more)
Electromagnetic mode coupling plays a key role in many resonant effects in nanophotonics. This coupling is also responsible for the appearance of bianisotropy, where electric and
magnetic responses become interconnected through the interaction of their respective modes. In this work, we develop a simple and general temporal coupled-mode theory model to describe off-diagonal
chiral bianisotropy. Using quasi-bound states in the continuum (q-BICs), we demonstrate how to control the hybridization of modes with opposite
symmetries, resulting in Rabi-like splitting between the hybrid states in the regime of strong electromagnetic mode coupling. Beyond revealing the physical origin of the hybrid modes, our model predicts and explains the emergence of dual-band asymmetric reflection and absorption, and how to achieve maximum directional absorption difference. The theoretical predictions are verified by full-wave simulations, showing very good agreement with theory. Furthermore, very strong reciprocal bianisotropy is demonstrated with the use of q-BICs in a deeply subwavelength metasurface in the optical frequency range. Our results provide a clear physical picture of the interaction process between modes, offering a compact theoretical framework for understanding and designing bianisotropic dielectric metasurfaces not only in the traditional regime but also in the strong coupling regime.
Read the full abstract ▾
All authors Luis Manuel Máñez-Espina, Bahman Amrahi, Viktar Asadchy, Ana Díaz-Rubio
Chemical Physics
Effect of the Gradient of the Spin-Polarization in Density Functional Approximations
Rohan Maniar and John P. Perdew
The construction of non-empirical density functional approximations is typically guided by the satisfaction of exact constraints. An important constraint is the recovery of the gradient expansion for slowly varying electron densities. In prior constructions of semilocal density functional approximations, the $\nabla \zeta$-dependent terms in the gradient expansion of the correlation have been dropped, where $\zeta$ is the relative
spin polarization. We propose a scheme by which such terms can be reintroduced into already constructed functionals without significantly affecting other constraints and norms. We implement this scheme on the Strongly Constrained and Appropriately Normed (SCAN) functional to construct a $\nabla \zeta$-corrected version of SCAN. The resulting functional is shown to provide improvements in transition-metal atoms and molecules without significantly affecting SCAN's accurate description of $sp$-systems. For the binding energy curve of the chromium dimer Cr$_2$, the SCAN underbinding is fully corected at large bond lengths and reduced at short bond lengths.
Read the full abstract ▾
Geophysics
A microstructural rheological model for transient creep in polycrystalline ice
Alex J. Vargas, Ranjiangshang Ran and Justin C. Burton
The slow creep of glacial ice plays a key role in sea-level rise, yet its transient deformation remains poorly understood. Glen's flow law, where strain rate is simply a function of stress, cannot predict the time-dependent creep behavior observed in experiments. Here we present a physics-based rheological model that captures all three regimes of transient creep in polycrystalline ice. The key components of the model are a series of Kelvin-Voigt mechanical elements that produce a power-law (Andrade) creep, and a single viscous element with microstructure and stress dependence that represents reorientation in the polycrystalline grains. The interplay between these components produces a minimum in the strain rate at approximately 1% strain, which is a universal but unexplained feature reported in experiments. Due to its transient nature, the model exhibits fractional power-law exponents in the stress dependence of the strain rate minimum, which has been conventionally interpreted as independent physical processes. Taken together, we provide a compact, mechanistic framework for transient ice rheology that generalizes to other polycrystalline materials and can be integrated into constitutive laws for ice-sheet models.
Read the full abstract ▾
Optics
Dual-wavelength Fourier Ptychographic Topography
Yi Shen, Tongyu Li, Hao Wang et al. (+7 more)
We introduce a dual-wavelength
Fourier ptychographic topography (FPT) method that extends the lambda/2 height-range limit of single-wavelength FPT. By reconstructing complex fields at two illumination wavelengths and exploiting their phase difference, the method achieves an effective synthetic wavelength lambda_s and an unambiguous range of lambda_s/2 without reducing lateral resolution. A noise-robust wrapped-number search is used to select per-pixel integer pairs (k1, k2), and a global refinement with circular TV regularization and soft bounds improves stability and preserves height discontinuities. The approach is validated through rigorous scattering-model-based simulations and experiments on structured silicon samples, demonstrating accurate height recovery in regimes where single-wavelength FPT exhibits phase wrapping. We analyze the limits of the FPT forward model and identify aspect ratio (AR) and phase modulation transfer function (ph-MTF) as key predictors of reconstruction fidelity. Simulations and experiments show that increasing AR beyond a practical threshold causes loss of high-frequency phase transfer and destabilizes dual-wavelength unwrapping. Within this AR range, dual-wavelength FPT provides robust, high-resolution topography suitable for
semiconductor and industrial metrology.
Read the full abstract ▾
All authors Yi Shen, Tongyu Li, Hao Wang, Jinyong Kim, Hojun Lee, Wookrae Kim, Jonghyeok Park, Junho Shin, Seungbeam Park, Lei Tian
Biological Physics
Spreading processes on heterogeneous active systems: spreading threshold, immunization strategies, and vaccination noise
Benjamín Marcolongo, Gustavo J. Sibona and Fernando Peruani
We study spreading processes in two-dimensional systems of heterogeneous active
agents that exhibit different individual active speeds. We obtain, combining kinetic and complex network theory, an analytical expression for the spreading threshold that depends not only on the first but also second moment of the speed distribution. Moreover, we prove that spreading can even occur for vanishing average active speed. Furthermore, we find that random vaccination strategies are ineffective in heterogeneous active systems, whereas targeted ones are effective. We also show that vaccination acts as (quenched) noise: it can decrease or increase the outbreak size. Our results offer insights into how information propagates in heterogeneous populations of active
agents.
Read the full abstract ▾
Physics and Society
Cultural evolution of human beauty standards
Louis Boucherie, Sagar Kumar, Katharina Ledebur et al. (+2 more)
Beauty standards shape self-perception and health through social comparison and objectification, while exposure to idealized imagery exacerbates body-image concerns. Media and fashion are central arbiters of these ideals, yet long-term, quantitative, intersectional studies on how representation has changed remain scarce. We assembled a
dataset of 793199 records spanning 25 years of advertising, magazine covers, runway shows, and editorials to quantify changes in anthropometric and demographic representation. We find a paradox in the
evolution of beauty ideals: while representational diversity has increased, the median model physique remains stable. This is driven by selective plus-size inclusion at the upper tail, while the typical physique continues to diverge from the US population. Intersectionally, non-white models are 4.5 times more likely to be plus-size, indicating that progress in size inclusivity falls disproportionately on multiple underrepresented identities. Stratifying the industry via a data-driven prestige hierarchy, we find that thinness is overrepresented at the top tier. Finally, comparing two regulatory interventions we observe that numeric thresholds are more effective at reducing underweight appearances. Our results quantify the cultural
evolution in media and fashion, revealing that inclusion has increased; however, gains are uneven and intersectionally concentrated on size and ethnicity, whereas the prevailing thin ideal remains largely unchanged.
Read the full abstract ▾
All authors Louis Boucherie, Sagar Kumar, Katharina Ledebur, August Lohse, Karolina Sliwa
Fluid Dynamics
Axial Symmetric Navier Stokes Equations and the Beltrami /anti Beltrami spectrum in view of Physics Informed Neural Networks
Pietro Fré
In this paper, I further continue an investigation on Beltrami Flows began in 2015 with A. Sorin and amply revised and developed in 2022 with M. Trigiante. Instead of a compact $3$-
torus $T^3=\mathbb{R}^3/\Lambda$ where $\Lambda$ is a crystallographic
lattice, as done in previous work, here I considered flows confined in a cylinder with identified opposite bases. In this
topology I considered axial symmetric flows and found a complete basis of axial symmetric harmonic $1$-forms that, for each energy level, decomposes into six components: two Beltrami, two anti-Beltrami and two closed forms. These objects, that are written in terms of trigonometric and Bessel functions, constitute a function basis for an $L^2$ space of axial symmetric flows. I have presented a general scheme for the search of axial symmetric solutions of Navier Stokes equation by reducing the latter to an hierachy of quadratic relations on the development coefficients of the flow in the above described functional basis. It is proposed that the coefficients can be determined by means of a Physics Informed like Neural Network optimization recursive
algorithm. Indeed the present paper provides the theoretical foundations for such a algorithmic construction that is planned for a future publication.
Read the full abstract ▾
Geophysics
Near real-time channel selection for Distributed Acoustic Sensing technology
Emanuele Bozzi, Giulio Pascucci, Giacomo Rapagnani et al. (+5 more)
Distributed Acoustic Sensing (DAS) technology is advancing seismic monitoring by providing dense observations near earthquake sources. However, the resulting data volumes often limit real-time processing capability, with most seismological applications focusing on retrospective analysis of seismic sequences. To address this challenge, we introduce ORION, a fast and versatile selector of high-quality DAS channels that efficiently reduces the amount of data to analyze. The method first adopts spatial clustering to identify cable segments with similar geometrical attributes (e.g, azimuth), and then performs channel selection within each section using waveform attributes (e.g., signal-to-noise ratio); this approach enables spatial sub-sampling while preserving azimuthal coverage. We demonstrate the flexibility of the selector across several cable geometries. Finally, we analyze a seismic sequence using ORION-selected channels and compare the source locations with those from a more conventional uniform distribution of channels along the cable, showing improvements in hypocenter accuracy.
Read the full abstract ▾
All authors Emanuele Bozzi, Giulio Pascucci, Giacomo Rapagnani, Gian Maria Bocchini, Rebecca Harrington, Arantza Ugalde, Gilberto Saccorotti, Francesco Grigoli
Biological Physics · Cross-listed from q-bio.PE
A mathematical model of Culex population abundance and the impact of vector control interventions in a patchy environment
Suman Bhowmick, Patrick Irwin, Kristina Lopez et al. (+2 more)
Recent mosquito-borne outbreaks have revealed vulnerabilities in our abatement programmes, raising concerns about how abatement-districts should choose optimal future control strategies. Spatial dissemination of vector-borne disease is strongly shaped by the movement of both hosts and mosquitoes, creating substantial overlap between vector activity and pathogen spread. We developed a mathematical model for Culex mosquito dynamics in a patchy landscape, integrating entomological observations, weather-driven factors, and the vector control practices of the Northwest Mosquito Abatement District (NWMAD) in Cook County, Illinois. By coupling a temperature-driven multi-patch ODE model with NWMAD's adulticide and larvicide interventions, we investigated how spatial heterogeneity and control timing influence mosquito abundance. We also evaluated how mosquito dispersal modifies intervention effectiveness by comparing single-patch and two-patch model outcomes. Our results showed that models ignoring spatial connectivity can substantially overestimate the impact of interventions or misidentify the thresholds of vector persistence. Through numerical simulations, we analysed continuous and pulsatile control approaches under varying spatial and temporal configurations. These findings provide insight into optimal strategies for managing Culex populations and mitigating mosquito-borne disease risk in weather-driven, spatially connected environments across Cook County, Illinois.
Read the full abstract ▾
All authors Suman Bhowmick, Patrick Irwin, Kristina Lopez, Megan Lindsay Fritz, Rebecca Lee Smith
Fluid Dynamics · Cross-listed from math.NA
Space-time discretization for barotropic flow stemming from a multisymplectic variational formulation
Mukthesh Mahadev and Marc Gerritsma
This study proposes and analyses a novel higher-order, structure preserving discretization method for inviscid barotropic flows from a Lagrangian perspective. The method is built on a multisymplectic variational principle discretized over a full space-time domain. Flow variables are encoded on a staggered space-time mesh, leveraging the principles of mimetic spectral element discretization. Unlike standard Lagrangian methods, which are prone to mesh distortion, this framework computes fluid deformations in a fixed reference configuration and systematically maps them to the physical domain via the Piola-Kirchhoff stress. Further, the structure preserving design ensures that the discrete analogues of the fundamental conservation laws for mass, momentum, and energy are satisfied up to machine precision. The formulation also inherently handles low-Mach number flows without specialized preconditioning. Numerical experiments on expansion and compression flows confirm the accuracy, stability, and exact conservation properties of the discretization.
Read the full abstract ▾
Plasma Physics
CIEMAT-QI4X: a reactor-relevant quasi-isodynamic stellarator configuration compatible with an island divertor
E. Sánchez, J. L. Velasco, I. Calvo et al. (+3 more)
A four-field-period quasi-isodynamic stellarator configuration is presented that exhibits small neoclassical and electrostatic turbulent transport, good fast-ion confinement over a wide range of $\beta$ values, small bootstrap current and an edge island structure compatible with an island divertor. This configuration, called CIEMAT-QI4X, has been obtained by building on the optimization strategy and sophisticating the methods employed in [Sánchez E. et al 2023 Nucl. Fusion 63 066037]. The optimization has been improved by incorporating metrics to control Mercier stability and by enforcing strict constraints on the rotational transform profile to achieve nested toroidal surfaces in the confinement region and a divertor island structure at the
plasma edge. Specifically, CIEMAT-QI4X has a 4/4 island chain at the edge that is resilient at least up to $\beta=4\%$, even when the bootstrap current is included. A corresponding set of filamentary coils is presented that generates the configuration with enough accuracy to preserve the aforementioned physics properties. In terms of physics performance, CIEMAT-QI4X establishes as a candidate for a stellarator fusion reactor design.
Read the full abstract ▾
All authors E. Sánchez, J. L. Velasco, I. Calvo, J. M. García-Regaña, C. Salcuni, J. A. Alonso
Applied Physics
Injection dynamics in spin-wave active ring oscillator (SWARO)
Anirban Mukhopadhyay, Ihor I. Syvorotka and Anil Prabhakar
We investigated injection locking in
spin-wave active ring oscillators (SWAROs) operating in the multi-mode regime. By applying external RF signals with varying frequency and power, we identified the locking behavior of individual modes and extracted the total locking ranges from spectral measurements. The results show asymmetric
evolution of the lower and upper locking boundaries with drive power for the lower-frequency SWARO modes, while the highest-frequency mode exhibits nearly symmetric behavior. A maximum locking range of over 11 MHz is observed at a drive power of -10 dBm. To interpret these results, we develop an Adler-like model that captures the dependence of the locking range on drive power, showing good agreement for the higher-frequency modes. For the lowest-frequency mode, however, the model underestimates the locking range at low drive and saturates at high drive power levels, while the experimental range increases monotonically, indicating the influence of multi-mode interactions. These findings establish SWARO as a useful platform for exploring injection phenomena in
spin-wave ring systems with delayed feedback and motivate the development of extended injection models that account for multi-mode dynamics.
Read the full abstract ▾
Atomic and Molecular Clusters · Cross-listed from cond-mat.stat-mech
Commissioning of an experiment for thermodynamic and spectroscopic studies of hydrogen isotopologues at cryogenic conditions
Joshua Kohpeiß, Dominic Batzler, Beate Bornschein et al. (+7 more)
To study thermodynamic properties and dynamic phase space behavior of hydrogen isotopologues (Q$_2$) at cryogenic temperatures and at high density, the Tritium Absorption InfraRed Spectroscopy 2 (T$_2$ApIR) experiment has been set up and commissioned at Tritium Laboratory Karlsruhe (TLK). In the frame of the experiment, Q$_2$ behavior in different phases, ortho/para states, temperatures (10 K - 300 K) and pressures (up to 2.5 bar a) will be investigated with optical methods, infrared and Raman spectroscopy. The facility consists of a fully tritium compatible cryostat, which includes an optical
cell, ortho/para converter and windows for optical and spectroscopic studies. The cryostat can be cooled below the H$_2$ triple point by a two-stage cryocooler and contains openings in the cryogenic shielding for the optical access. The challenge of combining these scientific requirements in a design with high amounts of tritium (14 g), in a limited space, all while maintaining the TLK safety philosophy was solved by the presented design. The experiment is ready to be fully integrated into the TLK closed loop tritium infrastructure. This contribution reports a comprehensive overview of the commissioning phase of the experimental facility and the results of the first commissioning experiments, including cryogenic performance tests, commissioning experiments with non-radioactive gases, and tests of the analytical instruments.
Read the full abstract ▾
All authors Joshua Kohpeiß, Dominic Batzler, Beate Bornschein, Lutz Bornschein, Robin Größle, Daniel Kurz, Ralph Lietzow, Alexander Marsteller, Michael Sturm, Stefan Welte