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Physics Physics

physics Watch Physics

Tuesday 30 December

Fluid Dynamics

The electrostatic-hydrodynamic interaction of two spheres in a linear compressional flow

Pijush Patra, Srikumar Warrier and Anubhab Roy

We investigate the collision dynamics of two like-charged dielectric spheres in a uniaxial compressional flow, accounting for non-continuum lubrication interactions, van der Waals attraction, and the complete finite-dielectric electrostatic interaction. Mutual polarization causes the electrostatic force to behave substantially differently from the point-charge approximation and can produce strong near-field attraction despite far-field Coulomb repulsion, depending on the particle size and charge ratios. We identify a critical electrostatic strength above which particles approaching from the far field cannot reach contact. This threshold corresponds to a saddle-node bifurcation of the relative-trajectory field on the compressional axis. Below this threshold, near-field polarization-induced attraction can increase the upstream interception area and substantially enhance the collision efficiency. We report that electrostatic interactions lead to non-monotonic variations of collision efficiency with electrostatic strength, particle size ratio, and charge ratio. When electrostatic interactions remain repulsive at all separations, increasing their strength suppresses collisions monotonically. Non-continuum lubrication and van der Waals interactions further modify the collision efficiency, although sufficiently strong polarization-induced attraction can dominate these near-field effects. For weak electrostatic interactions, a perturbation analysis expresses the leading correction to the collision efficiency as a weighted average of the electrostatic force along the limiting colliding trajectory, with the weight concentrated in the lubrication region; this prediction agrees closely with the numerical results. These results demonstrate that finite-size polarization and near-field hydrodynamic interactions jointly govern the collision behaviour of like-charged particles in compressional flows.
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Optics

Adiabatic approach for high harmonic generation in solids induced by intense low-frequency pulses

A.V. Flegel, Liang-Wen Pi and M.V. Frolov

An analytic description of high harmonic generation (HHG) in solids induced by intense low-frequency pulses is presented within an adiabatic approach, which treats laser-matter interactions nonperturbatively. We derive the analytical expression for the laser-dressed state of an electron in an arbitrary spatially periodic potential, taking into account multiband structure of the solid target. Closed-form formulas for electron current and HHG spectra are presented. Based on the developed theory, we provide an analytic explanation for key features of HHG yield and show that the interband mechanism of HHG prevails over the intraband one.
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Medical Physics

High Space-bandwidth Product Label-free Examination of iPSC-derived Brain Organoids via Fourier Ptychographic Microscopy

Mikolaj Krysa, Mikolaj Rogalski, Piotr Arcab et al. (+7 more)

Fourier ptychographic microscopy (FPM) is a promising quantitative phase imaging technique that enables high-resolution, label-free imaging over a large field-of-view. Here, we present the first application of FPM for the quantitative analysis of human brain organoid slices, providing a powerful, cost-effective, and label-free enhancement to the current gold-standard fluorescence microscopy. Brain organoids, prepared as thin (5 micrometer) slices, were imaged with a custom-built FPM system consisting of a standard light microscope (4x, 0.2 NA objective) and a 7x7 LED array. This configuration achieved a synthetic numerical aperture of 0.54 and a spatial resolution of approximately 488 nm across an area of 2.077 x 3.65 mm. Fluorescence microscopy was used in parallel for neurons, astrocytes, and nuclei labeling, providing rich fluorescence imaging. Moreover, we designed an automated method to merge classical resolution fluorescence images to visualize the whole brain organoid and align it with the numerically increased space-bandwidth product FPM image. The provided alignment method enables rich phase-fluorescence correlative imaging. Based on the segmentation performed on the stitched fluorescence images, we devised a quantitative phase analysis revealing a higher mean optical thickness of the nuclei versus astrocytes and neurons. Notably, nuclei located in neurogenic regions consistently exhibited significantly higher phase values (optical path difference) compared to nuclei elsewhere, suggesting cell-type-specific biophysical signatures. The label-free, quantitative, and high-throughput capabilities of the FPM approach demonstrated here make it a powerful and accessible tool for future structural and functional studies of whole-section brain organoid development and disease modeling studies.
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All authors Mikolaj Krysa, Mikolaj Rogalski, Piotr Arcab, Pawel Goclowski, Kamil Kalinowski, Piotr Zdańkowski, Vishesh K. Dubey, Mukesh Varshney, Balpreet S. Ahluwalia, Maciej Trusiak

Biological Physics

Local shear induces long-range suppression of cellular motion in stiff epithelial monolayers

Shahar Nahum, Adi Y. Elkabetz, Matan Elbaz et al. (+3 more)

As small particles skim our airways during breathing, or our intestines during digestion, the surface epithelium is subjected to local exogenous shear that deforms hundreds to thousands of tightly interacting cells. Unlike shear deformations applied at the macro-tissue scale or the micro-cell scale, the effects of such perturbations at the meso-scale remain largely unexplored. To address this, we developed a mesoscopic probe that adheres to the apical surface of an epithelial monolayer and applies magnetically driven local shear. We find that localized shear suppressed cellular migratory dynamics far beyond the immediate neighbors in stiffer layers, whereas in softer layers the same perturbation produced no detectable long-range change in dynamics. This mechano-transductive relationship is further supported by unconfined mature layers, in which increased stiffness was accompanied by restored shear responsiveness. Viewed at the level of collective dynamics, shear-induced migratory suppression in stiff layers was often accompanied by reduced MSD scaling exponents and changes in cell shape, but these responses were not fully captured by the epithelial jamming framework. Together, these observations provide a new perspective on how a local mechanical perturbation traverses the epithelial monolayer to influence both nearby and distant cellular environments.
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All authors Shahar Nahum, Adi Y. Elkabetz, Matan Elbaz, Liav Daraf, Yael Lavi, Lior Atia

Optics

Mathematical Theory for Photonic Hall Effect in Honeycomb Photonic Crystals

Wei Li, Junshan Lin, Jiayu Qiu et al. (+1 more)

In this work, we develop a mathematical theory for the photonic Hall effect and prove the existence of guided electromagnetic waves at the interface of two honeycomb photonic crystals. The guided wave resembles the edge states in electronic systems: it is induced by the topological Hall effect, and the wave propagates along the interface but not in the bulk media. Starting from a symmetric honeycomb photonic crystal that attains Dirac points at the high-symmetry points of the Brillouin zone, $K$ and $K'$, we introduce two classes of perturbations for the periodic medium. The perturbations lift the Dirac degeneracy, forming a spectral band valley at the points $K$ and $K'$ with well-defined topological phase that depends on the sign of the perturbation parameters. By employing the layer potential techniques and spectral analysis, we investigate the existence of guided wave along an interface when two honeycomb photonic crystals are glued together. In particular, we elucidate the relationship between the existence of the interface mode and the nature of perturbations imposed on the two periodic media separated by the interface.
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All authors Wei Li, Junshan Lin, Jiayu Qiu, Hai Zhang

Fluid Dynamics

Beyond chaos: fluctuations, anomalies and spontaneous stochasticity in fluid turbulence

Gregory L. Eyink and Nigel Goldenfeld

In this perspective, we consider the development of statistical hydrodynamics, focusing on the way in which the intrinsic stochasticity of turbulent phenomena was identified and is being explored. A major purpose of our discussion is to bring out the role of anomalies in turbulent phenomena, in ways that are not usually done, and to emphasize how the description of turbulent phenomena requires delicate considerations of asymptotic limits. The scope of our narrative includes selected historical aspects that are not usually emphasized, primarily due to G.I. Taylor, as well as discussions of certain aspects of the laminar-turbulent transition, the behaviour of turbulent drag at intermediate Reynolds numbers, and the statistics of fully-developed turbulence that exhibit spontaneous stochasticity.
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Physics and Society · Cross-listed from astro-ph.IM

Picture an Astronomer: Best Practices for Retaining Talent in Astrophysics

Ava Polzin, Katherine E. Whitaker, C. Megan Urry et al. (+85 more)

Women are consistently underrepresented in astrophysics yet are simultaneously subject to disproportionate attrition at every career stage. This disparity between demonstrated efficacy in job performance and ultimate career outcome was the primary motivation for the Picture an Astronomer series, which included both targeted public outreach to increase representation of women in astrophysics and high-level, solution-oriented discussions among professional astronomers. In March 2025, more than 200 astronomers came together in a hybrid-format symposium focused on the state of the field for female scientists, combining scientific exchange with discussions of policies and practices to strengthen retention of talent in the field. This white paper is the result of those discussions, offering a wide range of recommendations developed in the context of gendered attrition in astrophysics but which ultimately support a healthier climate for all scientists alike.
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All authors Ava Polzin, Katherine E. Whitaker, C. Megan Urry, Henna Abunemeh, Sanyukta Agarwal, Aadya Agrawal, Nathaniel Alden, Ann-Marsha Alexis, Sydney Andersen, Melanie Archipley, Yasmeen Asali, Katie Auchettl, Bradford Benson, Binod Bhattarai, Sarah Biddle, Madison Brady, Katelyn Breivik, Disha Chakraborty, Mikel Charles, Hsiao-Wen Chen, Josephine Chishala, Anirudh Chiti, Panagiota Eleftheria Christopoulou, Mi Dai, Flaminia Fortuni, Shanika Galaudage, Daniel Glazer, Anika Goel, Andrea Gokus, Jenny E. Greene, Ryn Grutkoski, Yiqing Guo, Joseph Guzman, Renée Hložek, Lindsay R. House, Lillian N. Joseph, Molly Beth Jourdan, Tanvi Karwal, Zuzanna Kocjan, Emily Koivu, Varun Kore, Andrey Kravtsov, Keerthi Kunnumkai, Shalini Kurinchi-Vendhan, Johannes U. Lange, Sarah R. Loebman, Kira Lund, Julie Malewicz, Olivia McAuley, Rebecca McClain, Stephen McKay, Emily McPike, Cassidy Metzger, Lamiya A. Mowla, Katherine Myers, Erica Nelson, Aline Novais, Camilla Nyhagen, Micah Oeur, Lou Baya Ould Rouis, Paarmita Pandey, Raagini Patki, Sonu Tabitha Paulson, Haile M. L. Perkins, Ashi Poorey, Izabella Pozo, Heather L. Preston, Pazit Rabinowitz, Alexandra S. Rahlin, Janiris Rodriguez-Bueno, Francisco Rodríguez Montero, Huei Sears, Álvaro Segovia Otero, Uliana Solovieva, Rachel Somerville, Jessica Speedie, Tjitske Starkenburg, Laura Stiles-Clarke, Chin Yi Tan, Yu-Hsuan Teng, Tanya Urrutia, Padmavathi Venkatraman, Margaret E. Verrico, Amanda Wasserman, Claire E. Williams, Tony Wong, Shirin Gul Zaidi, Chantene Zichterman

Atomic Physics

Sub-Ensemble Correlations as a Covariance Geometry

Zuoxian Wang, Yuhao Zhang, Gaopu Hou et al. (+6 more)

Conventional practice of spatially resolved detection in diffusion-coupled thermal atomic vapors implicitly treat localized responses as mutually independent. However, in this study, it is shown that observable correlations are governed by the intrinsic spatiotemporal covariance of a global spin-fluctuation field, such that spatial separation specifies only overlapping statistical projections rather than independent physical components. A unified field-theoretic description is established in which sub-ensembles are defined as measurement-induced statistical projections of a single stochastic field. Within this formulation, sub-ensemble correlations are determined by the covariance operator, inducing a natural geometry in which statistical independence corresponds to orthogonality of the measurement functionals. For collective spin fluctuations described by a diffusion-relaxation Ornstein-Uhlenbeck stochastic field, the covariance spectrum admits only a finite set of fluctuation modes in a bounded domain, imposing an intrinsic, field-level limit on the number of statistically distinguishable sub-ensembles. The loss of sub-ensemble independence is formalized through the notion of spatial sampling overlap, which quantifies the unavoidable statistical coupling arising from shared access to common low-order fluctuation modes. While multi-channel atomic magnetometry provides a concrete physical setting in which these constraints become explicit, the framework applies generically to diffusion-coupled stochastic fields.
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All authors Zuoxian Wang, Yuhao Zhang, Gaopu Hou, Zihua Liang, Gen Hu, Lu Liu, Yuan Sun, Feilong Xu, Mao Ye

Computational Physics · Cross-listed from cs.LG

Generative forecasting with joint probability models

Patrick Wyrod, Ashesh Chattopadhyay and Daniele Venturi

Chaotic dynamical systems exhibit strong sensitivity to initial conditions and often contain unresolved multiscale processes, making deterministic forecasting fundamentally limited. Generative models offer an appealing alternative by learning distributions over plausible system evolutions; yet, most existing approaches focus on next-step conditional prediction rather than the structure of the underlying dynamics. In this work, we reframe forecasting as a fully generative problem by learning the joint probability distribution of lagged system states over short temporal windows and obtaining forecasts through marginalization. This new perspective allows the model to capture nonlinear temporal dependencies, represent multistep trajectory segments, and produce next-step predictions consistent with the learned joint distribution. We also introduce a general, model-agnostic training and inference framework for joint generative forecasting and show how it enables assessment of forecast robustness and reliability using three complementary uncertainty quantification metrics (ensemble variance, short-horizon autocorrelation, and cumulative Wasserstein drift), without access to ground truth. We evaluate the performance of the proposed method on two canonical chaotic dynamical systems, the Lorenz-63 system and the Kuramoto-Sivashinsky equation, and show that joint generative models yield improved short-term predictive skill, preserve attractor geometry, and achieve substantially more accurate long-range statistical behaviour than conventional conditional next-step models.
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Atmospheric and Oceanic Physics

Towards mechanistic understanding in a data-driven weather model: internal activations reveal interpretable physical features

Theodore MacMillan and Nicholas T. Ouellette

Large data-driven physics models like DeepMind's weather model GraphCast have empirically succeeded in parameterizing time operators for complex dynamical systems with an accuracy reaching or in some cases exceeding that of traditional physics-based solvers. Unfortunately, how these data-driven models perform computations is largely unknown and whether their internal representations are interpretable or physically consistent is an open question. Here, we adapt tools from interpretability research in Large Language Models to analyze intermediate computational layers in GraphCast, leveraging sparse autoencoders to discover interpretable features in the neuron space of the model. We uncover distinct features on a wide range of length and time scales that correspond to tropical cyclones, atmospheric rivers, diurnal and seasonal behavior, large-scale precipitation patterns, specific geographical coding, and sea-ice extent, among others. We further demonstrate how the precise abstraction of these features can be probed via interventions on the prediction steps of the model. As a case study, we sparsely modify a feature corresponding to tropical cyclones in GraphCast and observe interpretable and physically consistent modifications to evolving hurricanes. Such methods offer a window into the black-box behavior of data-driven physics models and are a step towards realizing their potential as trustworthy predictors and scientifically valuable tools for discovery.
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Biological Physics

Complexity and dynamics of partially symmetric random neural networks

Nimrod Sherf, Si Tang, Dylan Hafner et al. (+4 more)

Neural circuits exhibit structured connectivity, including an overrepresentation of reciprocal connections between neuron pairs. Despite important advances, a full understanding of how such partial symmetry in connectivity shapes neural dynamics remains elusive. Here we ask how correlations between reciprocal connections in a random, recurrent neural network affect phase-space complexity, defined as the exponential proliferation rate (with network size) of the number of fixed points that accompanies the transition to chaotic dynamics. We find a striking pattern: partial anti-symmetry strongly amplifies complexity, while partial symmetry suppresses it. These opposing trends closely track changes in other measures of dynamical behavior, such as dimensionality, Lyapunov exponents, and transient path length, supporting the view that fixed-point structure is a key determinant of network dynamics. Thus, positive reciprocal correlations favor low-dimensional, slowly varying activity, whereas negative correlations promote high-dimensional, rapidly fluctuating chaotic activity. These results yield testable predictions about the link between connection reciprocity, neural dynamics and function.
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All authors Nimrod Sherf, Si Tang, Dylan Hafner, Jonathan D. Touboul, Xaq Pitkow, Kevin E. Bassler, Krešimir Josić

Biological Physics · Cross-listed from q-bio.MN

Epigenetic feedback reshapes dynamical landscapes in gene regulatory networks

Sascha H. Hauck, Sandip Saha, Narsis A. Kiani et al. (+1 more)

Understanding how gene regulatory networks (GRNs) give rise to stable and dynamic cellular states remains a central challenge in theoretical biology, particularly when slow epigenetic feedback reshapes the underlying regulatory landscape. While experimental approaches such as single-cell transcriptomics reveal rich dynamical behaviour, a tractable theoretical framework that links gene expression, epigenetic control, and collective dynamics remains challenging. Here, we develop an extended Dynamical Mean Field Theory (DMFT) framework for GRNs that incorporates epigenetic modifications as slow, feedback-driven variables. Building on the analogy between Hopfield networks and spin glass systems, we derive effective stochastic equations that reduce high-dimensional dynamics to a tractable form across multiple timescales. This formulation enables quantitative characterization of both stable and oscillatory regimes and reveals how epigenetic feedback reshapes the effective potential landscape governing cell fate decisions. Our model shows how epigenetic feedback regulation dynamically reshapes the Waddington landscape. Our results and methodology provide a unified theoretical framework for understanding developmental dynamics and epigenetic reprogramming in complex biological systems.
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All authors Sascha H. Hauck, Sandip Saha, Narsis A. Kiani, Jesper N. Tegner

Space Physics · Cross-listed from astro-ph.SR

Turbulence-Driven Corrugation of Collisionless Fast-Magnetosonic Shocks

Immanuel Christopher Jebaraj, Mikhail Malkov, Nicolas Wijsen et al. (+4 more)

Collisionless fast-magnetosonic shocks are often treated as smooth, planar boundaries, yet observations point to organized corrugation of the shock surface. A plausible driver is upstream turbulence. Broadband fluctuations arriving at the front can continually wrinkle it, changing the local shock geometry and, in turn, conditions for particle injection and radiation. We develop a linear-MHD formulation that treats the shock as a moving interface rather than a fixed boundary. In this approach the shock response can be summarized by an effective impedance determined by the Rankine-Hugoniot base state and the shock geometry, while the upstream turbulence enters only through its statistics. This provides a practical mapping from an assumed incident spectrum to the corrugation amplitude, its drift along the surface, and a coherence scale set by weak damping or leakage. The response is largest when the transmitted downstream fast mode propagates nearly parallel to the shock in the shock frame, which produces a Lorentzian-type enhancement controlled by the downstream normal group speed. We examine how compression, plasma $\beta$, and obliquity affect these corrugation properties and discuss implications for fine structure in heliospheric and supernova-remnant shock emission.
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All authors Immanuel Christopher Jebaraj, Mikhail Malkov, Nicolas Wijsen, Jens Pomoell, Vladimir Krasnoselskikh, Nina Dresing, Rami Vainio

Medical Physics

Finite element analysis of very large bone models based on micro-CT scans

Shani Martinez-Weissberg, Will Pazner and Zohar Yosibash

High-resolution voxel-based micro-finite element ($\mu$FE) models derived from $\mu$CT imaging enable detailed investigation of bone mechanics but remain computationally challenging at anatomically relevant scales. This study presents a comprehensive $\mu$FE framework for large-scale biomechanical analysis of an intact New Zealand White (NZW) rabbit femur, integrating advanced segmentation, scalable finite element solvers, and experimental validation using predominantly open-source libraries. Bone geometries were segmented from $\mu$CT data using the MIA clustering algorithm and converted into voxel-based $\mu$FE meshes, which were solved using the open-source MFEM library with algorithms designed for large-scale linear elasticity systems. The numerical solutions were verified by comparing with a commercial finite element solver, and by evaluating the performance of full assembly and element-by-element formulations within MFEM. Models containing over $8\times10^{8}$ DOFs were solved using moderate HPC resources, demonstrating the feasibility of anatomically realistic $\mu$FE simulations at this scale. Resolution effects were investigated by comparing models with voxel sizes of 20, 40, and 80 $\mu$m, revealing that 40 $\mu$m preserves boundary displacement and principal strain distributions with minimal bias while significantly reducing computational cost. Sensitivity analyses further showed that segmentation parameters influence the global mechanical response. Finally, $\mu$FE predictions were coupled with Digital Image Correlation measurements on an NZW rabbit femur under compression to calibrate effective bone material properties at the micron scale. The results demonstrate that large-scale, experimentally informed $\mu$FE modeling can be achieved using open-source tools, providing a robust foundation for preclinical assessment of bone mechanics and treatment-related risks.
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Optics

Achieving high-performance polarization-independent nonreciprocal thermal radiation with pattern-free heterostructures

Bach Do, Bardia Nabavi, Sina Jafari Ghalekohneh et al. (+3 more)

Many advanced energy harvesting technologies rely on advanced control of thermal emission. Recently, it has been shown that the emissivity and absorptivity of thermal emitters can be controlled independently in nonreciprocal emitters. While significant progress has been made in engineering these nonreciprocal thermal emitters, realizing a highly efficient, pattern-free emitter capable of supporting dual-polarization nonreciprocal emission remains a challenging task. Existing solutions are largely based on metamaterials and exhibit polarization-dependent behavior. This work proposes pattern-free multilayer heterostructures combining magneto-optical and magnetic Weyl semimetal materials and systematically evaluates their nonreciprocal emission performance for p- and s-polarized waves. The findings show that omnidirectional polarization-independent nonreciprocity can be achieved utilizing multilayer structures with different magnetization directions that do not follow simple vector summation. To further enhance the performance, Pareto optimization is employed to tune the key design parameters, enabling the maximization of nonreciprocal thermal emission in a given wavelength range. This approach offers a versatile strategy for designing high-performance thermal emitters tailored for multi-objective optical functionalities.
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All authors Bach Do, Bardia Nabavi, Sina Jafari Ghalekohneh, Taiwo Adebiyi, Bo Zhao, Ruda Zhang

Medical Physics

Analytical phase kurtosis of the constant gradient spin echo

Teddy X Cai, Nathan H Williamson and Peter J Basser

The Gaussian phase approximation (GPA) underlies many standard diffusion magnetic resonance (MR) signal models, yet its validity is rarely scrutinized. Here, we assess the validity of the GPA by analytically deriving the excess phase kurtosis $\kappa_4/\kappa_2^2$, where $\kappa_n$ is the $n^{\text{th}}$ cumulant of the accumulated phase distribution due to motion. We consider the signal behavior of the spin echo with constant gradient amplitude $g$ and echo time $T$ in several one-dimensional model systems: (1) a stationary Poisson pore-hopping model with uniform pore spacing $\Delta x$ and mean inter-hop time $\tau_{\text{hop}}$; (2) a trapped-release model in which spin isochromats are initially immobilized and then released with diffusivity $D$ following an exponentially-distributed release time, $\tau_{\text{rel}}$; and (3) restricted diffusion in a domain of length $L$. To our knowledge, this is among the first systematic analytical treatments of spin echo phase kurtosis without assuming Gaussian compartments or infinitesimally short gradient pulses. In the pore-hopping system, $\kappa_4/\kappa^2_2 = (9/5)\tau_{\text{hop}}/T$, inversely proportional to the mean hop number, $T/\tau_{\text{hop}}$. In the trapped-release system, $\kappa_4/\kappa_2^2$ is positive and decreases roughly log-linearly with $T/\langle\tau_{\text{rel}}\rangle$, where $\langle\tau_{\text{rel}}\rangle$ is the average release time. For restriction, $\kappa_4/\kappa_2^2$ vanishes at small and large $L/\sqrt{DT}$, but has complicated intermediate behavior. There is a negative peak at $L/\sqrt{DT}\approx 1.2$ and a positive peak at $L/\sqrt{DT}\approx 4.4$. Monte Carlo simulations are included to validate the analytical findings. Overall, we find that the GPA does not generally hold for these systems under moderate experimental conditions, i.e., $T=10\;\mathrm{ms}$, $g\approx 0.2-0.6\;\mathrm{T/m}$.
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Optics

Mid-Infrared Photothermal Relaxation Intensity Diffraction Tomography for Video-rate Volumetric Chemical Imaging

Danchen Jia, Dashan Dong, Tongyu Li et al. (+5 more)

Three-dimensional molecular imaging of living cells is essential for unraveling cellular metabolism and response to therapies. However, existing volumetric methods, including fluorescence microscopy and quantitative phase imaging, either require fluorescent labels or lack chemical specificity. Mid-infrared (mid-IR) photothermal microscopy provides label-free spectroscopic contrast with sub-micrometer resolution but is limited by slow acquisition rates, precluding 3D live-cell studies. Here, we present a photothermal relaxation intensity diffraction tomography (PRIDT) system that encodes mid-IR absorption induced refractive index change via a photothermal relaxation scheme and recovers it through intensity diffraction tomography. PRIDT achieves video-rate volumetric chemical imaging with up to 15 Hz per wavelength and offers lateral and axial resolutions of 264 nm and 1.12 um over a volumetric field of view of 50x50x10 um3. We showcase high-speed PRIDT imaging of protein and lipid metabolism in ovarian cancer cells and lipid-droplet dynamics in live cells. PRIDT opens new avenues for rapid, quantitative, three-dimensional molecular imaging in living systems.
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All authors Danchen Jia, Dashan Dong, Tongyu Li, Haonan Zong, Jiabei Zhu, Xinyan Teng, Lei Tian, Ji-Xin Cheng

Atomic Physics · Cross-listed from cond-mat.quant-gas

Assembling a Bose-Hubbard superfluid from tweezer-controlled single atoms

William J. Eckner, Theodor Lukin Yelin, Alec Cao et al. (+4 more)

Quantum simulation relies on the preparation and control of low-entropy many-body systems to reveal the behavior of classically intractable models. The development of new approaches for realizing such systems therefore represents a frontier in quantum science. Here we experimentally demonstrate a new protocol for generating ultracold, itinerant many-body states in a tunnel-coupled two-dimensional optical lattice. We do this by adiabatically connecting a near-ground-state-cooled array of up to 50 single strontium-86 atoms with a Bose-Hubbard superfluid. Through comparison with finite-temperature quantum-Monte-Carlo calculations, we estimate that the entropy per particle of the prepared many-body states is approximately $2 k_B$, and that the achieved temperatures are consistent with a significant superfluid fraction. This represents the first time that itinerant many-body systems have been prepared from rearranged atoms, opening the door to bottom-up assembly of a wide range of neutral-atom and molecular systems.
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All authors William J. Eckner, Theodor Lukin Yelin, Alec Cao, Aaron W. Young, Nelson Darkwah Oppong, Lode Pollet, Adam M. Kaufman

Geophysics

A Critical Assessment of PINNs and Operator Learning for Geotechnical Engineering

Krishna Kumar

Scientific machine learning (SciML) offers neural-network alternatives to numerical workflows in geotechnical engineering. This paper benchmarks multi-layer perceptrons (MLPs), physics-informed neural networks (PINNs), deep operator networks (DeepONet), and graph network simulators (GNS) against finite-difference and particle-based references on geotechnical benchmarks, and compares PINN inversion with automatic differentiation (AD) through a conventional solver. We evaluate each method for extrapolation, training, and inference cost, transfer across problem instances, and physics accuracy. An MLP trained on two years of Terzaghi consolidation fits the data, but at year ten predicts ~290 mm with ReLU and ~60 mm with tanh or sigmoid, against a reference of 99.3 mm. A PINN on a damped oscillator with a time domain inside [0,1] matches the closed form within that interval but fails outside, since the residual constrains the fit only where it is sampled. For the 1D wave equation, PINN training is ~96,000 times slower than finite-difference methods and less accurate. DeepONet avoids PINN retraining, yet for the beam on elastic foundation, its training cost equals ~1.8 million finite-difference solves, and inference is slower per query than the direct solver. GNS improves geometric transfer through local particle interactions, though formulations still need trajectories, large training sets, and substantial memory. In the inverse wave benchmark, AD through the finite-difference solver recovers the material profile in seconds with ~1% error. The results support a cautious role for SciML. Neural networks suit interpolation and pattern recognition inside validated domains, while inverse analysis should first try differentiable physics-based solvers when a reliable forward solver exists.
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Accelerator Physics

The sun as colliding beam, betatron cosmic ray factory

Richard M. Talman

A theory of cosmic ray production within the solar system (not extra-galactic) is presented. The sun's time variable magnetic flux linkage makes the sun (as well, perhaps, as Jupiter) a natural, all-purpose, betatron storage ring, with semi-infinite acceptance aperture, capable of storing and accelerating counter-circulating, opposite-sign, colliding beams. The puzzle of how positrons and anti-protons can be well represented at all energies, is explained, initially, by the low energy capture of particles of either sign by the sun's magnetic dipole field. Later, as the magnetic field bending has become negligible compared to the gravitational bending, both positive and negative beams will have survived the gradual transition from predominantly magnetic to predominantly gravitational bending. Later, anti-particles produced in QED beam-beam collisions of sufficiently high energy, are also accelerated. The high quality of cosmic ray data collected over recent decades, at steadily increasing energies, especially by the International Space Station (ISS), make the study of cosmic ray production mechanisms both timely and essential. The paper describes how longitudinal electric fields, explained by the Parker solar wind theory can enable the sun to serve as a “booster” accelerator of cosmic rays, increasing the maximum cosmic ray energies enough to produce the observed 13 orders of magnitude maximum particle energy and the energy flux needed to maintain the observed cosmic ray atmosphere equilibrium within the solar system. A steady state mechanism is described, based on semi-quantitative discussion of a relativistic Hamilton-Jacobi formalism, according to which the highest energy cosmic rays observed can have been produced by the Parker longitudinal electric field component, during fractionally brief, but periodic, circular or semi-circular turns centered on the sun.
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Optics

Impact of Angle Misalignment on the Performance of a combined Optical and millimeter-wave Transceiver enabled by a pair of Optical Harmonically Locked Lasers

Zichuan Zhou, Amany Kassem, Zun Htay et al. (+2 more)

We demonstrated combined free-space optics (FSO) and D-band(110-170GHz) millimeter(mm-wave) transceiver enabled by precisely locked lasers with low phase noise. Combined capacity and tolerance to angle misalignment are studied using 100Gb/s optical and mm-wave signals.
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All authors Zichuan Zhou, Amany Kassem, Zun Htay, Izzat Darwazeh, Zhixin Liu

Physics and Society

Decarbonizing China's private passenger vehicles: A dynamic material flow assessment of metal demands and embodied emissions

Junhong Liu, Nan Zhou, Minda Ma et al. (+1 more)

The continuous growth of China's private passenger vehicle fleet has intensified material demand and embodied carbon emissions, underscoring the need for effective decarbonization pathways. This study develops a transferable, dynamic material flow analysis framework to assess vehicle stocks, metal flows (steel, aluminum, and copper), and embodied emissions from 2000 to 2070, and to quantify the contributions of demand-side and technology-side efficiency measures. The results reveal that: (1) The vehicle fleet is projected to peak at 327-507 million vehicles by mid-century, with new energy vehicles dominating both in-use stocks and end-of-life flows by the 2040s. (2) Cumulative metal demand is projected to reach 1914-2990 million tonnes over the upcoming five decades, with 879-1320 million tonnes supplied from secondary sources under baseline conditions. Technology-oriented measures substantially enhance recycling performance, enabling secondary steel to fully meet manufacturing demand and allowing aluminum and copper cycles to approach near closure by 2070. (3) Correspondingly, cumulative embodied carbon emissions from vehicle metals by 2070 range from 4958 to 9218 megatonnes of carbon dioxide, with technological upgrading reducing emissions by 1051-1619 megatonnes. In collaborative scenarios, demand management accounts for 64.3% of total emission reductions, while technology-oriented measures become increasingly important over the medium to long term. Overall, the findings demonstrate that unmanaged demand growth can substantially offset technological mitigation gains, highlighting the necessity of integrated demand- and technology-oriented strategies. This study provides a systemic and transferable framework to guide circular economy development and deep decarbonization transitions in vehicle fleets in China and other emerging economies.
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All authors Junhong Liu, Nan Zhou, Minda Ma, Kairui You

Optics

From Disorder to Function: Entropy-Engineered Broadband Photonics with Ion-Transport-Stabilized Spectral Fidelity

Yuxiang Xin, Chen-Xin Yu, Jianru Wang et al. (+14 more)

The high-entropy halide-perovskite field has expanded rapidly, yet a key gap remains: configurational entropy is not yet a reliable, designable lever to co-deliver expanded photonic functionality and operational robustness with a composition-transferable mechanistic basis. Here we develop entropy-engineered rare-earth halide double-perovskite single crystals, Cs2Na(Sb, RE)Cl6 (RE3+ = Sc3+, Er3+, Yb3+, Tm3+), that simultaneously expand near-infrared (NIR) functionality and establish a mechanistic stability rule. Near-equiatomic B(III)-site alloying yields a single-phase high-entropy solid solution (Delta_Sconfig about 1.6R). Sb3+ serves as a sensitizer that unifies excitation and cooperatively activates multiple lanthanide channels, transforming the parent single-mode response into a broadband NIR output (~850-1600 nm) with three spectrally orthogonal fingerprint bands at 996, 1220, and 1540 nm. This tri-peak, self-referenced output enables redundancy-based ratiometric solvent identification and quantitative mixture sensing with reduced susceptibility to intensity drift. Accelerated aging under humidity and oxygen shows improved phase and emission stability versus single-component analogues. DFT and molecular dynamics attribute the robustness to strongly suppressed RE$^{3+}$/Cl$^-$ self-diffusion despite comparable H$_2$O/O$_2$ adsorption, kinetically impeding ion-migration-assisted reconstruction and degradation. Integration into a phosphor-converted LED delivers spectrally stable, broadband NIR illumination, establishing entropy engineering as a practical handle to couple expanded photonic functionality with mechanistically accountable durability in metal-halide photonics.
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All authors Yuxiang Xin, Chen-Xin Yu, Jianru Wang, Jianbo Jin, Minliang Lai, Yinan Wang, Shuwen Yan, Gu-wen Chen, Liang Fan, Xiachu Xiao, Yutao Yang, Luying Li, Han Wang, Zhi-Pan Liu, Jiang Tang, Li-Ming Yang, Zhuolei Zhang

Medical Physics

Iterative projected gradient descent for dynamic PET kernel reconstruction

Alan Miranda and Steven Staelens

Dynamic positron emission tomography (PET) reconstruction often presents high noise due to the use of short duration frames to describe the kinetics of the radiotracer. Here we introduce a new method to calculate a kernel matrix to be used in the kernel reconstruction for noise reduction in dynamic PET. We first show that the kernel matrix originally calculated using a U-net neural network (DeepKernel) can be calculated more efficiently using projected gradient descent (PGDK), with several orders of magnitude faster calculation time for 3D images. Then, using the PGDK formulation, we developed an iterative method (itePGDK) to calculate the kernel matrix without the need of high quality composite priors, instead using the noisy dynamic PET image for calculation of the kernel matrix. In itePGDK, both the kernel matrix and the high quality reference image are iteratively calculated using PGDK. We performed 2D simulations and real 3D mouse whole body scans to compare itePGDK with DeepKernel and PGDK. Brain parametric maps of cerebral blood flow and non-displaceable binding potential were also calculated in 3D images. Performance in terms of bias-variance tradeoff, mean squared error, and parametric maps standard error, was similar between PGDK and DeepKernel, while itePGDK outperformed these methods in these metrics. Particularly in short duration frames, itePGDK presents less bias and less artifacts in fast kinetics organs uptake compared with DeepKernel. itePGDK eliminates the need to define composite frames in the kernel method, producing images and parametric maps with improved quality compared with deep learning methods.
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Instrumentation and Detectors

Fast reconstruction-based ROI triggering via anomaly detection in the CYGNO optical TPC

F. D. Amaro, R. Antonietti, E. Baracchini et al. (+41 more)

Optical-readout Time Projection Chambers (TPCs) produce megapixel-scale images whose fine-grained topological information is essential for rare-event searches, but whose size challenges real-time data selection. We present an unsupervised, reconstruction-based anomaly-detection strategy for fast Region-of-Interest (ROI) extraction that operates directly on minimally processed camera frames. A convolutional autoencoder trained exclusively on pedestal images learns the detector noise morphology without labels, simulation, or fine-grained calibration. Applied to standard data-taking frames, localized reconstruction residuals identify particle-induced structures, from which compact ROIs are extracted via thresholding and spatial clustering. Using real data from the CYGNO optical TPC prototype, we compare two pedestal-trained autoencoder configurations that differ only in their training objective, enabling a controlled study of its impact. The best configuration retains (93.0 +/- 0.2)% of reconstructed signal intensity while discarding (97.8 +/- 0.1)% of the image area, with an inference time of approximately 25 ms per frame on a consumer GPU. The results demonstrate that careful design of the training objective is critical for effective reconstruction-based anomaly detection and that pedestal-trained autoencoders provide a transparent and detector-agnostic baseline for online data reduction in optical TPCs.
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All authors F. D. Amaro, R. Antonietti, E. Baracchini, L. Benussi, C. Capoccia, M. Caponero, L. G. M. de Carvalho, G. Cavoto, I. A. Costa, A. Croce, M. D'Astolfo, G. D'Imperio, G. Dho, E. Di Marco, J. M. F. dos Santos, D. Fiorina, F. Iacoangeli, Z. Islam, E. Kemp, H. P. Lima Jr., G. Maccarrone, R. D. P. Mano, D. J. G. Marques, G. Mazzitelli, P. Meloni, A. Messina, V. Monno, C. M. B. Monteiro, R. A. Nobrega, G. M. Oppedisano, I. F. Pains, E. Paoletti, F. Petrucci, S. Piacentini, D. Pierluigi, D. Pinci, F. Renga, A. Russo, G. Saviano, P. A. O. C. Silva, N. J. Spooner, R. Tesauro, S. Tomassini, D. Tozzi

Applied Physics · Cross-listed from quant-ph

Using NV centers in diamond to detect DC to very-low frequency magnetic fields

Valts Krumins, Ivars Krastins, Oskars Rudzitis et al. (+3 more)

In this work we present a compact and portable tabletop magnetometer that utilizes negatively charged nitrogen-vacancy (NV) centers in diamond. The magnetometer is operated using a dual microwave resonance detection approach in combination with an optically detected magnetic resonance (ODMR) technique (mitigating drifts in results due to changes of the diamond temperature), capable of simultaneously exciting and registering two ODMR transitions. The experimentally measured magnetic field noise-floor is $\approx 2.3~\textrm{nT}\sqrt{\textrm{Hz}}$ while the calculated shot-noise-limited magnetic field sensitivity is $\approx 585~\textrm{pT}\sqrt{\textrm{Hz}}$ when excited with a continuous wave laser at 0.5~W. These results pave the way for realizing a simple set-up magnetometer for precise single axis magnetic field measurements for example for accurate electric current measurements for stabilization purposes and magnetic communication applications.
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All authors Valts Krumins, Ivars Krastins, Oskars Rudzitis, Reinis Lazda, Florian Gahbauer, Marcis Auzinsh

Physics and Society

Strategic Network Abandonment

Sandro Claudio Lera and Andreas Haupt

Socio-economic networks, from cities and firms to collaborative projects, often appear resilient for long periods before experiencing rapid, cascading decline as participation erodes. We explain such dynamics through a framework of strategic network abandonment, in which interconnected agents choose activity levels in a network game and remain active only if participation yields higher utility than an improving outside option. As outside opportunities rise, agents exit endogenously, triggering equilibrium readjustments that may either dissipate locally or propagate through the network. The resulting decay dynamics are governed by the strength of strategic complementarities, measuring how strongly an agent's incentives depend on the actions of others. When complementarities are weak, decay follows a heterogeneous threshold process analogous to bootstrap percolation: failures are driven by local neighborhoods, vulnerable clusters can be identified ex ante, and large cascades emerge only through bottom-up accumulation of fragility. When complementarities are strong, departures propagate globally, producing rupture-like dynamics characterized by metastable plateaus, abrupt system-wide collapse, and limited predictive power of standard spectral or structural indicators. The comparative effective of intervention depends on the strength of complementarity as well: Supporting central agents is most effective under strong complementarities, whereas targeting marginal agents is essential when complementarities are weak. Together, our results reveal how outside options, network structure, and strategic interdependence jointly determine both the fragility of socio-economic networks and the policies required to sustain them.
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Medical Physics

First Positronium Lifetime Imaging using $^{52}$Mn and $^{55}$Co with a plastic-based PET scanner

Manish Das, Sushil Sharma, Ermias Yitayew Beyene et al. (+45 more)

Positronium Lifetime Imaging (PLI) extends positron emission tomography by using the lifetime of positronium atoms as a probe of tissue molecular architecture. In this work, we report the first PLI measurements performed with $^{52}$Mn and $^{55}$Co using the modular J-PET. Four samples were studied in each experiment: two Certified Reference Materials (polycarbonate and fused silica) and two human tissues (cardiac myxoma and adipose). The selection of PLI events was based on the registration of two 511~keV annihilation photons and one prompt gamma in triple coincidence. From the resulting lifetime spectra we extracted the mean ortho-positronium lifetime $\tau_{\text{oPs}}$ and the mean positron lifetime $\Delta T_{\text{mean}}$ for each sample. The measured values of $\tau_{\text{oPs}}$ in polycarbonate using both isotopes matches well with the certified reference values. Furthermore, $^{55}$Co reproduced identical results for fused-silica measurements at their respective uncertainty levels. In contrast, measurements with $^{52}$Mn in fused silica show a minor deviation, which could be caused by the Parafilm spacer. In myxoma and adipose tissue, the reduced $\tau_{\text{oPs}}$ values are mainly linked to the long storage history of the samples rather than to the choice of isotope. Comparing peak-to-background ratios and spectral purity, $^{55}$Co provides cleaner PLI data under the same experimental conditions. Although $^{52}$Mn offers a longer half-life and a multi gamma cascade enhancing $\beta^{+}$ + $\gamma$ coincidences, but at the expense of higher background. In this study, we demonstrate that the applied selection criteria on the data measured with the modular J-PET can be used for PLI studies even with radionuclides with complex decay patterns.
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All authors Manish Das, Sushil Sharma, Ermias Yitayew Beyene, Aleksander Bilewicz, Jarosław Choiński, Neha Chug, Catalina Curceanu, Eryk Czerwiński, Jakub Hajduga, Sharareh Jalali, Krzysztof Kacprzak, Tevfik Kaplanoglu, Łukasz Kapłon, Kamila Kasperska, Aleksander Khreptak, Grzegorz Korcyl, Tomasz Kozik, Karol Kubat, Deepak Kumar, Sumit Kumar Kundu, Anoop Kunimmal Venadan, Edward Lisowski, Filip Lisowski, Justyna Medrala-Sowa, Simbarashe Moyo, Wiktor Mryka, Szymon Niedźwiecki, Anand Pandey, Piyush Pandey, Szymon Parzych, Alessio Porcelli, Bartłomiej Rachwał, Martin Rädler, Narendra Rathod, Noman Razzaq, Axel Rominger, Kuangyu Shi, Magdalena Skurzok, Maciej Słotwiński, Anna Stolarz, Tomasz Szumlak, Pooja Tanty, Keyvan Tayefi Ardebili, Satyam Tiwari, Kavya Valsan Eliyan, Rafał Walczak, Ewa Ł. Stępień, Paweł Moskal

Fluid Dynamics

Hovering efficiency optimization of the cycloidal propeller with end plates

Han Zhen Li, Yu Hu, Lai Zhang et al. (+2 more)

Cycloidal propellers are known for their omnidirectional vectored thrust, enabling smooth transitions between hovering and forward flight, making them ideal for unmanned aerial vehicles (UAVs) and electric vertical take-off and landing (eVTOL) aircraft. However, cycloidal propellers tend to have lower hovering efficiency compared to screw propellers. Adding end plates to the blade tips can enhance hovering efficiency by reducing blade tip vortices. But the impact of these end plates and the optimal design for cycloidal propellers incorporating them have not been thoroughly studied. This paper seeks to optimize hovering efficiency and develop design theories for cycloidal propellers with end plates. Extensive force measurement experiments are conducted to identify designs with optimal hovering efficiency. The sliding mesh technique is employed to solve the unsteady Reynolds-averaged Navier-Stokes (URANS) equations for a detailed analysis. Experimental results indicate that the designs with end plates generally achieve significantly better hovering efficiency than those without end plates. End plates help to maintain hovering efficiency, even though the blade aspect ratio is as small as 1.5. The designs with stationary end plates are superior to those with rotating end plates because rotation introduces additional torque caused by the friction force. Designs featuring thick end plates outperform those with thin end plates, as the rounded edges can eliminate end plate vortices. The best design features stationary thick end plates, a chord-to-radius ratio of 0.65, and a large pitching amplitude of 40 degrees. It achieves a hovering efficiency of 0.72 with a blade aspect ratio of 3, which is comparable to that of helicopters. In contrast, for the cases without end plates, the highest hovering efficiency is merely 0.54.
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All authors Han Zhen Li, Yu Hu, Lai Zhang, Hong Bo Sun, Xu Chao Zhang