Peer Revenue Publish or profit

Papers

Fresh from arXiv, typeset properly. Highlighted words trade on the market.

Physics Physics

physics Watch Physics

Saturday 16 May

Classical Physics

Variational Openness

Francisco Monroy

Variational principles in mechanics, field theory and geometric analysis are usually formulated on closed admissible classes, where boundary variations are either fixed or independently cancelled through natural boundary conditions. Variational openness is formulated here as a conservative extension of this setting. Its central premise is that stationarity requires cancellation of the total first variation, not necessarily separate cancellation of bulk and boundary contributions. Separate Euler–Lagrange and boundary equations arise only when admissible variations are independently localizable. Two regimes are distinguished. In separable open systems, bulk and boundary variations remain independently testable, and stationarity yields the usual interior equation together with an open boundary balance. In regulated open systems, admissible variations form a graph subspace in which bulk and boundary displacements are linked by a compatibility operator. Stationarity then becomes a projected balance on the admissible exchange space, allowing nontrivial bulk–boundary action exchange before total cancellation occurs. At second order, the open action defines a closed quadratic form on the admissible graph space. For pressure-like boundary couplings, the open Hessian is obtained by subtracting from the stabilizing geometric form a boundary-pressure form pulled back through the compatibility operator. A Rayleigh–Ritz criterion then yields a critical threshold at which positivity and coercivity are lost. A minimal spherical example illustrates the corresponding regulated spectral shift. The framework contains fixed-boundary, natural-boundary and classical free-boundary problems as limiting cases, while extending stationarity to regulated bulk–boundary exchange classes.
Read the full abstract

Optics · Cross-listed from quant-ph

Quantum Optical Soliton Dynamics Beyond Linearization: An Open-System Approach

Chris Gustin, Ryotatsu Yanagimoto, Edwin Ng et al. (+1 more)

We introduce two approaches to modeling the quantum dynamics of optical $\chi^{(3)}$ solitons. Taking an open-system viewpoint, we project the underlying quantum field into system (soliton) and residual reservoir components. The reservoir is treated as either (i) a discrete “Lanczos supermode” (LSM) expansion which localizes dynamics to a few-supermode basis, or (ii) a non-local environment which can be traced out by deriving a Markovian master equation (ME). Using these methods, we analyze and identify the quantum structure of both the soliton's stability and its hierarchy of perturbations. Through numerical simulations, we confirm both methods effectively capture quantum-induced soliton phase shifts in a concise few-mode (single-mode for ME) basis, and the LSM approach also captures photon loss which arises from non-Markovian dispersive couplings. As neither method is limited to the linearized regime, our approaches provide powerful computational tools to analyze complex non-Gaussian quantum dynamics of solitons where other commonly-used methods fail, providing insight into such non-perturbative regimes. We also investigate radiation that occurs in the presence of higher-order dispersion with ultrashort pulses, deriving a ME that predicts photon loss consistent with classical theory, but find that both classical and ME theory dramatically underestimate the actual amount of dissipation, which we explain in terms of dispersive coupling-induced soliton broadening.
Read the full abstract

All authors Chris Gustin, Ryotatsu Yanagimoto, Edwin Ng, Hideo Mabuchi

Optics

Supercollimating photonic crystal scintillators

Seou Choi, Sachin Vaidya, Charles Roques-Carmes et al. (+1 more)

Scintillators convert X-ray energy into visible or near-visible photons, enabling applications in high-energy particle detection and X-ray imaging. Increasing scintillator thickness improves X-ray absorption but degrades spatial resolution due to diffraction-induced lateral spreading of emitted light, resulting in a fundamental trade-off between detection efficiency and image resolution. Here, we propose a class of three-dimensional photonic crystal scintillators that overcomes this limitation through supercollimation, in which light propagates with suppressed diffraction. We develop a multiscale modeling framework that integrates nanophotonic band-structure simulations with Monte Carlo particle transport to quantitatively evaluate the performance of such scintillators. Our results show that supercollimating photonic crystal scintillators can enhance spatial resolution by up to an order of magnitude relative to conventional bulk scintillators of equal thickness. This improvement leads to a substantial increase in detector quantum efficiency (DQE), particularly at high spatial frequencies, enabling fine features to be preserved at reduced X-ray dose. We further demonstrate that comparable image quality can be achieved with approximately an order-of-magnitude lower X-ray dose. By directly engineering light transport within the bulk of the scintillator, this work establishes a nanophotonic route to simultaneously improving resolution and dose efficiency in X-ray imaging.
Read the full abstract

All authors Seou Choi, Sachin Vaidya, Charles Roques-Carmes, Marin Soljačić

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

Simulation study of the cosmic ray Sun shadow with a time-dependent solar magnetic field model

Jie Xia, Ming-Yang Cui, Qiang Yuan et al. (+3 more)

During the propagation of cosmic rays in the solar system, the Sun will block those particles and form a shadow whose position and depth are very important probe of the magnetic fields in the Sun's corona, in the interplanetary space, and the Earth's vicinity. In this work we carry out Monte Carlo studies of the Sun shadow, with a novel approach to take into account daily variations of the coronal and interplanetary magnetic field models. This treatment is suitable for studies of short-term variations of the Sun shadow, which become detectable by the Large High Altitude Air Shower Observatory (LHAASO) experiment. Two different coronal magnetic field models, the Potential Field Source Surface (PFSS) and Current Sheet Source Surface (CSSS) models, with observational time-varying photospheric magnetic fields as boundary conditions, are studied in this work. The interplanetary magnetic fields are then derived using the Parker spiral model based on the coronal ones. Furthermore, both the coronal and interplanetary magnetic field strengths are corrected using the Parker Solar Probe (PSP) measurements. We compare the simulation results with the daily observations of Sun shadow by LHAASO in 2021, and find that the CSSS model generally shows better consistency of the displacement of the Sun shadow than the PFSS model.
Read the full abstract

All authors Jie Xia, Ming-Yang Cui, Qiang Yuan, Yi Zhang, Guang-Lu Shi, Li Feng

Computational Physics · Cross-listed from cond-mat.str-el

Static spin exchange-correlation kernel of the uniform electron gas at finite temperature

Pengcheng Hou, Zhiyi Li, Youjin Deng et al. (+1 more)

We determine the temperature and momentum dependence of the static spin exchange–correlation kernel of the unpolarized three-dimensional uniform electron gas using variational diagrammatic Monte Carlo. The calculations cover metallic densities with Wigner–Seitz radii $r_s=1\!-\!4$ and temperatures $T/T_F=1/16\!-\!8$, where $T_F$ is the Fermi temperature. At low temperature, the calculated kernel approaches established ground-state parametrizations. Heating suppresses its Fermi-scale minimum and reduces its magnitude, while the relative momentum dependence evolves nonmonotonically through the warm-dense crossover. At the two highest temperatures studied, the spin kernel is nearly constant over $q \leq 2k_F$, where $k_F$ is the Fermi wave number. The charge kernel at $r_s=1$ retains pronounced momentum dependence under the same conditions, making a local approximation to the XC kernel more accurate in the spin channel over this interval. The directly sampled uniform response determines the XC free-energy curvature with respect to spin polarization, independently of a fitted polarization dependence. This curvature sets the interaction contribution to the free-energy cost of weak polarization and differs by several percent from the Groth–Dornheim–Bonitz parametrization at elevated temperatures. These results provide momentum-resolved reference data for finite-temperature spin-response theories and direct constraints on the spin dependence of thermal free-energy functionals.
Read the full abstract

All authors Pengcheng Hou, Zhiyi Li, Youjin Deng, Kun Chen

Physics and Society

Editorial Trajectories in Wikipedia Reflect Underlying Hyperlink Structure

Yeonji Seo, Mi Jin Lee, Seung-Woo Son et al. (+2 more)

Wikipedia hyperlinks have primarily been studied as navigational tools for readers, but their role in how information providers move between articles during editing remains less explored. Here, we combine the hyperlink network among English Wikipedia articles with editorial histories to examine how article-to-article structure is associated with editors' transitions between articles. We first address the temporal aspect of edit transitions by showing that transitions between hyperlinked article pairs have shorter inter-event times (IETs) than those between non-hyperlinked pairs, indicating that connected articles are effectively closer in editing sequences. We then turn to the structural organization of editing behavior by coarse-graining the hyperlink network into 19 topical communities and measuring editors' topical diversity. Finally, we bring the temporal and structural views together by comparing each editor's transition network with the corresponding hyperlink subnetwork using Jaccard similarity. Combining the measures allows us to distinguish three editor types: 'Specialists' are characterized by focused editing within limited topical domains and transition patterns more closely aligned with the hyperlink structure (low topical diversity, shorter mean IETs, and higher Jaccard similarity), whereas 'generalists' cover broader topics and show weaker similarity to the hyperlink structure (high topical diversity, longer mean IETs, and lower Jaccard similarity). 'Bots' show a distinct algorithm-driven behavior, with low Jaccard similarity and the shortest mean IETs, a combination departing from human-editor patterns despite their often high topical diversity. Such findings demonstrate that the hyperlink structure is not just a static scaffold for reader navigation, but is observationally linked to the sequential organization of editorial activity in collaborative knowledge systems.
Read the full abstract

All authors Yeonji Seo, Mi Jin Lee, Seung-Woo Son, Hang-Hyun Jo, Yohsuke Murase

Instrumentation and Detectors

Photoluminescence of resin-based solder flux residue under ultraviolet excitation from 120 nm to 310 nm

Anna Hurhina, Marjolein Troost, Andreas Leonhardt et al. (+1 more)

Nuisance photoluminescence is a potential source of background in particle detectors that use noble liquids as target material for galactic dark matter particles and neutrinos. Liquid argon and xenon scintillate in the vacuum ultraviolet (VUV) wavelength range in response to particle interactions. Photoluminescent materials that absorb these photons can cause unexpected signals that may impede event reconstruction in these detectors. We illuminated residue from different types of commercial solder flux commonly used in liquid xenon detectors with ultraviolet and VUV light and measured their photoluminescence spectra and intensities. We find that all tested flux residues photoluminesce in the visible spectral region when exposed to VUV light.
Read the full abstract

All authors Anna Hurhina, Marjolein Troost, Andreas Leonhardt, Tina R. Pollmann

Optics

Dispersion-Engineered Terahertz Silicon Interconnects Enabling Terabit-Scale Data Links

Bodhan Chakraborty, Wenhao Wang, Nikhil Navaratna et al. (+5 more)

The rapid growth of artificial intelligence (AI) and data-centric computing is driving exabyte-scale data transfer, pushing conventional interconnect technologies toward fundamental bandwidth and energy limits. Although optical interconnects provide high-capacity and long-reach communication, their complexity and energy overhead limit scalability in short-reach chiplet-based and on-chip systems. Terahertz (THz) silicon interconnects offer a promising alternative by bridging electronics and photonics in compact, complementary metal-oxide-semiconductor (CMOS)-compatible platforms capable of high bandwidth and low latency. However, practical THz interconnects require simultaneous multi-band operation, dual-polarization support, low propagation loss, low group-velocity dispersion (GVD), and terabit-per-second throughput, while avoiding Bragg-induced stopbands and dispersion penalties at high frequencies. Here, we demonstrate a CMOS-compatible, centimetre-scale, multi-band on-chip THz data link achieving an aggregate throughput of 1.004 Tbps. The performance is enabled by suppressing Bragg-induced stopbands using dispersion-engineered, effective-medium-supported unclad silicon waveguides, resulting in flat transmission and low-ripple group delay across multiple THz bands. The waveguide platform operates from 220 to 500 GHz and supports both transverse-electric (TE) and transverse-magnetic (TM) polarizations with low path loss, low bending loss, and low GVD. Fourteen channels in a straight waveguide and twelve channels in a 90$^\circ$ bend achieve aggregate data rates of 1.004 Tbps and 0.895 Tbps, respectively, with GVD as low as 0.15 ps$^2$/mm over the full operating band. These results establish a scalable and energy-efficient THz interconnect platform for high-density on-chip and chip-to-chip communication fabrics targeting next-generation AI systems and emerging 6G technologies.
Read the full abstract

All authors Bodhan Chakraborty, Wenhao Wang, Nikhil Navaratna, Thomas Caiwei Tan, Pascal Szriftgiser, Hadjer Nihel Khelil, Guillaume Ducournau, Ranjan Singh

Instrumentation and Detectors

An Optical System for Monitoring Coil Parasitic Motion and Mass Position for Tsinghua Tabletop Kibble Balance

Weibo Liu, Kang Ma, Nanjia Li et al. (+3 more)

This paper presents a novel seven-channel optical measurement system for monitoring coil parasitic motion and mass position in the Tsinghua Tabletop Kibble balance. The system employs seven spectrally-confocal displacement sensors arranged in a distributed configuration to simultaneously measure the coil's translational ($x_{\rm{c}}, y_{\rm{c}}$), rotational ($\theta_x,\theta_y$) degrees of freedom, and the mass position offset ($x_{\rm{m}}, y_{\rm{m}}$) due to corner errors. Three vertically oriented sensors target an equilateral triangle target rigidly connected to the coil, enabling real-time calculation of tilt angles through geometric relationships. Two horizontally oriented sensors measure the translational displacement of a frame target on the coil assembly. Two additional horizontal sensors monitor the mass position to quantify corner errors. The initial experimental setup has been completed, featuring sufficient resolution and minimal signal loss, providing a new approach for alignment adjustment and corner error compensation in high-precision Kibble balances.
Read the full abstract

All authors Weibo Liu, Kang Ma, Nanjia Li, Wei Zhao, Songling Huang, Shisong Li

Instrumentation and Detectors

Design and Verification of a New Current Source for Tsinghua Tabletop Kibble Balance

Yuhan Ma, Kang Ma, Wei Zhao et al. (+3 more)

This paper presents an ultra-stable current source tailored for the one-mode, two-phase (OMTP) measurement scheme in Tsinghua tabletop Kibble balances. To achieve simultaneous high resolution and nA/A-level stability, a composite 'coarse-fine' control topology is proposed, utilizing a dual-DAC architecture and an active digital feedback loop. Experimental results show that the Allan deviation reaches 1 nA/A at an integration time of approximately 3 minutes, representing a tenfold improvement in measurement speed compared to commercial-source-based setups. Furthermore, the design offers a significant cost advantage, providing a satisfying option for high-precision, cost-effective mass realization.
Read the full abstract

All authors Yuhan Ma, Kang Ma, Wei Zhao, Lisha Peng, Songling Huang, Shisong Li

Plasma Physics

Critical velocity-space mode scalings in linear and nonlinear Landau damping for the Vlasov–Poisson system

Noah K. Guberman, J. Coughlin and A. S. Joglekar

The velocity-space resolution required to accurately simulate kinetic phenomena in the 1D-1V Vlasov–Poisson system is generally not known a priori. In this work, we determine the upper bound on the resolution requirement for linear and nonlinear Landau damping mediated by collisional diffusion, deriving analytical scalings for the critical Fourier and Hermite velocity-space mode numbers using a unified cascade-balance argument. The resulting scalings depend on the bounce frequency $\omega_b$, wavenumber $k\lambda_D$, and electron-electron collisional frequency $\nu$. We validate these predictions against an ensemble of 800 Vlasov–Fokker–Planck simulations, finding strong agreement with the predicted $\omega_b$ and $\nu$ dependencies.
Read the full abstract

Geophysics

Pretrain-to-alignment learning paradigm to improve geophysical AI applicability under scarce field labels and synthetic-to-field gaps: A case study of relative geologic time estimation in global shelf-edge clinothems

Hui Gao, Xinming Wu, Jiarun Yang et al. (+2 more)

Artificial intelligence (AI) has been increasingly applied to various geophysical scenarios, yet its practical deployment remains limited by scarce field labels, pronounced synthetic-to-field domain gaps, and insufficient physical consistency under complex and variable field conditions. To address these challenges, we propose a pretrain-to-alignment learning paradigm that systematically integrates self-supervised pretraining, synthetic supervision, prior-driven refinement, and domain-adaptation fine-tuning into a unified progressive learning workflow. In this paradigm, geophysical AI models are developed through sequential stages that progressively build field-relevant representations, task-specific mapping capability, field consistency, and target-specific adaptability. We validate this paradigm using cross-survey relative geologic time (RGT) estimation in global shelf-edge clinothems as a representative case study. Results from 3,000 field datasets spanning multiple sedimentary basins demonstrate that the proposed paradigm achieves accurate, robust, and well-generalized performance across diverse field surveys, while significantly improving fine-scale stratigraphic and structural details. More broadly, this study provides a practical methodological reference for a broader range of geophysical AI tasks, such as interpretation, regression, and inversion problems.
Read the full abstract

All authors Hui Gao, Xinming Wu, Jiarun Yang, Zhixiang Gao, Yimin Dou

Optics

Transient Gas-Dynamics Filamentation of High-PowerFemtosecond Laser Pulse in Compressed Argon

Yu.E. Geints, P.V. Babushkin, A.M. Kabanov et al. (+2 more)

We have experimentally investigated the spectral characteristics and spatial structure of femtosecond pulses from a titanium:sapphire laser during filamentation in an optical cell filled with argon at pressures up to 40 atm under pressure shock-drop conditions. This leads to the development of strong jet flows and vortex gas turbulence, which in turn triggers the early onset of multiple filamentation of the optical pulse and largescale broadening of its spectrum throughout the entire duration of the pressure drop. The magnitude of this spectrum broadening can reach 80 nm and is proportional to the initial gas pressure. Using computational fluid dynamics simulations, we studied the dynamics of the emergence, development, and relaxation of stimulated turbulence in compressed gas in the region of the cell outlet valve and assessed the effect it exerts on the propagating femtosecond pulse. The revealed regularities may serve as the basis for developing an effective method of controlling the spectrum of supercontinuum radiation via filamentation of highpower ultrashort laser pulses in gas cells under shock pressure release and rise conditions.
Read the full abstract

All authors Yu.E. Geints, P.V. Babushkin, A.M. Kabanov, V.K. Oshlakov, E.E. Khoroshaeva

Medical Physics

Topological structure of radiation-induced DNA damage encodes coupled LET-oxygen signatures

Renato III Fernan Bolo and Ramon Jose C. Bagunu

We present the first nuclear-scale persistent homology and Random Forest classification analysis of radiation-induced DNA double-strand break (DSB) topology across the clinical particle therapy range. Using TOPAS-nBio and the Voxel-Aware Oxygen model, we generated 2,450 simulated nuclei across 49 conditions (seven particle configurations, 0.2–70.7~keV/\textmu{}m; seven oxygen levels, 0.005–21%~O$_2$) and extracted a 107-feature matrix across seven modalities. DSB topology encodes particle identity, Spread-Out Bragg Peak (SOBP) position, and oxygen tension in a three-tier hierarchy, with fidelity at each tier governed by the physical mechanism controlling it. Particle identity and SOBP position are exactly decodable (balanced accuracy = 1.000). Oxygen-level classification degrades monotonically with LET from 0.517 (electrons) to 0.189 (carbon distal SOBP), with a charge-driven non-monotonicity at the helium-to-carbon transition confirming that atomic number, not LET alone, governs topological discriminability. The joint 49-class task achieves balanced accuracy 0.346, seventeen times above chance. Per-class recall peaks universally at 0.5%~O$_2$ (0.788–0.976 across all configurations), which is consistent with the OER curve inflection. Topological Summaries (persistent entropy, landscape integrals) dominate oxygen encoding at all LET ($\eta^2_{O_2} =\,$0.300–0.622). A partial-out test reveals two mechanistically separable channels: a count-mediated scale signal ($\eta^2_{O_2}$ survival ratio 0.062) and a count-independent shape signal preserved or enhanced in five of seven configurations (balanced accuracy survival ratio 1.011). Persistent entropy and landscape integrals, as novel radiobiological observables, provide a computational basis for characterizing oxygen-dependent damage topology in hypoxic tumor treatment planning.
Read the full abstract

Plasma Physics

FIRM3D: Fast ion reduced models in 3D

Elizabeth Paul, Alexey Knyazev, Michael Czekanski et al. (+4 more)

The dynamics of energetic particle (EP) species, born from fusion reactions or plasma heating schemes, are critical for predicting the behavior of magnetic confinement fusion experiments and future fusion reactors. Because energetic particles are largely collisionless, the orbits of Monte Carlo samples drawn from a given distribution function can be efficiently integrated in prescribed electromagnetic fields. In addition to the static magneto-hydrodynamic (MHD) equilibrium fields produced by the electromagnetic coils of a fusion device, MHD waves can be excited by – and resonantly transport – energetic particle populations. FIRM3D is an open-source Python/C++/CUDA software suite for modeling energetic particle dynamics in 3D magnetic fields, available at https://github.com/ColumbiaStellaratorTheory/firm3d. The core guiding-center integration routines grew out of SIMSOPT (Landreman et al., 2021), but have been extended to include additional physics and diagnostics not typically required in the stellarator optimization context. This standalone framework enables focused development of energetic particle physics capabilities with minimal dependencies, making it accessible to the broader stellarator and plasma physics community. Components of FIRM3D include interfaces with MHD equilibrium and wave stability software (BOOZ_XFORM, AE3D, FAR3D); CPU and GPU parallelized integration of the guiding center orbit equation, with symplectic and Runge-Kutta integrator options; and orbit visualization and transport diagnostics, including Poincare maps, orbit classification, and weighted Birkhoff averaging.
Read the full abstract

All authors Elizabeth Paul, Alexey Knyazev, Michael Czekanski, Alexandra Lachmann, Abdullah Hyder, Christopher Albert, Matt Landreman

Fluid Dynamics · Cross-listed from cond-mat.soft

Hydrodynamic cascade drives tumbling in sheared colloidal rod suspensions

Lucas H. P. Cunha, Paul F. Salipante, Peter D. Olmsted et al. (+1 more)

Modeling the dynamics of colloidal rods remains a central challenge in soft-matter physics due to the anisotropic and long-ranged nature of their interactions. Hydrodynamic interactions in rods suspensions are often assumed to be screened or too week to play any role in semi-dilute regimes, yet we find here these assumptions to break down at shear rates and concentrations that are often attained in experiments. Using particle-based simulations and scaling analysis, we uncover a cascade of tumbling events driven by hydrodynamic coupling among neighboring rods. This collective dynamics disrupts flow alignment and leads to a pronounced increase in viscosity and normal stress differences, in qualitative agreement with recent experiments. The discovery of this hydrodynamically-promoted cascade effect calls for a revision of existing constitutive models for colloidal rods and highlights hydrodynamic coupling as a key mechanism governing collective dynamics in highly anisotropic suspensions.
Read the full abstract

All authors Lucas H. P. Cunha, Paul F. Salipante, Peter D. Olmsted, Steven D. Hudson

Physics and Society

Universal Dynamics of Punctuated Progress

Yian Yin and Dashun Wang

Scientific and technological frontiers advance through punctuated dynamics, yet the principles governing these dynamics remain poorly understood. Here we collect and analyze datasets tracking the evolution of frontiers across 9 different domains, spanning materials discovery, structural biology, AI, computational biomedicine, data science, theoretical computer science, Formula-1 racing, and physical wheel building. Analyzing 6.8M solutions to 6.7K tasks, we uncover three universal patterns: (1) waiting times between new frontiers are heavy-tailed, with most attempts concentrated in long stasis; (2) frontier records accumulate at a sublinear rate, faster than logarithmic yet slower than linear growth; (3) record-breaking events are temporally correlated, generating short-term predictability yet long-term unpredictability. Despite the differences in the scale, scope, and definition of the settings, these patterns are remarkably consistent across all domains we study, and are not captured by models from complex systems, record statistics, economics of innovation, and cultural evolution. We trace the missing ingredient to the distinction between radical and incremental innovation, and develop a minimal, analytically solvable model incorporating both radical resets that restructure what is achievable and incremental refinements that exploit the current frontier. The simple model reproduces all three empirical regularities. Remarkably, the leading-order predictions are parameter-independent, identifying a new universality class governing punctuated progress and yielding testable predictions about how openness and access to frontier solutions shape the pace of advance. Overall, these results reveal universal dynamics governing punctuated progress and identify the interplay between radical resets and incremental refinements as the key driver of how scientific and technological frontiers advance.
Read the full abstract

Geophysics

Radial-Component Predominant-Mode Inversion of Rayleigh Waves: Application to DAS-based Site Characterization

Mrinal Bhaumik and Brady R. Cox

Distributed Acoustic Sensing (DAS) has emerged as a transformative technology for near-surface site characterization. When a vertical source is activated along the fiber, DAS measures only the in-line (radial) component of Rayleigh-wave motion. Dispersion data extracted from radial-component waveforms may differ from those obtained from vertical-component measurements, particularly under complex stratigraphic conditions. Hence, a component-consistent forward problem is desired when inverting radial-component DAS dispersion data to retrieve accurate shear wave velocity (Vs) profiles. This study presents a radial-component predominant-mode (RCPM) inversion framework designed for DAS-based surface-wave analysis that explicitly accounts for source-receiver directivity and modal sensitivity of the Rayleigh-wave radial component. The proposed approach matches measured dominant radial dispersion trends with the theoretical mode exhibiting the maximum modal participation. As a result, the RCPM framework eliminates the need for explicit modal indexing, provides a component-consistent interpretation of radial-component dispersion data, and substantially reduces reliance on subjective analyst-driven modal interpretations. The RCPM approach is systematically evaluated using three synthetic ground models and two field DAS datasets. The synthetic results demonstrate that modal energy distribution differs significantly between vertical and radial components in the presence of strong velocity contrasts and velocity reversals, and that conventional inversion approaches may misinterpret modal behavior, resulting in less accurate Vs profiles. In contrast, the RCPM method consistently captures the correct modal response and yields reliable Vs profiles. Application to two field DAS datasets further demonstrates good agreement between the inverted Vs profiles and independent invasive borehole measurements.
Read the full abstract

Friday 15 May

Applied Physics

Efficient dispersal of submicron solid particles for stratospheric aerosol injection

Yair Segev, Eitan Y. Levine, Yair Bar-Yoseph et al. (+8 more)

Stratospheric aerosol injection (SAI) using solid particles has been proposed as an alternative to sulfate aerosols for solar radiation modification, but practical deployment faces challenges in efficiently deagglomerating and dispersing powders as submicron particles. Here we experimentally demonstrate pneumatic dispersal of particles in optically optimal size ranges for SAI. Using spherical amorphous silica particles, we find that applying a hydrophobic surface treatment substantially improves dispersibility, with 50-85% of treated particle mass achieving submicron sizes compared to 10% for untreated particles. We compare the dispersal of treated particles of different sizes and find that 300 nm particles provide superior deagglomeration than 500 nm particles for the same air consumption. Theoretical modeling of the adhesion forces between particles, combined with surface roughness parameters extracted from atomic force microscopy, successfully predicted the relative dispersibility across different particle types. The pneumatic dispersal system achieved optimal performance at air-to-powder mass ratios of about 10:1. Using the measured dispersed particle sizes, we provide a scaling analysis suggesting that a feasibly sized fleet of dispersal aircraft could provide an aerosol layer sufficient for meaningful climate intervention. These results demonstrate that hydrophobic surface treatment and pneumatic dispersal can overcome the agglomeration challenge for SAI with solid particles.
Read the full abstract

All authors Yair Segev, Eitan Y. Levine, Yair Bar-Yoseph, Ori Amsallem, Yuval Dagan, Elad Laor, Shai Rahamim, Alon Luski, Eran Daniel, Eshani Hettiarachchi, Amyad Spector

Data Analysis and Statistics · Cross-listed from cs.SI

Conditional Entropy of Heat Diffusion on Temporal Networks

Samuel Koovely and Alexandre Bovet

Diffusion-based information-theoretic approaches provide new theoretical and practical tools to study complex networks. So far, they have not been generalized to temporal networks. In this work, we show that common entropic measures based on modeling diffusion on graphs, such as the entropy rate and the spectral entropy, do not generalize straightforwardly to temporal networks due to the process's non-stationarity and temporal asymmetries. Instead, we propose the conditional entropy of heat diffusion as an entropic measure for continuous-time temporal networks and study its properties. We show that this quantity is monotone in time, yielding an information-theoretic analog of the second law of thermodynamics for inhomogeneous diffusion on temporal networks. We provide an upper bound and suggest a lower bound on its evolution and explain how discrepancies from it arise due to asymmetric temporal paths. We then introduce a local version of conditional entropy, designed to probe diffusion over finite temporal windows, and show that it provides an informative signal for change-point detection in continuous-time temporal networks. We evaluate the proposed methodology on synthetic benchmarks, including comparative experiments with existing nonparametric baselines in the snapshot setting, and then apply it to a real-world temporal contact network. Finally, we show how to use detected change points to guide community detection on targeted sub-intervals, improving the quality and interpretability of the clustering results.
Read the full abstract

Biological Physics

Universal Extremum Seeking Mechanism for Lift Variation in Soaring Birds Flight: A New Paradigm in Computational Physics and Biology

Simone Martini, Dipesh Kunwar and Sameh A. Eisa

In this letter, we reveal a universal, very simple extremum seeking natural feedback law and mechanism that governs, adapts, and generates in real-time, optimized lift variations for successful energy gain flight in presence of wind shear. The introduced law/mechanism, which is computationally minimal and needs only sensory information of the wind or local energy rate (i.e., model-free and data-driven) is able to characterize and replicate dynamic soaring optimized flight physics of windward climb in real-time for a variety of soaring birds species, namely wandering albatross, black-browed albatross and grey-headed albatross. We confirm the effectiveness of this new simple, real-time law by successful comparisons with sophisticated non-real-time optimal control solver and reported biological data. Our results establish the proposed mechanism as a new paradigm in soaring flight physics. That is, our results substantially advance the computational physics/biology aspects of the problem while providing a biologically plausible theory for avian soaring behavior.
Read the full abstract

Instrumentation and Detectors

Environmental Stabilization of Perfect-Crystal Neutron Interferometry Using a Large Vacuum Chamber with Cryogenic Sample Access

Robert Valdillez, David G. Cory, Robert W. Haun et al. (+9 more)

Perfect-crystal neutron interferometry has been a useful tool in measuring nuclear-interactions, probing fundamental physics, and exploring quantum phenomenon. Historically, neutron interferometry experiments have been carried out at room temperature and standard atmospheric pressure. However, neutron interferometry is sensitive to changes in the local environment, especially thermal gradients across the crystal, resulting in phase drifts and systematic uncertainty. A need for measurements performed in different sample environments compound these issues. Fortunately, the use of a vacuum chamber has been shown to be an effective method of environmental isolation for perfect-crystal neutron interferometers. A large volume, highly versatile vacuum chamber has been installed at the Neutron Interferometry and Optics Facility at the NIST Center for Neutron Research to isolate interferometry from local temperature and pressure deviations as well as allowing for the introduction of cryogenically cooled samples. The prospect of incorporating a cryostat within a neutron interferometer opens up new areas of investigation, such as superconductivity. In addition to describing the vacuum chamber, we report on the first measurement of a cryogenic-cooled sample by a neutron interferometer. For this demonstration contrast was measured with a Ni60Cu40 sample between 4 K to 300 K.
Read the full abstract

All authors Robert Valdillez, David G. Cory, Robert W. Haun, Benjamin Heacock, Colin Heikes, Shannon F. Hoogerheide, Michael G. Huber, Taisiya Mineeva, Jeremy Paster, Dusan Sarenac, Dmitry A. Pushin, Albert R. Young

Instrumentation and Detectors

Enhanced Temperature Sensitivity in Ensemble NV Centers through Improved Optically Detected Magnetic Resonance Spectral Modeling

Yuki S. Kato, Shingo Sotoma, Keisuke Fujita et al. (+5 more)

Nitrogen-vacancy (NV) center ensembles provide a powerful platform for high-precision temperature sensing, with ongoing efforts to further enhance their measurement performance. In ensemble NV optically detected magnetic resonance (ODMR) spectra, commonly used Lorentzian and Voigt fitting models fail to accurately describe the spectral shape near the resonance frequency, leading to degraded precision in resonance-frequency determination and, consequently, temperature estimation. In this work, we analytically establish a new fitting method, termed dip-peak fitting, for extracting the resonance frequency from ensemble cw-ODMR spectra. Starting from a physical model that describes ensemble cw-ODMR spectra as a convolution of single-NV responses with distributed zero-field splitting and strain, we show that the spectral feature near resonance can be accurately approximated by a single Lorentzian function with a background term. The proposed fitting model reproduces the cw-ODMR spectrum around resonance more faithfully than conventional approaches, enabling faster and more accurate resonance-frequency determination under weaker microwave excitation. Experiments using fluorescent nanodiamond ensembles confirm the robustness and applicability of this method for high-precision temperature sensing.
Read the full abstract

All authors Yuki S. Kato, Shingo Sotoma, Keisuke Fujita, Masanori Fujiwara, Izuru Ohki, Yuichiro Matsuzaki, Norikazu Mizuochi, Yoshie Harada

Geophysics

Stress state, subsidence, and faulting in the Wilmington Oil Field, California: a multiphase flow-geomechanics modeling assessment (1936-2020)

Lluís Saló-Salgado, Josimar A. Silva, Andreas Plesch et al. (+3 more)

Nearly a century of oil production in the Wilmington Oil Field, Los Angeles Basin, California, has modified the stress state, caused nearly 9 m of ground surface subsidence, and been associated with earthquakes that sheared wells. This offers a unique opportunity to elucidate the processes that govern these phenomena: Since the 1930s, approximately 2.5 billion barrels of oil have been produced, accompanied by water injection volumes roughly an order of magnitude larger. Combined with extensive structural and geophysical constraints, this history allows us to interrogate the long-term geomechanical impacts of reservoir operations. Here, we assess (i) how the initial stress state, typically uncertain in the shallow crust ($<5$ km depth), influences subsidence and uplift, and (ii) how production and injection operations affect fault stability. Our numerical model, calibrated with published measurements of reservoir pressures and surface displacements, incorporates a detailed representation of fault surfaces within and around the field, well-level production and injection schedules, and an elastoplastic constitutive framework. Model results show that the previously assumed stress regime in the field (reverse faulting) needs to be reassessed$\unicode{x2014}$the best match to the ground deformation data is achieved when the sedimentary section is initialized with low deviatoric stress (i.e., not critically stressed). This suggests significant variation in the stress state with depth, including a likely change in the stress regime. DCFF values suggest minor destabilization on reservoir faults and larger changes on sub-horizontal bedding planes; both could explain the faulting that led to sheared wells and seismicity between 1947 and 1961.
Read the full abstract

All authors Lluís Saló-Salgado, Josimar A. Silva, Andreas Plesch, Franklin D. Wolfe, John H. Shaw, Ruben Juanes

Instrumentation and Detectors

High-Frequency Thermal Noise in Michelson Interferometers

Daniel Grass, Sander M. Vermeulen, Ian A. O. MacMillan et al. (+1 more)

Thermal noise in optics constrains the precision of optical experiments, including Michelson interferometers, optical clocks, and optomechanical sensors. While high-power optical experiments such as gravitational-wave detectors are currently limited mainly by quantum noise, new experiments incorporating recent insights from quantum metrology are being developed that evade the quantum shot noise background. In particular, Michelson interferometers that use photon-counting readout will look for weak, high-frequency signals. Since shot noise is no longer the dominant noise source with these readout schemes, it is important to accurately model thermal noise to characterize signals and design more sensitive experiments. However, previous modeling uses approximations that are no longer valid in these frequency regimes. In the MHz band, the quasistatic approximation does not apply. We therefore develop more general models of substrate and coating mechanical (Brownian) noise, substrate and coating thermoelastic noise, and coating thermorefractive noise. We validate the models with comparisons to previous low-frequency modeling and high-frequency spectra from an experiment that has already taken data, the Holometer. We then apply the new models to GQuEST, an experiment under construction.
Read the full abstract

All authors Daniel Grass, Sander M. Vermeulen, Ian A. O. MacMillan, Lee McCuller

Optics · Cross-listed from quant-ph

A Compact, Robust, and Tunable Open Microcavity Platform for Solid-State Quantum Electrodynamics

Thi D. Hoang, Fateme Mahdikhany, Zixuan Wang et al. (+4 more)

Open microcavities provide a powerful platform for studying cavity quantum electrodynamics in solid-state systems. However, operating open microcavities at cryogenic temperatures, as required for many solid-state quantum emitters, typically demands bulky and cryostat-specific vibration-mitigation setups. Here we report a compact, robust, and tunable mechanical host for an open microcavity. The complete mechanical assembly fits within a footprint of $1'' \times 1'' \times 0.5''$. Using this mechanical host, we observe no vibration-induced cavity broadening for an open microcavity with finesse exceeding 1,000 without cryostat customization or active locking. The assembly also enables in situ tuning of the cavity resonance over 3 nm, and the resonance of the same cavity remains within this range across multiple cooldowns. To further showcase the capability of this assembly, we demonstrate coupling between an InGaAs quantum dot and an open microcavity with a cooperativity exceeding unity. This platform provides a versatile testbed for fundamental cavity quantum electrodynamics and a scalable route to portable quantum light sources and spin-photon interfaces for quantum repeaters, quantum networks, and photonic quantum computing.
Read the full abstract

All authors Thi D. Hoang, Fateme Mahdikhany, Zixuan Wang, Richard Mirin, Kevin Silverman, Poolad Imany, Shuo Sun

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

Branching under First-Passage Resetting

Aanjaneya Kumar and James Holehouse

Many biological processes, from cell division to viral lysis, are triggered when an internal stochastic variable reaches a threshold. Here we introduce Branching under First-Passage Resetting, a general framework in which replication events arise endogenously from first-passage dynamics rather than from externally imposed lifetime clocks. We show that the resulting population dynamics obey an exact renewal equation linking single-trajectory first-passage statistics to the population growth rate. This mapping shows that, for fixed offspring number and fixed mean replication time, stochastic timing fluctuations necessarily enhance growth relative to a deterministic clock. When offspring yield depends on the first-passage time, however, fluctuations have non-trivial effects and expose a fundamental yield-delay trade-off: waiting longer can increase the number of descendants, but delays all future lineages. Our framework allows us to address this optimization problem analytically, and upon application to bacteriophage lysis, gives an optimal lysis time and growth rate consistent with empirical data.
Read the full abstract

Chemical Physics

Reducing the Complexity of Density-Matrix Functionals in a Real-Space-Decomposed DF+RDMF Scheme with the Adaptive Cluster Approximation

Konstantin Tamoev, Robert Schade and Thomas D. Kühne

Reduced density-matrix functional theory (RDMFT) provides a variational route to electronic correlations beyond conventional density-functional approximations, but explicit evaluations of density-matrix functionals still scale exponentially with the number of active one-particle states. We formulate and assess a real-space-decomposed density-functional plus reduced-density-matrix-functional (DF+RDMF) scheme in which the Coulomb interaction is partitioned locally in real space and the RDMF correction is evaluated only for the strongly correlated part of the interaction. The resulting local density-matrix functionals are further compressed using the adaptive cluster approximation (ACA), which performs a unitary rotation of the bath subspace before truncation and therefore preserves the local interaction while reducing the number of explicitly correlated bath states. As a molecular test case, we consider the bending potential of carbon suboxide, C$_3$O$_2$. While semilocal PBE favors a linear molecule, the DF+RDMF/ACA correction stabilizes a bent configuration in qualitative agreement with the quasilinear behavior inferred from spectroscopy. The approach provides a systematic embedding hierarchy for combining density functionals with explicitly correlated density-matrix corrections in extended or spatially inhomogeneous systems.
Read the full abstract

Geophysics · Cross-listed from cs.LG

In-context learning enables continental-scale subsurface temperature prediction from sparse local observations

Daniel O'Malley, Christopher W. Johnson, Javier E. Santos et al. (+10 more)

Continental-scale knowledge of subsurface temperature is limited by the cost and sparsity of borehole measurements, but such information is essential for geothermal resource assessment and for understanding heat transport in the shallow crust. The thermal field reflects the interaction between lithology, crustal structure, radiogenic heat production, and advective fluid flow, sometimes producing sharp anomalies that are smoothed by conventional interpolation or difficult to capture with physical models. Here we introduce In-Context Earth, a transformer-based model that uses sparse local borehole observations as geological context to predict continuous temperature-at-depth fields with calibrated uncertainty. In the contiguous United States, the model achieves a mean absolute error of 4.7 {\deg}C, outperforming the physics-informed Stanford Thermal Model, a model based on AlphaEarth embeddings, the multimodal Transparent Earth model, and universal kriging, while resolving sharper thermal gradients in geothermal provinces. Its uncertainty estimates are well calibrated, with a Kolmogorov-Smirnov statistic of 2.5%. Without finetuning, the model adapts to Alberta, Australia, and the United Kingdom (UK) using only 20 local observations at inference time, maintaining high accuracy in geologically distinct test regions with a mean absolute error of 2.2 {\deg}C in Alberta, 6.2 {\deg}C in Australia, and 5.4 {\deg}C in the UK. Interpretability analyses show that the model learns internal representations of subsurface properties it never observes during training, including seismic velocities, geochemistry, and crustal structure, and uses these representations in physically consistent ways. More broadly, this work shows that in-context learning can use sparse borehole observations for continental-scale subsurface characterization, without requiring dense measurements or region-specific retraining.
Read the full abstract

All authors Daniel O'Malley, Christopher W. Johnson, Javier E. Santos, Pablo Lara, Sandro Malusà, Bharat Srikishan, John Kath, Arnab Mazumder, Mohamed Mehana, David Coblentz, Nathan DeBardeleben, Earl Lawrence, Hari Viswanathan

Atomic Physics

Production of Intense Spin-Polarized Beams of Hydrogen Isotopes by Charge Transfer with High Density Raman-Pumped Alkali-Metal Vapors

Thad G. Walker, Cary B. Forest and Deniz D. Yavuz

It should be possible to generate multi-ampere spin-polarized beams of hydrogen isotopes by repeated charge-transfer collisions in highly spin-polarized Cs vapor. Estimates suggest that off-resonant Raman pumping with kW scale narrowband tunable light at 895 nm should be able to produce a 1 m long, 10 cm diameter volume of 80% polarized Cs vapor. The charge transfer collisions between the Cs and hydrogen result in a high nuclear spin-polarized negative ion beam that can be subsequently accelerated to high energy, neutralized, and be used to heat fusion plasmas with resulting increases in the fusion conversion efficiency.
Read the full abstract