Atmospheric and Oceanic Physics
Quantification of atmospheric carbon dioxide from the Geostationary Operational Environmental Satellite (GOES East)
Aaron Sonabend-W, Sean Campbell, John Platt et al. (+2 more)
There is a growing urgency to track greenhouse gasses with the resolution, precision and accuracy needed to support independent verification of $CO_2$ fluxes at local to global scales. The current generation of space-based sensors, however, only provides sparse observations in space and time. This challenge has fueled interest in the potential use of data from existing missions originally developed for other applications to infer global greenhouse gas variability. The Advanced Baseline Imager (ABI) onboard the Geostationary Operational Environmental Satellite (GOES-East), operational since 2017, provides full coverage of much of the western hemisphere at 10-minute intervals from geostationary orbit across 16 spectral channels at an approximately 2 km$^2$ spatial resolution. Here, we leverage this high spatial coverage and temporal revisit to develop Deep$XCO_2$, a single-pixel, physics-guided neural network to estimate dry-air column $CO_2$ mole fraction ($XCO_2$). Deep$XCO_2$ employs a time series of GOES-East's 16 spectral bands, ECMWF ERA5 lower tropospheric meteorology, MODIS surface reflectance,
solar and satellite viewing geometry, and day of year. The network was trained on collocated GOES-East and OCO-2/OCO-3 observations. Deep$XCO_2$ is able to capture realistic $XCO_2$ variability when compared against a held-out year of OCO-2 and OCO-3 observations, and against observations from the TCCON network. We also present case studies illustrating the use of Deep$XCO_2$ to observe $XCO_2$ enhancements over urban areas and drawdown over agricultural regions. Overall, while the precision of GOES-East derived $XCO_2$ can never rival that of dedicated instruments, the unprecedented combination of contiguous geographic coverage, 10-minute temporal frequency, and multi-year record offers the potential to observe aspects of atmospheric $CO_2$ variability currently unseen from space.
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All authors Aaron Sonabend-W, Sean Campbell, John Platt, Christopher Van Arsdale, Anna M. Michalak
Physics and Society
Stop Drawing Scientific Claims from LLM Social Simulations Without Robustness Audits
Jinyi Ye, Lei Cao, Ding Chen et al. (+1 more)
The scientific claims drawn from LLM social simulations should be no stronger than the robustness audits that support them. Generative
agents bring new expressive power to
agent-based modeling, enabling simulations of collective social processes like cooperation, polarization, and norm formation. Yet they also introduce complexity through additional architectural choices, such as
agent specification,
memory representation, interaction protocols, and environment design. Small perturbations that appear minor to researchers can cascade into macro-level outcomes through repeated interaction, creating a "butterfly effect." Consequently, scientific claims drawn from LLM social simulations may reflect implementation artifacts rather than the social mechanisms being modeled. We support this position with two case studies: a repeated Prisoner's Dilemma and a social media echo chamber simulation. Across multiple models, minor perturbations in persona format and game-instruction framing shift cooperation rates by up to 76 percentage points, while network homophily and hub assignment produce significant and consistent shifts in polarization metrics. We also find that sensitivity is unevenly distributed across both architectural choices and model families: the same perturbation that produces the 76 pp shift in one frontier model only shifts another by 1 pp. Robustness is therefore a property that should be measured per claim and per model, not assumed. To address this validation gap, we introduce TRAILS (Taxonomy for Robustness Audits In LLM Simulations), a robustness-audit taxonomy spanning three levels of simulation design:
agent (micro-level), interaction (meso-level), and system (macro-level). We call for robustness to become a first-order validation requirement before LLM social simulations are used to explain mechanisms, evaluate interventions, or inform decisions.
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All authors Jinyi Ye, Lei Cao, Ding Chen, Emilio Ferrara
Optics
Giant nonlinear optical chirality in twisted heterobilayers
Xiang Zhang, Bo Li, Leyi Zhao et al. (+7 more)
Twisting two dissimilar monolayer
semiconductors induces structural chirality that remains largely elusive in linear optics but becomes remarkably pronounced in the nonlinear regime. Here we demonstrate that MoS2/WSe2 heterobilayers exhibit
giant, twist-tunable nonlinear chirality in second-harmonic generation (SHG). The sign of SHG circular dichroism is governed by structural handedness, and its magnitude reaches 1.96 near a 30{\deg} twist angle under 1260-nm excitation, approaching the theoretical limit of 2. Furthermore, reversed chirality is observed when light is incident from opposite directions. Using a layer-resolved model, we attribute this phenomenon to helicity-dependent interference between the two monolayer SHG fields, mediated by a nonlinear Pancharatnam-Berry phase. These findings establish that the relative orientation of atomically thin layers can deterministically control nonlinear
chiral responses, identifying twisted 2D
heterostructures as a versatile platform for nonlinear
chiral photonics, frequency conversion, and ultracompact light-matter interfaces.
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All authors Xiang Zhang, Bo Li, Leyi Zhao, Pengzhi Wang, Luwei Zhou, Jiangbo Peng, Gan Wang, Kian Ping Loh, Tao-Yuan Du, Mingjie Li
Chemical Physics
Simulating Exciton Transport with Complex Absorbing Potentials
Dimitri Bazile, Justin Caram, Chern Chuang et al. (+1 more)
We introduce a
stochastic framework based on complex absorbing potentials (CAPs) to investigate
exciton transport in large molecular aggregates. Within this approach, CAPs act as non-Hermitian reservoirs and sinks that enable effective measurement of transport efficiency. We apply this framework to cyanine dye aggregates and examine how vacancy defects and system size influence
exciton dynamics in two-dimensional sheets and quasi-one-dimensional tubes. We also introduce a CAPs-based classification scheme that links molecular packing in 2D aggregates to transport behavior. Our results demonstrate how aggregate
topology and structural disorder govern
exciton dynamics and provide guidance for designing materials with enhanced energy transport.
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All authors Dimitri Bazile, Justin Caram, Chern Chuang, Daniel Neuhauser
Fluid Dynamics
Scale-conditioned structure-based closure for homogeneous turbulence: Ray-Column Interacting Particle Representation Model
Stavros C. Kassinos
The particle representation model (PRM) and interacting particle representation model (IPRM) describe homogeneous
turbulence through orientation-conditioned structural states. In their original form, the conditional state is organized by the unit spectral direction, while the radial spectral coordinate is integrated out. We introduce a scale-conditioned Ray-Column extension in which the spectral vector is decomposed into orientation and radial wavenumber, and the conditional structure state is projected onto finite radial bands. The formulation starts from the continuum spectral tensor and is then reduced to the ray-packet ensemble sums used in the implementation. The bands are projections of an orientation-wavenumber tensor density and retain scale-conditioned structural populations for closure evaluation. The rapid dynamics remain ray-packet resolved, while the nonlinear slow and terminal closure coefficients are evaluated from band-aggregate structure tensors formed by integrating over orientation and wavenumber within each band. The present reference closure omits conservative cascade modeling among bands. A reference closure is built from PRM rapid kinematics, band-local effective-gradient response, slow rotational randomization, and an active large-scale enstrophy (LSE) terminal-drain map. In the active-LSE closure, the misalignment-sensing factor Psi_fd regularizes the LSE structure-to-dissipation map; the Ray-Column formulation evaluates this map on band-aggregate structural populations. The model is assessed in irrotational strain, homogeneous shear,
elliptic-streamline, and rotating-shear configurations. The rotating-shear comparison with filtered LES data illustrates the payoff of retaining band information: filtered or low-pass observables can be formed before scale information is lost in the one-point reconstruction.
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Classical Physics · Cross-listed from cond-mat.stat-mech
Variational Boundary Fluctuations as a First-Principles Origin of Langevin Noise
Francisco Monroy
Stochastic forces are usually postulated or obtained by eliminating environmental degrees of freedom. Here we identify a variational origin: fluctuating endpoint data in Hamilton's principle induce fluctuations of the on-shell action. Hamilton–Jacobi propagation transports this boundary imprint, whose gradient generates an effective Langevin force inherited from boundary-action fluctuations. The resulting force is not freely specifiable: its amplitude is filtered by the Hessian of Hamilton's principal function, yielding multiplicative and state-dependent noise. Homogeneous additive Langevin forcing is recovered only as a Markovian coarse-grained limit.
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Fluid Dynamics
Shear alignment and tensorial Taylor–Aris dispersion of Brownian rods in a circular tube
Jingsen Feng and Xu Chu
Brownian rods disperse in pressure-driven flow through a coupling between axial shear, anisotropic translational
diffusion and Jeffery–Brownian rotation. Classical tube Taylor–Aris theory treats transverse mixing as a scalar process, and existing passive-rod reductions have mainly addressed planar geometries. A circular tube adds two ingredients: the shear strength varies with radius and freely rotating rods sample a three-dimensional orientation space. We formulate a tensorial Taylor–Aris theory for dilute axisymmetric rods in Poiseuille flow by solving the local steady orientation Fokker–Planck problem and using its second moments to close a conservative axisymmetric transport equation. The long-wave reduction shows how each part of the
diffusion tensor enters the one-dimensional limit. The radial diffusivity sets the invariant cross-sectional measure and the
cell problem for the leading Taylor coefficient; the radial–axial component produces an inverse-Péclet correction to the migration speed; the axial component gives the direct diffusivity. The central mechanism is the streamwise
alignment generated in high-shear annular layers.
Alignment reduces radial diffusivity there, shifts the long-time sampling of the velocity profile toward slower streamlines, and amplifies the radial
cell response. In strong shear this raises the Taylor coefficient by about \(23\%\) for aspect ratio \(p=1000\) and by about \(30\%\) in the infinitely slender limit, approaching the fully aligned bound. Direct simulations of the full tensorial equation validate the asymptotic coefficients. The same radial mixing operator also gives a Sturm–Liouville spectral model that tracks finite-time relaxation from different radial injections to the long-time Taylor regime.
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Atmospheric and Oceanic Physics
Longwang: Zero-Shot Global Spatiotemporal Precipitation Downscaling with a Latent Generative Prior
Yue Wang and Daniele Visioni
High-resolution precipitation information is essential for
climate impact assessment, yet global
climate models remain too coarse to resolve key small-scale processes. Existing machine learning downscaling methods often require paired low- and high-resolution data for supervised learning, are tied to fixed regions or scale factors during inference, and can be computationally expensive to train and run in physical space. Here we introduce Longwang, a zero-shot latent generative framework for global spatiotemporal precipitation downscaling. Longwang learns a context-conditioned latent generative prior and combines it with a physically informed observation operator through posterior sampling, enabling daily O(10 km) precipitation fields to be generated from monthly O(100 km) inputs. On ERA5 reanalysis, Longwang outperforms standard posterior sampling with an unconditional generative prior in reconstructing fine-scale spatial patterns, preserving temporal coherence, and recovering extreme precipitation intensities. The framework further generalizes to historical
climate simulations and future
climate projections under substantial distribution shift.
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Fluid Dynamics
Self-focusing of helicity drives finite-time singularities in inviscid flows
Mokhtar Adda-Bedia and Sergio Rica
This paper deals with the longstanding quest of the possible existence of finite-time singularities in the equations governing the dynamics of inviscid fluids, namely, Euler equations. Here, two contributions are brought for the case of perfect fluids with finite initial energy. First, a self-similar velocity field inspired by Leray Ansatz is proposed which allows for a separation of variables that transforms the original partial differential Euler equations to a nonlinear system of ordinary differential equations. This system can be solved semi-analytically and allows a continuum set of solutions parametrised by a self-similar exponent, $\nu$. Second, we use the conservation laws of Euler equations to select the possible finite-time singular solutions and the related self-similar exponents. We find that the helicity is the driving mechanism of the blow-up through a self-focusing mechanism. The flow near the singularity separates into two phases. A first phase is within a tubular region that shrinks as a power-law $(t_c-t)^\nu$, with $t_c$ the blow-up time, where the helicity is focused. This region is separated by a sharp interface from an outer region where the vorticity, and thus helicity, is identically zero. We found that the finite-time singularity may be either point-like or line-like depending on the dynamics of the tubular region along its axis of
symmetry. Incidentally for a point-like singularity we recover the Leray scaling $\nu=1/2$ paving the way to a generalisation of this approach for the Navier-Stokes equations. Finally, we
conjecture that if the helicity vanishes initially, no finite-time singularity would be possible, since in this case the singularity occurs at infinite time from the initial condition.
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Fluid Dynamics
Spatio-Temporal Signatures of Intermittency in Helically Rotating Turbulence through Topological Data Analysis
Snigdhashree Mallick, Yashwanth Ramamurthi, Shiva Kumar Malapaka et al. (+1 more)
A central challenge in hydrodynamic
turbulence is identifying precisely when, and at which length scales, strong turbulent fluctuations (STFs) emerge and develop into intermittent events, which are often obscured by conventional statistical diagnostics. We address this problem by applying a Topological Data Analysis (TDA) framework to reveal the spatiotemporal signatures of intermittency in low-resolution ($128^3$) helically rotating turbulent flows. Vorticity magnitude and length-scale (eddy size) fields are used as scalar observables for TDA: vorticity characterizes rotational dynamics that generate multiscale flow structures, while length-scale fields encode the scales at which intermittent activity arises. Their evolving
topology is quantified using persistence diagrams and Wasserstein-distance metrics. Compared with traditional statistical approaches, this framework is more sensitive to localized and short-lived flow variations, enabling clearer detection of intermittent behavior. Pronounced variations in Wasserstein-distance heatmaps provide direct signatures of STFs across space and time. Together, these results demonstrate that TDA offers an effective complementary tool for detecting STFs that lead to intermittency within turbulent regime.
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All authors Snigdhashree Mallick, Yashwanth Ramamurthi, Shiva Kumar Malapaka, Amit Chattopadhyay
Applied Physics
Modeling Growth and Plasma Oxygen Effects on Metal Purity in Platinum EBID
Marianna D'Amato, Linda Piscopo, Hanna Le Jeannic et al. (+2 more)
Electron Beam-Induced Deposition (EBID) enables site-specific nanofabrication but suffers from significant carbon contamination, limiting its applicability in plasmonics, nanoelectronics, and sensing. In this study, we investigate the relationship between EBID process parameters such as beam current, acceleration voltage, and dwell time, and the platinum-to-carbon composition of deposited nanostructures. Using Energy Dispersive X-Ray Spectroscopy (EDX), we establish a hindered exponential growth model that correlates deposit composition with fabrication conditions. To enhance metal purity, we apply
plasma oxygen treatment, exposing EBID deposits to a 30 W
plasma for 30 minutes in a tabletop
plasma generator. Post-treatment EDX analysis confirms a systematic increase in platinum content, while SEM inspection reveals nanostructure shrinkage due to carbon removal. This work aims to provide a framework for optimizing EBID fabrication and post-processing strategies to enhance material performance.
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All authors Marianna D'Amato, Linda Piscopo, Hanna Le Jeannic, Alberto Bramati, Antonio Balena
Optics
van der Waals Nanogap Loading of a \ce{TiO2} Nanobar Metasurface for Dual-Channel Fano Refractive Index Sensing
Shoumik Debnath and Sudipta Saha
Filling the gap of a \ce{TiO2} nanobar-pair metasurface with $\alpha$-\ce{MoO3}, a biaxial orthorhombic
crystal, produces two high-$Q$ Fano resonances with unequal quality factors: $Q_\mathrm{TE} = 87$ at 863.3~nm and $Q_\mathrm{TM} = 31$ at 960.1~nm, separated by 97~nm. The same device with amorphous \ce{Sb2S3}, which is isotropic, gives $Q_\mathrm{TE}=66$ and $Q_\mathrm{TM}=20$, a ratio of 3.35 against 2.85 for $\alpha$-\ce{MoO3}, so the inequality of the two quality factors is not specific to the biaxial
crystal and originates instead in the in-plane anisotropy of the resonator geometry. An unequal pair of quality factors is therefore not by itself evidence of material anisotropy. What the biaxial fill controls at fixed geometry is the partitioning of the response between the two channels: each polarization samples a different principal index, so the two resonance positions, the two linewidths and the ratio of the two sensitivities respond to a single material choice in different proportions. The TE channel delivers sensitivity $S=155.3$~nm~RIU$^{-1}$, figure of merit $15.71$~RIU$^{-1}$, and an ideal refractive index resolution of $6.44\times10^{-5}$~RIU; TM delivers $S=139.1$~nm~RIU$^{-1}$, $4.44$~RIU$^{-1}$, and $7.19\times10^{-5}$~RIU. Simultaneous readout produces a fixed polarization response with isotropic slope 0.896, which the gap material changes: the same geometry filled with amorphous \ce{Sb2S3} gives 0.620. All results reported here are numerical; no device was fabricated and no measurement was performed.
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Computational Physics · Cross-listed from math.NA
Quantum circuits for the advection-diffusion equation with boundary conditions based on LCHS
Leyu Chen, Tiegang Liu, Liang Xu et al. (+1 more)
This paper proposes a systematic and explicit
quantum circuit framework for solving advection-
diffusion equations with boundary conditions, based on the Linear Combination of
Hamiltonian Simulations (LCHS) method.By employing the Finite Volume Method (FVM) combined with various flux construction schemes, we elaborate the design of
quantum circuits tailored explicitly for Robin boundary conditions (including Dirichlet and Neumann boundary conditions as special cases) and periodic boundary conditions. The Robin boundary elimination is encoded by newly constructed endpoint-projector
circuits, and all physical and boundary-induced inhomogeneous terms are incorporated through an outer linear combination of
unitaries (LCU). The error analysis adopts an LCU-weighted form, preserving the decay of the LCHS kernel in the product-formula bounds. Complementing this analysis, a comprehensive gate complexity analysis demonstrates the
quantum advantages over classical computing in high-dimensional scenarios. We simulate the proposed
circuits on a fault-tolerant emulator, and numerical results validate the effectiveness of the proposed framework across homogeneous, inhomogeneous, and high-dimensional cases.The proposed framework is compatible with numerous spatial discretization methods and numerical schemes, extends naturally to other linear PDEs, and establishes a practical foundation for solving large-scale PDE problems on future fault-tolerant
quantum computers.
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All authors Leyu Chen, Tiegang Liu, Liang Xu, Kun Wang
Optics
Semi-analytical Model of Multi-tile Rectangular Waveguide-fed Metasurfaces using Coupled Dipole Modeling Framework
Insang Yoo, Michael Boyarsky and David R. Smith
We present a semi-analytical model to analyze multi-tile metasurface
antennas consisting of a set of metasurface tiles and a practical power-dividing network that excites the tiles. The metasurface tiles consist of arrays of rectangular waveguides with subwavelength metamaterial radiators etched into their top walls, each of which can be accurately modeled as polarizable dipoles. The feed structure for the arrays comprises a slotted waveguide attached to their bottom wall, with coupling slots inserted into the common wall that are likewise modeled as polarizable dipoles. The proposed semi-analytical model employs a coupled-dipole framework that accurately captures dipolar interactions among constituent elements within the metasurface tiles, along with a multi-port network analysis technique that accounts for electromagnetic interactions between the tiles and the power divider, thereby forming a self-consistent formulation. The proposed model enables the prediction of key performance metrics, including overall S-parameters, radiation patterns, and gain, and is validated through full-wave numerical simulations. By significantly reducing the computational complexity associated with electrically large apertures, the proposed framework enables rapid and efficient modeling of the overall structure, thereby facilitating iterative optimization. The proposed model has potential applications as an efficient forward model for the design of wireless systems requiring large-aperture metasurface
antennas, including remote sensing and next-generation wireless communication networks.
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History and Philosophy of Physics · Cross-listed from cs.DL
The Curious Case of Max Planck retracted papers. When past scientific practices meet contemporary publishing norms
Yves Gingras and Mahdi Khelfaoui
This article examines the case of two papers published in Naturwissenschaften by the physicist Max Planck that were retrospectively marked as "retracted" on Springer digital platform. Rather than originating in scientific fraud, these withdrawals appear to result from contemporary digitization and copyright-management procedures applied anachronistically to historical publications. Through an investigation of the circulation history of Planck 1940 and 1942 philosophical essays, the article shows that republication across multiple formats was a common and legitimate practice within the scientific publishing culture of the early 20th century. Such practices only became problematic with the later transformation of the scientific article into a countable and proprietary unit within systems of bibliometric evaluation and commercial academic publishing. This article argues that contemporary notions such as "duplicate publication" and "self-plagiarism" are historically situated categories that cannot be applied retrospectively without distorting the historical record. More broadly, the Planck case reveals how digital scholarly infrastructures controlled by large commercial publishers can limit the accessibility of the scientific past.
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Fluid Dynamics
Solutocapillary instability in slipping falling films
Sanghasri Mukhopadhyay, Séverine Millet, Bastien Di Pierro et al. (+1 more)
We present a comprehensive framework for
gravity-driven, surfactant-laden thin films flowing over slippery substrates, elucidating how wall slip modifies the coupled hydrodynamics and interfacial transport. A long-wave model is formulated with a conservative bulk-surface mass balance and a Navier slip condition. The Orr-Sommerfeld
eigenvalue problem governs the linear regime, while a weighted-residual model captures the nonlinear
evolution over a range of
equilibrium surfactant coverages, Marangoni strengths, and adsorption kinetics. The analysis predicts a non-monotonic variation of the critical Reynolds number with
equilibrium coverage, exhibiting a maximum at intermediate $\Gamma_e$, and a slip-induced transition from single- to double-hump solitary structures with increasing Marangoni number, accompanied by attenuated capillary ripples. Under fast adsorption kinetics, the surface field homogenizes, preserving the mean film shape and flux while flattening both the surface concentration $\Gamma$ and the bulk inventory $\chi + h\phi$. A spurious interfacial mass growth reported by Pascal et al.(PRF, 2019) and D'Alessio et al.(JFM, 2020) is resolved through a revised surface balance ensuring strict conservation. Wall slip thus emerges as a key control parameter, reducing viscous resistance and mitigating Marangoni back-stress. The slip parameter $\beta$ is a useful control knob for surfactant-laden films. Slip prevents fragile multi-hump bound states, promoting a single broad crest or an almost flat, uniform sheet by carefully bonding $\beta$ to wave selection, ripple damping, and the bulk-surface surfactant balance.
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All authors Sanghasri Mukhopadhyay, Séverine Millet, Bastien Di Pierro, Asim Mukhopadhyay
Data Analysis and Statistics
Integrating Bayesian Spectral Deconvolution and Expert Scientific Reasoning for Robust Peak Estimation
Hayato Okubo, Yoshifumi Amamoto, Toshimitsu Aritake et al. (+5 more)
Spectral deconvolution is essential for extracting peak structures that encode material properties and chemical structures, but conventional automated methods often fail when spectra contain high-intensity noise or unknown background components. In practice, scientists rarely interpret spectra in isolation. Instead, they identify physically meaningful peaks by relating spectral structures to auxiliary information such as physical-property values, chemical structures, and trends across related measurements. Here, we propose a
Bayesian framework that integrates spectral deconvolution with a model of expert scientific
reasoning. In this work, expert scientific
reasoning refers to the practice of evaluating candidate spectral structures by their consistency with independently measured physical-property values, rather than to manual expert intervention during inference. We formalize this
reasoning as a physical-property regression layer, implemented using Gaussian process regression, and couple it with
Bayesian spectral deconvolution. By averaging the physical-property likelihood over posterior predictive spectra inferred from
Bayesian spectral deconvolution, the proposed method selects spectral models according to the consistency between inferred spectral structures and physical-property information. We validate the framework using synthetic spectra with high-intensity noise or unknown backgrounds and infrared spectra of poly(lactic acid). The method recovers physically meaningful peak structures that conventional
Bayesian spectral deconvolution misses or misidentifies from spectra alone, including weak peaks in poly(lactic acid) IR spectra related to measured degradation rates. These results demonstrate that integrating expert scientific
reasoning with
Bayesian spectral deconvolution enables robust peak estimation under conditions where spectrum-only inference is unreliable.
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All authors Hayato Okubo, Yoshifumi Amamoto, Toshimitsu Aritake, Hiroyuki Kumazoe, Shiryu Nakano, Evan Jamison, Satoshi Tanaka, Yoh-ichi Mototake
Fluid Dynamics · Cross-listed from math-ph
Resolving the viscosity operator ambiguity on Riemannian manifolds via a kinematic selection principle
Zhi-Wei Wang and Samuel L. Braunstein
On a general Riemannian
manifold the Navier-Stokes equations admit several inequivalent formulations, differing in the choice of viscous operator: the Hodge
Laplacian, the Bochner
Laplacian, or the deformation
Laplacian. We show that a Lagrangian kinematic construction, in which the strain rate is built from the rate of change of inner products of Lie-dragged connecting vectors, uniquely selects the deformation
Laplacian for fluids whose configuration space is intrinsically the
manifold. The Hodge
Laplacian is excluded at the kinematic step (before introducing constitutive assumptions) because the strain rate constructed from inner-product geometry is symmetric and has no antisymmetric part. We further show that when the fluid arises as a thin-shell limit of an ambient three-dimensional flow, the operator that emerges depends on the boundary condition imposed in the normal direction: stress-free (Navier slip) conditions recover the deformation
Laplacian, while Hodge boundary conditions recover the Hodge
Laplacian, via an explicit decomposition of the ambient Bochner
Laplacian into intrinsic and extrinsic pieces. The intrinsic piece is the deformation
Laplacian regardless of the boundary condition. As an analytical confirmation, we show that the kinematic selection is consistent with the known failure of the energy inequality for the Hodge
Laplacian on the
hyperbolic plane $\HH^2$: the deformation
Laplacian is coercive on $\HH^2$ while the Hodge
Laplacian is not, because the
Ricci term has the opposite sign in the two operators. We further prove that on any complete two-dimensional
manifold with Gaussian
curvature bounded above by a negative constant, the incompressible Navier-Stokes equation with the deformation
Laplacian admits a unique global weak solution with exponential energy decay, resolving the analytical obstruction preventing the corresponding result for the Hodge
Laplacian.
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Atmospheric and Oceanic Physics · Cross-listed from cs.LG
Beyond Linear Superposition: Discovering Climate Features in AI Weather Models with KAN-SAE
Minjong Cheon
Deep learning weather prediction models achieve remarkable predictive skill yet remain largely opaque: we know little about how they represent physical
climate phenomena internally. Mechanistic interpretability through Sparse Autoencoders (SAEs) offers a principled route to decomposing these representations, but existing SAEs assume strictly linear feature superposition - a constraint ill-suited for the highly nonlinear atmospheric dynamics encoded in modern
transformers. We introduce KAN-SAE, a sparse autoencoder whose encoder replaces the standard ReLU with learnable per-feature B-spline activations drawn from Kolmogorov-Arnold Networks (KANs), allowing each latent dimension to develop its own nonlinear gating profile. Applied to Sonny, KAN-SAE discovers 975 alive features (vs. 566 for a linear baseline, a 72% improvement) with 20% lower inter-feature redundancy and comparable reconstruction fidelity. Without any
climate supervision, KAN-SAE identifies an interpretable European heatwave feature spatially concentrated over western Europe, and a western Pacific typhoon tracker confirmed by causal steering experiments. Our results demonstrate that nonlinear activations are essential for mechanistic interpretability of deep learning weather prediction models, recovering
climate features that remain invisible to linear baselines.
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Optics
Overcoming noise-agility trade-off in integrated lasers for precision sensing
Di Yu, Yitian Tong, Yu Xia et al. (+16 more)
Lasers that combine narrow linewidths with rapid tunability are critical for applications such as coherent optical ranging, distributed fiber-optic sensing, and precision spectroscopy. Despite significant progress in integrated
laser technologies, the concurrent realization of low phase noise and frequency agility on a single integrated platform remains challenging owing to a fundamental architectural trade-off: conventional integrated
laser designs typically suppress phase noise via high-$Q$ resonators, yet the extended
photon lifetimes inherent to such resonators intrinsically constrain tuning speed. Here, we address this noise-agility trade-off by introducing a
laser architecture that achieves ultralow phase noise and ultrafast tunability simultaneously. Rather than relying on ultrahigh-$Q$ resonators for self-injection locking, our design employs strong synthetic feedback within a Pockels-tunable, resonator-enhanced distributed Bragg reflector to suppress phase noise. As a proof of concept, we demonstrate a hybrid integrated
laser with a short-term linewidth of 29 Hz, realized using a lithium niobate external cavity with a loaded $Q$ of only 0.62 million. The adoption of a moderate resonator $Q$ relaxes the
photon-lifetime constraint on tuning speed, enabling sub-exahertz-per-second tuning rates and a chirp nonlinearity as low as 0.14%. Leveraging this
laser, we implement a frequency-modulated continuous-wave
LiDAR system that achieves a relative ranging precision of $1.7 \times 10^{-4}$ at a measurement rate of $1\,\text{MSa s}^{-1}$, without requiring complex chirp linearization techniques. We further demonstrate fiber-optic acoustic sensing capable of detecting sub-$\mu\epsilon$ dynamic strain, underscoring the platform's versatility for high-speed precision optical measurements. Our work provides a route toward cost-effective yet high-performance sensing and metrology systems.
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All authors Di Yu, Yitian Tong, Yu Xia, Yuntao Zhu, Yuemin Li, Mingfei Liu, Zhaoting Geng, Yuhao Huang, Yaoran Huang, Zheng Li, Jie Wang, Yunqi Fu, Hongjie Liang, Hao Fang, Jinwen Lin, Xuewen Chen, Kang Li, Xinlun Cai, Chao Xiang
Optics
Unified Topological Dynamics of Merging Bound States in the Continuum for High-Order Topological Charges
Keren Wang, Lujun Huang and Wei Wang
Bound states in the continuum (BICs) are polarization singularities in momentum space whose topological charges (TCs) govern advanced light-matter interactions. While
lattice symmetry protects the existence of robust BICs at the $\Gamma$-point (SP-BICs), it also restricts their TCs to low-order values. Achieving high-order TCs in common
crystal lattices, such as $C_4$-symmetric systems, has therefore remained an open question. Here, we systematically demonstrate that high-order TCs that surpass fundamental
symmetry bounds can be created through the rich dynamics of a parameter-driven merging process of off-$\Gamma$ BICs. We introduce a unified
geometric framework based on the interplay between Fabry-Pérot interference and guided resonances, which uncovers different types of merging BICs dynamics, including near-isotropic, anisotropic, and cross-merging. Leveraging this mechanism, we realize unconventional TCs of up to $\pm3$ at either a
symmetry-protected BIC or a degeneracy point in a simple $C_4$-symmetric photonic
crystal slab. We further show that this high-order
topology enables the generation of high-quality Bessel OAM beams, providing a physically transparent route toward engineering high-order topological photonics.
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Plasma Physics
Comparison of Tomographic Reconstruction Algorithms for Infrared Imaging Video Bolometer Diagnostic in Plasma Devices
Vinit Pandya, Santosh P. Pandya, Ansh Patel et al. (+2 more)
Infrared Imaging
Video Bolometer (IRVB) measures total radiation power loss from
plasma in 2 dimensions through a pinhole camera geometry. Where a free-standing thin metal foil act as a broad band absorber from Soft X-Rays to IR radiation. This configuration produces line-integrated signals with poloidal and toroidal coverage that must be inverted to recover the
plasma radiation emissivity distribution on a poloidal cross-section. This study compares the tomographic methods implemented to IRVB brightness data reconstruction, namely Minimum Fisher Information (MFI), Phillips-Tikhonov regularization (PTR), and Maximum-Likelihood Expectation-Maximization (MLEM). The comparison assessment is organized around several aspects of bolometer measurements, namely viewing geometry configuration, non-negativity, robustness to noise, sensitivity to prior assumptions, convergence speed, and peak preservation. The present work also details the IRVB forward modelling process, construction of synthetic phantoms, and a validation of these reconstruction methods based on typical expected emissivity profiles, namely symmetric Gaussian distribution at
plasma center, symmetric hollow-radiation emissivity profile, asymmetric radiation profiles across the poloidal cross-section, and divertor-side radiation emission profiles. The outcome is to emphasize the practical tradeoffs among reconstruction accuracy, numerical stability, and suitability for real-time or offline usage of these reconstruction methods, particularly for the IRVB camera viewing system.
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All authors Vinit Pandya, Santosh P. Pandya, Ansh Patel, Kumudni Tahiliani, Kumar Ajay
Instrumentation and Detectors
PyNMC: An Open-Source Framework for Neutron Multiplicity Counting Simulation Coupling OpenMC, FREYA, and ALPHANSO
Christopher Fichtlscherer
Neutron multiplicity counting (NMC) underpins plutonium assay in
nuclear safeguards, arms control, and disarmament verification, but existing simulation tools are essentially limited to MCNPX-PoliMi [1] (export-controlled, MCNP license required) and ONMS [2] (open-source but built on Geant4 with no scripting API); other codes (RMC, MCNP-PTA) are institute-internal. We present PyNMC, an open-source, Python-native NMC simulation framework that couples OpenMC for transport with FREYA for event-by-event correlated
prompt-
neutron emission and ALPHANSO for native ($\alpha$, n)-source estimates, together with collision-level time-tagged event recording and a Python shift-register post-processor cross-validated against ONMS. The framework is validated against the ESARDA
Neutron Multiplicity
Benchmark on bare $^{252}$Cf (c2-10, c2-100), the low-multiplication Pu metal case c3s (M = 1.12 from an independent k-
eigenvalue calculation; ESARDA spec M = 1.08), and a 10 g PuO2 sample with an ($\alpha$, n)-source term (c4s); an internal stress-test extension to a $\approx 100$ g Pu metal sample at M = 1.29 is reported alongside but lies beyond the ESARDA participant range. For c4s, ALPHANSO gives $\alpha$ = 0.78 with modern cross-section data; the reported
benchmark comparison rescales the ($\alpha$,n) rate to the ESARDA value $\alpha$ = 0.853. Simulated rates agree with point-model predictions for all cases, and with the published ESARDA participant-code scatter where participant results exist. The framework is shipped as a Docker container under the MIT license and is openly available on GitHub at github.com/cfichtlscherer/nmc.
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Chemical Physics
Chemical Interpretation of Time-Dependent Coupled-Cluster Theory
Aparna Krishnan, Håkon Emil Kristiansen, Benjamin G. Peyton et al. (+2 more)
While providing a highly accurate framework for simulating
laser-induced many-electron dynamics in atom and molecules, including linear and nonlinear steady-state and transient absorption spectra, time-dependent coupled-cluster theory does not offer a straightforward interpretation in chemical terms. This should be contrasted with conventional time-independent equation-of-motion coupled-cluster or frequency-dependent response models where a simple eigenvector analysis readily reveals the dominant orbital-excitation character of individual excited states. We fill this gap by expanding the left and right coupled-cluster functions in Slater-determinant basis, thus allowing for a time-dependent generalization of configuration weights that can be used to track populations throughout a simulation. The same expansions are used to decompose the time-dependent electric-dipole moment and autocorrelation function, providing a computationally straightforward approach to the assignment of absorption peaks to orbital transitions for single-reference systems. At the time-dependent coupled-cluster singles-and-doubles level of theory, we demonstrate the power of the proposed methodology by assigning valence lines in the linear absorption spectra of four ten-electron molecules (HF, H2O, NH3, and CH4) with different point-group
symmetries, validating the assignment by comparison with equation-of-motion coupled-cluster singles-and-doubles theory. In addition, core-level excitations are assigned for HF, H2O, and NH3. Finally, the usefulness of time-dependent configuration weights is illustrated by applications to an impulsive stimulated X-ray Raman scattering process in the Ne atom and to a transient pump-probe spectrum of the HF molecule.
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All authors Aparna Krishnan, Håkon Emil Kristiansen, Benjamin G. Peyton, T. Daniel Crawford, Thomas Bondo Pedersen
Fluid Dynamics
Designing single-layer PDMS devices for micron to millimeter-scale deformations
Leon V. Gebhard, Alexandre S. Avaro, Gabriel Amselem et al. (+1 more)
The elasticity of PDMS has played a central role in advancing important microfluidic technologies, ranging from early valves to sophisticated organ-on-a-chip systems. However, most deformable microfluidic devices are based on geometries that require complex multi-layer PDMS architectures and include thin membranes, leading to difficult microfabrication and poor stability. Recently, Jain, Belkadi et al. (Biofabrication 16.3 (2024): 035010) introduced a single-layer PDMS device in which a wide and long microfluidic channel was deformed by pressurizing two adjacent air chambers. While they demonstrated how the channel ceiling deformation can be leveraged to compress biological materials, it remains unknown how the device geometry influences this deformation. Here, a systematic numerical study is performed on 14,336 variants of this device, through which the height of the PDMS layer is identified as the main feature that determines the ceiling deformation. Three modes of channel deformation are identified as the geometry are varied: a U shape with a central minimum, a W shape with two minima and a central maximum, or an inverse U shape with an upward-bulging single maximum. The numerical results are validated in experiments that reproduce the three modes for the predicted geometries and demonstrate vertical ceiling deformations ranging from a few microns to the millimeter scale. The generality of this approach is demonstrated for two example applications: A fully closing single-layer microfluidic valve and an optical lens of controllable anisotropic magnification. This work leverages the rapid prototyping enabled by 3D printing or micro-milling to open new perspectives in microfluidic actuation.
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All authors Leon V. Gebhard, Alexandre S. Avaro, Gabriel Amselem, Charles N. Baroud