Tootfinder

Will we ever see the shooter again, hear anything about him, or will it be like he hardly existed, like a second page of search results?
The truth itself seems to be in more danger than potus ever was.
#USpol #WHCD

The file-based markdown version of #logseq is officially put into maintenance-only mode or rather fully retired. The software has not even reached version 1.0 and will be stopped being developed.
Sadly that's what many warned of, when the devs started working on the database version.

I just had to … ¯\_(ツ)_/¯
#shimmyshimmyya

edit_wikibooks: Wikipedia book edits (2010)
Two bipartite user-page networks extracted from Wikipedia, about books. A user connects to a page if that user edited that page. Edits (edges) are timestamped. Edge weights represent counts of the number of edits.
This network has 960 nodes and 1308 edges.
Tags: Informational, Web graph, Multigraph, Timestamps

Allies of the Trump administration
are reportedly circulating a document
that they say would grant the president sweeping powers over elections,
including the ability to ban mail-in ballots,
by declaring a national emergency
over disproven allegations of interference by China in the 2020 election,
a new Washington Post report finds.
Right-wing activists who claim to be in contact with the White House
have drafted a 17-page executive order
…

Draft Order to Declare National Emergency on Elections Circulating Trump Allies
The draft is written to allow Trump to label mail-in ballots and voting machines as agents of foreign influence.

[2026-03-27 Fri (UTC), 8 new articles found for physics.chem-ph Chemical Physics]
toXiv_bot_toot

does anybody happen to know if the results of the #europeana Linked Data Task Force have been published somewhere?
This page here https://pro.europeana.eu/index.php/projec…

Full Single-Quantum Control of Particles in Penning Traps for Symmetry Tests at the Quantum Limit
J. M. Cornejo, J. -A. Coenders, A. Lissel, N. Poljakov, M. Prasse, Y. Priewich, J. Schaper, M. Schubert, B. Hampel, M. Schilling, S. Ulmer, C. Ospelkaus
https://arxiv.org/abs/2602.22802

Replaced article(s) found for physics.ao-ph. https://arxiv.org/list/physics.ao-ph/new
[1/1]:
- Smoothing and spatial verification of global fields
Gregor Skok, Katarina Kosovelj
https://arxiv.org/abs/2412.00936 https://mastoxiv.page/@arXiv_physicsaoph_bot/113587890587543610
- Radiosonde-constrained reconstructions reveal a weakening Northern Hadley circulation
Matic Pikovnik, \v{Z}iga Zaplotnik
https://arxiv.org/abs/2503.05331 https://mastoxiv.page/@arXiv_physicsaoph_bot/114137034331234752
- Non-stationary time series attribution for heatwaves over Europe
Pascal Meurer, Sebastian Buschow, Svenja Szemkus, Petra Friederichs
https://arxiv.org/abs/2601.05841 https://mastoxiv.page/@arXiv_physicsaoph_bot/115881278944409798
- Enabling High-Accuracy Data Assimilation with Limited Ensembles via Machine Learning-Based Covari...
Zhou Yao, Zhilin Li, Li Zhao, Zeng Liu, Zhaokuan Lu, Seungnam Kim, Guangyao Wang
https://arxiv.org/abs/2605.11639 https://mastoxiv.page/@arXiv_physicsaoph_bot/116566237831166337
toXiv_bot_toot

📰 Vielen Dank für Eure #Spenden zur Unterstützung der Technikkosten, um alles am Laufen zu halten. Shoutout an alle #Steady-Förderer! 👍
Es geht los: Die vermaledeiten Amazon-Affiliate-Links werden seit Februar schrittweise gelöscht.
Hier kann man Steady-Mäzen werden:

KlimaCrew
Ich informiere über Zukunftsthemen, um Menschen vor Risiken zu warnen und Fortschritte sichtbar zu machen.

Modular interpretation of the Weil-Petersson metric asymptotics for abelian varieties
Andres Gomez
https://arxiv.org/abs/2602.23140 https://arxiv.org/pdf/2602.23140 https://arxiv.org/html/2602.23140
arXiv:2602.23140v1 Announce Type: new
Abstract: As a first step towards a refined description of the asymptotic of the Weil-Petersson metric on the moduli space of polarized Calabi-Yau manifolds we investigate the concrete case of abelian varieties by linking such asymptotic with the multi-scale collapsing limits of the parametrized flat tori, as explicitly classified by Odaka.
toXiv_bot_toot

Introducing pixelation with applications
J. Daisie Rock
https://arxiv.org/abs/2603.25432 https://arxiv.org/pdf/2603.25432 https://arxiv.org/html/2603.25432
arXiv:2603.25432v1 Announce Type: new
Abstract: Motivated by the desire for a new kind of approximation, we define a type of localization called pixelation. We present how pixelation manifests in representation theory and in the study of sites and sheaves. A path category is constructed from a set, a collection of "paths" into the set, and an equivalence relation on the paths. A screen is a partition of the set that respects the paths and equivalence relation. For a commutative ring, we also enrich the path category over its modules (=linearize the category with respect to the ring) and quotient by an ideal generated by paths (possibly 0). The pixelation is the localization of a path category, or the enriched quotient, with respect to a screen. The localization has useful properties and serves as an approximation of the original category. As applications, we use pixelations to provide a new point of view of the Zariski topology of localized ring spectra, provide a parallel story to a ringed space and sheaves of modules, and construct a categorical generalization of higher Auslander algebras of type $A$.
toXiv_bot_toot

Hidden Higher-Order Vulnerabilities in Simplicial Complexes Revealed by Branch-Consistent Functional Robustness
Kaiming Luo
https://arxiv.org/abs/2603.24286 https://arxiv.org/pdf/2603.24286 https://arxiv.org/html/2603.24286
arXiv:2603.24286v1 Announce Type: new
Abstract: Robustness of higher-order networks is often quantified by the instantaneous smallest positive eigenvalue of the Hodge $1$-Laplacian under simplex deletion. We show that this observable is generically ill-defined: along a deletion trajectory, eigenvalue branches can switch, so the quantity being monitored may correspond to different nonharmonic modes at different steps. The primary issue is therefore definitional rather than algorithmic. We resolve it by fixing the first nonharmonic branch of the intact complex and following that same branch throughout the damage process, which defines a branch-consistent functional robustness. Triangle sensitivities then follow directly from first-order perturbation theory, making the resulting mode-sensitive deletion protocol a consequence of the observable itself rather than an independent heuristic. Across synthetic and empirical clique complexes, removing only a small fraction of triangles is sufficient to drive the tracked mode to collapse, while graph-level observables remain unchanged because the $1$-skeleton is exactly preserved. The same framework also reveals bridge-like localization of functionally critical simplices and provides a compact predictor of dynamical timescales.
toXiv_bot_toot

From synthetic turbulence to true solutions: A deep diffusion model for discovering periodic orbits in the Navier-Stokes equations
Jeremy P Parker, Tobias M Schneider
https://arxiv.org/abs/2602.23181 https://arxiv.org/pdf/2602.23181 https://arxiv.org/html/2602.23181
arXiv:2602.23181v1 Announce Type: new
Abstract: Generative artificial intelligence has shown remarkable success in synthesizing data that mimic complex real-world systems, but its potential role in the discovery of mathematically meaningful structures in physical models remains underexplored. In this work, we demonstrate how a generative diffusion model can be used to uncover previously unknown solutions of a nonlinear partial differential equation: the two-dimensional Navier-Stokes equations in a turbulent regime. Trained on data from a direct numerical simulation of turbulence, the model learns to generate time series that resemble physically plausible trajectories. By carefully modifying the temporal structure of the model and enforcing the symmetries of the governing equations, we produce synthetic trajectories that are periodic in time, despite the fact that the training data did not contain periodic trajectories. These synthetic trajectories are then refined into true solutions using an iterative solver, yielding 111 new periodic orbits (POs) with very short periods. Our results reveal a previously unobserved richness in the PO structure of this system and suggest a broader role for generative AI: not as replacements for simulation and existing solvers, but as a complementary tool for navigating the complex solution spaces of nonlinear dynamical systems.
toXiv_bot_toot

The mediocrity of well-paid people whose only job is to make the line go up is really something to behold.
#KLM #inspirationalUpsellHeader #inspirationalUpsellToggle…

Diffusion in interacting two-dimensional systems under a uniform magnetic field
{\L}ukasz Iwanek, Marcin Mierzejewski, Adam S. Sajna
https://arxiv.org/abs/2603.25659 https://

Ahh I just noticed that when I import GPX tracks into #wanderer, it creates routes but no activity. That's why my stats page is empty (and as I found it out, I remember that I asked that... A long while ago).
Now I wonder, if I want to import and add the activities for 2026... Doing it retrospectively for 2025 is too much effort to me (with too little value). 🤔

RE: https://mastodon.social/@arstechnica/116618619694373891
“‘To cut and paste page by page, the text from each page would have been an hour’s worth of work, of mindless cutting and pasting. ChatGPT did it in about four seconds.’
To which the obv…

Application of the aperiodic defect model to a negatively charged monovacancy in phosphorene
Charlotte Rickert, Lily Barta, Ernst-Christian Flach, Daniel Kats, Denis Usvyat
https://arxiv.org/abs/2603.23761 https://arxiv.org/pdf/2603.23761 https://arxiv.org/html/2603.23761
arXiv:2603.23761v1 Announce Type: new
Abstract: We apply the recently introduced aperiodic defect model (ADM) to a negatively charged monovacancy in a phosphorene monolayer. In contrast to conventional supercell approaches, the ADM treats a single defect embedded in the true non-defective crystalline mean field thereby avoiding spurious defect-defect interactions and the need for charge corrections. At the same time, it effectively reduces the calculation to a fragment, enabling the use of high-level molecular electronic-structure methods. Converging the Hartree-Fock and correlation contributions to the thermodynamic limit yields a benchmark CCSD(T)/POB-TZVP-rev2 formation energy of 0.91 eV for the negatively charged monovacancy in the (5|9) configuration. The excitation energy to the lowest singlet excited state of this defect at the EOM-CCSD/POB-TZVP-rev2 level is found to be 1.95 eV. Overall, the ADM provides a highly promising route towards quantitatively accurate and systematically improvable descriptions of defects in solids and on surfaces, bridging the gap between solid-state physics and molecular quantum chemistry.
toXiv_bot_toot

Stabilization of Rydberg Dissipative Time Crystals Using a Scanning Fabry Perot Interferometer Transfer Lock
Darmindra Arumugam, Brook Feyissa
https://arxiv.org/abs/2602.22498 h…

Calibrations for the Sasaki volume on odd spheres and the no-gap problem
Jonas Matuzas
https://arxiv.org/abs/2602.22961 https://arxiv.org/pdf/2602.22961 https://arxiv.org/html/2602.22961
arXiv:2602.22961v1 Announce Type: new
Abstract: For each odd sphere $S^{n}$ with $n=2m 1\ge 5$, we consider the Sasaki volume functional $\mathrm{Vol}^S(V)=\int_{S^{n}}\sqrt{\det(I (\nabla V)^{\top}(\nabla V))}\,d\mathrm{vol}$ on smooth unit tangent vector fields $V$. Using the Brito--Chacon--Naveira calibration $\omega=a\wedge\Theta$ on the unit tangent bundle $E=UTS^{n}$, we establish the universal calibrated lower bound $\mathrm{Vol}^S(V)\ge c(m;1)\,\mathrm{vol}(S^{n})$, where $c(m;1)=4^{m}/\binom{2m}{m}$. In the relaxed (integral-current) setting, we show that the section-constrained stable mass in $E$ equals the calibration value and is attained by an $\omega$-calibrated mass-minimizing integral $n$-cycle in the section class.
We also analyze the equality case on smooth graphs. If a smooth graph is $\omega$-calibrated on an open set, then it satisfies the rigidity system $\nabla_V V=0$ and $\nabla_X V=\lambda X$ for all $X\perp V$, hence is locally a radial distance-gradient field. In particular, for $m\ge 2$ there is no smooth unit field on $S^n$ whose graph is $\omega$-calibrated everywhere.
Finally, we construct an explicit smooth recovery sequence (presented in detail for $S^5$ and then extended to all odd dimensions) and prove a uniform nonvanishing estimate for the polar-shell normalization in the patching construction. As a consequence, $\inf_{V}\,\mathrm{Vol}^S(V)=c(m;1)\,\mathrm{vol}(S^{n})$, so there is no Lavrentiev gap.
toXiv_bot_toot

Nonlocal-coupling-based control of coherence resonance in an ensemble of non-excitable oscillators
Aleksey Ryabov, Vladimir V. Semenov
https://arxiv.org/abs/2603.24210 https://arxiv.org/pdf/2603.24210 https://arxiv.org/html/2603.24210
arXiv:2603.24210v1 Announce Type: new
Abstract: It is shown that nonlocal coupling provides for controlling the collective noise-induced dynamics of non-excitable oscillators in the regime of coherence resonance. This effect is demonstrated by means of numerical simulation on an example of coupled generalized Van der Pol oscillators near the saddle-node bifurcation of limit cycles. In particular, it has been established that increasing the coupling radius allows to enhance the effect of coherence resonance which is reflected in the evolution of the dependence of the correlation time on the noise intensity and the power spectrum transformations. Nonlocal coupling is considered as an intermediate option between local and global coupling topologies which are also discussed as a tool for controlling coherence resonance.
toXiv_bot_toot

On the spatial structure and intermittency of soot in a lab-scale gas turbine combustor: Insights from large-eddy simulations
Leonardo Pachano, Daniel Mira, Abhijit Kalbhor, Jeroen van Oijen
https://arxiv.org/abs/2602.23155 https://arxiv.org/pdf/2602.23155 https://arxiv.org/html/2602.23155
arXiv:2602.23155v1 Announce Type: new
Abstract: This work presents a numerical investigation of soot formation in the Cambridge lab-scale gas turbine combustor. Large-eddy simulations (LES) of a swirl-stabilized ethylene flame are performed using the flamelet generated manifold method coupled with a discrete sectional model to account for soot formation, growth, and oxidation. The study aims to elucidate the mechanism governing the spatial structure and intermittency of soot, supported by comparisons with experimental data. The predicted soot distribution agrees well with measurements, with peak concentrations near the bluff body. Flow recirculation is identified as the key mechanism driving soot accumulation in fuel-rich regions, where surface reactions dominate soot mass growth. Soot intermittency arises from fluctuations in the flow field driven by interactions between the flame front and the recirculation vortex. Two soot modeling approaches are evaluated, differing in their treatment of soot model quantities: the first approach employs on-the-fly computation of source terms (FGM-C), while the second uses fully pre-tabulated source terms (FGM-T). Their predictive performance and computational cost are compared in the context of unsteady, sooting flames in swirl-stabilized combustors.
toXiv_bot_toot

Lagged sea-surface-temperature precursors of the leading PM2.5 mode in China
Yuan Chen, Dan Zhao, Xu Li
https://arxiv.org/abs/2605.25436 https://arxiv.org/pdf/2605.25436 https://arxiv.org/html/2605.25436
arXiv:2605.25436v1 Announce Type: new
Abstract: Fine particulate matter(PM2.5) pollution in China is strongly modulated bymeteorological variability, yet its seasonal predictability from oceanic signals remains unclear. Here we identify the leading PM2.5 variability mode over China and show that it is preceded by coherent sea-surface-temperature anomaly clusters by more than one season. These oceanic precursors influence summer PM2.5 mainly by altering precipitation and lowlevel ventilation, and winter PM2.5 by modulating boundary-layer height and near-surface stagnation. Using the four largest precursor regions, a simple regression model achieves significant independent prediction skill for both summer and winter PM2.5 variability. Our results reveal a physical pathway linking sea-surface-temperature memory to regional aerosol pollution and provide a basis for seasonal air-quality risk assessment.
toXiv_bot_toot

[2026-03-27 Fri (UTC), 8 new articles found for physics.chem-ph Chemical Physics]
toXiv_bot_toot

webkb: WebKB graphs (1998)
Web graphs crawled from four Computer Science departments in 1998, with each page manually classified into one of 7 categories: course, department, faculty, project, staff, student, or other. All graphs included in a single .zip; also included are 'co-citation' graphs, which links i and j if they both point to some k. Edge weights count the number of links from i to j.
This network has 286 nodes and 1002 edges.
Tags: Informational, Web gra…

[2026-02-27 Fri (UTC), 2 new articles found for physics.atom-ph Atomic Physics]
toXiv_bot_toot

Josephson effects in an interaction-asymmetric junction across the BCS-BEC crossover
Tingyu Zhang, Hiroyuki Tajima
https://arxiv.org/abs/2603.25577 https://

Application of the aperiodic defect model to a negatively charged monovacancy in phosphorene
Charlotte Rickert, Lily Barta, Ernst-Christian Flach, Daniel Kats, Denis Usvyat
https://arxiv.org/abs/2603.23761

[2026-03-26 Thu (UTC), 2 new articles found for nlin.AO Adaptation and Self-Organizing Systems]
toXiv_bot_toot

Acoustic Signatures of Pinch-Off Cavities During Water-Entry
Zirui Liu, Tongtong Ding, Mingyue Kuang, Zimeng Li, Junyi Zhao, A-Man Zhang, Shuai Li
https://arxiv.org/abs/2602.22761 https://arxiv.org/pdf/2602.22761 https://arxiv.org/html/2602.22761
arXiv:2602.22761v1 Announce Type: new
Abstract: This study experimentally, numerically, and theoretically investigates the cavity/bubble dynamics and radiated acoustics during the water entry of a centimeter-scale cylindrical projectile with a conical nose. Experiments were conducted in a laboratory tank, employing synchronized high-speed imaging and hydrophone measurements to characterize the cavity closure modes and their resultant acoustic signatures across a range of Froude numbers. The acoustic signal features a weak radiated signal upon impact, followed by significant pressure oscillations spanning more than 20 cycles in the flow field after cavity elongation and pinch-off. A numerical model based on the Finite Volume Method (FVM) successfully captures these physical processes. Subsequently, a semi-theoretical model that incorporates the projectile's boundary effect is developed from potential flow theory. The model not only yields a dominant cavity oscillation frequency that agrees well with experimental data, but also reveals that the boundary effect leads to a cavity oscillation frequency markedly higher than the Minnaert frequency of an equivalent-volume ellipsoidal bubble containing an internal rigid core. The dominant cavity frequency falls nearly linearly with Fr, governed by nose geometry and projectile inertia. This study clarifies the underlying physics connecting cavity dynamics during water entry to underwater acoustic radiation.
toXiv_bot_toot

JAX-SCM v1.0: a modern atmospheric single-column model for boundary layer research
Maximilian Pierzyna
https://arxiv.org/abs/2605.24544 https://arxiv.org/pdf/2605.24544 https://arxiv.org/html/2605.24544
arXiv:2605.24544v1 Announce Type: new
Abstract: We present JAX-SCM v1.0, an open-source atmospheric single-column model for boundary layer research, implemented in Python using the JAX computing library. The model solves for horizontal wind, potential temperature, and specific humidity, combined with prognostic turbulent kinetic energy and turbulent statistics parameterized by the Mellor-Yamada-Nakanishi-Niino level-2.5 (MYNN-2.5) turbulence closure. We verify the implementation against three well-established benchmark cases covering neutral (turbulent Ekman layer), stable (GABLS1), and convective (Wangara Day 33) conditions. Close agreement with reference solutions is demonstrated across all regimes. By building on JAX, the model benefits from just-in-time compilation and native GPU support. While JAX-SCM is not yet fully differentiable, basing it on JAX also lays the foundation for future integration with machine learning components. The model is designed for simplicity and modularity, lowering the barrier to entry for users and developers alike.
toXiv_bot_toot

Replaced article(s) found for physics.atom-ph. https://arxiv.org/list/physics.atom-ph/new
[1/1]:
- Time-resolving the birth of photoelectrons in strong-filed ionization with an isolated attosecond...
Kunlong Liu, Yidian Tian, Pengcheng Li

Kelvin wave and soliton propagation in classical viscous vortex filaments
Elio Sterkers, Giorgio Krstulovic
https://arxiv.org/abs/2602.22439 https://arxiv.org/pdf/2602.22439 https://arxiv.org/html/2602.22439
arXiv:2602.22439v1 Announce Type: new
Abstract: Vortex filaments are highly rotating localized structures of fluids that admits several types of excitation. Here, we study them by using numerical simulations of the three-dimensional incompressible Navier-Stokes equations. We first address the propagation of Kelvin waves, helicoidal excitations propagating along the filament, and measure their dispersion relation which turns out to be in good agreement with the original Lord Kelvin predictions. Then, inspired by the connection between vortex line dynamics and an integrable system, we show numerically the existence of solitons propagating along vortex filaments and study the collision of two of such structures. Finally, we show numerically the experimental feasibility of studying vortex solitons in the lab, by proposing an experiment for their generation.
toXiv_bot_toot

Crosslisted article(s) found for physics.atom-ph. https://arxiv.org/list/physics.atom-ph/new
[1/1]:
- Toward nanophotonic platforms for solid-state $^{229}$Th nuclear clocks
Sandro Kraemer, et al.

Seeing Inside the Storm: Improving Nowcasting by Integrating Meteorological Drivers
Minghui Qiu, Jun Chen, Lin Chen, Weifeng Chen, Shuxin Zhong, Zhidan Liu, Yu Zhang, Kaishun Wu
https://arxiv.org/abs/2605.24067 https://arxiv.org/pdf/2605.24067 https://arxiv.org/html/2605.24067
arXiv:2605.24067v1 Announce Type: new
Abstract: Most nowcasting systems, built on radar reflectivity, focus on current precipitation, ignoring the atmospheric precursors -- such as low-level convergence, turbulent eddies, and latent heating -- that offer a fleeting window to foresee storm birth. We introduce MeteoLogist, a physics-inspired radar intelligence framework that models the full life cycle of convection -- from its precursors to organized storm evolution. However, exploiting these precursors is non-trivial: they originate from multiple meteorological drivers -- thermodynamic, kinematic, and microphysical -- that evolve asynchronously (C1) and remain spatially fragmented (C2). To this end, MeteoLogist designs three tightly integrated components. The Physics-Tailored Encoders process radar echoes according to their intrinsic physical scales and semantics, forming thermodynamic, kinematic, and microphysical streams that capture distinct dynamical regimes. The Temporal-Phase Aligner addresses C1 by leveraging causal temporal attention to capture when and how different drivers interact and activate. The Cross-Field Spatial Aggregator addresses C2 through cross-regional fusion, aligning weak and scattered precursors across neighboring cells to expose upstream triggers and enforce spatial coherence. Evaluated on 3D-NEXRAD (2020--2022, US-wide), MeteoLogist boosts high-impact detection (CSI40) by 9.7% over strong baselines, and achieves a remarkable 37.67% gain during the storm-developing stage -- demonstrating true foresight in sensing storms before they appear. The code can be found in the supplementary material.
toXiv_bot_toot

[2026-02-27 Fri (UTC), 4 new articles found for physics.flu-dyn Fluid Dynamics]
toXiv_bot_toot

Automating Computational Chemistry Workflows via OpenClaw and Domain-Specific Skills
Mingwei Ding, Chen Huang, Yibo Hu, Yifan Li, Zitian Lu, Xingtai Yu, Duo Zhang, Wenxi Zhai, Tong Zhu, Qiangqiang Gu, Jinzhe Zeng
https://arxiv.org/abs/2603.25522 https://arxiv.org/pdf/2603.25522 https://arxiv.org/html/2603.25522
arXiv:2603.25522v1 Announce Type: new
Abstract: Automating multistep computational chemistry tasks remains challenging because reasoning, workflow specification, software execution, and high-performance computing (HPC) execution are often tightly coupled. We demonstrate a decoupled agent-skill design for computational chemistry automation leveraging OpenClaw. Specifically, OpenClaw provides centralized control and supervision; schema-defined planning skills translate scientific goals into executable task specifications; domain skills encapsulate specific computational chemistry procedures; and DPDispatcher manages job execution across heterogeneous HPC environments. In a molecular dynamics (MD) case study of methane oxidation, the system completed cross-tool execution, bounded recovery from runtime failures, and reaction network extraction, illustrating a scalable and maintainable approach to multistep computational chemistry automation.
toXiv_bot_toot

Volador 1.0: A Data-Driven Air-Sea Full-Coupling Regional Forecast Model with Submesoscale-Permitting Based on MOE-Swin-Transformer Framework
Yuhang Zhu, Jianxin Wang, Yu-kun Qian, Yineng Li, Yahui Liu, Yankun Gong, Shilin Tang, Shiqiu Peng, Tao Song
https://arxiv.org/abs/2605.24032 https://arxiv.org/pdf/2605.24032 https://arxiv.org/html/2605.24032
arXiv:2605.24032v1 Announce Type: new
Abstract: A data-driven air-sea full-coupling regional forecast model with submesoscale-permitting, named "Volador 1.0", is developed for the South China Sea (SCS). The model features a Swin-Transformer framework integrated with a Mixture-of-Experts (MoE) system, a latent space interaction architecture based on Cross-Grid Bidirectional Cross-Attention, and a fast-slow dual-branch architecture. Both the three-month hindcast test and the 15-day operational real-time forecasting demonstrate that Volador 1.0 has a very encouraging and promising performance in 0-72h forecasting of temperature and salinity in the 0-500m upper ocean as well as the sea surface height with root-mean-square-error (RMSE) or mean absolute error (MAE) smaller than or at least comparable to those from the reanalysis datasets REDOS V2.0 and GLORYS12 and the state-of-the-art regional numerical model Regional Ocean Modeling System (ROMS). In particular, Volador 1.0 demonstrates its capability of capturing/forecasting submesoscale processes including internal waves, with an energy spectrum well representing sub- to mesoscale energy cascade as expected by the classical turbulence theory. Further analysis based on ablation experiments shows that the air-sea full-coupling framework, which takes into account the dynamic exchanges of momentum and heat fluxes between the atmosphere and the ocean, indeed helps improve the model's performance compared to the non-full-coupling one. Volador 1.0, though still subject to refinement in the coming future with a large space for improvement, blazes a path for an accurate, fine and fast marine environment forecasting, and thus could help promote our capability of disaster prevention and mitigation in the SCS as well as in other coastal regions where these innovative techniques can be applied.
toXiv_bot_toot

Crosslisted article(s) found for physics.atom-ph. https://arxiv.org/list/physics.atom-ph/new
[1/1]:
- Atomic-referenced Hz-linewidth lasers via fiber interferometric stabilization
Changmin Ahn, Hansol Jeong, Seoyeon Yang, Junyong Choi, Igju Jeon, Hanseb Moon, Jungwon Kim

From synthetic turbulence to true solutions: A deep diffusion model for discovering periodic orbits in the Navier-Stokes equations
Jeremy P Parker, Tobias M Schneider
https://arxiv.org/abs/2602.23181

Enabling ab initio geometry optimization of strongly correlated systems with transferable deep quantum Monte Carlo
P. Bern\'at Szab\'o, Zeno Sch\"atzle, Frank No\'e
https://arxiv.org/abs/2603.25381 https://arxiv.org/pdf/2603.25381 https://arxiv.org/html/2603.25381
arXiv:2603.25381v1 Announce Type: new
Abstract: A faithful description of chemical processes requires exploring extended regions of the molecular potential energy surface (PES), which remains challenging for strongly correlated systems. Transferable deep-learning variational Monte Carlo (VMC) offers a promising route by efficiently solving the electronic Schr\"odinger equation jointly across molecular geometries at consistently high accuracy, yet its stochastic nature renders direct exploration of molecular configuration space nontrivial. Here, we present a framework for highly accurate ab initio exploration of PESs that combines transferable deep-learning VMC with a cost-effective estimation of energies, forces, and Hessians. By continuously sampling nuclear configurations during VMC optimization of electronic wave functions, we obtain transferable descriptions that achieve zero-shot chemical accuracy within chemically relevant distributions of molecular geometries. Throughout the subsequent characterization of molecular configuration space, the PES is evaluated only sparsely, with local approximations constructed by estimating VMC energies and forces at sampled geometries and aggregating the resulting noisy data using Gaussian process regression. Our method enables accurate and efficient exploration of complex PES landscapes, including structure relaxation, transition-state searches, and minimum-energy pathways, for both ground and excited states. This opens the door to studying bond breaking, formation, and large structural rearrangements in systems with pronounced multi-reference character.
toXiv_bot_toot

Improving Ensemble CAPE Forecasts with a Diffusion Model Incorporating Aerosol Information
Zachary James, Joseph Guinness, Arthur DeGaetano
https://arxiv.org/abs/2605.24009 https://arxiv.org/pdf/2605.24009 https://arxiv.org/html/2605.24009
arXiv:2605.24009v1 Announce Type: new
Abstract: Convective available potential energy (CAPE) is an important variable for forecasting severe weather and understanding deep convection and precipitation. The latest versions of the Global Forecast System (GFS) and related Global Ensemble Forecast System (GEFS) have exhibited a bias towards underestimating CAPE values during the summertime. We train an artificial intelligence (AI) diffusion model to improve the skill and uncertainty quantification of afternoon 6-hour lead time ensemble forecasts over the United States. Our model takes a GFS CAPE forecast as input and outputs an ensemble that significantly outperforms both GFS and GEFS 6-hour forecasts on root mean square error, continuous ranked probability score, and Brier score. We propose a two-stage training pipeline to leverage both a larger historical GFS forecast dataset and a smaller historical GEFS dataset, despite the two using initialization and parameterization schemes that vary over time. We also show that classifier-free guidance can be used to control the skill and spread of the forecasts. We then demonstrate the versatility of our framework by adding aerosol optical depths (AODs) of black carbon, organic carbon, dust, sea salt, and sulfates as additional input features. Aerosols can invigorate or suppress convection depending on atmospheric conditions. Our AI models effectively incorporate aerosols to produce improved CAPE forecasts. We interpret the model components by using permutation feature importance to rank the influence of the different AODs and find that black carbon, organic carbon, and sulfate aerosols have a greater impact on the model's CAPE predictions than sea salt and dust aerosols.
toXiv_bot_toot

Experimental and theoretical studies of hyperfine structures in $^{21}$Na
Junho Won, Jeongsu Ha, Deuk Soon Ahn, Sunghoon Ahn, Vivek Chavan, Anastasiia Chekhovska, Gyoungmo Gu, Kevin Insik Hahn, Seongjin Heo, Jangyong Huh, Dahee Kim, Do Gyun Kim, Dong Geon Kim, Jung Bog Kim, Sunji Kim, Yeong Seok Kim, Yung Hee Kim, Zeren Korkulu, Donghyeon Kwak, Jens Lassen, Jin Ho Lee, Jung Woo Lee, Chaeyeong Lim, Joochun Park, Ben Ohayon, Sung Jong Park, Xesus Pereira-Lopez, Peter Plattner, Sung Jae P…

On the spatial structure and intermittency of soot in a lab-scale gas turbine combustor: Insights from large-eddy simulations
Leonardo Pachano, Daniel Mira, Abhijit Kalbhor, Jeroen van Oijen
https://arxiv.org/abs/2602.23155

Complementary Eigen-Zundel Interpretation Reconciles Thermodynamics and Spectroscopy of Excess Protons in Aqueous HF Solutions
Louis Lehmann, Florian N. Br\"unig, Jonathan Scherlitzki, Morten Lehmann, Martin Kaupp, Beate Paulus, Roland R. Netz
https://arxiv.org/abs/2603.25371 https://arxiv.org/pdf/2603.25371 https://arxiv.org/html/2603.25371
arXiv:2603.25371v1 Announce Type: new
Abstract: Aqueous solutions of HF and HCl behave very differently at intermediate concentrations: HCl dissociates completely, whereas HF remains only partially dissociated and forms bifluoride (HF$_2^-$). This should lead to different excess-proton spectra in HF and HCl solutions, in contrast to experimental reports. Using ab initio molecular dynamics, we show that in HF the proton is not firmly bound to F$^-$, as suggested by textbook chemistry, but dynamically shared with a hydrating water molecule. This is rationalized by a modified Eigen-state description which also explains the formation of HF$_2^-$. The similar vibrational spectra of HF and HCl solutions are explained by a complementary Zundel picture in terms of almost identical excess proton transfer free-energy profiles for HF and HCl. These results reconcile thermodynamic and spectroscopic observations and provide a unified microscopic picture of excess protons in aqueous solution.
toXiv_bot_toot

Quantification of atmospheric carbon dioxide from the Geostationary Operational Environmental Satellite (GOES East)
Aaron Sonabend-W, Sean Campbell, John Platt, Christopher Van Arsdale, Anna M. Michalak
https://arxiv.org/abs/2605.23991 https://arxiv.org/pdf/2605.23991 https://arxiv.org/html/2605.23991
arXiv:2605.23991v1 Announce Type: new
Abstract: 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 for inferring 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 at 16 wavelengths at an approximately 2$km^2$ spatial resolution. Here, we leverage this high spatial coverage and temporal revisit to develop a single-pixel, physics-guided neural network to estimate dry-air column $CO_2$ mole fraction ($XCO_2$). The model 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. Training used collocated GOES-East and OCO-2/OCO-3 observations. We also present case studies illustrating the use of the model 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.
toXiv_bot_toot

Acoustic Signatures of Pinch-Off Cavities During Water-Entry
Zirui Liu, Tongtong Ding, Mingyue Kuang, Zimeng Li, Junyi Zhao, A-Man Zhang, Shuai Li
https://arxiv.org/abs/2602.22761

Deep learning of committor and explainable artificial intelligence analysis for identifying reaction coordinates
Toshifumi Mori, Kei-ichi Okazaki, Kang Kim, Nobuyuki Matubayasi
https://arxiv.org/abs/2603.25237 https://arxiv.org/pdf/2603.25237 https://arxiv.org/html/2603.25237
arXiv:2603.25237v1 Announce Type: new
Abstract: In complex molecular systems, the reaction coordinate (RC) that characterizes transition pathways is essential to understand underlying molecular mechanisms. This review surveys a framework for identifying the RC by applying deep learning to the committor, which provides the most reliable measure of the progress along a transition path. The inputs to the neural network are collective variables (CVs) expressed as functions of atomic coordinates of the system, and the corresponding RC is predicted as the output by training the network on the committor as the learning target. Because deep learning models typically operate in a black-box manner, it is difficult to determine which input variables govern the predictions. The incorporation of eXplainable Artificial Intelligence (XAI) techniques enables quantitative assessment of the contributions of individual input variables to the predictions. This approach allows the identification of CVs that play dominant roles and demonstrates that the committor distribution on the surface using important CVs is separated by well-defined boundaries. The framework provides an explainable deep learning strategy for assigning a molecular mechanism from the RC and is applicable to a wide range of complex molecular systems.
toXiv_bot_toot

Crosslisted article(s) found for physics.atom-ph. https://arxiv.org/list/physics.atom-ph/new
[1/1]:
- Non-equilibrium pathway to mesoscale ordering in ethanol-water binary liquid
Xinyue Jiang, Yating Shang, Jianhui Li, Zhaoyong Zou, Yanxia Zuo, Yuqun Xie

[2026-05-26 Tue (UTC), 6 new articles found for physics.ao-ph Atmospheric and Oceanic Physics]
toXiv_bot_toot

Kelvin wave and soliton propagation in classical viscous vortex filaments
Elio Sterkers, Giorgio Krstulovic
https://arxiv.org/abs/2602.22439 https://arxiv.…

A sustainable photocatalytic pathway for concurrent hydrogen and value-added chemical production utilizing microalgae as bio-scavenger in water
Ho Truong Nam Hai, Augusto Ducati Luchessi, Kaveh Edalati
https://arxiv.org/abs/2603.24924 https://arxiv.org/pdf/2603.24924 https://arxiv.org/html/2603.24924
arXiv:2603.24924v1 Announce Type: new
Abstract: Microalgae are an abundant bioorganic material source and play a significant role in life on Earth by conducting photosynthesis for carbon dioxide (CO2) capture and its conversion to oxygen (O2). In this study, a combination of microalgae as a negative-CO2-emitting sacrificial agent with the traditional photocatalytic water-splitting process using brookite TiO2, as a model photocatalyst, is introduced as a new strategy to maximize green hydrogen (H2) production while converting microalgae to valuable products, like methane (CH4) and carbon monoxide (CO). The process, under optimal conditions, produces up to 0.990 mmol/g.h of H2 without cocatalyst addition and 3.200 mmol/g.h with platinum (Pt) cocatalyst, which is 13 times higher than the production rate without microalgae. The strategy of using microalgae in photocatalysis has high potential in green H2 production, as it not only eliminates valuable hole sacrificial agents, like alcohol, but also produces other useful compounds, like CH4 and CO. Moreover, this sustainable process contributes to CO2 capture and conversion during microalgae cultivation.
toXiv_bot_toot

Self-calibrated multiparameter measurement of three-dimensional microwave fields
Yupeng Wang, Xinghan Wang, Aishik Panja, Md. Ehsanuzzaman, Chuan-Hsun Li, Qi-Yu Liang
https://arxiv.org/abs/2605.26098

[2026-02-27 Fri (UTC), 4 new articles found for physics.flu-dyn Fluid Dynamics]
toXiv_bot_toot

Implementation of the multigrid Gaussian-Plane-Wave algorithm with GPU acceleration in PySCF
Rui Li, Xing Zhang, Qiming Sun, Yuanheng Wang, Junjie Yang, Garnet Kin-Lic Chan
https://arxiv.org/abs/2603.24881 https://arxiv.org/pdf/2603.24881 https://arxiv.org/html/2603.24881
arXiv:2603.24881v1 Announce Type: new
Abstract: We introduce a GPU-accelerated multigrid Gaussian-Plane-Wave density fitting (FFTDF) approach for efficient Fock builds and nuclear gradient evaluations within Kohn-Sham density functional theory, as implemented in the GPU4PySCF module of PySCF. Our CUDA kernels employ a grid-based parallelization strategy for contracting Gaussian basis function pairs and achieve up to 80% of the FP64 peak performance on NVIDIA GPUs, with no loss of efficiency for high angular momentum (up to f-shell) functions. Benchmark calculations on molecules and solids with up to 1536 atoms and 20480 basis functions show up to 25x speedup on an H100 GPU relative to the CPU implementation on a 28-core shared memory node. For a 256-water cluster, the ground-state energy and nuclear gradients can be computed in ~30 seconds on a single H100 GPU. This implementation serves as an open-source foundation for many applications, such as ab initio molecular dynamics and high-throughput calculations.
toXiv_bot_toot

Emergent conservation in atmospheric chemical mechanisms
Beatriz Lucia G. Rodriguez, Patrick Obin Sturm, Daniel Getter, Sam J. Silva
https://arxiv.org/abs/2605.27271 https://

From Vintage Mythology to Topological Physics: Unveiling a Universal Structural Attractor in Alcoholic Beverage Aging
Xinyue Jiang, Heng Yang, Zhiyin Jiu, Youxi Luo, Lin Chen, Yuqun Xie
https://arxiv.org/abs/2605.25472

Permeation of hydrogen across graphdiyne: molecular dynamics vs. quantum simulations and role of membrane motion
Mateo Rodr\'iguez, Jos\'e Campos-Mart\'inez, Marta I. Hern\'andez
https://arxiv.org/abs/2603.24827 https://arxiv.org/pdf/2603.24827 https://arxiv.org/html/2603.24827
arXiv:2603.24827v1 Announce Type: new
Abstract: Previous research based on electronic structure calculations and molecular dynamics (MD) simulations have demonstrated that graphdiyne (GDY) is a very suitable two-dimensional membrane for the separation of small molecules in a gas mixture of different species. However, quantum effects may play a role in the dynamics of these permeation processes when light molecules are the ones involved in the crossing of the GDY subnanometric pores. In this work we report rigorous quantum-mechanical calculations together with equivalent MD simulations of the transport of H2 molecules through a static GDY membrane, as a case study for the validity of the application to these problems of classical dynamics. The force fields employed are based on an improved Lennard-Jones formulation, with parameters optimized by means of accurate ab initio calculations. It is found that, although quantum effects are still significant at the temperatures of interest (between 250 and 350 K), MD simulations are able to reasonably reproduce the dependence of the quantum permeances with the temperature. Moreover, MD permeances computed with quantum corrections through Feynman-Hibbs effective potentials provide a lower bound to quantum permeances, while the pure classical counterpart gives an upper bound, thus leading to a well delimited range of confidence of the permeation results. Furthermore, within MD simulations it is possible to incorporate the thermal motion of the GDY layer and in this situation it is observed an enhancement of the permeances with respect to the fixed membrane case, due to a significant reduction of the permeation barriers when the GDY atoms are allowed to vibrate. It seems apparent therefore, that modeling the membrane motion is crucial to provide reliable simulations of the gas transport features.
toXiv_bot_toot

FPGA-based disturbance-observer servo for broadband noise suppression in laser frequency stabilization
Meung Ho Seo, Jae Hoon Lee, Young-Ho Park, Hyun-Gue Hong, Seji Kang, Myoung-Sun Heo, Sang-Bum Lee, Taeg Yong Kwon, Sangwon Seo, Sang Eon Park
https://arxiv.org/abs/2605.25471

Autotuning T-PaiNN: Enabling Data-Efficient GNN Interatomic Potential Development via Classical-to-Quantum Transfer Learning
Vivienne Pelletier, Vedant Bhat, Daniel J. Rivera, Steven A. Wilson, Christopher L. Muhich
https://arxiv.org/abs/2603.24752 https://arxiv.org/pdf/2603.24752 https://arxiv.org/html/2603.24752
arXiv:2603.24752v1 Announce Type: new
Abstract: Machine-learned interatomic potentials (MLIPs), particularly graph neural network (GNN)-based models, offer a promising route to achieving near-density functional theory (DFT) accuracy at significantly reduced computational cost. However, their practical deployment is often limited by the large volumes of expensive quantum mechanical training data required. In this work, we introduce a transfer learning framework, Transfer-PaiNN (T-PaiNN), that substantially improves the data efficiency of GNN-MLIPs by leveraging inexpensive classical force field data. The approach consists of pretraining a PaiNN MLIP architecture on large-scale datasets generated from classical molecular simulations, followed by fine-tuning (dubbed autotuning) using a comparatively small DFT dataset. We demonstrate the effectiveness of autotuning T-PaiNN on both gas-phase molecular systems (QM9 dataset) and condensed-phase liquid water. Across all cases, T-PaiNN significantly outperforms models trained solely on DFT data, achieving order-of-magnitude reductions in mean absolute error while accelerating training convergence. For example, using the QM9 data set, error reductions of up to 25 times are observed in low-data regimes, while liquid water simulations show improved predictions of energies, forces, and experimentally relevant properties such as density and diffusion. These gains arise from the model's ability to learn general features of the potential energy surface from extensive classical sampling, which are subsequently refined to quantum accuracy. Overall, this work establishes transfer learning from classical force fields as a practical and computationally efficient strategy for developing high-accuracy, data-efficient GNN interatomic potentials, enabling broader application of MLIPs to complex chemical systems.
toXiv_bot_toot

The Pseudospectral Method for the Dirac Equation with Confining Potential
Dengshan Liu, Huihui Xie, Pengxiang Du, Jian Li, Tomoya Naito
https://arxiv.org/abs/2605.25390 https://…

Crosslisted article(s) found for physics.ao-ph. https://arxiv.org/list/physics.ao-ph/new
[1/1]:
- Hybrid Quantum-Classical Corrective Diffusion Modeling for Meteorological Downscaling
Rui Wang, Edoardo Pasetto, Amer Delilbasic, Morris Riedel, Kristel Michielsen, Gabriele Cavallaro
https://arxiv.org/abs/2605.23403 https://mastoxiv.page/@arXiv_csLG_bot/116634262222667592
toXiv_bot_toot

Electronic properties of the Radium-monochalcogenides RaX (X = O,S,Se) and RaO /- ions
Mateo Londo\~no, Jes\'us P\'erez-R\'ios
https://arxiv.org/abs/2603.24590 https://arxiv.org/pdf/2603.24590 https://arxiv.org/html/2603.24590
arXiv:2603.24590v1 Announce Type: new
Abstract: We present a theoretical investigation on the electronic structure and properties of radium monochalcogenides, with chalcogens O, S, and Se, as well as the ionic species RaO /-. Our approach combines fully relativistic and partially relativistic quantum-chemistry methods. Electronic properties are obtained using the exact two-component Hamiltonian-based coupled-cluster approach with single, double, and perturbative triple excitations [CCSD(T) X2C], while potential energy curves are computed using an internally contracted multireference configuration interaction method, including relativistic effects through small-core pseudopotentials and Pauli-Breit operator diagonalization (MRCI Q ECP SO). The dimers exhibit very large permanent dipole moments and sizable dipolar polarizabilities, while the Franck-Condon factors among the lowest electronic states are highly non-diagonal. These features are discussed in terms of the divalent character of the chemical bonding in the neutral species.
toXiv_bot_toot

Minimally Destructive Fast Imaging of Single Atoms in an Optical Tweezer Array with Coherent Excitation
Rei Yokoyama, Takumi Kashimoto, Kosuke Shibata, Yuki Kawamura, Toshi Kusano, Chih-Han Yeh, Reiji Asano, Yuma Nakamura, Tetsushi Takano, Yosuke Takasu, Yoshiro Takahashi
https://arxiv.org/abs/2605.24175

Orientation Reconstruction of Proteins using Coulomb Explosions
Tomas Andr\'e, Alfredo Bellisario, Nicusor Timneanu, Carl Caleman
https://arxiv.org/abs/2603.24553 https://arxiv.org/pdf/2603.24553 https://arxiv.org/html/2603.24553
arXiv:2603.24553v1 Announce Type: new
Abstract: We solve the orientation recovery of a tumbling protein in the gas phase from single-event measurements of the spatial positions of its ions after an X-ray laser induced explosion. We simulate diffracted X-ray signal and ion dynamics under experimental conditions and compare our method to conventional orientation recovery in single-particle imaging with X-ray free-electron lasers using only diffraction data. We reconstruct 3D diffraction intensities using orientations recovered from the ion signatures and retrieve the electron density with established phase-retrieval algorithms. We test our orientation recovery procedure on 56 proteins ranging from 14 to 52 kDa (1800 to 6500 atoms), achieving roughly an angular error of around 5{\deg}. The resulting 3D electron-density reconstructions are compared to ground-truth volumes simulated at the same nominal resolution, and achieve the resolution at the edge of the detector in conditions similar to current single-particle imaging setups. We investigate the reconstruction quality and demonstrate that ion data can be used for reliable orientation recovery of particles in single-particle imaging, achieving orientation on par or better than currently used recovery techniques. This work shows the potential of ion detection for retrieving additional information from the sample fragmentation, and boost single particle imaging with X-ray lasers in the cases where the diffraction signal is a limiting factor.
toXiv_bot_toot

[2026-05-26 Tue (UTC), 5 new articles found for physics.atom-ph Atomic Physics]
toXiv_bot_toot

Two-dimensional IR-Raman spectroscopy of vibrational polaritons: Role of dipole surfaces
Xinwei Ji, Tomislav Begusic, Tao E. Li
https://arxiv.org/abs/2603.24521 https://arxiv.org/pdf/2603.24521 https://arxiv.org/html/2603.24521
arXiv:2603.24521v1 Announce Type: new
Abstract: Nonlinear spectroscopy provides a unique perspective to understand time-resolved molecular dynamics under vibrational strong coupling (VSC). Herein, equilibrium-nonequilibrium cavity molecular dynamics simulations are performed to compute the two-dimensional (2D) infrared-infrared-Raman (IIR) spectroscopy of liquid water under VSC. In conventional computational chemistry practices, accurate molecular spectra are often constructed by using an advanced molecular dipole or polarizability model to post-process molecular dynamics trajectories evolved under a computationally efficient potential. By contrast, this work highlights the necessity of employing a consistent dipole surface model in both CavMD simulations and spectroscopic post-processing. While utilizing inconsistent dipole models only mildly influences the linear polariton spectrum, it severely distorts 2D spectra in wide frequency regions. With a consistent dipole-induced-dipole model, compared to the outside-cavity molecular 2D-IIR spectrum, the cavity 2D-IIR spectrum splits the OH stretch band to a pair of polariton branches along only the IR (not Raman) axis, while fading molecular signals at other frequency regions. This work provides the foundation for employing direct CavMD simulations to construct 2D spectra of realistic molecules under VSC.
toXiv_bot_toot

Molecular effects in low-energy muon transfer from muonic hydrogen to oxygen
I. Boradjiev, A. Adamczak, D. Bakalov, M. Baruzzo, R. Benocci, M. Bonesini, S. Capra, E. Christova, M. Clemenza, M. Danailov, P. Danev, E. Fasci, L. Gianfrani, A. D. Hillier, K. Ishida, A. Menegolli, E. Mocchiutti, S. Monzani, L. Moretti, C. Pizzolotto, R. Rossini, A. Sbrizzi, M. Stoilov, H. S. Tonchev, A. Vacchi, E. Vallazza, K. Yokoyama

Restoring missing low scattering angle data in two-dimensional diffraction patterns of isolated molecules
Yanwei Xiong, Martin Centurion
https://arxiv.org/abs/2603.24334 https://arxiv.org/pdf/2603.24334 https://arxiv.org/html/2603.24334
arXiv:2603.24334v1 Announce Type: new
Abstract: Anisotropic two-dimensional diffraction signals contain more information than the conventional isotropic signals for both gas phase ultrafast electron and X-ray diffraction experiments and are common in typical time-resolved diffraction experiments due to the use of linearly polarized lasers to excite the sample that imprints spatial anisotropy on the molecules. We report an iterative algorithm to restore the missing data at low scattering angles in a two-dimensional diffraction signal, which is essential to obtain real-space representation. The iterative algorithm transforms two-dimensional signals back and forth between the momentum transfer domain and the real space domain through Fourier and Abel transforms and apply real space constraints to retrieve missing signal at low scattering angles. The algorithm only requires an approximate a-priori knowledge of the shortest and longest internuclear distances in the molecule. We demonstrated successful retrieval of the missing signal in simulated patterns and in experimentally measured diffraction patterns from laser-induced alignment of trifluoroiodomethane molecules.
toXiv_bot_toot

Very sensitive vapor-cell quasi-DC atomic E-field sensor
Amy Damitz, George Burns, Yuan-Yu Jau
https://arxiv.org/abs/2603.23751 https://arxiv.org/pdf/2603.…

Collective Electronic Polarization Drives Charge Asymmetry at Oil-Water Interfaces
Gabriele Amante, Klaudia Mrazikova, Gabriele Centi, Sylvie Roke, Ali Hassanali, Giuseppe Cassone
https://arxiv.org/abs/2603.24142 https://arxiv.org/pdf/2603.24142 https://arxiv.org/html/2603.24142
arXiv:2603.24142v1 Announce Type: new
Abstract: Why kinetically stable oil droplets in water spontaneously acquire a negative charge remains one of the most vigorously debated questions in interfacial science. Here, we combine neural-network based deep potential molecular dynamics with a data-driven and information theory approach to probe the real-space electron density at an extended decane-water interface. While decane-water clusters show nearly symmetric forward and backward charge transfer (CT) and thus negligible net CT, the extended interface displays a systematic electronic asymmetry, yielding a net CT from water to the hydrocarbon phase producing an average surface charge density of $\sim0.006~e^{-}\,\mathrm{nm}^{-2}$ on the oil phase. This imbalance is accompanied by much larger intra-phase self-polarization, particularly within the hydrocarbon phase, demonstrating that collective many-body polarization dominates the interfacial electronic response. Structural analysis reveals an asymmetry between forward C--H$\cdots$O and backward O--H$\cdots$C motifs, providing a microscopic origin for a net CT from one phase to the other. Curiously, both the water O--H and decane C--H covalent bonds incur subtle contractions which originate from a response to the charge-separation layers at the interface. These features are fully consistent with the weak improper hydrogen-bonds forming at the oil-water interface that results in blue-shifts of the C-H modes.
toXiv_bot_toot

A high-flux atomic strontium oven with light-driven flux modulation
Kenneth M. Hughes, Jesse S. Schelfhout, Charu Mishra, Timothy Leese, Elliot Bentine, Christopher J. Foot
https://arxiv.org/abs/2603.25567

Spectral convergence of sum-of-Gaussians tensor neural networks for many-electron Schr\"odinger equation
Teng Wu, Qi Zhou, Huangjie Zheng, Hehu Xie, Zhenli Xu
https://arxiv.org/abs/2603.23897 https://arxiv.org/pdf/2603.23897 https://arxiv.org/html/2603.23897
arXiv:2603.23897v1 Announce Type: new
Abstract: We present an improved version of the sum-of-Gaussians tensor neural network (SOG-TNN) architecture for solving many-electron Schr\"{o}dinger equation for one-dimensional soft-Coulomb systems. Model reduction techniques are introduced to reduce the number of tensor-factorized bases under the SOG approximation of the kernel. The Slater determinant ansatz is employed so that the anti-symmetric property of the wave function can be strictly preserved. Numerical results show that the SOG-TNN achieves high accuracy with remarkably small basis sizes. Robust spectral convergence with respect to the basis size is also observed, consistently characterized by a mixed algebraic-exponential model for the error decay. These findings validate that the SOG-TNN architecture provides an ultra-efficient and low-rank representation of complex multi-electron wave functions, shedding light on high-fidelity quantum calculations in larger-scale many-electron systems.
toXiv_bot_toot

Radiative Association of Ag and H: Formation of AgH from Ab Initio Calculations
Lin Jiang, Yu Wang, Yukun Yang, Xuanbing Qiu, Yali Tian, Guqing Guo, Ling Liu, Chuanliang Li, Yong Wu
https://arxiv.org/abs/2603.25297

Automating Computational Chemistry Workflows via OpenClaw and Domain-Specific Skills
Mingwei Ding, Chen Huang, Yibo Hu, Yifan Li, Zitian Lu, Xingtai Yu, Duo Zhang, Wenxi Zhai, Tong Zhu, Qiangqiang Gu, Jinzhe Zeng
https://arxiv.org/abs/2603.25522

Binding Energy of Muonic Beryllium: Perturbative versus All--Order Calculations
Shikha Rathi, Ulrich D. Jentschura, Paul Indelicato, Ben Ohayon
https://arxiv.org/abs/2603.25278 …

Enabling ab initio geometry optimization of strongly correlated systems with transferable deep quantum Monte Carlo
P. Bern\'at Szab\'o, Zeno Sch\"atzle, Frank No\'e
https://arxiv.org/abs/2603.25381

Portable laser-cooled ytterbium beam clock based on an ultra-narrow optical transition
R. F. Offer, E. Klantsataya, A. P. Hilton, A. Strathearn, N. Bourbeau H\'ebert, C. J. Billington, S. Watzdorf, S. K. Scholten, B. White, M. Nelligan, T. M. Stace, A. N. Luiten
https://arxiv.org/abs/2603.25261…

Complementary Eigen-Zundel Interpretation Reconciles Thermodynamics and Spectroscopy of Excess Protons in Aqueous HF Solutions
Louis Lehmann, Florian N. Br\"unig, Jonathan Scherlitzki, Morten Lehmann, Martin Kaupp, Beate Paulus, Roland R. Netz
https://arxiv.org/abs/2603.25371

Self-energy corrections to the ionization energies in sodium-like ions: comparison of the \textit{ab initio} QED and model-QED-operator approaches
P. Yang, A. V. Malyshev, E. A. Prokhorchuk, I. I. Tupitsyn, V. M. Shabaev, D. P. Usov
https://arxiv.org/abs/2603.25212

Deep learning of committor and explainable artificial intelligence analysis for identifying reaction coordinates
Toshifumi Mori, Kei-ichi Okazaki, Kang Kim, Nobuyuki Matubayasi
https://arxiv.org/abs/2603.25237

Sensing T-violating nuclear moments of paramagnetic ions in crystals
Aleksandar Radak, Mingyu Fan, Bassam Nima, Yuiki Takahashi, Amar Vutha
https://arxiv.org/abs/2603.24907 http…

A sustainable photocatalytic pathway for concurrent hydrogen and value-added chemical production utilizing microalgae as bio-scavenger in water
Ho Truong Nam Hai, Augusto Ducati Luchessi, Kaveh Edalati
https://arxiv.org/abs/2603.24924

Absence of Far-Detuned Attractive Optical Traps for Alkali Rydberg Atoms
Gabriel E. Patenotte, Youngshin Kim, Samuel Gebretsadkan, Kang-Kuen Ni
https://arxiv.org/abs/2603.24789 …

Implementation of the multigrid Gaussian-Plane-Wave algorithm with GPU acceleration in PySCF
Rui Li, Xing Zhang, Qiming Sun, Yuanheng Wang, Junjie Yang, Garnet Kin-Lic Chan
https://arxiv.org/abs/2603.24881

Permeation of hydrogen across graphdiyne: molecular dynamics vs. quantum simulations and role of membrane motion
Mateo Rodr\'iguez, Jos\'e Campos-Mart\'inez, Marta I. Hern\'andez
https://arxiv.org/abs/2603.24827

Replaced article(s) found for physics.atom-ph. https://arxiv.org/list/physics.atom-ph/new
[1/1]:
- Restricted-Geometry Quantum Models Beyond Atoms: Application of the Eckhardt-Sacha approach to NS...
Lars C. Bannow, Jan H. Thiede, Micha{\l} Ogryzek, Dmitry K. Efimov, Jakub…

Autotuning T-PaiNN: Enabling Data-Efficient GNN Interatomic Potential Development via Classical-to-Quantum Transfer Learning
Vivienne Pelletier, Vedant Bhat, Daniel J. Rivera, Steven A. Wilson, Christopher L. Muhich
https://arxiv.org/abs/2603.24752

Crosslisted article(s) found for physics.atom-ph. https://arxiv.org/list/physics.atom-ph/new
[1/1]:
- Optical repumping and atom number balancing in a two-color MOT
Deutschle, S\'ark\'any, Negyedi, Fort\'agh, G\"unther, Courteille

Electronic properties of the Radium-monochalcogenides RaX (X = O,S,Se) and RaO /- ions
Mateo Londo\~no, Jes\'us P\'erez-R\'ios
https://arxiv.org/abs/2603.24590 https…

[2026-03-26 Thu (UTC), 2 new articles found for physics.atom-ph Atomic Physics]
toXiv_bot_toot

Orientation Reconstruction of Proteins using Coulomb Explosions
Tomas Andr\'e, Alfredo Bellisario, Nicusor Timneanu, Carl Caleman
https://arxiv.org/abs/2603.24553 https://…

Near-deterministic loading of optical tweezer arrays via repulsive barricade potentials
Archie C. Baldock, Alex J. Matthies, Luke Caldwell, Hannah J. Williams
https://arxiv.org/abs/2604.22406

Two-dimensional IR-Raman spectroscopy of vibrational polaritons: Role of dipole surfaces
Xinwei Ji, Tomislav Begusic, Tao E. Li
https://arxiv.org/abs/2603.24521 https://

[2026-04-27 Mon (UTC), 1 new article found for physics.atom-ph Atomic Physics]
toXiv_bot_toot

Restoring missing low scattering angle data in two-dimensional diffraction patterns of isolated molecules
Yanwei Xiong, Martin Centurion
https://arxiv.org/abs/2603.24334 https:/…

Collective Electronic Polarization Drives Charge Asymmetry at Oil-Water Interfaces
Gabriele Amante, Klaudia Mrazikova, Gabriele Centi, Sylvie Roke, Ali Hassanali, Giuseppe Cassone
https://arxiv.org/abs/2603.24142

Spectral convergence of sum-of-Gaussians tensor neural networks for many-electron Schr\"odinger equation
Teng Wu, Qi Zhou, Huangjie Zheng, Hehu Xie, Zhenli Xu
https://arxiv.org/abs/2603.23897