Showing 1–50 of 3,819 results for author: De, D

GENIE: Generative Neural Inference for Epidemics

Authors: Laura M. Guzmán-Rincón, George R. E. Bradley, Joel Kandiah, Kyriakos Flouris, Pietro Liò, Paul J. Birrell, Alexander E. Zarebski, Daniela De Angelis

Abstract: The SARS-CoV-2 pandemic highlighted the ongoing risk infectious diseases pose to society and the value of reliable information on the likely future burden. When forecasting an epidemic at fine spatial resolution, traditionally used mechanistic compartmental model struggle to capture highly complex granular transmission dynamics, resulting in inaccurate and overconfident forecasts. However, detaile… ▽ More The SARS-CoV-2 pandemic highlighted the ongoing risk infectious diseases pose to society and the value of reliable information on the likely future burden. When forecasting an epidemic at fine spatial resolution, traditionally used mechanistic compartmental model struggle to capture highly complex granular transmission dynamics, resulting in inaccurate and overconfident forecasts. However, detailed Agent-Based Models (ABMs), are challenging to calibrate and are too computationally expensive to use in real-time. Amortized simulation-based inference promises to overcome this difficulty by exploiting the power of machine learning (ML) to perform approximate forecasting at near-real-time using arbitrarily complex models of epidemics. In this work we introduce Generative Neural Inference for Epidemics (GENIE), a spatio-temporal ML-based framework for high-resolution forecasting of the burden of respiratory pathogens. GENIE is designed to reflect two key characteristics of outbreaks: (i) shared biological mechanisms across locations and (ii) location-specific characteristics affecting transmission dynamics. This results in the model architecture having two modules: (i) a Local Infection Encoder - which learns to represent disease dynamics shared across all locations and (ii) a Local Profile Encoder - which learns location-specific representations. Using simulations from a high-resolution spatio-temporal ABM, GENIE is trained to generate samples from an approximate posterior predictive distribution of future epidemic trajectories. Benchmarked against established statistical and ML models, GENIE demonstrates superior performance across a range of measures including the timing and magnitude of peak hospitalisations. △ Less

Submitted 20 August, 2026; originally announced August 2026.

Multi-Method Causal Evidence Synthesis: Ranking Candidate Drivers by Convergent Cross-Method Evidence from Observational Data

Authors: Manish Gupta, Dipanjan De

Abstract: Practitioners inferring causality from observational data usually rely on a single method and treat its output as causal truth. Recent tools select an optimal method for a dataset, and recent ensembles aggregate multiple causal-discovery algorithms into one graph, but little work pools evidence across different mathematical traditions, including non-causal ones. We present Multi-Method Causal Evid… ▽ More Practitioners inferring causality from observational data usually rely on a single method and treat its output as causal truth. Recent tools select an optimal method for a dataset, and recent ensembles aggregate multiple causal-discovery algorithms into one graph, but little work pools evidence across different mathematical traditions, including non-causal ones. We present Multi-Method Causal Evidence Synthesis (MCES), a framework that ranks which candidate drivers in an observational system are most likely relevant to a set of outcomes, and with what strength of evidence. MCES runs eleven methods across eight mathematical traditions on observational panel data and pools their outputs into a Convergent Evidence Score (CES), a linear opinion pool. CES quantifies convergence of evidence across analytical lenses: the degree to which methods with different assumptions point to the same driver-outcome relationship. It does not claim causal identification in the interventionist sense; it supports hypothesis prioritization, not a transferable probability of causation. MCES first applies Structural-Behavioral Decomposition to remove definitional (algebraic) relationships, then runs all methods, normalizes outputs to [0,1], and pools them. We distinguish MCES from method selection, structural ensembles, prediction ensembles, and literature synthesis. Using synthetic data with embedded ground truth, the Sachs protein-signaling benchmark, six Bayesian-network structure benchmarks, and two further synthetic domains, we show MCES ranks true edges near the top (Precision@5 = 1.0, Precision@10 = 0.96 on the primary scenario), with a low empirical rate of null pairs reaching Moderate-or-higher convergence. Our central point is not that the pool beats every individual method, but that no single method is uniformly best across the evaluated scenarios, so MCES offers a method-agnostic default. △ Less

Submitted 20 August, 2026; originally announced August 2026.

Comments: 36 pages, 4 figures, 17 tables. Reference implementation available from the authors on request

Constraints on ultralight bosons from merging binary and remnant black holes observed during the second and third parts of the fourth LIGO-Virgo-KAGRA observing run

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, A. Abe, I. Abouelfettouh, F. Acernese, K. Ackley, A. Adam, S. Adhicary, D. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend, L. Aiello, A. Ain, P. Ajith, T. Akutsu , et al. (1786 additional authors not shown)

Abstract: We present constraints on ultralight bosons using binary black hole mergers observed in the second and third parts of the fourth LIGO-Virgo-KAGRA observing run. Directed searches are conducted for long-transient gravitational waves from ultralight vector boson clouds around merger remnants, using a hidden-Markov-model (HMM) tracking scheme. We target the remnant black holes formed in the binary co… ▽ More We present constraints on ultralight bosons using binary black hole mergers observed in the second and third parts of the fourth LIGO-Virgo-KAGRA observing run. Directed searches are conducted for long-transient gravitational waves from ultralight vector boson clouds around merger remnants, using a hidden-Markov-model (HMM) tracking scheme. We target the remnant black holes formed in the binary coalescences that produced GW250114 and GW250207. We find no evidence for such signals from either target. Estimating our search sensitivity at a threshold corresponding to a 1% false alarm probability, we thus disfavor vector boson masses in the range of $[2.80, 3.95]\times 10^{-13}$ eV with greater than 90% confidence. In addition, we derive constraints on ultralight scalar and vector bosons from the inferred high spins of the constituent black holes in three binaries, using events GW240515, GW241113, and GW241225_08. The excluded mass ranges in this approach depend on the assumed black-hole ages. At $10^5$ years, corresponding to typical dynamically formed binaries, we exclude scalar and vector bosons in the ranges $[1.39, 6.94]\times 10^{-13}$ eV and $[0.32, 14.4]\times 10^{-13}$ eV at 90% confidence, respectively. △ Less

Submitted 11 August, 2026; originally announced August 2026.

Comments: 27 pages (12 pages author list, 15 pages main paper), 5 figures

Report number: LIGO-P2600218

Predicting Mechanical Properties of Lignin-Containing Polyurethane Rigid Foams from Microstructure Using Convolutional Neural Networks

Authors: Ilige S. Hage, Charbel Y. Seif, Jose Enrico Q. Quinsaat, Daniel J. van de Pas, Richard Vendamme, Walter Eeversd, Karolien Vanbroekhovend, Elias Feghalid

Abstract: Bio-based alternatives for conventional rigid foams have proven to be good substituents owing to their enhanced sustainability and competitive performance. However, because their manufacturing processes are complex and destructive testing is often impractical, this study investigates whether microstructural features can be correlated with mechanical properties in lignin-containing rigid polyuretha… ▽ More Bio-based alternatives for conventional rigid foams have proven to be good substituents owing to their enhanced sustainability and competitive performance. However, because their manufacturing processes are complex and destructive testing is often impractical, this study investigates whether microstructural features can be correlated with mechanical properties in lignin-containing rigid polyurethane (PU) foams using machine-learning approaches. Various types and percentages of lignin-based polyols were investigated as a partial polyol replacement. Scanning electron microscopy (SEM) images and corresponding mechanical compression data were used to train a custom state-of-art dual-head convolutional neural network (CNN) targeting the specific prediction of density, specific compression modulus, specific yield strength, and specific compression strength. The CNN was optimized with a weighted multi-output loss function, achieving strong predictive performance R2 values ranging from 0.850 to 0.91 and correlation coefficients above 0.92 while maintaining mean absolute error percentages below 9%. This proves the trained network capability to predict and capture morphological features governing load bearing responses. On the other hand, Grad-CAM visualization revealed that the network focused its predictions on physically meaningful microstructural regions such as cell walls and strut junctions, which confirm that the proposed network can be classified as an interpretable, non-destructive and data-driven framework for predicting and understanding bio-based PU foams mechanical behavior, hence reducing the inconvenience caused by time consuming manufacturing and destructive testing. △ Less

Submitted 11 August, 2026; originally announced August 2026.

Do Stack Overflow Answer Edits Occur Beyond Java? A Replication on Python and JavaScript

Authors: Chaiyong Ragkhitwetsagul, In-on Wiratsin, Matheus Paixao, Denis De Sousa, Pongpop Lapvikai, Peter Haddawy

Abstract: Stack Overflow answers are continually revised by the community, and the edits made to their code snippets are a potential source of improvements for code that has been reused in open-source projects. A recent empirical study established this for Java, reporting that 16.11% of accepted Java answers are edited and that the resulting recommendations concentrate in highly popular GitHub projects. Whe… ▽ More Stack Overflow answers are continually revised by the community, and the edits made to their code snippets are a potential source of improvements for code that has been reused in open-source projects. A recent empirical study established this for Java, reporting that 16.11% of accepted Java answers are edited and that the resulting recommendations concentrate in highly popular GitHub projects. Whether that behaviour is a property of Stack Overflow or a property of the Java community has remained an open question. We replicate the study on Python and JavaScript, the two most widely used languages alongside Java, applying the same SOTorrent-based extraction pipeline, the same clone search tool, Siamese+, and the same project popularity criteria. Analysing 840,132 accepted Python answers and 1,144,185 accepted JavaScript answers, we find that 41.25% and 39.10% respectively have been edited at least once, roughly two and a half times the Java rate, while the number of revisions per edited answer is almost invariant across the three languages at 2.78, 2.68 and 2.82. Searching 100 GitHub projects per language, we find that the number of matched answer edits increases monotonically from low- to medium- to high-popularity projects in both languages, from 80 to 156 to 977 for Python and from 32 to 71 to 353 for JavaScript. The difference is statistically significant for Python but not for JavaScript. The central findings of the original study therefore generalise beyond Java, with the supply of candidate improvements considerably larger in both replication languages than in the original. △ Less

Submitted 12 August, 2026; v1 submitted 8 August, 2026; originally announced August 2026.

Search for gamma-ray spectral lines from dark matter annihilation with the H.E.S.S. Inner Galaxy Survey

Authors: H. E. S. S. Collaboration, F. Aharonian, H. Ashkar, V. Barbosa Martins, R. Batzofin, Y. Becherini, D. Berge, K. Bernlohr, M. Bottcher, C. Boisson, J. Bolmont, F. Brun, B. Bruno, T. Bulik, C. Burger-Scheidlin, S. Casanova, J. Celic, M. Cerruti, A. Chen, M. Chernyakova, J. O. Chibueze, O. Chibueze, B. Cornejo, G. Cotter, J. de Assis Scarpin , et al. (94 additional authors not shown)

Abstract: Spectral gamma-ray line features are expected as key signatures from dark matter (DM) annihilations of TeV-scale particle DM. Observations of the Galactic Centre with atmospheric Cherenkov telescopes are unique to probe thermal-relic TeV particle DM, well beyond the reach of direct detection and collider searches. We report here on the search for line signals in very-high-energy gamma rays using d… ▽ More Spectral gamma-ray line features are expected as key signatures from dark matter (DM) annihilations of TeV-scale particle DM. Observations of the Galactic Centre with atmospheric Cherenkov telescopes are unique to probe thermal-relic TeV particle DM, well beyond the reach of direct detection and collider searches. We report here on the search for line signals in very-high-energy gamma rays using data from the Inner Galaxy Survey, consisting of 546 hours of H.E.S.S. observations of the inner few degrees of the Galactic Centre. No significant signal is detected. We then compute the exclusion limits on the annihilation line cross section $\langle σv \rangle_{\rm line}$, with a two-dimensional log-likelihood ratio test statistics, exploiting spectral and spatial features of the DM signal. Assuming an Einasto DM density profile for the Milky Way, our results provide the most constraining limits so far, reaching $\langle σv \rangle_{\rm line} = 2.3$ $\times$ $10^{-28}$ and $2.4 \times$ $10^{-27}$ cm$^3$s$^{-1}$ for DM masses of 1 and 10 TeV, respectively. The present limits are used to constrain the widely searched Wino, Higgsino and Quintuplet models. For the first time, thermal Higgsino DM is probed for DM Milky Way models. △ Less

Submitted 7 August, 2026; originally announced August 2026.

Comments: Accepted in Phys. Rev. Lett., includes Supplemental materials. 6+7 pages, 2+1 figures, 0+2 tables

A Detailed Analysis of Intermediate-scale Structure in Optical Extinction Curves: Expanded Census and Two-family Classification

Authors: C. M. Gunasekera, M. Decleir, K. D. Gordon, G. C. Clayton, B. Günay, D. V. De Putte, P. Yanchulova

Abstract: The features of interstellar extinction curves serve as powerful diagnostics for interstellar dust, revealing information about its composition, size distribution, and the physical and chemical processes that shape it. D. Massa et al. reported three faint but wide extinction features, termed intermediate-scale structures (ISS) at 4370, 4870, 6300 Å. Since then, three additional ISS features have b… ▽ More The features of interstellar extinction curves serve as powerful diagnostics for interstellar dust, revealing information about its composition, size distribution, and the physical and chemical processes that shape it. D. Massa et al. reported three faint but wide extinction features, termed intermediate-scale structures (ISS) at 4370, 4870, 6300 Å. Since then, three additional ISS features have been reported in the literature at 7700, 5400, 8500 Å, all with widths greater than any known diffuse interstellar band. We present new optical and UV Hubble Space Telescope/STIS spectra for a sample of 24 early-type OB stars. We used these data combined with 50 literature targets for a systematic, homogeneous analysis of ISS features, with the aim of investigating their observational behavior to help constrain their carriers. This analysis revealed nine more candidate ISS features. We also find that ISS features can be arranged into two main families, which we call $α$ and $β$, according to correlations between the feature strengths. Finally, we find strong correlations between the 2175 Å bump strength and ISS features at 4353, 4847, 6443, 7710 Å, suggesting their possible carbonaceous origin. △ Less

Submitted 6 August, 2026; originally announced August 2026.

Comments: 22 pages, 12 figures

Estimating the sensitivity of the IceCube Upgrade to probe the interior of the Earth using atmospheric neutrino oscillations

Authors: The IceCube Collaboration, R. Abbasi, M. Ackermann, J. Adams, S. K. Agarwalla, J. A. Aguilar, M. Ahlers, J. M. Alameddine, S. Ali, N. M. Amin, K. Andeen, C. Arg{ü}elles, S. Athanasiadou, S. N. Axani, R. Babu, X. Bai, A. Balagopal V., S. W. Barwick, V. Basu, R. Bay, J. J. Beatty, J. Becker Tjus, P. Behrens, J. Beise, C. Bellenghi , et al. (399 additional authors not shown)

Abstract: The IceCube Upgrade is a densely instrumented central region of the IceCube Neutrino Observatory, deployed during the 2025-26 polar season. It will reduce the detector's energy threshold and improve overall reconstruction capabilities for multi-GeV atmospheric neutrinos, which in turn enhance their sensitivity to Earth matter effects as they traverse through the deep Earth. In this study, we descr… ▽ More The IceCube Upgrade is a densely instrumented central region of the IceCube Neutrino Observatory, deployed during the 2025-26 polar season. It will reduce the detector's energy threshold and improve overall reconstruction capabilities for multi-GeV atmospheric neutrinos, which in turn enhance their sensitivity to Earth matter effects as they traverse through the deep Earth. In this study, we describe the potential of the IceCube Upgrade to observe Earth matter effects on atmospheric neutrinos and estimate the detector's sensitivity to probe key features of the Preliminary Reference Earth Model by utilizing these observations. We highlight the IceCube Upgrade's capability to estimate the mass of the Earth and verify the non-homogeneous distribution of matter density within the Earth. We also estimate the IceCube Upgrade sensitivity to measure the correlated densities of the Earth layers while incorporating constraints from the mass and moment of inertia of the Earth. Neutrino-based results would be independent and complementary to the seismic and gravitational measurements. △ Less

Submitted 6 August, 2026; originally announced August 2026.

Comments: 20 pages, 13 figures, 2 tables, and 1 appendix

ePIC Early Science Report

Authors: D. Abbott, N. Abdelrahman, S. Abhijit, I. Abualrob, R. B. Achari, J. Adam, L. Adamczyk, K. Adkins, A. Affolder, K. Agarwal, J. Agarwala, N. Agrawal, C. A. Aidala, W. Akers, A. Al-bataineh, S. N. Alam, M. Alekseev, P. R. Altieri, J. -S. Alvarado Gallenao, S. B. L. Amar, R. Ammendola, I. Amos Cali, G. An, D. Anderson, E. Anderssen , et al. (774 additional authors not shown)

Abstract: This Early Science Report from the ePIC Collaboration outlines the compelling physics program achievable during the first years of operation of the Electron-Ion Collider (EIC), prior to the establishment of the full design luminosity and energy range. The analyses are based on realistic early-running beam configurations and detailed Geant4 ePIC detector simulations, hit digitization and data recon… ▽ More This Early Science Report from the ePIC Collaboration outlines the compelling physics program achievable during the first years of operation of the Electron-Ion Collider (EIC), prior to the establishment of the full design luminosity and energy range. The analyses are based on realistic early-running beam configurations and detailed Geant4 ePIC detector simulations, hit digitization and data reconstruction. The projected studies from the physics working groups of ePIC span inclusive, semi-inclusive, exclusive, diffractive and tagging, as well as jet and heavy flavor measurements in both electron-proton and electron-ion collisions. Even before the collider reaches its full design performance, these measurements will constrain parton distribution functions in nucleons and nuclei, access transverse-momentum-dependent and spin-dependent observables, probe gluon dynamics in nuclei, and initiate a program of imaging of quarks and gluons. Each measurement is directly connected to the core science pillars of the EIC, identified in the 2018 report by the National Academy of Sciences: understanding the origin of the nucleon mass, unraveling the spin structure of the nucleon, and exploring the emergent properties of dense gluonic matter. The results presented here provide examples that demonstrate that the early years of EIC running with ePIC will deliver novel world-leading insights into Quantum Chromodynamics. In addition, the early science program will establish measurement and analysis methodologies that will pave the way to the subsequent full EIC physics program. △ Less

Submitted 5 August, 2026; originally announced August 2026.

Report number: epic-AN-AC-2026-004

On the Diversity of Analogy Making in Large Language Models

Authors: Yuanhao Shen, Daniel Xavier de Sousa, Caio César Sifuentes Barcelos, Hongyu Guo, Xiaodan Zhu

Abstract: Large Language Models (LLMs) have demonstrated remarkable potential for analogy making, a core cognitive capability that drives novelty and creativity. While prior research has extensively investigated the applications and underlying mechanisms of LLM-based analogy making, its output diversity remains largely unexplored, despite being essential for broadening cross-domain connections and fostering… ▽ More Large Language Models (LLMs) have demonstrated remarkable potential for analogy making, a core cognitive capability that drives novelty and creativity. While prior research has extensively investigated the applications and underlying mechanisms of LLM-based analogy making, its output diversity remains largely unexplored, despite being essential for broadening cross-domain connections and fostering scientific innovation. In this work, we present a comprehensive evaluation of analogy diversity across ten state-of-the-art open- and closed-source LLMs. Our findings highlight a concerning issue of domain homogeneity, a prevalent tendency for LLMs to generate analogies from a narrow set of target domains, limiting both inter-query and intra-model diversity. Furthermore, our analysis reveals a fundamental trade-off in existing LLM diversity-enhancement methods: increasing output diversity often comes at the expense of output quality. Finally, our causal analysis of LLM information flow reveals substantial differences in the model-sensitive regions governing analogy diversity across LLMs, suggesting a potential mechanism for the observed diversity-quality trade-off. To our knowledge, this is among the first studies to systematically investigate output diversity in LLM-based analogy making. △ Less

Submitted 4 August, 2026; originally announced August 2026.

PDRs4All XXII. Near-Infrared continuum in the Orion Bar

Authors: Takashi Onaka, Emmanuel Dartois, Els Peeters, Olivier Berne, Emilie Habart, Christiaan Boersma, Jan Cami, Asuncion Fuente, Javier R. Goicoechea, Ozan Lacinbala, Yoko Okada, Alexander G. G. M. Tielens, Dries Van De Putte, Francois Boulanger, Thomas Pino, Yong Zhang

Abstract: Conspicuous excess emission is present in the near-infrared (NIR) region in various objects, including reflection nebulae, planetary nebulae, and nearby galaxies. However, the spatial distribution and spectral shape of the excess emission remain poorly understood. We studied the NIR continuum emission spectroscopically and obtained its spatial distribution relative to the aromatic infrared band (A… ▽ More Conspicuous excess emission is present in the near-infrared (NIR) region in various objects, including reflection nebulae, planetary nebulae, and nearby galaxies. However, the spatial distribution and spectral shape of the excess emission remain poorly understood. We studied the NIR continuum emission spectroscopically and obtained its spatial distribution relative to the aromatic infrared band (AIB) at 3.3um in the Orion Bar prototypical photodissociation region (PDR). We aim to characterize its spectral shape and discuss its origin. We employed 3D spectroscopic data of the Orion Bar taken with the integrated field unit of NIRSpec on JWST from the Early Release Science program "PDRs4All." Contribution from the foreground ionized gas was estimated using the Cloudy code and subtracted. The observed regions were divided into nine physically distinct regions and an average spectrum was derived for each region. The nine regions, including the ionized gas, atomic PDR, and molecular PDR, clearly show remaining continuum in the region 1--4.5um. The continuum at wavelengths longer than 2.7um shows good correlations with the 3.3um AIB, while the correlation of the continuum at 1.2um is not significant. We further find that the NIR continuum in the Orion Bar can be approximated by a summation of two blackbodies. The low-temperature component correlates with the AIB well, while the high-temperature component does not. The average spectra also show absorption features at 3.0 and 4.27um, which are attributed to the presence in the spectra of water ice and CO2 ice. We discuss possible origins of the NIR continuum, among which recurrent fluorescence from carbon clusters better explains the observed low-temperature component. The presence of ice species suggests a contribution from a deeper layer of the PDR along the line of sight producing characteristic ice absorption features. △ Less

Submitted 16 August, 2026; v1 submitted 4 August, 2026; originally announced August 2026.

Comments: 15 pages, 13 figures. To appear in Astronomy & Astrophysics

Graph Signal Surrogate Generation for Statistical Testing of Covariance Structure on Directed Graphs

Authors: Chun Hei Michael Chan, Alexandre Cionca, Dimitri Van De Ville

Abstract: Non-parametric statistical testing is based on surrogate data generation that randomizes chosen features in the empirical data. In the graph setting, graph signal processing (GSP) brings forward versatile schemes; e.g., to preserve smoothness of graph signals as measured by the Dirichlet energy. However, how to deal with directed graphs remains an active area of research. We begin by revisiting th… ▽ More Non-parametric statistical testing is based on surrogate data generation that randomizes chosen features in the empirical data. In the graph setting, graph signal processing (GSP) brings forward versatile schemes; e.g., to preserve smoothness of graph signals as measured by the Dirichlet energy. However, how to deal with directed graphs remains an active area of research. We begin by revisiting the definition of directed graph wide-sense stationarity. The surrogate signals preserve covariance under the stationary assumption. We demonstrate the feasibility of the scheme to detect irregular node covariance and benchmark our method against conventional schemes using the symmetrized graph. We also investigate how the level of asymmetry affects the detection performance, thus assessing the advantages of the presented approach. Finally, we show results for a real-world graph extracted from the Freeman EIES social network dataset. △ Less

Submitted 3 August, 2026; originally announced August 2026.

Comments: Accepted at EUSIPCO 2026

Breakdown of the optical saturation regime in molecular single-photon emitters

Authors: Hugo Levy-Falk, Daniele De Bernardis, Elena Fanella, Louise Morlaës, Costanza Toninelli

Abstract: Solid-state single organic molecules, such as dibenzoterrylene (DBT) in organic matrices, are prominent deterministic single-photon sources, usually modeled as effective two-level systems (TLS). We show that single DBT molecules in anthracene nanocrystals, under strong continuous-wave driving, depart from this picture: instead of the expected saturation, fluorescence is strongly suppressed at high… ▽ More Solid-state single organic molecules, such as dibenzoterrylene (DBT) in organic matrices, are prominent deterministic single-photon sources, usually modeled as effective two-level systems (TLS). We show that single DBT molecules in anthracene nanocrystals, under strong continuous-wave driving, depart from this picture: instead of the expected saturation, fluorescence is strongly suppressed at high resonant pump power, while the linewidth broadens beyond the TLS prediction -- an \emph{anomalous saturation} regime. Comparing coherent and incoherent excitation and independently calibrating temperature via phonon-induced dephasing rules out laser-induced heating and intersystem crossing. Instead, a model of intensity-dependent excited-state absorption (ESA) toward a short-lived dark state quantitatively reproduces both the fluorescence suppression and the linewidth broadening. We further show that matrix quality mitigates this quenching, and that pulsed excitation schemes are strategic toward full population inversion, with direct implications for quantum nanophotonics and molecular optomechanics. △ Less

Submitted 1 August, 2026; originally announced August 2026.

Synchronization, Kinematic Waves and Spike-Phase-Separation in Feedback Ising Neural Networks on Heterogeneous Graphs

Authors: Anna Poggialini, Irem Topal, Fabrizio Lombardi, Daniele De Martino

Abstract: Structural heterogeneity constrains collective dynamics in complex systems. However, its analytical tractability out of equilibrium remains limited. In this work, we study a class of kinetic Ising neural networks driven out of equilibrium by a homeostatic feedback loop between the neuronal excitability and the population firing rate. Using a Curie-Weiss heterogeneous mean-field approximation valid… ▽ More Structural heterogeneity constrains collective dynamics in complex systems. However, its analytical tractability out of equilibrium remains limited. In this work, we study a class of kinetic Ising neural networks driven out of equilibrium by a homeostatic feedback loop between the neuronal excitability and the population firing rate. Using a Curie-Weiss heterogeneous mean-field approximation validated by Monte Carlo simulations, we provide an analytical characterization of how a macroscopic synchronized limit cycle emerges via an Andronov-Hopf bifurcation on heterogeneous networks. We derive closed-form phase boundaries and show that the onset of oscillations is explicitly controlled by network heterogeneity through the degree moment ratio. Degree heterogeneity decouples the spiking rate per neuron m from the spiking rate per synapse u, generating physical phenomena absent in homogeneous systems. These include (i) kinematic waves of sequential, degree-ordered activations propagating from the network periphery to the hubs, and (ii) a low-temperature phase-separated state emerging via a pitchfork bifurcation. We prove that for highly heterogeneous topologies, this phase-separated fixed point stabilizes and dynamically destroys the synchronized limit cycle. These results provide a mathematical framework for understanding how heterogeneity regulates macroscopic oscillations and out-of-equilibrium transitions in neural networks △ Less

Submitted 30 July, 2026; originally announced July 2026.

Comments: 15 pages, 5 figures

A Unified Discrete Gradient-SAV Framework for Structure-Preserving Integration

Authors: Elena Celledoni, David Martín de Diego, Brynjulf Owren, Miguel Vaquero

Abstract: We present a framework combining discrete gradient (DG) methods with the Scalar Auxiliary Variable (SAV) approach to construct structure-preserving integrators for dissipative and conservative systems. The key observation is that SAV quadratization lifts the dynamics to an extended state space on which the modified energy has an exact discrete-gradient identity. This viewpoint yields three integra… ▽ More We present a framework combining discrete gradient (DG) methods with the Scalar Auxiliary Variable (SAV) approach to construct structure-preserving integrators for dissipative and conservative systems. The key observation is that SAV quadratization lifts the dynamics to an extended state space on which the modified energy has an exact discrete-gradient identity. This viewpoint yields three integrators with different accuracy and cost profiles: a first-order semi-implicit Forward Euler scheme, a second-order self-adjoint Midpoint scheme, and a second-order Predictive scheme with reduced implicitness. The construction extends to almost-Poisson systems and preserves selected Casimir invariants under an enforceable discrete condition. Numerical experiments cover the Allen--Cahn equation, an Ohta--Kawasaki-type nonlocal gradient flow, a double-well Hamiltonian oscillator, and a Poisson system with a nonlinear cubic Casimir. △ Less

Submitted 30 July, 2026; originally announced July 2026.

Comments: 32 pages, 7 figures

MSC Class: 65P10; 65L05; 37M15; 70H05

An efficient one-loop EFTofLSS framework for Vainshtein-screened Horndeski gravity

Authors: Stan Verhoeve, Dani de Boe, Gen Ye, Alessandra Silvestri

Abstract: We present an extension of \texttt{PyBird} for one-loop large-scale structure analyses of modified gravity models. We implement support for quasi-static, Vainshtein-screened luminal Horndeski models (in EFTofDE and covariant formalisms) and nDGP, and replace the Green's function approach with a direct ODE method for computing the exact time-dependent functions entering the perturbation kernels. Th… ▽ More We present an extension of \texttt{PyBird} for one-loop large-scale structure analyses of modified gravity models. We implement support for quasi-static, Vainshtein-screened luminal Horndeski models (in EFTofDE and covariant formalisms) and nDGP, and replace the Green's function approach with a direct ODE method for computing the exact time-dependent functions entering the perturbation kernels. The new implementation improves computational efficiency while maintaining numerical consistency with the standard approach, and we validate the resulting one-loop matter power spectrum against $N$-body simulations for the $α_i\proptoΩ_{\rm DE}$ parametrization. We apply this framework to constrain the $α_i \propto a^3$ and $α_i \propto Ω_{\rm DE}$ parametrizations using Planck CMB, BOSS full-shape, and DESI DR2 BAO data, finding that full-shape information significantly tightens the constraints. We further showcase the pipeline for the cubic Galileon and nDGP models, demonstrating its applicability beyond the phenomenological amplitude parametrizations to covariant modified-gravity theories. Finally, we assess the impact of the Einstein--de Sitter approximation and find that exact time dependence can be retained at modest computational cost, which may become relevant for future large-scale structure surveys. △ Less

Submitted 29 July, 2026; originally announced July 2026.

Comments: 35 pages, 9 figures

Advanced Virgo during the LIGO-Virgo-KAGRA fourth observing run

Authors: Virgo Collaboration, F Acernese, A Agapito, D Agarwal, I-L Ahrend, L Aiello, A Ain, W Ali, A Allocca, W Amar, A Amato, F Amicucci, C Amra, M Andia, T Andri, S Antier, F Arciprete, F Armato, N Arnaud, L Asprea, M Assiduo, S Assis de Souza Melo, P Astone, F Attadio, F Aubin , et al. (524 additional authors not shown)

Abstract: From April 10, 2024 to November 18, 2025 Advanced Virgo participated in the fourth observing run of the network of gravitational-wave detectors, together with Advanced LIGO and KAGRA. For this observing run Advanced Virgo has completed its design optical configuration with the installation of a signal recycling mirror. In this paper we describe the challenges encountered in commissioning this opti… ▽ More From April 10, 2024 to November 18, 2025 Advanced Virgo participated in the fourth observing run of the network of gravitational-wave detectors, together with Advanced LIGO and KAGRA. For this observing run Advanced Virgo has completed its design optical configuration with the installation of a signal recycling mirror. In this paper we describe the challenges encountered in commissioning this optical configuration, alongside the other upgrades performed between the third and fourth observing run. The Virgo detector operated with a 68.9% duty cycle and with an angle-averaged median range to binary neutron star mergers of 53 Mpc. △ Less

Submitted 29 July, 2026; originally announced July 2026.

Comments: 54 pages, 21 figures

Report number: VIR-0259F-26

Global 21cm Measurement Calibration Methodology

Authors: Martin Bucher, Christian J. Kirkham, Eloy de Lera Acedo, Dirk I. L. de Villiers, Saurabh Pegwal

Abstract: 21cm global signal observations present a unique set of calibration challenges owing to the absolute character of the required measurement. Since differential measurements on the sky cannot be used for observing the global signal, typically a number of calibration sources with differing noise temperatures and source impedances are used to determine the four noise parameters and the power gain of t… ▽ More 21cm global signal observations present a unique set of calibration challenges owing to the absolute character of the required measurement. Since differential measurements on the sky cannot be used for observing the global signal, typically a number of calibration sources with differing noise temperatures and source impedances are used to determine the four noise parameters and the power gain of the amplification chain. Because of the broadband nature of the measurement, the antenna impedance varies with frequency in a manner different from the calibration sources, so that the simplest three-way Dicke switching strategy is not adequate. We present a self-contained and explicit derivation of the calibration equations and reconcile expressions from the early global 21cm observation literature with the results obtained following the amplifier noise representation formalism commonly used in the electrical engineering literature. We also present a condition in terms of Möbius geometry on the complex $Γ$- (or $Z$-) plane defining the choice of calibration source impedances required. △ Less

Submitted 29 July, 2026; originally announced July 2026.

Comments: LaTeX, 7 pages with 4 figures

Reversal of a flat plate into its wake: a minimal model for wake capture

Authors: Dirk de Boer, Abel-John Buchner

Abstract: In reciprocating flapping-like motions, wing-wake interaction plays a crucial role in fluid force generation. While this effect's existence has been acknowledged, particularly in explaining discrepancies between measured forces and quasi-steady approximations, fundamental research on the mechanism underlying this interaction and its scaling remains limited. To address this, we investigate the exce… ▽ More In reciprocating flapping-like motions, wing-wake interaction plays a crucial role in fluid force generation. While this effect's existence has been acknowledged, particularly in explaining discrepancies between measured forces and quasi-steady approximations, fundamental research on the mechanism underlying this interaction and its scaling remains limited. To address this, we investigate the excess drag force, relative to quasi-steady estimates, acting on a flat plate during the reversal phase of a forward and back translational motion. The flow produced by this motion, studied at insect-flight-relevant Reynolds numbers, serves as a simplified analogue to biological flapping. We demonstrate that interaction with pre-existing wake flow indeed generates excess drag. The main parameter governing this interaction is the distance travelled before reversal, which influences both magnitude and temporal dynamics of the peak drag. We link our observations to optimal vortex formation, as the time trace of the additional drag during reversal is qualitatively altered by the detachment of the starting vortex ring: vortex detachment and re-formation lead to two distinct wake-force peaks. Furthermore, as the pre-reversal distance traversed increases, the wake interaction force post-reversal decays more slowly. Flow observations reveal a similar spatial decay of the streamwise velocity in the wake at the moment of reversal, suggesting a direct link. Representing the starting vortex as a point vortex indicates that the wake's spatial scaling, and commensurately the temporal scaling of the wing-wake interaction effect, is primarily governed by the vortex ring position, shape, and circulation. This simplification reveals a dependence on the pre-reversal translation distance that can be described by a combined fourth-root and linear scaling. △ Less

Submitted 28 July, 2026; originally announced July 2026.

High-energy neutrino emission from the Milky Way

Authors: R. Abbasi, M. Ackermann, J. Adams, J. A. Aguilar, M. Ahlers, J. M. Alameddine, S. Ali, N. M. Amin, K. Andeen, C. Argüelles, S. Athanasiadou, S. N. Axani, R. Babu, X. Bai, A. Balagopal V., S. W. Barwick, V. Basu, R. Bay, J. J. Beatty, J. Becker Tjus, P. Behrens, J. Beise, C. Bellenghi, S. Benkel, S. BenZvi , et al. (398 additional authors not shown)

Abstract: The Milky Way hosts astrophysical objects that accelerate cosmic rays to energies beyond the reach of terrestrial particle accelerators. It remains a longstanding goal to locate the sites of these powerful Galactic engines and understand how cosmic rays propagate through the Galaxy, leading to the production of high-energy neutrinos. In this paper, we combine event morphologies characteristic of a… ▽ More The Milky Way hosts astrophysical objects that accelerate cosmic rays to energies beyond the reach of terrestrial particle accelerators. It remains a longstanding goal to locate the sites of these powerful Galactic engines and understand how cosmic rays propagate through the Galaxy, leading to the production of high-energy neutrinos. In this paper, we combine event morphologies characteristic of all three neutrino flavours and apply recent improvements in ice modelling, calibration and reconstruction to 12 years of IceCube data. With a predefined, global analysis we establish high-energy neutrino emission from the Galactic plane at 5.7 $σ$ significance. A further study shows that the inner region of the Galaxy is a prominent neutrino source, with 217 shower events with visible energy above 5 TeV compared with an expected background of 154.4 $\pm$ 4.1. These results herald a new era of Galactic multi-messenger astronomy, creating new opportunities to study cosmic-ray propagation and probe neutrino properties over kiloparsec distances. △ Less

Submitted 28 July, 2026; originally announced July 2026.

Fast optical spectroscopic observations of PSR J1023+0038 over one orbital period

Authors: M. M. Messa, M. C. Baglio, P. D'Avanzo, G. Illiano, F. Coti Zelati, K. Alabarta, D. de Martino, Y. D. Hu, A. Miraval Zanon, A. Reguitti, S. Campana

Abstract: Transitional millisecond pulsars (tMSPs) are neutron-star binaries that switch between rotation-powered and accretion-powered states, providing a key link between low-mass X-ray binaries and millisecond radio pulsars. In their sub-luminous disc state, these systems exhibit complex variability whose origin is still debated. We present high-time-resolution optical spectroscopic observations of the t… ▽ More Transitional millisecond pulsars (tMSPs) are neutron-star binaries that switch between rotation-powered and accretion-powered states, providing a key link between low-mass X-ray binaries and millisecond radio pulsars. In their sub-luminous disc state, these systems exhibit complex variability whose origin is still debated. We present high-time-resolution optical spectroscopic observations of the tMSP PSR J1023+0038 obtained during its sub-luminous disc state. Our dataset covers for the first time a full orbital cycle at minute-timescale cadence. We detect significant variability in the main properties of the optical emission lines, including the equivalent width (EW) and full width at half maximum (FWHM), on timescales of minutes. A comparison between the temporal evolution of these quantities reveals indications of correlated behaviour, with some FWHM minima coinciding with decreases in the EW. This may point to episodes of matter ejection from the inner regions of the accretion disc, possibly associated with switches to low modes. The Doppler tomography of the H$α$ and H$β$ emission lines suggests the presence of asymmetric emission structures, consistent with a scenario in which part of the accreting material is expelled from the system. In addition, the optical continuum shows variability consistent with a possible orbital modulation associated with the irradiated companion star, although its characterisation is limited by the observing conditions. Our results provide new constraints on the short-timescale behaviour of tMSPs in the sub-luminous disc state and support scenarios in which accretion and outflow processes coexist. Further multiwavelength observations, particularly including simultaneous X-ray coverage, will be crucial to establish a direct link between the observed optical variability and the high/low mode switches. △ Less

Submitted 28 July, 2026; originally announced July 2026.

Comments: Accepted for publication in Astronomy&Astrophysics journal, Sect. 7. Stellar structure and evolution. The official acceptance date is 25/07/2026

Simulation of combined radio and radar signals at the Radar Echo Telescope for Cosmic Rays

Authors: K. Nivedita, I. Loudon, J. Loonen, P. Allison, J. J. Beatty, D. Z. Besson, A. Connolly, A. Cummings, C. Deaconu, S. de Kockere, K. D. de Vries, I. Esteban, D. Frikken, C. Hast, E. Huesca Santiago, C. -Y. Kuo, A. Kyriacou, U. A. Latif, V. Lukic, C. McLennan, K. Mulrey, J. Nam, S. Prohira, J. P. Ralston, M. F. H. Seikh , et al. (7 additional authors not shown)

Abstract: To explore neutrino astronomy at high energies (> 10 PeV), the Radar Echo Telescope for Cosmic Rays (RET-CR) was developed to assess the feasibility of a radar technique for detecting particle cascades in ice, serving as a precursor to the Radar Echo Telescope for Neutrinos (RET-N). The main concept of RET-CR is that, as a high-energy cosmic-ray air-shower core propagates into the high-altitude ic… ▽ More To explore neutrino astronomy at high energies (> 10 PeV), the Radar Echo Telescope for Cosmic Rays (RET-CR) was developed to assess the feasibility of a radar technique for detecting particle cascades in ice, serving as a precursor to the Radar Echo Telescope for Neutrinos (RET-N). The main concept of RET-CR is that, as a high-energy cosmic-ray air-shower core propagates into the high-altitude ice sheet, a dense secondary-particle cascade is created, which is very similar to that of an in-ice high-energy neutrino-induced cascade. At RET-CR, the expected signal consists of three distinct components: radio emission from the in-air particle shower, Askaryan radio emission from the secondary in-ice cascade, and the radar signal itself arising from the reflection of the transmitted radio signal from the ionisation trail of the in-ice secondary cascade. In this work, we present the first combined simulation-based package and study aimed at characterising the combined radio and radar signals at the in-ice receivers at RET-CR. We describe the simulation framework and provide a detailed discussion of the salient features of the radio and radar signals, including their spatial footprints and temporal characteristics, as predicted for the shallow in-ice detectors. △ Less

Submitted 27 July, 2026; originally announced July 2026.

The beamformed trigger of RNO-G: its design and in-field performance

Authors: RNO-G Collaboration, :, S. Agarwal, J. A. Aguilar, N. Alden, S. Ali, P. Allison, M. Betts, D. Besson, A. Bishop, O. Botner, S. Bouma, S. Buitink, R. Camphyn, J. Chan, S. Chiche, B. A. Clark, K. Couberly, D. Dakroub, K. D. de Vries, C. Deaconu, P. Giri, C. Glaser, H. Gui, A. Hallgren , et al. (55 additional authors not shown)

Abstract: The Radio Neutrino Observatory in Greenland (RNO-G) is a neutrino detector under construction at Summit Station, with 8 out of a planned 35 stations currently deployed. We have designed and deployed a new phased array (PA) trigger based on delay-and-sum beamforming and power integration. This trigger improves detector performance by suppressing thermal noise and better targeting neutrino-induced A… ▽ More The Radio Neutrino Observatory in Greenland (RNO-G) is a neutrino detector under construction at Summit Station, with 8 out of a planned 35 stations currently deployed. We have designed and deployed a new phased array (PA) trigger based on delay-and-sum beamforming and power integration. This trigger improves detector performance by suppressing thermal noise and better targeting neutrino-induced Askaryan signals. The new PA trigger has been deployed since the 2025 season. The trigger performance has been characterized using test pulses and calibration pulsers both in the lab and in-situ, and we find across these tests a 25% average reduction in the signal-to-noise ratio (SNR) needed to trigger on signals. Simulations are shown to be representative of the detector, and simulated trigger efficiencies are within 10% of measured data. Following the in-situ trigger validation, we use data-driven trigger performance to inform simulations of the detector effective volumes. The PA trigger increases our effective volume significantly, by over a factor of 2 below 0.1 EeV and at least a factor of 1.3 at the highest energies of 100 EeV. △ Less

Submitted 27 July, 2026; originally announced July 2026.

Comments: 27 pages, 17 figures, to be submitted to JINST

Lagrange interpolation processes based on the zeros of anti-Gauss Jacobi polynomials

Authors: Patricia Díaz de Alba, Luisa Fermo, Valerio Loi, Donatella Occorsio

Abstract: This paper introduces and investigates a new Lagrange interpolation process based on the zeros of anti-Gauss Jacobi polynomials. Fundamental properties of anti-Gauss nodes, including their asymptotic distribution, are established, together with estimates for the associated polynomials and their derivatives. These results provide the basis for the construction of an interpolation process whose weig… ▽ More This paper introduces and investigates a new Lagrange interpolation process based on the zeros of anti-Gauss Jacobi polynomials. Fundamental properties of anti-Gauss nodes, including their asymptotic distribution, are established, together with estimates for the associated polynomials and their derivatives. These results provide the basis for the construction of an interpolation process whose weighted Lebesgue constants exhibit logarithmic growth, ensuring optimal approximation properties. Compared with previously known interpolation schemes based on Jacobi nodes, the proposed process achieves optimal Lebesgue constants for a shifted range of endpoint weight parameters, allowing the use of smaller endpoint weight exponents. Convergence estimates are established for functions in suitable weighted Sobolev spaces, and numerical experiments support the theoretical findings. △ Less

Submitted 23 July, 2026; originally announced July 2026.

MSC Class: 41A05; 41A10; 42C05

Probing the baryonic--dark matter connection in galaxy clusters using X-rays with gated recurrent unit neural networks

Authors: Asif Iqbal, Subhabrata Majumdar, Weiguang Cui, Elena Rasia, Gabriel W. Pratt, Daniel de Andres

Abstract: Accurate cluster mass measurements are crucial for cosmology, yet conventional hydrostatic equilibrium (HSE) methods can suffer from systematic biases, particularly in dynamically disturbed systems. We present a gated recurrent unit (GRU) based deep learning framework for predicting three-dimensional mass profiles of galaxy clusters from spherically averaged intra-cluster medium (ICM) radial profi… ▽ More Accurate cluster mass measurements are crucial for cosmology, yet conventional hydrostatic equilibrium (HSE) methods can suffer from systematic biases, particularly in dynamically disturbed systems. We present a gated recurrent unit (GRU) based deep learning framework for predicting three-dimensional mass profiles of galaxy clusters from spherically averaged intra-cluster medium (ICM) radial profiles. By treating ICM profiles as sequential data, the GRU captures radial dependencies and naturally handles profiles with different radial samplings. We train and validate the model using high-resolution hydrodynamical simulations from The Three Hundred Project, achieving unbiased mass predictions with a typical 1$σ$ scatter of $\sim$5% over most of the cluster region, significantly improving upon HSE estimates. The model provides radius-dependent uncertainty estimates and remains robust against variations in data quality and cluster morphology. When trained jointly on independent simulation suites (GIZMO-SIMBA and GADGET-X), it successfully generalises across both simulations. Feature importance analysis shows that enclosed gas mass is the dominant predictor, with pressure and temperature providing additional information on the radial mass distribution. We further apply the GRU model to X-ray observations of the REXCESS and X-COP cluster samples from XMM-Newton and compare the inferred mass profiles with HSE estimates. The HSE masses are systematically lower than the GRU predictions for the higher-mass X-COP sample, while the REXCESS sample shows mass differences that are close to zero on average. This work provides a data-driven framework for cluster mass inference that bridges simulations and observations and can be extended to multi-wavelength datasets, including Sunyaev-Zel'dovich and optical observations. △ Less

Submitted 22 July, 2026; originally announced July 2026.

Comments: 21 pages, 21 figures, 4 tables, submitted to A&A, abstract abridged for arXiv submission, comments welcome

GWTC-5.0: Tests of General Relativity

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, A. Abe, I. Abouelfettouh, F. Acernese, K. Ackley, A. Adam, S. Adhicary, D. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend, L. Aiello, A. Ain, P. Ajith, T. Akutsu , et al. (1800 additional authors not shown)

Abstract: The signals from the LIGO-Virgo-KAGRA network of gravitational-wave (GW) detectors allow us to perform sensitive tests of general relativity (GR) in the dynamical and strong-field regime of gravity. We present the results of seven tests of GR using the observed binary signals in the fifth GW Transient Catalog (GWTC-5.0), i.e., up to and including the second part of the fourth observing run (O4b).… ▽ More The signals from the LIGO-Virgo-KAGRA network of gravitational-wave (GW) detectors allow us to perform sensitive tests of general relativity (GR) in the dynamical and strong-field regime of gravity. We present the results of seven tests of GR using the observed binary signals in the fifth GW Transient Catalog (GWTC-5.0), i.e., up to and including the second part of the fourth observing run (O4b). We restrict our analysis to the confident signals, henceforth called events, observed by at least two detectors that have estimated false alarm rates $\le 10^{-3} \ \rm{yr}^{-1}$. These include 72 events from O4b and five events from the first part of the fourth observing run that are now analyzed due to their increased significance from updated search results, bringing the total number of events for tests of GR in the cumulative GWTC to 168. After subtracting the best-fit waveforms, we find the residuals are consistent with detector noise for all events considered. We also find no strong evidence for additional polarizations beyond those predicted by GR. We perform tests of GW generation, improving the constraints on deviations from the GR post-Newtonian coefficients by factors of 1.2-2.6. Finally, we find overall consistency of the remnants with GR using both time- and frequency-domain methods. For GW240621_195059, postmerger data are consistent with the dominant quadrupolar ($\ell=|m|=2$) mode of a Kerr black hole and its first overtone, with spurious high-frequency content preventing a spectroscopic constraint of GR. In the frequency-domain ringdown analysis, the GR prediction lies in the tails of the combined results, possibly due to the limited catalog size. However, the combined results indicate improved consistency with GR over GWTC-4.0, owing to the contribution of GW250114 with a network matched-filter signal-to-noise ratio of 76.9. Overall, we find no evidence for physics beyond GR. △ Less

Submitted 21 July, 2026; originally announced July 2026.

Comments: 44 pages and 10 figures

Report number: LIGO-P2500781

Governing Well in the Algorithmic Age: The Foundations of Digital Statecraft

Authors: Zeynep Engin, Tim Gordon, Viviana Bastidas, Tom Crick, Jon Crowcroft, Jean-Martin Denis, David J. Hand, Lauren Maffeo, Jakob Mökander, Irene Ng, Anastasija Nikiforova, Giulio Quaggiotto, David Uriel Socol de la Osa, Rhonda Syler, Philip Treleaven, Stefaan Verhulst

Abstract: The digital substrate - data, algorithms, infrastructure, platforms, applications - is being governed without adequate conceptual foundations. The ability and legitimacy required to govern this substrate, and to govern with it, are simultaneously misaligned, contested, and structurally absent. We introduce digital statecraft as the organising concept for this emerging field, arguing that 'digital'… ▽ More The digital substrate - data, algorithms, infrastructure, platforms, applications - is being governed without adequate conceptual foundations. The ability and legitimacy required to govern this substrate, and to govern with it, are simultaneously misaligned, contested, and structurally absent. We introduce digital statecraft as the organising concept for this emerging field, arguing that 'digital' reconstitutes the statecraft question rather than merely extending its domain. The concept operates on two dimensions - statecraft over digital systems, concerning the authority and capacity of the state in relation to the digital substrate itself, and statecraft with digital systems, concerning the deployment of algorithmic tools as instruments of governing authority. And it rests on two foundational requirements, technical coherence and legitimate authority, that are genuinely in tension. We derive ten principles of digital statecraft from these foundations, each naming a condition whose absence produces an identifiable and structural governance failure: public interest first, human-machine complementarity, governability by design, systemic coherence, hybrid institutions, adaptive governance, human centricity and civic agency, accountable and traceable authority, judgment across time, and the non-delegable core. This article takes the state as the starting point, the institutional form that developed historically in response to the problem of effective and legitimate public governance, and the only current candidate for which the full set of legitimacy conditions is institutionally available. But the digital statecraft programme holds open a deeper question than just whether states can reform themselves: governing well in the algorithmic age may require rethinking the boundaries, scale, and affiliative basis of statehood itself. △ Less

Submitted 16 August, 2026; v1 submitted 20 July, 2026; originally announced July 2026.

Comments: 27 pages

Feature-driven anomaly flagging in obscured active galactic nucleus light curves with autoencoders

Authors: Natale De Bonis, Demetra De Cicco, Stefano Cavuoti, Ylenia Marruccia, Dragana Ilić, Andjelka B. Kovacević, Giuseppe Riccio, Simone Vaccaro

Abstract: Active galactic nuclei (AGN) are among the most complex classes of astrophysical objects, displaying a wide range of variability and observational properties. Identifying unusual AGN is crucial for understanding the physical mechanisms behind their emission better and for discovering potentially new subclasses or rare behaviors. With the increasing volume of data from next-generation surveys, mach… ▽ More Active galactic nuclei (AGN) are among the most complex classes of astrophysical objects, displaying a wide range of variability and observational properties. Identifying unusual AGN is crucial for understanding the physical mechanisms behind their emission better and for discovering potentially new subclasses or rare behaviors. With the increasing volume of data from next-generation surveys, machine-learning-based anomaly detection offers a promising approach to flagging and investigating such outliers systematically. We explore the use of unsupervised algorithms with a feature-driven approach to flag anomalous AGN, further explored by a human expert. The main focus is on obscured AGN, which tend to be harder to characterize. The algorithm we used was an AutoEncoder, which we trained on features extracted from the light curves rather than working with the light curves directly. The unsupervised nature of the method allows the detection of anomalies without relying on labeled data. To properly characterize the feature space and the detection process, we used the SHAP method. Our method flagged $11.18\%$ of the AGN we studied as anomalous. We focused in particular on anomalous obscured AGN and identified a refined subset of features that yields a comparable performance to the full set. Together with an in-depth analysis of the anomalies, this provides insight into how the AutoEncoder assigns anomalous status and which features are most indicative of astrophysically interesting behaviors or phenomena. △ Less

Submitted 20 July, 2026; originally announced July 2026.

Strong edge-colouring via local flag algebras

Authors: Eoin Davey, Eoin Hurley, Rémi de Joannis de Verclos, Ross J. Kang, Jan Volec

Abstract: The strong chromatic index $χ'_s(G)$ is the smallest number of colours needed to colour the edges of a graph $G$ so that any two edges at distance at most $2$ receive different colours. Using the \emph{local flag algebra} framework introduced in a companion paper, we prove $χ'_s(G) \leq 1.73\,Δ(G)^2$ for every graph $G$ of maximum degree $Δ(G)$, $χ'_s(G) \leq 1.6255\,Δ(G)^2$ for every bipartite… ▽ More The strong chromatic index $χ'_s(G)$ is the smallest number of colours needed to colour the edges of a graph $G$ so that any two edges at distance at most $2$ receive different colours. Using the \emph{local flag algebra} framework introduced in a companion paper, we prove $χ'_s(G) \leq 1.73\,Δ(G)^2$ for every graph $G$ of maximum degree $Δ(G)$, $χ'_s(G) \leq 1.6255\,Δ(G)^2$ for every bipartite $G$, and $χ'_s(G) \leq 1.6633\,Δ_A(G)\,Δ_B(G)$ for every bipartite $G$ of side maximum degrees $Δ_A(G), Δ_B(G)$ with rational $Δ_B(G)/Δ_A(G) \in (0, 1]$, provided $Δ(G)$, $Δ_A(G)$, $Δ_B(G)$ are sufficiently large. These three bounds make progress towards three established conjectures: those of Erdős-Nešetřil (1985) for general graphs, Faudree-Gyárfás-Schelp-Tuza (1989) for bipartite graphs, and Brualdi-Quinn Massey (1993) in the asymmetric bipartite setting. Additionally, for the random bipartite graph $G \sim G(n_A, n_B, p)$ at constant $p \in (0,1)$ and bounded aspect ratio $\max(n_A, n_B) = O(\min(n_A, n_B))$, we prove the Brualdi-Quinn Massey bound $χ'_s(G) \leq Δ_A(G)\,Δ_B(G)$ asymptotically almost surely. △ Less

Submitted 19 July, 2026; originally announced July 2026.

Comments: 23 pages

MSC Class: 05C15; 05C35; 05C80; 05-08

Symmetry-isolated magnetoelectric electro-optic effects in noncentrosymmetric metals

Authors: C. O. Ascencio, D. J. P. de Sousa, Seungjun Lee, Tony Low

Abstract: We classify the symmetry-constrained forms of the Berry curvature dipole $\mathbf{D}$, gyrotropic magnetic tensor $\mathbf{K}$, and magnetoelectric electro-optic (EO) tensor $\mathbf{G}$, which describe metallic optical and EO effects in time-reversal symmetric, noncentrosymmetric metals. We identify 11 space groups (SGs) in which $\mathbf{D}$ and $\mathbf{K}$ vanish by symmetry while… ▽ More We classify the symmetry-constrained forms of the Berry curvature dipole $\mathbf{D}$, gyrotropic magnetic tensor $\mathbf{K}$, and magnetoelectric electro-optic (EO) tensor $\mathbf{G}$, which describe metallic optical and EO effects in time-reversal symmetric, noncentrosymmetric metals. We identify 11 space groups (SGs) in which $\mathbf{D}$ and $\mathbf{K}$ vanish by symmetry while $\mathbf{G}$ remains allowed, thereby providing a more direct route to observing the recently predicted magnetoelectric EO effects associated with $\mathbf{G}$. First-principles based calculations confirm that $\mathbf{D}$ and $\mathbf{K}$ vanish for representative materials, while $\mathbf{G}$ remains allowed and tunable via Fermi level shifting. We further show that the choices of SG and experimental configuration provide complementary paths for isolating $\mathbf{G}$-driven EO effects, including cases where $\mathbf{D}$ and $\mathbf{K}$ are also symmetry-allowed. In an oblique-incidence geometry, the $\mathbf{D}$-driven response produces a helicity-even absorption or gain correction, whereas the $\mathbf{G}$-driven response couples the $s$ and $p$ optical sectors and produces a bias-induced circular dichroism with a characteristic $\sinθ\cosθ$ angular dependence. This provides a direct experimental route for separating the $\mathbf{D}$- and $\mathbf{G}$-driven EO signatures in noncentrosymmetric metals. △ Less

Submitted 19 July, 2026; originally announced July 2026.

Comments: 13 pages, 4 figures

VAR-PZnn: A machine-learning framework for AGN photometric redshifts using color and variability-based features

Authors: S. Satheesh-Sheeba, P. Sánchez-Sáez, R. J. Assef, T. Anguita, R. Shirley, M. Salvato, P. Arévalo, T T. Ananna, F. E. Bauer, C. G. Bornancini, W. N. Brandt, D. De Cicco, M. Espinoza-Ortiz, J. Fagin, M. Fatović, A. W. Graham, H. Guo, L. Hernandez-García, D. Ilić, A. B. Kovačević, P. Lira, A. I. Malz, M. Marculewicz, D. Marsango, C. Mazzucchelli , et al. (17 additional authors not shown)

Abstract: Photometric redshift estimation for active galactic nuclei (AGNs) remains a fundamental challenge for current and upcoming large-scale photometric surveys. Traditional spectral energy distribution (SED) fitting suffers from color-redshift degeneracies, particularly for AGNs whose power-law continua hide the strong spectral features required to anchor redshift estimates. While AGN variability provi… ▽ More Photometric redshift estimation for active galactic nuclei (AGNs) remains a fundamental challenge for current and upcoming large-scale photometric surveys. Traditional spectral energy distribution (SED) fitting suffers from color-redshift degeneracies, particularly for AGNs whose power-law continua hide the strong spectral features required to anchor redshift estimates. While AGN variability provides additional constraining power, existing frameworks require multi-band light curves that are not always available. This work presents VAR-PZnn, a fully connected mixture density network that integrates 26 variability features extracted from ZTF g-band light curves with optical photometry from Pan-STARRS1, mid-infrared (MIR) photometry from CatWISE, and, for a subsample, NIR photometry from UKIDSS. The model is trained and tested on 72,728 spectroscopically confirmed AGNs/QSOs spanning 0.01 < z < 4.5 and g-band magnitudes from 17 to 21.5. For the main sample, we achieve σ_{NMAD} = 0.058 and an outlier fraction of η= 8.2%, which reduces to 5.4% when the 10% of sources with the highest predicted uncertainty are excluded. An ablation study demonstrates that MIR photometry provides the dominant constraint for photo-z accuracy, while variability features serve as a secondary refiner. Using UKIDSS NIR data as a proxy for future synergies between LSST and space-based missions like Euclid and Roman, we obtain η= 13.3% without MIR data and η= 4.6% when MIR is available. We benchmark against Low-Resolution Templates (LRT) SED fitting (η= 28.7%) and the VAR-PZ framework; applying single-band VAR-PZ priors worsens LRT performance to η= 39.4% due to single-band light-curve degeneracies, confirmed via simulations (η= 27.6% to 28.1%). This framework provides a scalable approach for the Legacy Survey of Space and Time (LSST). △ Less

Submitted 17 July, 2026; originally announced July 2026.

Comments: 18 pages, 12 figures, 4 tables, Submitted to Astronomy & Astrophysics Journal

Breakdown of Smooth Shock Solutions in Transient Relativistic Hydrodynamics

Authors: Davi D. de Oliveira, Gabriel S. Denicol

Abstract: In this work, we demonstrate that shock solutions in the Israel-Stewart framework lose regularity once the shock velocity reaches a critical value, and a discontinuity emerges in the solution, which can be interpreted as a second shock wave. This subshock arises as a consequence of the finite speed of information propagation inherent to the Israel-Stewart theory. We then perform numerical simulati… ▽ More In this work, we demonstrate that shock solutions in the Israel-Stewart framework lose regularity once the shock velocity reaches a critical value, and a discontinuity emerges in the solution, which can be interpreted as a second shock wave. This subshock arises as a consequence of the finite speed of information propagation inherent to the Israel-Stewart theory. We then perform numerical simulations to confirm the breakdown of solution continuity. Subsequently, we propose two regularization procedures to extend the domain of continuous shock solutions. The first employs a third-order extension, which introduces new kinetic fields, while the second incorporates a small numerical bulk viscosity. Both methods effectively increase the maximum propagation speed of the Israel-Stewart theory and extend the range over which regular shock solutions exist. Thus, we confirm that this loss of regularity is a direct consequence of the Israel-Stewart framework. These results suggest that Israel-Stewart theory may not provide an adequate description of ultra-relativistic shock waves. △ Less

Submitted 31 July, 2026; v1 submitted 17 July, 2026; originally announced July 2026.

Ultraviolet direct absorption microscopy for single particle protein/nucleic acid quantification

Authors: C. J. Richards, D. van de Lockand, D. Wolters, M. Liebel

Abstract: Bio-nanoparticles are pivotal to next generation nanotherapeutics, but providing single-particle biomolecular characterization remains a crucial challenge. Herein we present ultra-violet direct absorption microscopy (UV-DAM) to tackle this challenge. UV-DAM is based on a tailored illumination scheme for absorption-only imaging, combined with a custom deep UV light source. Combined, they provide bi… ▽ More Bio-nanoparticles are pivotal to next generation nanotherapeutics, but providing single-particle biomolecular characterization remains a crucial challenge. Herein we present ultra-violet direct absorption microscopy (UV-DAM) to tackle this challenge. UV-DAM is based on a tailored illumination scheme for absorption-only imaging, combined with a custom deep UV light source. Combined, they provide biomolecular specificity with single particle sensitivity. As such, UV-DAM provides rapid, label-free, high resolution, biochemical imaging. Enabled by these capabilities, we implement the classic nucleic acid:protein absorption assay at the single virus level where we demonstrate UV-DAM's ability to distinguish empty from DNA-loaded viral capsids based on bimolecularly specific absorption fingerprints. UV-DAM presents the translation from bulk UV-visible spectrometry to single-particle assessment, a crucial advancement for nanomedicine characterization where particle loading efficiencies are often heterogenous. Beyond this, UV-DAM is applicable to a wide range of nanomaterials or investigation of biological process with high spatio-temporal resolution and intrinsic molecular contrast. △ Less

Submitted 16 July, 2026; originally announced July 2026.

Discrete-time generalized canonical transformations for non-autonomous systems

Authors: Leonardo Colombo, David Martin de Diego, Riccardo Muradore, Damiano Rigo, Nicola Sansonetto

Abstract: A dynamical system is said to be \emph{non-autonomous} when the differential equations describing its evolution depends explicitly on time. Among the various geometric approaches to investigate such systems, the cosymplectic formulation provides a natural framework that extends symplectic geometry to time-dependent Hamiltonians systems. However, preserving the associated geometric structures under… ▽ More A dynamical system is said to be \emph{non-autonomous} when the differential equations describing its evolution depends explicitly on time. Among the various geometric approaches to investigate such systems, the cosymplectic formulation provides a natural framework that extends symplectic geometry to time-dependent Hamiltonians systems. However, preserving the associated geometric structures under numerical discretization remains a challenging problem: standard integrators, such as explicit Euler schemes, generally fail to conserve the cosymplectic volume or the underlying Poisson structure. In this work we propose a geometric method for the discretization of non-autonomous Hamiltonian systems based on \emph{generalized canonical transformations}. The approach constructs a symplectomorphism on the extended phase space $T^*(Q \times \mathbb{R})$ whose projection onto $T^*Q \times \mathbb{R}$ defines a structure-preserving discrete flow. We show that this formulation guarantees the preservation of key invariants, including the volume form, the Poisson bracket, and the symplectic structure on each time fiber. △ Less

Submitted 14 July, 2026; originally announced July 2026.

Learning Forced Multibody Dynamics on Lie Groups

Authors: Martine Dyring Hansen, Marta Ghirardelli, Elena Celledoni, David Martin de Diego, Brynjulf Owren

Abstract: We propose an architecture for learning the dynamics of mechanical systems based on discrete forced Euler-Lagrange equations on Lie groups using only position data. By formulating the dynamics directly on manifold-valued configuration spaces, the method naturally respects the geometric structure of the systems and preserves geometric invariants and conservation laws. The reliance on position measu… ▽ More We propose an architecture for learning the dynamics of mechanical systems based on discrete forced Euler-Lagrange equations on Lie groups using only position data. By formulating the dynamics directly on manifold-valued configuration spaces, the method naturally respects the geometric structure of the systems and preserves geometric invariants and conservation laws. The reliance on position measurements alone makes the framework applicable in settings where velocity data are unavailable or noisy. The approach extends naturally to multibody systems, accommodates external control inputs, and demonstrates strong performance on both synthetic and real-world datasets. △ Less

Submitted 14 July, 2026; originally announced July 2026.

Local flag algebras

Authors: Eoin Davey, Eoin Hurley, Rémi de Joannis de Verclos, Ross J. Kang, Jan Volec

Abstract: We introduce local flag algebras, a variant of Razborov's flag algebra framework in which densities are normalised by the maximum degree $Δ(G)$ rather than the order $|G|$. The framework supports the same semidefinite-method machinery as the classical version, but is tailored to extremal problems that scale with the maximum degree. As an illustrative first application we bound the number of pentag… ▽ More We introduce local flag algebras, a variant of Razborov's flag algebra framework in which densities are normalised by the maximum degree $Δ(G)$ rather than the order $|G|$. The framework supports the same semidefinite-method machinery as the classical version, but is tailored to extremal problems that scale with the maximum degree. As an illustrative first application we bound the number of pentagons in a triangle-free graph $G$ as a function of $|G|$ and $Δ(G)$. △ Less

Submitted 14 July, 2026; originally announced July 2026.

Comments: 30 pages, 1 figure

MSC Class: 05C35; 05-08; 05C25

Cluster-Weighted EDMD

Authors: Lorenzo Tomaz, Judd Rosenblatt, Flavio Kicis, Thomas B. Jones, Diogo Schwerz de Lucena

Abstract: Extended Dynamic Mode Decomposition (EDMD) approximates Koopman operators from data, but a single global operator is inefficient when different state-space regions exhibit distinct local dynamics. We introduce Cluster-Weighted EDMD (CW-EDMD), which jointly learns a soft phase-space partition and a per-cluster EDMD operator. Its Expectation-Maximization (EM) objective assigns each transition based… ▽ More Extended Dynamic Mode Decomposition (EDMD) approximates Koopman operators from data, but a single global operator is inefficient when different state-space regions exhibit distinct local dynamics. We introduce Cluster-Weighted EDMD (CW-EDMD), which jointly learns a soft phase-space partition and a per-cluster EDMD operator. Its Expectation-Maximization (EM) objective assigns each transition based on both geometric proximity and prediction residuals, so clusters specialize where local Koopman models are accurate rather than where the data are dense. On Lorenz, damped pendulum, and Duffing systems, across 36 configurations and 10 seeds, CW-EDMD improves matched-degree EDMD in one-step and 5s-rollout prediction. Across 288 paired comparisons, there are significant error reductions in 258 cases, increases in 4, and no differences in 26. Median one-step error reductions are 57x, 2.7x, and 12x on pendulum, Duffing, and Lorenz, respectively. △ Less

Submitted 13 July, 2026; originally announced July 2026.

Comments: Accepted at the International Conference on Scientific Computing and Machine Learning 2026 (SCML2026)

A Non-Commutative Voronovskaya Theorem for Quantum Neural Network Operators

Authors: Rômulo Damasclin Chaves dos Santos, Delvonei Alves de Andrade

Abstract: We prove a complete asymptotic expansion for quantum neural network operators when they approximate arbitrary quantum channels. This is the non-commutative analogue of the classical Voronovskaya theorem. The expansion reveals that the approximation error splits into three fundamentally different parts: integer powers of \(1/n\) involving ordinary Fréchet derivatives; fractional powers governed by… ▽ More We prove a complete asymptotic expansion for quantum neural network operators when they approximate arbitrary quantum channels. This is the non-commutative analogue of the classical Voronovskaya theorem. The expansion reveals that the approximation error splits into three fundamentally different parts: integer powers of \(1/n\) involving ordinary Fréchet derivatives; fractional powers governed by Marchaud fractional derivatives, which capture the Hölder smoothness of the channel; and purely quantum commutator terms that have no classical counterpart. The remainder is bounded sharply by an explicit constant: \[ \norm{R_{m,n}(Φ,\bullet)}_\diamond \le C_{m,γ,d} \|Φ\|_{\cC^{m,γ}} \, n^{-(m+γ)} (\log n)^{3m/2}. \] We present a numerical test for a classical analogue that confirms the predicted convergence rate and the logarithmic correction, directly validating the asymptotic theory. Based on this expansion, we obtain three major advances: a quantum central limit theorem for the fluctuations of quantum neural network operators, a method to construct optimal interpolation geodesics between quantum channels via Kubo-Ando means, and a systematic understanding of how fractional smoothness limits the acceleration of quantum neural network approximations. The numerical test further demonstrates that the theoretical rates are sharp and that logarithmic enhancements are unavoidable. Altogether, our work builds a rigorous bridge between classical approximation theory, fractional calculus, and quantum machine learning, offering both theoretical insight and practical tools for designing and analyzing quantum neural networks in finite dimensions. △ Less

Submitted 1 July, 2026; originally announced July 2026.

Comments: 24 pages

MSC Class: 41A60; 47A58; 46N50; 81P45; 26A33

Anomalous field evolution of the mixed-state linewidth in the second superconducting dome of LaFeAsO$_{1-x}M_x$ ($M={\rm F,H}$)

Authors: Rustem Khasanov, Pierre Dalmas de Réotier, Samuele Sanna, Gianrico Lamura, Hubertus Luetkens, Matteo Moroni, Pietro Carretta, Rhea Kappenberger, Rowena Wachtel, Bernd Büchner, Sabine Wurmehl, Nikolai D. Zhigadlo

Abstract: We report a transverse-field muon-spin rotation/relaxation ($μ$SR) study of the internal-field distribution in the mixed state of LaFeAsO$_{0.89}$F$_{0.11}$ and LaFeAsO$_{0.75}$H$_{0.25}$, representative of the first (SC1) and second (SC2) superconducting domes of the LaFeAsO$_{1-x}M_x$ ($M={\rm F,H}$) family, respectively. Below the superconducting transition temperature $T_{\rm c}$, the linewidt… ▽ More We report a transverse-field muon-spin rotation/relaxation ($μ$SR) study of the internal-field distribution in the mixed state of LaFeAsO$_{0.89}$F$_{0.11}$ and LaFeAsO$_{0.75}$H$_{0.25}$, representative of the first (SC1) and second (SC2) superconducting domes of the LaFeAsO$_{1-x}M_x$ ($M={\rm F,H}$) family, respectively. Below the superconducting transition temperature $T_{\rm c}$, the linewidth of the internal-field distribution increases in both samples, indicating the formation of a vortex lattice. Above $T_{\rm c}$, the linewidth remains field dependent and increases approximately linearly with field, consistent with broadening of the powder spectrum caused by an anisotropic Knight shift. After subtraction of this normal-state contribution, the superconducting linewidth $σ_{\rm sc}$ exhibits qualitatively different field dependences in the two samples. At 4K, the SC1 ($x_{\rm F}=0.11$) sample shows the expected monotonic decrease with increasing field, whereas the SC2 ($x_{\rm H}=0.25$) sample develops a pronounced local maximum near 3T. A contour representation of $σ_{\rm sc}(T,H)$ further reveals a ridge of local maxima whose field position, $H_{σ,\max}(T)$, shifts to lower fields upon warming and disappears near $T_{\rm c}$. The anomalous field evolution observed in the SC2 sample is consistent with an additional field-induced contribution associated with enhanced Pauli-paramagnetic effects, highlighting the distinct electronic character of the two superconducting domes. △ Less

Submitted 11 July, 2026; originally announced July 2026.

Comments: 6 pages, 3 figures

The Three Hundred Project: Validating $H_0$ inference from mock X-ray and millimetre analyses of galaxy clusters

Authors: F. De Luca, H. Bourdin, P. Mazzotta, E. Rasia, A. Kozmanyan, W. Cui, M. De Petris, D. de Andres, G. Yepes

Abstract: Measurements of thermodynamical quantities in galaxy clusters are differently affected by simplified modelling of radially averaged observables in the X-ray and millimetre bands. This includes assumptions about the cosmological model and the morphology of the cluster intracluster medium (ICM). Within a large sample of clusters extracted from The Three Hundred hydrodynamical simulations, we assess… ▽ More Measurements of thermodynamical quantities in galaxy clusters are differently affected by simplified modelling of radially averaged observables in the X-ray and millimetre bands. This includes assumptions about the cosmological model and the morphology of the cluster intracluster medium (ICM). Within a large sample of clusters extracted from The Three Hundred hydrodynamical simulations, we assess the systematic differences expected from the morphological assumptions between ICM temperatures as inferred from X-ray spectroscopy or joint X-ray and millimetre imaging. We find that these differences show a well-defined statistical behaviour that correlates with the cluster dynamical and morphological indicators. We then investigate how joint inferences of cluster temperature profiles, a priori informed by this statistical behaviour, allow us to constrain cosmological parameters inferred from the apparent cluster sizes. Assuming a flat $Λ$ cold dark matter ($Λ$CDM) cosmology and priors on $Ω_\mathrm{m}$ and the helium abundance, this method provides us with unbiased estimates of the Hubble constant, $H_0$, characterised with a precision of about $4\%$ and $1.5\%$ for samples of 100 and 1000 clusters, respectively, and ultimately limited by systematic uncertainties of about $0.6$--$0.8\, {\rm km\, s^{-1} Mpc^{-1}}$. This work highlights the potential of joint X-ray and millimetre observations of galaxy cluster samples to place tight constraints on $H_0$. △ Less

Submitted 21 July, 2026; v1 submitted 9 July, 2026; originally announced July 2026.

Comments: Accepted for publication in A&A

Modular Pretraining Enables Access Control

Authors: Ethan Roland, Murat Cubuktepe, Erick Martinez, Stijn Servaes, Keenan Pepper, Mike Vaiana, Diogo Schwerz de Lucena, Judd Rosenblatt, Addie Foote, Cem Anil, Alex Cloud

Abstract: AI developers face a dual-use dilemma. An AI capability that helps one user cure a disease can help another synthesize one. This dilemma could be resolved with access control, limiting dual-use AI capabilities to trusted deployments with a legitimate need. A gold standard for access control would be to serve separate models with different capabilities to different users. However, training and depl… ▽ More AI developers face a dual-use dilemma. An AI capability that helps one user cure a disease can help another synthesize one. This dilemma could be resolved with access control, limiting dual-use AI capabilities to trusted deployments with a legitimate need. A gold standard for access control would be to serve separate models with different capabilities to different users. However, training and deploying multiple models is prohibitively expensive. To address this challenge, we propose gradient-routed auxiliary modules (GRAM), a pre-training method that adds modules to a neural network and selectively updates them to induce specialization. Ablating a module at inference time removes its capability from the network, approximating a model trained on filtered data. We evaluate GRAM on synthetic stories and realistic dual-use data spanning virology, cybersecurity, nuclear physics, and specialized code. These experiments show that GRAM disables targeted capabilities while preserving the rest, and resists their recovery under finetuning better than post-hoc unlearning. Most importantly, a Chinchilla-optimal scaling analysis from 50M to 5B parameters shows that the gap between data-filtered and full-data models widens with scale on removed capabilities but stays small on retained ones, and that GRAM closely tracks data filtering. GRAM's training cost is independent of the number of supported capability profiles, yielding a 5x reduction over data filtering in our 5-profile setting. △ Less

Submitted 8 July, 2026; originally announced July 2026.

Sub-Torque-Balance Upper Limits on Continuous Gravitational Waves from Scorpius X-1

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, the Precision Ephemerides for Gravitational-Wave Searches, Project, :, A. G. Abac, I. Abouelfettouh, F. Acernese, K. Ackley, A. Adam, C. Adamcewicz, S. Adhicary, D. Adhikari, N. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend , et al. (1814 additional authors not shown)

Abstract: We present the results of a search for continuous gravitational waves from the low-mass X-ray binary Scorpius X-1 using LIGO data from the first part of the fourth LIGO-Virgo-KAGRA observing run. By applying the resampling version of the cross-correlation pipeline to search for signal frequencies $f_0$ between $25$ and $200\un{Hz}$ (corresponding to neutron star spin frequencies of $12.5$ to… ▽ More We present the results of a search for continuous gravitational waves from the low-mass X-ray binary Scorpius X-1 using LIGO data from the first part of the fourth LIGO-Virgo-KAGRA observing run. By applying the resampling version of the cross-correlation pipeline to search for signal frequencies $f_0$ between $25$ and $200\un{Hz}$ (corresponding to neutron star spin frequencies of $12.5$ to $100\un{Hz}$ for GW due to triaxiality, or $\sim15-20$ to $\sim120-150\un{Hz}$ for GW due to $r$-modes), we set upper limits below the standard torque balance level, independent of neutron star spin inclination, for $50\un{Hz}\lesssim f_0\lesssim200\un{Hz}$. While uncertainties in the modelling of torque and equation of state limit the strength of our inference, our results nonetheless argue against torque balance in this spin range for a neutron star described by a hadronic equation of state. The most sensitive upper limits on the gravitational wave amplitude $h_0$, at the upper end of the frequency band searched, approach $5\times10^{-26}$ marginalized over inclination angle and $2\times10^{-26}$ assuming the most favorable inclination. The marginalized upper limits correspond to a sensitivity depth of $70-75\un{Hz}^{-1/2}$, improving sensitivity considerably over previous searches. Expressed as constraints on the triaxial deformation of the neutron star, the limits correspond to an ellipticity of $3\times10^{-5}$ if the GW frequency $f_0$ is $75\un{Hz}$ and $3\times10^{-6}$ if $f_0=200\un{Hz}$, approaching deformations which could be supported by ordinary nuclear matter. Outliers from the search were ruled out as potential signals by a combination of hierarchical followup and analysis of additional data from later in the observing run. △ Less

Submitted 8 July, 2026; originally announced July 2026.

Comments: 30 pages, 7 figures

Report number: LIGO-P2500260-v10

How Hard Is Quantum Advantage? A Cloud Microphysics Stress Test for Variational Quantum Models

Authors: Felix Herbort, Ellen Sarauer, Daniel Ohl de Mello, Paul Christiansen, Steffen Hien, Cedric Brügmann, Dieter Jaksch, Veronika Eyring, Martin Kiffner, Mierk Schwabe

Abstract: Quantum machine learning (QML) could have the potential to leverage advantages of quantum over classical computing but still lacks strong evidence of actual improvements and scalability, partly due to phenomena such as barren plateaus. In this paper, we employ a hybrid quantum neural network (QNN) on a dataset on cloud microphysics, containing processes for phase transitions of water in the atmosp… ▽ More Quantum machine learning (QML) could have the potential to leverage advantages of quantum over classical computing but still lacks strong evidence of actual improvements and scalability, partly due to phenomena such as barren plateaus. In this paper, we employ a hybrid quantum neural network (QNN) on a dataset on cloud microphysics, containing processes for phase transitions of water in the atmosphere and its related temperature changes, which are highly relevant for accurate climate predictions and projections. To reach optimal performance of our QNNs, we employ a rich and trainable frequency spectrum together with expressivity enhancing classical postprocessing. We find that our QNNs strongly benefit from extensive hyperparameter optimization and thereby demonstrate the feasibility of applying QNNs to complex physical systems. At the same time, the QNNs are outperformed by classical baselines in the form of simple fully-connected neural networks. We discuss identified bottlenecks of this class of quantum models to learn the full complexity of the cloud microphysics dataset to show that there is a need to further understand and improve variational quantum models for machine learning such that they might fill the gap where classical models fail or are inefficient. △ Less

Submitted 6 July, 2026; originally announced July 2026.

Comments: 18 pages, 6 figures

An End-to-End Multi-Stage Kill-Chain Attack on Quantum Neural Networks: Demonstration on Trapped-Ion Hardware

Authors: Cedric Brügmann, Daniel Herr, Daniel Ohl de Mello, Pascal Debus, Maximilian Wendlinger, Kilian Tscharke, Juris Ulmanis, Alexander Erhard, Arthur Schmidt, Fabian Petsch

Abstract: We demonstrate an end-to-end, multi-stage attack against a quantum neural network (QNN) model that is executed on a trapped-ion quantum computer. Our chain combines side-channel reconnaissance, crosstalk characterization, adversarial example generation, and a physical crosstalk attack that realizes the adversarial perturbation on the device. We cover the full attack chain on ion traps and report t… ▽ More We demonstrate an end-to-end, multi-stage attack against a quantum neural network (QNN) model that is executed on a trapped-ion quantum computer. Our chain combines side-channel reconnaissance, crosstalk characterization, adversarial example generation, and a physical crosstalk attack that realizes the adversarial perturbation on the device. We cover the full attack chain on ion traps and report the corresponding superconducting-hardware experiments in the appendix. We discuss implications for QaaS providers and hardware mitigations. △ Less

Submitted 3 July, 2026; originally announced July 2026.

Comments: 19 pages, 33 figures

Bidirectional phase sensitivity in holographic phototransient microscopy

Authors: Emmanuel Kotu Robertson, Dennis van de Lockand, Matz Liebel

Abstract: Mid-infrared photothermal microscopy combines the chemical specificity of infrared absorption with the spatial resolution of visible-light detection, but practical implementations face a persistent trade-off between forward-scattering (FWS) and backward-scattering (BWS) detection geometries. FWS provides quantitative, shape-independent phase contrast but requires two-sided optical access that is d… ▽ More Mid-infrared photothermal microscopy combines the chemical specificity of infrared absorption with the spatial resolution of visible-light detection, but practical implementations face a persistent trade-off between forward-scattering (FWS) and backward-scattering (BWS) detection geometries. FWS provides quantitative, shape-independent phase contrast but requires two-sided optical access that is difficult to achieve in aqueous or thick samples. BWS offers convenient single-sided access, but its signals are strongly distorted by depth-dependent interference for micron-scale objects. Here we present a bidirectional femtosecond mid-infrared pump-probe holographic microscope capable of switching between FWS and BWS geometries within a single instrument, and use it to introduce and validate a new imaging modality, internal forward scattering (IFS). IFS exploits the back-reflection generated at the top surface of the mid-infrared-transparent sample substrate as an internally generated forward-scattering illumination wave, isolated from the directly backscattered field via temporal coherence gating. Using polystyrene beads on CaF2 substrates in air, water, and a refractive-index-matched glycerol-water mixture, we show that IFS reproduces the signal magnitudes and temporal dynamics of true FWS measurements while retaining the mechanical simplicity and single-sided accessibility of BWS. These results establish IFS as a practical, quantitative alternative to conventional FWS and BWS geometries for photothermal, and more broadly quantitative phase, imaging, with direct relevance to single-sided imaging of biological or solvent-contained specimens. △ Less

Submitted 3 July, 2026; originally announced July 2026.

Detecting Architectural Drift in Safety-Critical Firmware through Runtime Trace Analysis

Authors: Domenico Francesco De Angelis, Marco De Luca, Domenico Amalfitano, Pasquale Cimmino, Anna Rita Fasolino

Abstract: Maintaining consistency between architectural design and runtime-observed behavior is challenging in long-lived safety-critical firmware. This paper presents a runtime-informed methodology for detecting architectural drift in ISO 26262-compliant firmware. The approach collects hardware-assisted execution traces, abstracts them into message exchanges among firmware components, and compares the resu… ▽ More Maintaining consistency between architectural design and runtime-observed behavior is challenging in long-lived safety-critical firmware. This paper presents a runtime-informed methodology for detecting architectural drift in ISO 26262-compliant firmware. The approach collects hardware-assisted execution traces, abstracts them into message exchanges among firmware components, and compares the resulting runtime behavior with design-time sequence diagrams through a deterministic differencing step. The computed delta identifies discrepancies as confirmed, missing, additional, or inverted, while a constrained LLM-based step generates a human-readable report only to support expert review. We evaluate the methodology in an industrial firmware context through agreement-based validation and a practitioner survey. Results over 26 test cases show strong agreement between the generated deltas and expert-curated references, while practitioners perceive the reports as useful for interpreting drift, reducing manual analysis effort, and supporting safety-oriented documentation activities. The findings suggest that combining runtime trace analysis, deterministic architectural differencing, and constrained LLM-based reporting can practically support architectural drift detection in evolving safety-critical firmware. △ Less

Submitted 3 July, 2026; originally announced July 2026.

Comments: accepted at 42nd IEEE International Conference on Software Maintenance and Evolution (ICSME 2026)

High-Energy Neutrino Tomography of the Earth's Interior with IceCube

Authors: The IceCube Collaboration, R. Abbasi, M. Ackermann, J. Adams, J. A. Aguilar, M. Ahlers, J. M. Alameddine, S. Ali, N. M. Amin, K. Andeen, C. Argüelles, S. Athanasiadou, S. N. Axani, R. Babu, X. Bai, A. Balagopal V., S. W. Barwick, V. Basu, R. Bay, J. J. Beatty, J. Becker Tjus, P. Behrens, J. Beise, C. Bellenghi, S. Benkel , et al. (395 additional authors not shown)

Abstract: The Earth's interior reflects its geological evolution, from accretion to present-day dynamics. Its structure drives the geodynamo in the outer core, generating the magnetic field that shields the surface from charged cosmic radiation. The primary observables of the Earth's interior are its radial density distribution and derived quantities such as its mass and moment of inertia. These have tradit… ▽ More The Earth's interior reflects its geological evolution, from accretion to present-day dynamics. Its structure drives the geodynamo in the outer core, generating the magnetic field that shields the surface from charged cosmic radiation. The primary observables of the Earth's interior are its radial density distribution and derived quantities such as its mass and moment of inertia. These have traditionally been inferred from gravity and seismic wave propagation, which probe the macroscopic response of matter to gravitational and elastic forces. Here we instead constrain the Earth's density profile using high-energy neutrinos observed by the IceCube Neutrino Observatory at the South Pole. We analyze 10.7 years of predominantly muon-neutrino data spanning 500 GeV--100 TeV, including atmospheric neutrinos produced by cosmic-ray interactions in the Earth's atmosphere and the diffuse astrophysical neutrino flux. Neutrino attenuation depends on both the traversed column density and neutrino energy. By measuring the zenith- and energy-dependent flux suppression, we infer the Earth's radial density profile by fitting a concentric uniform-density shell model that incorporates neutrino fluxes, interaction cross sections, detector response, and glacial-ice systematic uncertainties. From the resulting density posteriors, we derive the Earth's mass and polar moment of inertia as measured by neutrinos. These are the most precise weak-interaction measurements of these quantities to date and are consistent with the Preliminary Reference Earth Model and independent gravitational determinations. Our results demonstrate that neutrinos provide a novel probe of planetary interiors via a distinct physical interaction, complementing gravity and seismology. With improved detectors and precision, neutrinos will further contribute to a multifaceted understanding of the Earth's structure. △ Less

Submitted 7 July, 2026; v1 submitted 2 July, 2026; originally announced July 2026.

WavePID: Low-energy flavor identification using single-PMT time series in IceCube

Authors: The IceCube Collaboration, R. Abbasi, M. Ackermann, J. Adams, J. A. Aguilar, M. Ahlers, J. M. Alameddine, S. Ali, N. M. Amin, K. Andeen, C. Argüelles, S. Athanasiadou, S. N. Axani, R. Babu, X. Bai, A. Balagopal V., S. W. Barwick, V. Basu, R. Bay, J. J. Beatty, J. Becker Tjus, P. Behrens, J. Beise, C. Bellenghi, S. Benkel , et al. (395 additional authors not shown)

Abstract: The IceCube Neutrino Observatory, a cubic-kilometer detector at the South Pole, identifies neutrino flavor through event morphology. Sparse photon detection makes this classification particularly challenging in the 5--100~GeV regime, the energy range relevant for oscillation measurements and searches for physics beyond the Standard Model. We introduce WavePID, a template-based log-likelihood-ratio… ▽ More The IceCube Neutrino Observatory, a cubic-kilometer detector at the South Pole, identifies neutrino flavor through event morphology. Sparse photon detection makes this classification particularly challenging in the 5--100~GeV regime, the energy range relevant for oscillation measurements and searches for physics beyond the Standard Model. We introduce WavePID, a template-based log-likelihood-ratio classifier that exploits nanosecond-scale timing on individual detector modules through three observables: the distance to the reconstructed vertex, the early-charge fraction, and the module-to-module time difference. Evaluated on a cascade-enriched sample selected by a state-of-the-art graph neural network, WavePID improves both cascade purity and classification performance over the neural network alone. This demonstrates that per-module pulse timing carries flavor-identification information complementary to morphology-based classifiers, opening a new physics-motivated observable for low-energy neutrino reconstruction. Geant4 simulations associate this signal with differences in Cherenkov emission geometry between muon tracks and electromagnetic showers. These results motivate exploiting nanosecond-scale pulse timing in future low-energy classifiers and in detector designs with improved per-module timing in next-generation neutrino telescopes. △ Less

Submitted 20 August, 2026; v1 submitted 2 July, 2026; originally announced July 2026.

Comments: 14 pages with 7 figures; plus 3 pages supplemental material, submitted to Journal of Instrumentation

How Indian Dermatologists are Utilizing Artificial Intelligence for Clinical Practice and Workflow Management: A Nationwide Survey with a Special Focus on atopic dermatitis

Authors: Dipayan Sengupta, Saumya Panda, Sandipan Dhar, Dipankar De, Deepika Pandhi, Narayanan B

Abstract: Background: Dermatology AI has mainly focused on image-based diagnosis, while chronic disease workflows have received less attention. We surveyed Indian dermatologists to map routine clinical challenges, with a focus on atopic dermatitis (AD), and assess current AI use. Methods: A nationwide cross-sectional survey commissioned by the Society for Eczema Studies included 377 practicing Indian derm… ▽ More Background: Dermatology AI has mainly focused on image-based diagnosis, while chronic disease workflows have received less attention. We surveyed Indian dermatologists to map routine clinical challenges, with a focus on atopic dermatitis (AD), and assess current AI use. Methods: A nationwide cross-sectional survey commissioned by the Society for Eczema Studies included 377 practicing Indian dermatologists. The survey assessed clinical challenges, AD workflow barriers, AI use, adoption barriers, and ethical concerns. Analyses used descriptive statistics, chi-square tests, false discovery rate correction, and multivariable logistic regression. Results: Patient adherence (61.3%) and treatment planning in difficult or refractory cases (57.0%) were reported more often than diagnostic uncertainty (48.0%). In AD care, severity scoring was reported as a challenge by 47.7% and had the lowest satisfaction among measured workflow areas. Current AI use was reported by 49.9%, most often involving general large language models for literature synthesis, documentation, and academic tasks rather than specialized image analysis. Barriers differed by experience: dermatologists with more than 20 years of practice more often cited lack of training, while those with 5 years or less more often cited lack of clinical utility after trying AI tools. AI users were more likely than non-users to report concern about patient self-misdiagnosis and anxiety, which remained significant after adjustment for experience and academic affiliation. Conclusion: Respondents reported using general-purpose AI mainly for cognitive and administrative tasks, while their clinical needs centered on chronic disease management and AD workflow support. Clinician-supervised workflow tools may be more useful than standalone diagnostic applications. △ Less

Submitted 3 June, 2026; originally announced July 2026.

Comments: 28 pages, 5 tables

Searching for the elusive CH2+ with the James Webb Space Telescope. Another carbocation to constrain astrochemical networks

Authors: M. Zannese, L. H. Coudert, E. Dartois, P. Dell'Ova, O. Roncero, P. del Mazo-Sevillano, U. Jacovella, B. Gans, J. R. Goicoechea, D. Van De Putte, C. Boersma, E. Habart, E. Peeters, J. Cami, R. Chown, I. Schroetter, O. Kannavou

Abstract: Carbocations are key species in interstellar chemistry, providing entry points for building larger hydrocarbons. CH+, and more recently, CH3+, have been detected. Other carbocations await detection to provide a comprehensive view of the astrochemical network that is at work in the interstellar medium. We search for CH2+ in objects in which CH3+ was detected and evaluate the most favorable conditio… ▽ More Carbocations are key species in interstellar chemistry, providing entry points for building larger hydrocarbons. CH+, and more recently, CH3+, have been detected. Other carbocations await detection to provide a comprehensive view of the astrochemical network that is at work in the interstellar medium. We search for CH2+ in objects in which CH3+ was detected and evaluate the most favorable conditions for detecting the elusive CH2+ reactive cation. We calculated the CH2+ rotational and rovibrational transitions expected to contribute in the mid- to far-infrared, focusing on the lower-energy rovibrational levels. We then calculated CH2+ infrared emission spectra at different excitation temperatures and compared them to JWST spectra of the externally irradiated disk d203-506 in Orion, where CH+ and CH3+ have already been detected. We used thermochemical models to predict the abundance and spatial morphology of CH2+ to better understand its nondetection. The comparison to JWST spectra allowed us to provide excitation-temperature-dependent upper limits to the excited column density. These are several times lower than those detected for CH+ and CH3+ in their excited states. Based on model calculations for photodissociation regions and assuming similar excitation temperatures, the upper limit derived from observations and CH2+ model spectrum is either slightly above or below the column density expected from models of photodissociation regions. We provide a list of tabulated transitions to allow the community to search for this carbocation in future observations as CH2+ is key in providing observational constraints on astrochemical models. △ Less

Submitted 1 July, 2026; originally announced July 2026.

Comments: Accepted to A&A on the 16/06/2026