Showing 1–50 of 1,124 results for author: Weber, M

Early Exploration of the Scientific Discovery Space for the Habitable Worlds Observatory

Authors: Courtney D. Dressing, Danica Adams, Evelyne Alecian, Gagandeep Anand, Giada Arney, Sarah Gomes Aroucha Barbosa, Martin Barstow, Joanna K. Barstow, Rachael L. Beaton, Eduardo Bendek, Svetlana Berdyugina, Julie Biedermann, Sarah Blunt, Sanchayeeta Borthakur, Kara Brugman, Joseph N. Burchett, Eric Burns, Jenna M. Cann, Ludmila Carone, Cody A. Carr, Richard Cartwright, Renyue Cen, Jean-yves Chaufray, Pin Chen, Lígia F Coelho , et al. (302 additional authors not shown)

Abstract: The Habitable Worlds Observatory (HWO) is a future NASA flagship mission concept identified by the Astro2020 Decadal Survey as the highest priority for large space missions. HWO should conduct "transformative astrophysics" and search for biosignatures in the atmospheres of approximately 25 potentially Earth-like planets. To further the early-stage development of HWO, NASA formed the Science, Techn… ▽ More The Habitable Worlds Observatory (HWO) is a future NASA flagship mission concept identified by the Astro2020 Decadal Survey as the highest priority for large space missions. HWO should conduct "transformative astrophysics" and search for biosignatures in the atmospheres of approximately 25 potentially Earth-like planets. To further the early-stage development of HWO, NASA formed the Science, Technology, Architecture Review Team (START). In turn, START invited the scientific community to join working groups to explore the potential discovery space. In this paper, we present 70 science cases that resulted from this process. The cases address four scientific pillars: growth of galaxies (15 cases), evolution of the elements (13 cases), solar systems in context (32 cases), and living worlds (10 cases). Combined, they would address 27 of the 30 science questions and discovery areas identified by Astro2020. The 140 observing programs needed for the 70 investigations encompass a rich variety of spectroscopic (for 87% of science cases) and photometric (for 30%) observations extending from the UV to the NIR. Additionally, high-contrast and polarimetric capabilities would be needed for 34% and 27% of science cases, respectively. Access to UV wavelengths is critical: 83% of science cases need data at wavelengths <400 nm, and 26% extend to <100 nm. In the NIR, 26% of science cases need observations at wavelengths >=2000 nm. Pursuing the full portfolio of science would also necessitate precise astrometry for planet mass measurement, rapid response capabilities, a large instantaneous field of regard, non-sidereal tracking, saturation mitigation strategies, and high dynamic range. △ Less

Submitted 11 August, 2026; originally announced August 2026.

Comments: 215 pages, 18 figures, 16 tables. This to-be-submitted manuscript summarizes and synthesizes science cases developed by the Habitable Worlds Observatory START and science working groups. See Table 1 for a roadmap, Table 5 for a list of science cases, Figure 11 for a visualization of common observational needs, Figure 16 for connections to Astro2020, and Tables 6-15 (after conclusions) for details

Ollivier's Ricci Curvature on Complex-weighted Graphs

Authors: Yu Tian, Eleanor Wiesler, Melanie Weber

Abstract: Understanding the geometry of complex networks is critical for effective modeling and analysis across domains. While discrete notions of Ricci curvature have emerged as powerful tools for characterizing both local and global network structure, existing formulations are largely confined to undirected networks with real-valued weights. This limits the use of curvature-based analysis of directional a… ▽ More Understanding the geometry of complex networks is critical for effective modeling and analysis across domains. While discrete notions of Ricci curvature have emerged as powerful tools for characterizing both local and global network structure, existing formulations are largely confined to undirected networks with real-valued weights. This limits the use of curvature-based analysis of directional and complex-weighted relations that arise naturally in many applications, from social and biological systems to quantum and signal-processing networks. In this work, we introduce a principled extension of Ollivier's Ricci curvature to complex-weighted graphs, which encompasses directed graphs as a special case. We establish fundamental theoretical properties of this new notion, including relations to the magnetic Laplacian and combinatorial upper and lower bounds that relate curvature to cycle structure in local neighborhoods. We further develop computational methods for curvature estimation and demonstrate their utility in community detection on directed networks. △ Less

Submitted 10 August, 2026; originally announced August 2026.

Comments: 32 pages, 11 figures

MSC Class: 68R10; 68Q25; 51F99

Adaptive Symmetry Discovery for Dynamical System Identification

Authors: Behrooz Tahmasebi, Melanie Weber

Abstract: Dynamical systems model trajectory data generated by fixed underlying dynamics, with applications ranging from biology to physics. Especially in scientific settings, dynamical systems are not generic but often exhibit symmetries imposed by physical laws, formalized through equivariance with respect to group actions. The identification problem concerns recovering the parameters of a system from obs… ▽ More Dynamical systems model trajectory data generated by fixed underlying dynamics, with applications ranging from biology to physics. Especially in scientific settings, dynamical systems are not generic but often exhibit symmetries imposed by physical laws, formalized through equivariance with respect to group actions. The identification problem concerns recovering the parameters of a system from observed trajectories. In this work, we study adaptive symmetry discovery for dynamical system identification and address how a system can be identified from a single trajectory when it is equivariant with respect to an unknown symmetry group. To this end, we first show that for known symmetries, the system can be identified from a significantly shorter single trajectory than in the generic setting, and we precisely characterize this improvement. We then consider the automatic symmetry discovery setting, proposing a method to learn the symmetry group directly from a single trajectory and incorporate it into the identification procedure, achieving the same optimal trajectory length as in the known-symmetry case. Our analysis relies on tools from group representation theory and the expander properties of Cayley graphs, and may be of independent interest for the study of symmetries in dynamical systems. △ Less

Submitted 8 August, 2026; originally announced August 2026.

Comments: 38 pages, 1 figure. Published at ICML 2026

Journal ref: International Conference on Machine Learning (ICML) 2026

Dissipation-induced bulk and boundary criticality in the Haldane chain

Authors: Zhenjiu Wang, Manuel Weber

Abstract: We study the Haldane chain coupled to a dissipative ohmic bath. Using large-scale quantum Monte Carlo simulations, we identify a second-order quantum phase transition into an antiferromagnetic state with spontaneously broken SO(3) symmetry that is governed by an interacting fixed point with dynamical exponent $z\approx 2$. We derive a generalized string order parameter which indicates that the sym… ▽ More We study the Haldane chain coupled to a dissipative ohmic bath. Using large-scale quantum Monte Carlo simulations, we identify a second-order quantum phase transition into an antiferromagnetic state with spontaneously broken SO(3) symmetry that is governed by an interacting fixed point with dynamical exponent $z\approx 2$. We derive a generalized string order parameter which indicates that the symmetry-protected topological ground state of the Haldane chain is stable for weak dissipation and develops a nontrivial scaling dimension at criticality. In particular, its topological edge modes display nontrivial boundary criticality that is distinct from an equivalent transition out of a trivial state; for the latter, we perform an accurate $ε$ expansion of a dissipative $φ^4$ theory with ordinary boundary conditions. Our setup realizes a spin impurity in a critical yet nonconformal antiferromagnet and paves the way for continuously tunable boundary criticality controlled by dissipation. △ Less

Submitted 6 August, 2026; originally announced August 2026.

A Bayesian approach to the long-baseline neutrino oscillation sensitivity of DUNE

Authors: DUNE Collaboration, S. Abbaslu, F. Abd Alrahman, A. Abed Abud, R. Acciarri, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, K. Adhikari, C. Adriano, K. Agudelo-Jaramillo, F. Akbar, F. Alemanno, N. S. Alex, L. Aliaga Soplin, A. Alqaisi, O. Alterkait, A. Alton, R. Alvarez, T. Alves, A. Aman, H. Amar, R. M. Amarinei, P. Amedo , et al. (1262 additional authors not shown)

Abstract: The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is evaluated using a Bayesian Markov Chain Monte Carlo (MCMC) approach. This analysis uses the same underlying sensitivity inputs as previous DUNE studies [Eur. Phys. J. C 80, 978 (2020)], and therefore does not present updated DUNE sensitivities, but instead explores the additional inferences accessible usi… ▽ More The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is evaluated using a Bayesian Markov Chain Monte Carlo (MCMC) approach. This analysis uses the same underlying sensitivity inputs as previous DUNE studies [Eur. Phys. J. C 80, 978 (2020)], and therefore does not present updated DUNE sensitivities, but instead explores the additional inferences accessible using a Bayesian approach. We present four-dimensional posterior probability distributions of the oscillation parameters, highlighting the breadth of correlation in the parameter space of interest, especially between $\sin^2 θ_{23}$ and $\sin^2 θ_{13}$. We exploit the flexibility of the Bayesian framework to incorporate parameter constraints post hoc and assess the impact of applying a reactor short-baseline $θ_{13}$ constraint. A significant increase in the sensitivity to the $θ_{23}$ octant is found when including the constraint. Posterior distributions of derived quantities can be easily constructed from MCMC results. This work presents the first study of DUNE's sensitivity to the Jarlskog invariant, $J$, a quantity that provides a parametrisation-independent measure of charge-parity violation in the leptonic sector. △ Less

Submitted 4 August, 2026; originally announced August 2026.

Comments: 20 pages, 5 figures

Report number: FERMILAB-PUB-26-0548-LBNF

Train Small, Deploy Large: Zero-Shot GNN Transfer Through Geometric Renormalization

Authors: Robert Jankowski, Pedro Almagro-Blanco, Marián Boguñá, Melanie Weber, M. Ángeles Serrano

Abstract: Graph neural networks (GNNs) can operate on large graphs but become infrastructure-sensitive at the scale of millions of nodes and typically require scalable training techniques for even larger graphs. This raises a central question: when can a model trained on a smaller, scaled-down replica of a graph be deployed on the full-resolution graph without retraining? We introduce a zero-shot transfer p… ▽ More Graph neural networks (GNNs) can operate on large graphs but become infrastructure-sensitive at the scale of millions of nodes and typically require scalable training techniques for even larger graphs. This raises a central question: when can a model trained on a smaller, scaled-down replica of a graph be deployed on the full-resolution graph without retraining? We introduce a zero-shot transfer protocol in which a GNN is trained on a graph coarse-grained by geometric renormalization (GR), and the resulting weights are transferred directly to the original network. Across synthetic and real-world networks, training on GR scaled-down replicas preserves much of the original-scale predictive performance while significantly reducing training cost. We further find that learned representations and predictive trajectories remain aligned across scales. These findings suggest that structural similarity may be more important than network size in determining GNN transferability, opening a path toward scale-equivariant graph architectures. △ Less

Submitted 30 July, 2026; originally announced July 2026.

Powers of the Vandermonde determinant are eventually non-SNP

Authors: Thien Le, Melanie Weber

Abstract: We prove a conjecture of Monical, Tokcan, and Yong that every fixed positive power of the Vandermonde determinant is non-SNP in all sufficiently many variables, where a polynomial is non-SNP if there is a lattice point in its Newton polytope that does not appear with nonzero coefficient. This means our result proves that for every even power $k\geq4$, there is always such a missing lattice monomia… ▽ More We prove a conjecture of Monical, Tokcan, and Yong that every fixed positive power of the Vandermonde determinant is non-SNP in all sufficiently many variables, where a polynomial is non-SNP if there is a lattice point in its Newton polytope that does not appear with nonzero coefficient. This means our result proves that for every even power $k\geq4$, there is always such a missing lattice monomial in large enough dimensions. The odd case follows from alternation, and the quadratic case was previously known. For every even power $k\geq4$, we exhibit an explicit lattice point in the Newton polytope of $a_{δ_k}^k$ whose coefficient vanishes. The vanishing is obtained from a Dyson constant-term identity, proved using the finite-variable Jack scalar product and Macdonald's specialization formula. The key even-power construction and proof strategy arose from prompting with OpenAI Codex (GPT Sol 5.6 Extra High), a large language model; the complete transcript appears in the appendix. The authors subsequently checked and organized the argument. The accompanying Lean formalization is available at https://github.com/steven-le-thien/vandermonde-snp. △ Less

Submitted 26 July, 2026; originally announced July 2026.

Comments: 34 pages

Operation and performance of ProtoDUNE Dual Phase liquid argon time projection chamber

Authors: DUNE Collaboration, S. Abbaslu, F. Abd Alrahman, A. Abed Abud, R. Acciarri, L. P. Accorsi, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, K. Adhikari, C. Adriano, K. Agudelo-Jaramillo, F. Akbar, F. Alemanno, N. S. Alex, L. Aliaga Soplin, A. Alqaisi, M. Alrashed, A. Alton, R. Alvarez, T. Alves, A. Aman, H. Amar, R. Amarinei , et al. (1341 additional authors not shown)

Abstract: ProtoDUNE-DP was the largest ever built Liquid Argon Time Projection Chamber (LArTPC) operating in Dual-Phase (DP) mode, with a liquid target and charge read-out placed in the gas. It had an active volume of $6\times6\times6$\,m$^3$ corresponding to an active mass of 300\,t (total LAr mass of 720\,t), constructed at the CERN Neutrino Platform and took data from 2019 to 2020 with cosmic muons. In P… ▽ More ProtoDUNE-DP was the largest ever built Liquid Argon Time Projection Chamber (LArTPC) operating in Dual-Phase (DP) mode, with a liquid target and charge read-out placed in the gas. It had an active volume of $6\times6\times6$\,m$^3$ corresponding to an active mass of 300\,t (total LAr mass of 720\,t), constructed at the CERN Neutrino Platform and took data from 2019 to 2020 with cosmic muons. In ProtoDUNE-DP the electric drift field is oriented in the vertical direction, causing the electrons to drift vertically towards the anode at the top. The ionization charge is then extracted into the gaseous argon above the liquid surface, amplified by Townsend avalanches, and collected by the charge readout planes. The detector experienced significant technical problems affecting the long-term operation of the Charge Readout Planes, formed by the Large Electron Multipliers, but other critical segments demonstrated required performance including the delivery of -300 kV to the TPC cathode, verification of replaceable charge read-out electronics, and operation of the photon detection system. ProtoDUNE-DP experience resulted in improved designs of the Vertical Drift LArTPC. △ Less

Submitted 21 July, 2026; v1 submitted 17 July, 2026; originally announced July 2026.

Comments: 103 pages, 66 figures

Report number: FERMILAB-PUB-26-0466-LBNF

Ionized gas emission in protoplanetary disks with the SKAO

Authors: Greta Guidi, Christian Rab, Barbara Ercolano, Michael L. Weber, Claudio Codella, Izaskun Jiménez-Serra, Evgenia Koumpia, John D. Ilee, Enrique Macías, Elena Viscardi, Yinhao Wu, Francesca Bacciotti, Asmita Bhandare, Eleonora Bianchi, Tyler Bourke, Luca Cacciapuoti, Antonio Garufi, Geoffroy Lesur, Vincent Piétu, Linda Podio, Giovanni Sabatini, Leonardo Testi, Claudia Toci

Abstract: Protoplanetary disks represent a crucial stage in the evolution of Young Stellar Objects towards the formation of fully formed planetary systems. While substantial progress has been made in the last decades in the characterization of the dust and molecular gas in these systems, the ionized component remains poorly understood. Ionized gas traces important processes such as photoevaporation, accreti… ▽ More Protoplanetary disks represent a crucial stage in the evolution of Young Stellar Objects towards the formation of fully formed planetary systems. While substantial progress has been made in the last decades in the characterization of the dust and molecular gas in these systems, the ionized component remains poorly understood. Ionized gas traces important processes such as photoevaporation, accretion, disk winds, and jets, and therefore is key to studying disk dynamics, evolution, and ultimately planet formation. In this paper, we investigate the capabilities of the forthcoming SKA telescope to probe this component in protoplanetary disks within nearby star forming regions. We present state-of-the-art simulations of photoevaporative, magneto-thermal, and magnetohydrodynamic winds, and generate theoretical predictions and synthetic SKAO observations to assess its potential in detecting and characterizing free-free emission and Hydrogen recombination lines. Finally, we discuss synergies with complementary facilities and how they will provide a comprehensive, multi-scale view of disk winds and offer critical insights on the mechanisms driving disk evolution and the onset of planet formation. △ Less

Submitted 8 July, 2026; originally announced July 2026.

Comments: Published in Advancing Astrophysics with the SKA II (AASKAII), 2026 (arXiv:2606.20366). Report-no:AASKAII/Guidi01. Advancing Astrophysics with the SKA II (AASKAII) outlines the transformative scientific advances that will be enabled by the SKA telescopes

Report number: AASKAII/Guidi01

CRexit observed: probing cosmic ray transport in the circumgalactic medium with absorption line spectra

Authors: Matthias Weber, Timon Thomas, Christoph Pfrommer, Tanya Urrutia

Abstract: Cosmic rays (CRs) likely provide dynamically important non-thermal pressure support in the circumgalactic medium (CGM), but how their transport physics shapes observable absorption signatures remains uncertain. We investigate whether absorption-line diagnostics can distinguish between different CR transport regimes in CR-pressure-dominated halos. Using high-resolution simulations, we generate synt… ▽ More Cosmic rays (CRs) likely provide dynamically important non-thermal pressure support in the circumgalactic medium (CGM), but how their transport physics shapes observable absorption signatures remains uncertain. We investigate whether absorption-line diagnostics can distinguish between different CR transport regimes in CR-pressure-dominated halos. Using high-resolution simulations, we generate synthetic spectra along large ensembles of sightlines and measure column densities, equivalent widths, covering fractions (CFs), velocity widths, abundance ratios, and stacked absorption profiles for ions tracing cool, warm, and hot gas. We find that the effective CR transport speed strongly regulates the multiphase structure of the CGM. Efficient CR transport enhances the formation of cool ($T\sim10^4$ K) and warm ($T\sim10^5$ K) gas, leading to deeper and broader absorption lines of low- and intermediate-ionization species. The two-moment CR transport model produces the strongest MgII and SiII absorption and reaches MgII CFs consistent with the range inferred for star-forming galaxies. In contrast, slow CR transport underproduces cool, low-ionization gas and yields substantially weaker absorption. We also find that the origin of CIV-bearing gas changes with CR transport: slow transport mainly produces extended warm halo gas, whereas efficient transport shifts much of the CIV absorption into mixing layers around cool clouds. The high-ionization tracer OVI responds more weakly, indicating that CR transport primarily regulates the cool condensed phase and its interfaces rather than the volume-filling hot halo. These findings suggest that absorption-line measurements of cool and transition-phase gas can provide valuable constraints on the effective transport of CRs through the CGM. △ Less

Submitted 7 July, 2026; originally announced July 2026.

Comments: Submitted to A&A, 20 pages, 13 figures

Production and installation of wavelength-shifting reflective light enhancers for the Short-Baseline Near Detector

Authors: R. Acciarri, L. Aliaga-Soplin, R. Alvarez-Garrote, D. Andrade Aldana, C. Andreopoulos, A. Antonakis, S. Balasubramanian, A. Barnard, V. Basque, J. Bateman, M. C. Bazetto, A. Beever, E. Belchior, M. Betancourt, A. Bhat, M. Bishai, A. Blake, B. Bogart, D. Brailsford, A. Brandt, S. Brickner, M. B. Brunetti, L. Camilleri, D. Caratelli, D. Carber , et al. (172 additional authors not shown)

Abstract: We report on the design, production, and installation of a wavelength-shifting reflective system on the cathode of the Short-Baseline Near Detector (SBND), a liquid argon time projection chamber located along the Fermilab Booster Neutrino Beam. To increase and homogenize scintillation-light collection, 64 double-sided plates were fabricated from FR4, laminated with specular reflector film and coat… ▽ More We report on the design, production, and installation of a wavelength-shifting reflective system on the cathode of the Short-Baseline Near Detector (SBND), a liquid argon time projection chamber located along the Fermilab Booster Neutrino Beam. To increase and homogenize scintillation-light collection, 64 double-sided plates were fabricated from FR4, laminated with specular reflector film and coated with 300 $μ$g/cm$^2$ of tetraphenyl butadiene (TPB) wavelength shifter using controlled physical vapor deposition. The coating uniformity was validated through dedicated measurements of deposited mass and profilometry studies. Because exposure to ambient blue/UV light could degrade the TPB, protective filtering and controlled storage conditions were implemented during handling and installation. The coated plates were assembled between conductive meshes for high-voltage compatibility and installed in situ during detector integration. This system constitutes the largest TPB-coated area deployed in a neutrino detector. It operates in conjunction with SBND's photon detection system, which consists of photomultiplier tubes and X-ARAPUCAs. Early light-collection measurements show high uniformity and light response across the detector, supporting improved triggering, calorimetry, and position reconstruction in SBND. △ Less

Submitted 24 June, 2026; originally announced June 2026.

Data Augmentation: A Fourier Analysis Perspective

Authors: Behrooz Tahmasebi, Melanie Weber, Stefanie Jegelka

Abstract: Data augmentation is a simple and model-agnostic approach for exploiting known invariances in learning problems. Given a group acting on the input space, one augments the training set with transformed copies of each sample. Because it exploits symmetries without modifying the underlying learning algorithm, data augmentation can be applied broadly across learning methods. However, this universality… ▽ More Data augmentation is a simple and model-agnostic approach for exploiting known invariances in learning problems. Given a group acting on the input space, one augments the training set with transformed copies of each sample. Because it exploits symmetries without modifying the underlying learning algorithm, data augmentation can be applied broadly across learning methods. However, this universality comes at a computational cost: when the group is large, full group-sized augmentation quickly becomes computationally infeasible. This raises a fundamental question: Can partial data augmentation achieve the same statistical benefits as full augmentation in terms of generalization and sample complexity? We develop a general framework for investigating this question using Fourier analysis and the representation theory of finite groups. We show that, for a broad class of classical learning problems, partial data augmentation based on a randomly sampled subset of group elements achieves the same minimax rates as full augmentation, up to an approximation error that vanishes as the subset size increases. Our results provide a theoretical explanation for why partial augmentation can retain the statistical benefits of full augmentation despite enforcing symmetry only approximately, and shed light on a recently raised question in learning with symmetries: whether statistically optimal learning under general group invariances can be achieved using computationally scalable methods. Moreover, we prove a complementary impossibility result: enforcing exact invariance via data augmentation requires averaging over the entire group, and cannot be achieved by any strict subset when the hypothesis space is sufficiently expressive. Together, these results provide a unified perspective on full and partial data augmentation, as well as exact and approximate symmetry enforcement. △ Less

Submitted 23 June, 2026; originally announced June 2026.

Comments: 42 pages, 1 figure. Published at COLT 2026

Journal ref: Conference on Learning Theory (COLT) 2026

Probing Nuclear Effects with Transverse Kinematic Imbalance in Muon-neutrino Induced Charged-Current $π^0$ Production on Argon with the MicroBooNE Detector

Authors: MicroBooNE collaboration, P. Abratenko, D. Andrade Aldana, J. Asaadi, A. Ashkenazi, S. Balasubramanian, B. Baller, A. Barnard, G. Barr, D. Barrow, J. Barrow, V. Basque, J. Bateman, B. Behera, O. Benevides Rodrigues, S. Berkman, A. Bhat, V. Bhelande, M. Bhattacharya, A. Binau, M. Bishai, A. Blake, B. Bogart, T. Bolton, M. B. Brunetti , et al. (170 additional authors not shown)

Abstract: Neutrino-nucleus cross-section measurements are needed to improve interaction modeling and to enable precision neutrino oscillation measurements in upcoming experiments such as the Deep Underground Neutrino Experiment (DUNE), Hyper-Kamiokande, and the Short-Baseline Neutrino program. Baryon-resonance neutrino interactions constitute a dominant contribution near the peak of the DUNE neutrino energy… ▽ More Neutrino-nucleus cross-section measurements are needed to improve interaction modeling and to enable precision neutrino oscillation measurements in upcoming experiments such as the Deep Underground Neutrino Experiment (DUNE), Hyper-Kamiokande, and the Short-Baseline Neutrino program. Baryon-resonance neutrino interactions constitute a dominant contribution near the peak of the DUNE neutrino energy spectrum. We present the first measurement of muon neutrino charged-current resonance-like interactions on argon using transverse kinematic imbalance variables with the MicroBooNE detector. These observables are highly sensitive to the modeling of final-state interactions. This measurement probes kinematic imbalances using the reconstructed momenta of the muon, leading proton, and neutral pion. A comprehensive characterization of the $π^0$-proton final state is presented; however, none of the models considered are able to simultaneously reproduce all measured observables. △ Less

Submitted 22 June, 2026; originally announced June 2026.

Operadic categories as (pseudo)-simplicial groupoids

Authors: Michael Batanin, Joachim Kock, Mark Weber

Abstract: From any operadic category O we construct a simplicial groupoid X (slightly pseudo in a specific way), called the operadic nerve. It integrates all the structure of chosen-local-terminals, fibre functor, and cardinality functor into a single simplicial groupoid, which can be seen as an undecking of the ordinary nerve of O in the Kleisli category for the symmetric-monoidal-groupoid monad S: we have… ▽ More From any operadic category O we construct a simplicial groupoid X (slightly pseudo in a specific way), called the operadic nerve. It integrates all the structure of chosen-local-terminals, fibre functor, and cardinality functor into a single simplicial groupoid, which can be seen as an undecking of the ordinary nerve of O in the Kleisli category for the symmetric-monoidal-groupoid monad S: we have the equation DX = SNO, where D is upper decalage. The construction leads to a new characterisation of operadic categories, in which all the axioms end up as simplicial identities, and where the notion of operad over an operadic category takes the form of a simplicial map subject to well-known pullback conditions (the notion of IKEO map). △ Less

Submitted 14 June, 2026; originally announced June 2026.

Comments: 47pp

Report number: CPH-GEOTOP-DNRF151 MSC Class: 18M60 (Primary); 18N50; 18D10 (Secondary)

First Measurement of Sub-GeV $ν_μ$ Charged-Current Coherent Pion Production on Argon in MicroBooNE

Authors: MicroBooNE collaboration, P. Abratenko, D. Andrade Aldana, J. Asaadi, A. Ashkenazi, S. Balasubramanian, B. Baller, A. Barnard, G. Barr, D. Barrow, J. Barrow, V. Basque, J. Bateman, B. Behera, O. Benevides Rodrigues, S. Berkman, A. Bhat, M. Bhattacharya, V. Bhelande, A. Binau, M. Bishai, A. Blake, B. Bogart, T. Bolton, M. B. Brunetti , et al. (167 additional authors not shown)

Abstract: We report a measurement of the charged-current coherent pion production cross section on argon using the MicroBooNE liquid argon time projection chamber exposed to the Booster Neutrino Beam at Fermilab. The measurement uses the MicroBooNE data set corresponding to $1.26 \times 10^{21}$ protons on target with a mean neutrino energy of $0.8$~GeV. The flux-averaged cross section is measured to be… ▽ More We report a measurement of the charged-current coherent pion production cross section on argon using the MicroBooNE liquid argon time projection chamber exposed to the Booster Neutrino Beam at Fermilab. The measurement uses the MicroBooNE data set corresponding to $1.26 \times 10^{21}$ protons on target with a mean neutrino energy of $0.8$~GeV. The flux-averaged cross section is measured to be $(9.1 \pm 1.2_{\text{stat}} \pm 1.2_\text{syst}) \times 10^{-40}\,\text{cm}^2/\text{Ar}$. This result represents the first measurement of charged-current coherent pion production on argon at sub-GeV neutrino energies. Due to its clean two-body kinematics, where the neutrino interacts coherently with the entire nucleus producing a forward muon and pion with no nuclear breakup, this process provides a useful tool for constraining neutrino flux uncertainties in current and future oscillation experiments such as DUNE. △ Less

Submitted 11 June, 2026; originally announced June 2026.

Report number: FERMILAB-PUB-26-0335-PPD

Contrastive Neural Algorithmic Reasoning for Graph Coloring

Authors: Thien Le, Tianyu Zhao, Melanie Weber

Abstract: Graph coloring seeks to assigns colors to a graph's nodes so that adjacent nodes receive different colors, using as few colors as possible. Here, we study approximate $k$-coloring, where the goal is to use at most $k$ colors while minimizing the number of monochromatic edges. This problem is central to graph theory and has applications in areas such as scheduling and resource allocation. Recent un… ▽ More Graph coloring seeks to assigns colors to a graph's nodes so that adjacent nodes receive different colors, using as few colors as possible. Here, we study approximate $k$-coloring, where the goal is to use at most $k$ colors while minimizing the number of monochromatic edges. This problem is central to graph theory and has applications in areas such as scheduling and resource allocation. Recent unsupervised GNN approaches optimize each instance directly, precluding generalization across graph sizes and distributions. We instead propose a contrastive learning framework that learns transferable coloring geometry where the embeddings of same-color nodes align, while adjacent nodes' representations are pushed toward distinct directions. We analyze the resulting population objective over bounded-size graphs. For unit-norm embeddings, we show that its optima have a line-prototype structure: Representations of nodes of the same color collapse to a shared one-dimensional subspace, and edges connect orthogonal subspaces. This geometry yields stationarity conditions in the supervised setting and is preserved by projected subgradient dynamics under a balanced-coloring assumption. In an unnormalized variant, gradient descent has a max-margin bias governed by a quotient-graph hard-margin problem. Experiments on synthetic and real-world graphs show that contrastive GNN encoders generalize effectively and produce low-conflict colorings, matching and sometimes improving on greedy approaches. △ Less

Submitted 2 June, 2026; originally announced June 2026.

Comments: 52 pages, 5 figures, 45 tables

Characterizing the energy resolution of the MicroBooNE LArTPC at the MeV scale using monoenergetic features of $^{208}$Tl decays

Authors: MicroBooNE collaboration, P. Abratenko, D. Andrade Aldana, J. Asaadi, A. Ashkenazi, S. Balasubramanian, B. Baller, A. Barnard, G. Barr, D. Barrow, J. Barrow, V. Basque, J. Bateman, B. Behera, O. Benevides Rodrigues, S. Berkman, A. Bhat, M. Bhattacharya, V. Bhelande, A. Binau, M. Bishai, A. Blake, B. Bogart, T. Bolton, M. B. Brunetti , et al. (167 additional authors not shown)

Abstract: A detailed understanding of the capabilities and fidelity of low-energy reconstruction is crucial for taking advantage of MeV-scale neutrino physics opportunities in liquid argon time projection chambers (LArTPCs). This study presents a measurement of the resolution of reconstructed energy in the MicroBooNE LArTPC at $\approx 1.5$ MeV. The characterization is performed using monoenergetic signals… ▽ More A detailed understanding of the capabilities and fidelity of low-energy reconstruction is crucial for taking advantage of MeV-scale neutrino physics opportunities in liquid argon time projection chambers (LArTPCs). This study presents a measurement of the resolution of reconstructed energy in the MicroBooNE LArTPC at $\approx 1.5$ MeV. The characterization is performed using monoenergetic signals generated by $2.614$ MeV $γ$-rays from $^{208}$Tl decays undergoing pair production in the detector. The resolution is found to be ($7.52 \pm 0.78 \text{(stat)} \pm 0.92 \text{(syst)}$)%. This value is consistent with the MicroBooNE simulation prediction of ($9.70 \pm 0.65 \text{(stat)}$)% at the $1.6 σ$ level. This study represents the first ever measurement of LArTPC energy resolution at the MeV scale and provides a pathway for monoenergetic energy calibrations in future experiments using LArTPC detectors. △ Less

Submitted 17 August, 2026; v1 submitted 28 May, 2026; originally announced May 2026.

Comments: 15 pages, 9 figures, and 2 tables

Report number: FERMILAB-PUB-26-0288

Boolean Algebra -- Driven Sepsis Diagnosis

Authors: Marcus Weber, Kai Kappert, Marco Reidelbach, Ambros Gleixne, Konstantin Fackeldey, Wolfgang Bauer

Abstract: Sepsis remains a diagnostic challenge due to its heterogeneous molecular signatures and complex immune responses. In this study, we develop a logical data analysis framework based on Boolean polynomial rings. This method constructs an ideal $\mathcal{I}$ of selection criteria that isolate empty subsets of previously analyzed patient data. This approach enables the derivation of interpretable class… ▽ More Sepsis remains a diagnostic challenge due to its heterogeneous molecular signatures and complex immune responses. In this study, we develop a logical data analysis framework based on Boolean polynomial rings. This method constructs an ideal $\mathcal{I}$ of selection criteria that isolate empty subsets of previously analyzed patient data. This approach enables the derivation of interpretable classification rules based on biomarker profiles. We demonstrate that logical data analysis identifies distinct logical patterns for positive and negative sepsis classification. For instance, elevated levels of GLP-1 and MyD88 are associated with septic states in our dataset, whereas high TRAIL and low MyD88 concentrations may suggest a non-septic condition. Importantly, a new way to integrate expert knowledge to filter out potential overfitting or dataset-specific artifacts is shown. Our findings highlight the utility of logics in generating transparent, biologically plausible rules for a data-based and expert-based understanding of sepsis. Moreover, we show how data analysis can benefit from algebraic structures. △ Less

Submitted 28 May, 2026; originally announced May 2026.

Towards Distillation Guarantees under Algorithmic Alignment for Combinatorial Optimization

Authors: Thien Le, Melanie Weber

Abstract: Distillation transfers knowledge from a large model trained on broad data to a smaller, more efficient model suitable for deployment. In structured prediction settings, prior knowledge about the task can guide the choice of a target architecture that is algorithmically aligned with the underlying problem. Building on recent learning-theoretic analyses of decision-tree (DT) distillation (Boix-Adser… ▽ More Distillation transfers knowledge from a large model trained on broad data to a smaller, more efficient model suitable for deployment. In structured prediction settings, prior knowledge about the task can guide the choice of a target architecture that is algorithmically aligned with the underlying problem. Building on recent learning-theoretic analyses of decision-tree (DT) distillation (Boix-Adsera, 2024), we study when distillation succeeds for combinatorial optimization tasks. We focus on the case where the target model is a graph neural network whose architecture is aligned with a dynamic programming (DP) algorithm for the task. Assuming that the source model is sufficiently rich, formalized through the linear representation hypothesis (LRH) (Elhage et al., 2022; Park et al., 2024), we show that the distillation problem can be solved efficiently in the complexity parameters of the DP transition function, represented as a DT. Our results provide a rigorous sufficient condition for successful distillation in the flavour of algorithmic alignment. △ Less

Submitted 19 May, 2026; originally announced May 2026.

Comments: 22 pages

Neural Network-Based Virtual Wheel-Speed Sensor for Enhanced Low-Velocity State Estimation

Authors: Hendrik Schäfke, Daniel O. M. Weber, Askar Vagapov, Christoph Schweers, Thomas Seel, Simon F. G. Ehlers

Abstract: Accurate wheel speed information is crucial for vehicle control and state estimation. Conventional sensors suffer from quantization and latency, especially at low velocities, while motor-speed signals in electric vehicles are distorted by drivetrain torsion. This work presents a neural-network-based virtual wheel-speed sensor that fuses wheel-speed and motor-speed signals to reduce errors from bot… ▽ More Accurate wheel speed information is crucial for vehicle control and state estimation. Conventional sensors suffer from quantization and latency, especially at low velocities, while motor-speed signals in electric vehicles are distorted by drivetrain torsion. This work presents a neural-network-based virtual wheel-speed sensor that fuses wheel-speed and motor-speed signals to reduce errors from both sources. Validated on real-world Volkswagen ID.7 data, the real-time capable model achieves an error reduction of up to 85% compared to the production sensor and 47% compared to an optimized zero-phase filter, providing a smooth signal for driver-assistance functions. The results demonstrate robust generalization across diverse real-world maneuvers within the vehicle platform. △ Less

Submitted 12 May, 2026; originally announced May 2026.

Comments: Accepted for publication in the Proceedings of the 22nd IFAC World Congress, Busan, Republic of Korea, 2026

Improved muon energy estimation using a detailed model of multiple Coulomb scattering in the MicroBooNE LArTPC

Authors: MicroBooNE Collaboration, P. Abratenko, D. Andrade Aldana, J. Asaadi, A. Ashkenazi, S. Balasubramanian, B. Baller, A. Barnard, G. Barr, D. Barrow, J. Barrow, V. Basque, J. Bateman, B. Behera, O. Benevides Rodrigues, S. Berkman, A. Bhat, M. Bhattacharya, V. Bhelande, A. Binau, M. Bishai, A. Blake, B. Bogart, T. Bolton, M. B. Brunetti , et al. (167 additional authors not shown)

Abstract: We present an improved technique for estimating a muon's energy by measuring the deflections along its path inside the MicroBooNE detector from multiple Coulomb scattering (MCS). This approach implements several innovations that better capture detector non-idealizations compared to previous MCS-based muon energy estimators. As a result, it achieves improved resolution, reduced bias, and better dat… ▽ More We present an improved technique for estimating a muon's energy by measuring the deflections along its path inside the MicroBooNE detector from multiple Coulomb scattering (MCS). This approach implements several innovations that better capture detector non-idealizations compared to previous MCS-based muon energy estimators. As a result, it achieves improved resolution, reduced bias, and better data-model agreement. Using model simulation, for fully contained events the estimated bias is within 1% and the estimated resolution varies from 4.3% to 10% as muon energy increases from 0.1 GeV to 2 GeV. For events with particles exiting the detector volume, at least a meter of reconstructed muon track, and a muon energy below 2 GeV, the estimated bias is less than 2% and the estimated resolution varies from 7% to 17% over muon energy. These demonstrate significant improvements over the performance of previous work using an MCS-based energy estimator at MicroBooNE, which achieves twice as large a resolution as well as a bias of 20% over the same energy region. Data-model goodness-of-fit studies are used to validate the estimator's performance on data, showing good agreement within model uncertainties. △ Less

Submitted 14 July, 2026; v1 submitted 4 May, 2026; originally announced May 2026.

Comments: 13 figures, 26 pages

CompleteRXN: Toward Completing Open Chemical Reaction Databases

Authors: Gabriel Vogel, Minouk Noordsij, Evgeny Pidko, Jana M. Weber

Abstract: Chemical reaction datasets such as USPTO suffer from substantial incompleteness, frequently missing byproducts, co-reactants, and stoichiometric coefficients. This limits their applicability and reliability in downstream applications. Here, we introduce CompleteRXN, a large-scale supervised benchmark for reaction completion under realistic missing-data conditions. We construct a dataset of aligned… ▽ More Chemical reaction datasets such as USPTO suffer from substantial incompleteness, frequently missing byproducts, co-reactants, and stoichiometric coefficients. This limits their applicability and reliability in downstream applications. Here, we introduce CompleteRXN, a large-scale supervised benchmark for reaction completion under realistic missing-data conditions. We construct a dataset of aligned incomplete and atom-balanced reactions by mapping USPTO records to curated mechanistic reactions. We evaluate representative baselines, including a novel encoder-decoder reaction completion model with constrained decoding, the Constrained Reaction Balancer (CRB), and a recent algorithmic method, SynRBL. On our CompleteRXN benchmark, the CRB achieves high performance across splits of increasing difficulty, reaching 99.20% equivalence accuracy on the random split and 91.12% on the extreme out-of-distribution split. SynRBL produces many balanced and chemically plausible completions, but with lower accuracy on the benchmark test splits. Across all methods, performance degrades with increasing incompleteness. We observe a substantial drop when evaluating on reactions outside the benchmark (full uncurated USPTO), highlighting the gap between benchmark performance and practical robustness and motivating future work. △ Less

Submitted 28 May, 2026; v1 submitted 30 April, 2026; originally announced May 2026.

Charge readout electronics for the DUNE horizontal drift far detector: design and performance in ProtoDUNE-HD

Authors: DUNE Collaboration, S. Abbaslu, F. Abd Alrahman, A. Abed Abud, R. Acciarri, L. P. Accorsi, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, K. Adhikari, C. Adriano, K. Agudelo-Jaramillo, F. Akbar, F. Alemanno, N. S. Alex, L. Aliaga Soplin, A. Alqaisi, M. Alrashed, A. Alton, R. Alvarez, T. Alves, A. Aman, H. Amar, R. Amarinei , et al. (1346 additional authors not shown)

Abstract: DUNE (Deep Underground Neutrino Experiment) is a long-baseline neutrino oscillation experiment currently under construction, whose far detectors will be the largest liquid argon time projection chambers ever built. This detector design calls for custom-built cryogenic front-end electronics to meet its performance requirements. This paper describes the charge readout electronics that will be used i… ▽ More DUNE (Deep Underground Neutrino Experiment) is a long-baseline neutrino oscillation experiment currently under construction, whose far detectors will be the largest liquid argon time projection chambers ever built. This detector design calls for custom-built cryogenic front-end electronics to meet its performance requirements. This paper describes the charge readout electronics that will be used in the DUNE horizontal drift (HD) far detector and presents performance results using data from the ProtoDUNE-HD detector, a 770 ton liquid argon time projection chamber operated at the CERN Neutrino Platform in 2024 that served as the final prototype of the DUNE HD design. △ Less

Submitted 12 August, 2026; v1 submitted 26 April, 2026; originally announced April 2026.

Comments: Accepted version

Report number: FERMILAB-PUB-26-0270-LBNF, CERN-EP-2026-128

Journal ref: JINST 21 (2026) P08018

VLTI-GRAVITY measurements of cool evolved stars: II. Pulsation properties and mass-loss process of the Mira star R Car and the red supergiant VX Sgr

Authors: D. Jadlovský, M. Wittkowski, A. Chiavassa, K. Kravchenko, B. Freytag, S. Höfner, J. Krtička, C. Paladini, G. Rau, M. Brož, T. Granzer, M. Weber

Abstract: The mass-loss process of red supergiant (RSG) and asymptotic giant branch (AGB) stars and its relation to variability are poorly constrained. We study two evolved stars, the Mira-type AGB star R Car and the extreme RSG VX Sgr. Our sample comprises 54 VLTI-GRAVITY snapshots taken over 7 years, being the largest VLTI time-series dataset to date. We determine the angular diameter as a function of tim… ▽ More The mass-loss process of red supergiant (RSG) and asymptotic giant branch (AGB) stars and its relation to variability are poorly constrained. We study two evolved stars, the Mira-type AGB star R Car and the extreme RSG VX Sgr. Our sample comprises 54 VLTI-GRAVITY snapshots taken over 7 years, being the largest VLTI time-series dataset to date. We determine the angular diameter as a function of time. The radii of the photosphere ($R_{\star}$) and atomic atmospheric layers are variable and relate to the light curve with phase shifts, showing a maximum radius near visual brightness minima. The more extended CO layers show longer, irregular periods and maximum extensions of $\sim 1.3-1.7 \: R_{\star}$ for R Car, and of $\sim 1.5-2.2 \: R_{\star}$ for VX Sgr. Comparison with CO5BOLD simulations revealed a similar behavior. Furthermore, during 2020-2021, VX Sgr exhibited an extreme mass-loss event similar to that of Betelgeuse, preceded by two strong shocks and culminating with the extreme expansion of H$_2$O and CO layers, both up to $\sim 2.2 \: R_{\star}$. During this event, we detected Brackett $γ$ and Balmer emission lines, both of which are signatures of a shock propagating through the atmosphere. The Mira R Car showed a photospheric radius $R_{\star} = 280 \pm 25 \: \rm R_\odot$, with a fundamental mode (FM) pulsation amplitude $\sim13 \%$ of $R_{\star} $. During its active cycle, the RSG VX Sgr showed $R_{\star} = 1556 \pm 110 \: \rm R_\odot$ with FM amplitude $ \sim13 \%$ of $R_{\star} $, the same as R Car. During its quiescent cycle, it showed $R_{\star}= 1456 \pm 108 \: \rm R_\odot$ and low-amplitude pulsations near the first overtone, only $\sim4 \%$ of $R_{\star} $. This supports a steady mass loss for Miras related to stable, large-amplitude FM pulsation, whereas the mass-loss process for RSGs may be dominated by extreme events connected to changes in the pulsation mode. △ Less

Submitted 27 July, 2026; v1 submitted 23 April, 2026; originally announced April 2026.

Comments: Accepted for publication in A&A, a language-corrected version

Journal ref: A&A, 711, A259 (2026)

Electrically switchable vacancy state revealed by in-operando positron experiments

Authors: Ric Fulop, Laurence Lyons IV, Robert Nick, Marc H. Weber, Ming Liu, Haig Atikian, Uwe Bauer, Alexander C. Barbati, Neil Gershenfeld

Abstract: Whether the flash state in electrically driven solids involves non-equilibrium defect production or is accounted for by Joule heating alone has been debated since 2010. Using positron annihilation spectroscopy on copper, we observe a fully reversible, electrically switchable vacancy population: the DBS S-parameter rises above baseline whenever applied current exceeds a critical density and returns… ▽ More Whether the flash state in electrically driven solids involves non-equilibrium defect production or is accounted for by Joule heating alone has been debated since 2010. Using positron annihilation spectroscopy on copper, we observe a fully reversible, electrically switchable vacancy population: the DBS S-parameter rises above baseline whenever applied current exceeds a critical density and returns on current removal. Positron lifetime spectroscopy independently confirms open-volume defect formation and reveals a void to cluster relaxation hierarchy. The current-induced vacancy concentration exceeds the thermal-equilibrium value at 352C by > 106x, is present only while current is applied, and vanishes within minutes. The nucleation rate scales steeply with the applied current, connecting the minute-scale kinetics resolved here to the sub-second flash events observed in ceramic sintering. These results demonstrate current-induced Frenkel-pair production in a metal and identify a defect-mediated, non-equilibrium contribution to the flash state. △ Less

Submitted 23 April, 2026; originally announced April 2026.

Latent Structure of Affective Representations in Large Language Models

Authors: Benjamin J. Choi, Melanie Weber

Abstract: The geometric structure of latent representations in large language models (LLMs) is an active area of research, driven in part by its implications for model transparency and AI safety. Existing literature has focused mainly on general geometric and topological properties of the learnt representations, but due to a lack of ground-truth latent geometry, validating the findings of such approaches is… ▽ More The geometric structure of latent representations in large language models (LLMs) is an active area of research, driven in part by its implications for model transparency and AI safety. Existing literature has focused mainly on general geometric and topological properties of the learnt representations, but due to a lack of ground-truth latent geometry, validating the findings of such approaches is challenging. Emotion processing provides an intriguing testbed for probing representational geometry, as emotions exhibit both categorical organization and continuous affective dimensions, which are well-established in the psychology literature. Moreover, understanding such representations carries safety relevance. In this work, we investigate the latent structure of affective representations in LLMs using geometric data analysis tools. We present three main findings. First, we show that LLMs learn coherent latent representations of affective emotions that align with widely used valence--arousal models from psychology. Second, we find that these representations exhibit nonlinear geometric structure that can nonetheless be well-approximated linearly, providing empirical support for the linear representation hypothesis commonly assumed in model transparency methods. Third, we demonstrate that the learned latent representation space can be leveraged to quantify uncertainty in emotion processing tasks. Our findings suggest that LLMs acquire affective representations with geometric structure paralleling established models of human emotion, with practical implications for model interpretability and safety. △ Less

Submitted 11 April, 2026; v1 submitted 7 April, 2026; originally announced April 2026.

Effective Dynamics and Transition Pathways from Koopman-Inspired Neural Learning of Collective Variables

Authors: Alexander Sikorski, Luca Donati, Marcus Weber, Christof Schütte

Abstract: The ISOKANN (Invariant Subspaces of Koopman Operators Learned by Artificial Neural Networks) framework provides a data-driven route to extract collective variables (CVs) and effective dynamics from complex molecular systems. In this work, we integrate the theoretical foundation of Koopman operators with Krylov-like subspace algorithms, and reduced dynamical modeling to build a coherent picture of… ▽ More The ISOKANN (Invariant Subspaces of Koopman Operators Learned by Artificial Neural Networks) framework provides a data-driven route to extract collective variables (CVs) and effective dynamics from complex molecular systems. In this work, we integrate the theoretical foundation of Koopman operators with Krylov-like subspace algorithms, and reduced dynamical modeling to build a coherent picture of how to describe metastable transitions in high-dimensional systems based on CVs. Starting from the identification of CVs based on dominant invariant subspaces, we derive the corresponding effective dynamics on the latent space and connect these to transition rates and times, committor functions, and transition pathways. The combination of Koopman-based learning and reduced-dimensional effective dynamics yields a principled framework for computing transition rates and pathways from simulation data. Numerical experiments on one-, two-, and three-dimensional benchmark potentials illustrate the ability of ISOKANN to reconstruct the coarse-grained kinetics and reproduce transition times across enthalpic and entropic barriers. △ Less

Submitted 7 April, 2026; originally announced April 2026.

Electron dynamics mediate the water-carbon π bond

Authors: N. LeMessurier, E. Katz, R. Pant, S. Ganley, H. Salzmann, L. M. McCaslin, J. M. Weber, J. D. Eaves

Abstract: The intermolecular interaction between a water molecule and the electrons in aromatic π systems--the water-π bond--lies at the heart of many chemical processes, yet its properties remain challenging to measure experimentally and model computationally. Infrared spectroscopy of pyrene anions hydrated by a single water molecule reveals vibrational and electronic motions that are often hidden in conde… ▽ More The intermolecular interaction between a water molecule and the electrons in aromatic π systems--the water-π bond--lies at the heart of many chemical processes, yet its properties remain challenging to measure experimentally and model computationally. Infrared spectroscopy of pyrene anions hydrated by a single water molecule reveals vibrational and electronic motions that are often hidden in condensed phase measurements. Results from new machine-learning approaches to potentials and dipole moments show that the electron dynamics of the aromatic π cloud quench signals from some of water's vibrations and amplify others. The observed interplay between electronic and vibrational motions has general implications for modeling intermolecular interactions between water and aromatic systems in clusters, solutions, and at interfaces. △ Less

Submitted 10 April, 2026; v1 submitted 3 April, 2026; originally announced April 2026.

Comments: 19 Pages, 4 Figures

Scintillation light calibrations, systematic uncertainties, and triggering efficiency in the MicroBooNE detector

Authors: MicroBooNE collaboration, P. Abratenko, D. Andrade Aldana, L. Arellano, J. Asaadi, A. Ashkenazi, S. Balasubramanian, B. Baller, A. Barnard, G. Barr, D. Barrow, J. Barrow, V. Basque, J. Bateman, B. Behera, O. Benevides Rodrigues, S. Berkman, A. Bhat, M. Bhattacharya, V. Bhelande, A. Binau, M. Bishai, A. Blake, B. Bogart, T. Bolton , et al. (169 additional authors not shown)

Abstract: Scintillation light, produced alongside ionisation charge from particle interactions, plays a critical role in liquid argon time projection chamber (LArTPC) detectors. A detailed understanding of its production and detection mechanisms is essential for robust calibration, systematic uncertainty evaluation, and physics analysis. This article describes the MicroBooNE light simulation, light-based tr… ▽ More Scintillation light, produced alongside ionisation charge from particle interactions, plays a critical role in liquid argon time projection chamber (LArTPC) detectors. A detailed understanding of its production and detection mechanisms is essential for robust calibration, systematic uncertainty evaluation, and physics analysis. This article describes the MicroBooNE light simulation, light-based triggering schemes, photomultiplier tube gain calibration, light response stability, and light-based systematic uncertainties over the course of five years of data collection. In addition, we present a measurement of scintillation light triggering efficiency, focusing on the lowest-light regime relevant to rare-event searches and low-energy neutrino interactions. Finally, we discuss two notable observations in MicroBooNE's data, both reported here for the first time: an approximately 50% decline in MicroBooNE's light yield over time, concentrated in the first two years of running; and a higher than expected O(200 kHz) rate of single photoelectron noise. The results presented provide an important benchmark of long-term light detection performance in LArTPC neutrino detectors. △ Less

Submitted 24 March, 2026; originally announced March 2026.

On-the-Fly Lifting of Coarse Reaction-Coordinate Paths to Full-Dimensional Transition Path Ensembles

Authors: Christof Schütte, Alexander Sikorski, Jakob Kresse, Marcus Weber

Abstract: Effective dynamics on a low-dimensional collective-variable (CV) or latent space can be simulated far more cheaply than the underlying high-dimensional stochastic system, but exploiting such coarse predictions requires lifting: turning a coarse CV trajectory into dynamically consistent full-dimensional states and path ensembles, without relying on global sampling of invariant or conditional fiber… ▽ More Effective dynamics on a low-dimensional collective-variable (CV) or latent space can be simulated far more cheaply than the underlying high-dimensional stochastic system, but exploiting such coarse predictions requires lifting: turning a coarse CV trajectory into dynamically consistent full-dimensional states and path ensembles, without relying on global sampling of invariant or conditional fiber measures. We present a local, on-the-fly lifting strategy based on guided full-system trajectories. First an effective model in CV space is used to obtain a coarse reference trajectory. Then, an ensemble of full-dimensional trajectories is generated from a guided version of the original dynamics, where the guidance steers the trajectory to track the CV reference path. Because guidance biases the path distribution, we correct it via pathwise Girsanov reweighting, yielding a correct-by-construction importance-sampling approximation of the conditional law of the uncontrolled dynamics. We further connect the approach to stochastic optimal control, clarifying how coarse models can inform variance-reducing guidance for rare-event quantities. Numerical experiments demonstrate that inexpensive coarse transition paths can be converted into realistic full-system transition pathways (including barrier crossings and detours) and can accelerate estimation of transition pathways and statistics while providing minimal bias through weighted ensembles. △ Less

Submitted 24 March, 2026; originally announced March 2026.

Tritium as an Unambiguous Isotopic Tracer for Nanoscale Hydrogen Analysis by Atom Probe Tomography

Authors: Maria Vrellou, Alexander Welle, Stefan Wagner, Marco Weber, Rolf Rolli, Hans-Christian Schneider, Astrid Pundt, Xufei Fang, Christoph Kirchlechner

Abstract: Accurate nanoscale detection of hydrogen is essential for understanding hydrogen-related phenomena in materials, yet conventional deuterium tracing is often complicated by residual background hydrogen. This study evaluates tritium as an unambiguous isotopic marker for nanoscale hydrogen analysis in metals using atom probe tomography (APT). Titanium was selected for its ability to incorporate hydro… ▽ More Accurate nanoscale detection of hydrogen is essential for understanding hydrogen-related phenomena in materials, yet conventional deuterium tracing is often complicated by residual background hydrogen. This study evaluates tritium as an unambiguous isotopic marker for nanoscale hydrogen analysis in metals using atom probe tomography (APT). Titanium was selected for its ability to incorporate hydrogen isotopes, providing a suitable platform for tritium detection. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) and electron backscatter diffraction (EBSD) were performed prior to tritium charging to characterize the initial composition and microstructure. APT analysis in laser-mode before and after tritium charging, at three post-charging intervals, enables tracking of tritium incorporation over time. Thermal desorption analysis (TDA) confirmed the presence of tritium and complemented the SIMS measurements, highlighting the role of the surface oxide layer in modulating tritium release. This work serves as a fundamental benchmarking study for leveraging tritium and APT as a combined tool for understanding the nanoscale location of hydrogen in materials, being relevant for interpreting local processes related to e.g., hydrogen embrittlement. △ Less

Submitted 17 March, 2026; originally announced March 2026.

Design and operation of a flash lamp for vacuum ultraviolet light production

Authors: Silas Bosco, Jonas Bürgi, Livio Calivers, Richard Diurba, Johannes Furrer, Jan Kunzmann, Saba Parsa, Sascha Rivera, Nicolas Sallin, Camilla Tognina, Serhan Tufanli, Michele Weber, Dominik Wermelinger

Abstract: Noble liquids, notably argon and xenon, are utilised as both detector media and as the detector target for dark matter and neutrino physics experiments. When the noble liquid is excited by particles, it scintillates vacuum ultraviolet light, which sensors then detect. A major focus of the detector development community is on producing precision light sensors for noble liquid detectors. We introduc… ▽ More Noble liquids, notably argon and xenon, are utilised as both detector media and as the detector target for dark matter and neutrino physics experiments. When the noble liquid is excited by particles, it scintillates vacuum ultraviolet light, which sensors then detect. A major focus of the detector development community is on producing precision light sensors for noble liquid detectors. We introduce a flash lamp to test VUV-sensitive light sensors with light at wavelengths observed at noble liquid detectors. This paper discusses the design and presents results from a flash lamp prototype operated at room temperature. △ Less

Submitted 14 May, 2026; v1 submitted 16 March, 2026; originally announced March 2026.

Journal ref: Instruments 2026, 10(2), 29

Measurements of the electron neutrino-argon differential cross section without pions in the final state in MicroBooNE

Authors: MicroBooNE collaboration, P. Abratenko, D. Andrade Aldana, L. Arellano, J. Asaadi, A. Ashkenazi, S. Balasubramanian, B. Baller, A. Barnard, G. Barr, D. Barrow, J. Barrow, V. Basque, J. Bateman, B. Behera, O. Benevides Rodrigues, S. Berkman, A. Bhat, M. Bhattacharya, V. Bhelande, A. Binau, M. Bishai, A. Blake, B. Bogart, T. Bolton , et al. (168 additional authors not shown)

Abstract: We present a new measurement of the electron neutrino charged current cross section on argon without pions in the final state. This measurement uses the full MicroBooNE booster neutrino beam dataset of $1.3\times 10^{21}$ protons on target collected at Fermi National Accelerator Laboratory. Events are considered both with and without protons above the kinetic energy visibility threshold. Different… ▽ More We present a new measurement of the electron neutrino charged current cross section on argon without pions in the final state. This measurement uses the full MicroBooNE booster neutrino beam dataset of $1.3\times 10^{21}$ protons on target collected at Fermi National Accelerator Laboratory. Events are considered both with and without protons above the kinetic energy visibility threshold. Differential cross sections are extracted in proton and electron kinematics, including energy and angle relative to the neutrino beam direction. The relationship between the hadronic and leptonic systems is explored through the angle between the proton and electron directions. The resulting cross sections are compared to a variety of available generator predictions using different models of neutrino interactions. We find good agreement with most models in lepton kinematics and some discrepancies in the hadronic system modeling, particularly in proton angle. △ Less

Submitted 14 August, 2026; v1 submitted 13 March, 2026; originally announced March 2026.

Report number: FERMILAB-PUB-26-0054-CSAID-PPD

Journal ref: Phys. Rev. D 114, 032006 (12 August, 2026)

Inverse Excitation Hierarchy in Doubly-Heavy Tetraquarks within the Diquark Model

Authors: Maximilian Weber, Daiki Suenaga, Masayasu Harada

Abstract: We investigate the $T_{cc}$ tetraquark, treating it as a bound state of a heavy diquark and a light antidiquark. Using the Silvestre-Brac potential and solving the Schrödinger equation via the Gaussian Expansion Method, we find that the excitation energy between the heavy diquark and light antidiquark is unexpectedly larger than that between the two light anti-quarks within the anti-diquark -- con… ▽ More We investigate the $T_{cc}$ tetraquark, treating it as a bound state of a heavy diquark and a light antidiquark. Using the Silvestre-Brac potential and solving the Schrödinger equation via the Gaussian Expansion Method, we find that the excitation energy between the heavy diquark and light antidiquark is unexpectedly larger than that between the two light anti-quarks within the anti-diquark -- contrary to the naive expectation where the former is smaller than the latter. We trace this inversion of the mass hierarchy to the centrifugal force acting on the light degree of freedom. Applying the same framework to other systems ($T_{bb}, Λ_b, Λ_c$) yields qualitatively identical behavior, demonstrating the robustness of the mechanism. These results provide new insights into diquark dynamics and the mass structure of exotic hadrons. △ Less

Submitted 24 June, 2026; v1 submitted 4 March, 2026; originally announced March 2026.

Comments: 14 pages, 9 figures, 4 tables

Protein Graph Neural Networks for Heterogeneous Cryo-EM Reconstruction

Authors: Jonathan Krook, Axel Janson, Joakim Andén, Melanie Weber, Ozan Öktem

Abstract: We present a geometry-aware method for heterogeneous single-particle cryogenic electron microscopy (cryo-EM) reconstruction that predicts atomic backbone conformations. To incorporate protein-structure priors, we represent the backbone as a graph and use a graph neural network (GNN) autodecoder that maps per-image latent variables to 3D displacements of a template conformation. The objective combi… ▽ More We present a geometry-aware method for heterogeneous single-particle cryogenic electron microscopy (cryo-EM) reconstruction that predicts atomic backbone conformations. To incorporate protein-structure priors, we represent the backbone as a graph and use a graph neural network (GNN) autodecoder that maps per-image latent variables to 3D displacements of a template conformation. The objective combines a data-discrepancy term based on a differentiable cryo-EM forward model with geometric regularization, and it supports unknown orientations via ellipsoidal support lifting (ESL) pose estimation. On synthetic datasets derived from molecular dynamics trajectories, the proposed GNN achieves higher accuracy compared to a multilayer perceptron (MLP) of comparable size, highlighting the benefits of a geometry-informed inductive bias. △ Less

Submitted 25 February, 2026; originally announced February 2026.

Demonstration and performance of an online data selection algorithm for liquid argon time projection chambers using MicroBooNE

Authors: MicroBooNE collaboration, P. Abratenko, D. Andrade Aldana, L. Arellano, J. Asaadi, A. Ashkenazi, S. Balasubramanian, B. Baller, A. Barnard, G. Barr, D. Barrow, J. Barrow, V. Basque, J. Bateman, B. Behera, O. Benevides Rodrigues, S. Berkman, A. Bhat, M. Bhattacharya, V. Bhelande, A. Binau, M. Bishai, A. Blake, B. Bogart, T. Bolton , et al. (169 additional authors not shown)

Abstract: The MicroBooNE detector is a liquid argon time projection chamber (LArTPC) that produces three-dimensional images of particle interactions using ionization charge collected by anode wire plane arrays and scintillation light collected by a light detection system. In addition to testing long-standing experimental neutrino anomalies and performing measurements of neutrino interactions with argon nucl… ▽ More The MicroBooNE detector is a liquid argon time projection chamber (LArTPC) that produces three-dimensional images of particle interactions using ionization charge collected by anode wire plane arrays and scintillation light collected by a light detection system. In addition to testing long-standing experimental neutrino anomalies and performing measurements of neutrino interactions with argon nuclei using the Fermilab Booster Neutrino Beam, MicroBooNE aims to develop methodologies for rare beyond the Standard Model and off-beam physics searches. Looking ahead to the upcoming Deep Underground Neutrino Experiment (DUNE), with MicroBooNE serving as a valuable testbed, achieving high sensitivity and livetime for off-beam physics while satisfying data processing and storage constraints will require data-driven, intelligent, and online or real-time data selection techniques. These techniques are essential for reducing data rates and preserving rare signals with high accuracy. In this paper, we describe a fast data selection algorithm suitable for online execution to identify electrons from stopping cosmic ray muons in the MicroBooNE detector utilizing ionization charge information, and present its performance. This represents the first demonstration of online data selection in a LArTPC using real data and charge information exclusively and provides an important proof-of-principle for applying such techniques to other LArTPC experiments such as the Short-Baseline Near Detector and DUNE. △ Less

Submitted 10 July, 2026; v1 submitted 11 February, 2026; originally announced February 2026.

Report number: FERMILAB-PUB-25-0954-PPD

Probing the structure of cyclic hydrocarbon molecules with X-ray-induced Coulomb explosion imaging

Authors: Kurtis D. Borne, Rebecca Boll, Thomas M. Baumann, Surjendu Bhattacharyya, Martin Centurion, Keyu Chen, Benjamin Erk, Alberto De Fanis, Ruaridh Forbes, Markus Ilchen, Edwin Kukk, Huynh V. S. Lam, Xiang Li, Lingyu Ma, Tommaso Mazza, Michael Meyer, Terence Mullins, J. Pedro F. Nunes, Asami Odate, Shashank Pathak, Daniel Rivas, Philipp Schmidt, Florian Trinter, Sergey Usenko, Anbu S. Venkatachalam , et al. (5 additional authors not shown)

Abstract: Coulomb explosion imaging (CEI) is a powerful experimental technique that maps a molecule's geometric structure onto the momenta of ionic molecular fragments produced by rapid multiple ionization. Here, we apply CEI induced by pulses from an X-ray free-electron laser in order to image and distinguish complex hydrocarbon isomers with the chemical formula C7H8: toluene, cycloheptatriene, and 1,6-hep… ▽ More Coulomb explosion imaging (CEI) is a powerful experimental technique that maps a molecule's geometric structure onto the momenta of ionic molecular fragments produced by rapid multiple ionization. Here, we apply CEI induced by pulses from an X-ray free-electron laser in order to image and distinguish complex hydrocarbon isomers with the chemical formula C7H8: toluene, cycloheptatriene, and 1,6-heptadiyne. The measured fragment-ion momentum distributions show discernible differences between the three isomers and provide signatures of specific carbon and hydrogen sites in the molecule. In contrast to previous work, we demonstrate that distinct 'marker atoms' are not strictly required for constructing a meaningful molecular frame of reference for the interpretation of the momentum-space data. Our work paves the way for tracking the ultrafast motion of nuclei during isomerization reactions in pure hydrocarbons. △ Less

Submitted 3 February, 2026; originally announced February 2026.

Grounding Large Language Models in Reaction Knowledge Graphs for Synthesis Retrieval

Authors: Olga Bunkova, Lorenzo Di Fruscia, Sophia Rupprecht, Artur M. Schweidtmann, Marcel J. T. Reinders, Jana M. Weber

Abstract: Large Language Models (LLMs) can aid synthesis planning in chemistry, but standard prompting methods often yield hallucinated or outdated suggestions. We study LLM interactions with a reaction knowledge graph by casting reaction path retrieval as a Text2Cypher (natural language to graph query) generation problem, and define single- and multi-step retrieval tasks. We compare zero-shot prompting to… ▽ More Large Language Models (LLMs) can aid synthesis planning in chemistry, but standard prompting methods often yield hallucinated or outdated suggestions. We study LLM interactions with a reaction knowledge graph by casting reaction path retrieval as a Text2Cypher (natural language to graph query) generation problem, and define single- and multi-step retrieval tasks. We compare zero-shot prompting to one-shot variants using static, random, and embedding-based exemplar selection, and assess a checklist-driven validator/corrector loop. To evaluate our framework, we consider query validity and retrieval accuracy. We find that one-shot prompting with aligned exemplars consistently performs best. Our checklist-style self-correction loop mainly improves executability in zero-shot settings and offers limited additional retrieval gains once a good exemplar is present. We provide a reproducible Text2Cypher evaluation setup to facilitate further work on KG-grounded LLMs for synthesis planning. Code is available at https://github.com/Intelligent-molecular-systems/KG-LLM-Synthesis-Retrieval. △ Less

Submitted 22 January, 2026; originally announced January 2026.

Comments: Accepted at ML4Molecules 2025 (ELLIS UnConference workshop), Copenhagen, Denmark, December 2, 2025. Workshop page: https://moleculediscovery.github.io/workshop2025/

VERIDAH: Solving Enumeration Anomaly Aware Vertebra Labeling across Imaging Sequences

Authors: Hendrik Möller, Hanna Schoen, Robert Graf, Matan Atad, Nathan Molinier, Anjany Sekuboyina, Bettina K. Budai, Fabian Bamberg, Steffen Ringhof, Christopher Schlett, Tobias Pischon, Thoralf Niendorf, Josua A. Decker, Marc-André Weber, Bjoern Menze, Daniel Rueckert, Jan S. Kirschke

Abstract: The human spine commonly consists of seven cervical, twelve thoracic, and five lumbar vertebrae. However, enumeration anomalies may result in individuals having eleven or thirteen thoracic vertebrae and four or six lumbar vertebrae. Although the identification of enumeration anomalies has potential clinical implications for chronic back pain and operation planning, the thoracolumbar junction is of… ▽ More The human spine commonly consists of seven cervical, twelve thoracic, and five lumbar vertebrae. However, enumeration anomalies may result in individuals having eleven or thirteen thoracic vertebrae and four or six lumbar vertebrae. Although the identification of enumeration anomalies has potential clinical implications for chronic back pain and operation planning, the thoracolumbar junction is often poorly assessed and rarely described in clinical reports. Additionally, even though multiple deep-learning-based vertebra labeling algorithms exist, there is a lack of methods to automatically label enumeration anomalies. Our work closes that gap by introducing "Vertebra Identification with Anomaly Handling" (VERIDAH), a novel vertebra labeling algorithm based on multiple classification heads combined with a weighted vertebra sequence prediction algorithm. We show that our approach surpasses existing models on T2w TSE sagittal (98.30% vs. 94.24% of subjects with all vertebrae correctly labeled, p < 0.001) and CT imaging (99.18% vs. 77.26% of subjects with all vertebrae correctly labeled, p < 0.001) and works in arbitrary field-of-view images. VERIDAH correctly labeled the presence 2 Möller et al. of thoracic enumeration anomalies in 87.80% and 96.30% of T2w and CT images, respectively, and lumbar enumeration anomalies in 94.48% and 97.22% for T2w and CT, respectively. Our code and models are available at: https://github.com/Hendrik-code/spineps. △ Less

Submitted 20 January, 2026; originally announced January 2026.

Large-scale time-series spectroscopy for stellar ages

Authors: David Gruner, Sydney A. Barnes, Ansgar Reiners, Klaus G. Strassmeier, Cristina Chiappini, Jörg Weingrill, Michael Weber, Ilya Ilyin, Thomas Granzer, Özgün Adebali, Jean-Michel Désert, Marica Valentini, Dario Fritzewski, Paolo Ventura, Alfio Bonanno, Jose-Dias do Nascimento, Jorge Melendez, Santosh Joshi, Yong-Cheol Kim

Abstract: To date, Galactic Astronomy has largely concerned itself with astrophysical processes, and with the locations, space motions and compositions of objects. Consider, for example, the elucidation of the components of the Galaxy over the past decades, its mapping as enabled by Gaia and its predecessors, the photometric and spectroscopic characterization of innumerable astrophysical objects in various… ▽ More To date, Galactic Astronomy has largely concerned itself with astrophysical processes, and with the locations, space motions and compositions of objects. Consider, for example, the elucidation of the components of the Galaxy over the past decades, its mapping as enabled by Gaia and its predecessors, the photometric and spectroscopic characterization of innumerable astrophysical objects in various wavelength ranges, both from the ground and from space, and the expanding discovery and characterization of exoplanets; all focused on the current, static Galaxy. This White Paper proposes a dedicated program to derive stellar ages from time-series spectroscopy to hasten the transformation of this static conception into a dynamical one with age-labeled objects and events. △ Less

Submitted 15 January, 2026; originally announced January 2026.

Comments: White Paper submitted to ESO for the "Expanding Horizons: Transforming Astronomy in the 2040s" Call

Can photoevaporation open gaps in protoplanetary discs?

Authors: Michael L. Weber, Barbara Ercolano, Giovanni Picogna

Abstract: We investigate whether photoevaporation alone can open and sustain gaps in protoplanetary discs by coupling the evolving disc structure with the photoevaporative flow in two dimensional radiation hydrodynamical simulations. Our results show that once a density depression forms, the local mass-loss rate decreases sharply, suppressing further gap deepening. Viscous inflow and radial mass transport a… ▽ More We investigate whether photoevaporation alone can open and sustain gaps in protoplanetary discs by coupling the evolving disc structure with the photoevaporative flow in two dimensional radiation hydrodynamical simulations. Our results show that once a density depression forms, the local mass-loss rate decreases sharply, suppressing further gap deepening. Viscous inflow and radial mass transport along the disc surface act to partially refill the depleted region, preventing complete clearing. The resulting configuration is a persistent, partially depleted zone whose evolution is largely insensitive to the initial disc morphology. This behaviour challenges the standard paradigm that photoevaporation efficiently carves clean inner cavities and directly produces transition discs. However, the pressure maximum at the outer edge of the depression may still trap dust grains, giving rise to transition disc like observational signatures. We also present a first-order prescription to approximate this behaviour in one dimensional disc evolution models, suitable for use in planet formation and population synthesis studies. Although the prescription improves upon static mass-loss treatments, it remains approximate, underscoring the need for further multidimensional simulations and parameter-space exploration to derive robust recipes for global disc and planet population models. △ Less

Submitted 13 January, 2026; originally announced January 2026.

Comments: Accepted for publication in MNRAS Letters 5 pages 6 Fugures

Reconstruction of atmospheric neutrinos in DUNE's horizontal-drift far-detector module

Authors: DUNE Collaboration, S. Abbaslu, F. Abd Alrahman, A. Abed Abud, R. Acciarri, L. P. Accorsi, M. A. Acero, M. R. Adames, G. Adamov, M. Adamowski, C. Adriano, F. Akbar, F. Alemanno, N. S. Alex, K. Allison, M. Alrashed, A. Alton, R. Alvarez, T. Alves, A. Aman, H. Amar, P. Amedo, J. Anderson, D. A. Andrade, C. Andreopoulos , et al. (1325 additional authors not shown)

Abstract: This paper reports on the capabilities in reconstructing and identifying atmospheric neutrino interactions in one of the Deep Underground Neutrino Experiment's (DUNE) far detector modules, a liquid argon time projection chamber (LArTPC) with horizontal drift (FD-HD) of ionization electrons. The reconstruction is based upon the workflow developed for DUNE's long-baseline oscillation analysis, with… ▽ More This paper reports on the capabilities in reconstructing and identifying atmospheric neutrino interactions in one of the Deep Underground Neutrino Experiment's (DUNE) far detector modules, a liquid argon time projection chamber (LArTPC) with horizontal drift (FD-HD) of ionization electrons. The reconstruction is based upon the workflow developed for DUNE's long-baseline oscillation analysis, with some necessary machine-learning models' retraining and the addition of features relevant only to atmospheric neutrinos such as the neutrino direction reconstruction. Where relevant, the impact of the detection of the charged particles of the hadronic system is emphasized, and comparisons are carried out between the case when lepton-only information is considered in the reconstruction (as is the case for many neutrino oscillation experiments), versus when all particles identified in the LArTPC were included. Three neutrino direction reconstruction methods have been developed and studied for the atmospheric analyses: using lepton-only information, using all reconstructed particles, and using only correlations from reconstructed hits. The results indicate that incorporating more than just lepton information significantly improves the resolution of both neutrino direction and energy reconstruction. The angle reconstruction algorithms developed in this work result in no strong dependence on particle direction for reconstruction efficiencies or neutrino flavor identification. This comprehensive review of the reconstruction of atmospheric neutrinos in DUNE's FD-HD LArTPC is the first step towards developing a first neutrino oscillation sensitivity analysis, which will ready DUNE for its first measurements. △ Less

Submitted 9 January, 2026; originally announced January 2026.

Comments: 43 pages, 23 figures

Report number: FERMILAB-PUB-25-0961-LBNF

Neural Algorithmic Reasoning for Approximate $k$-Coloring with Recursive Warm Starts

Authors: Knut Vanderbush, Melanie Weber

Abstract: Node coloring is the task of assigning colors to the nodes of a graph such that no two adjacent nodes have the same color, while using as few colors as possible. It is the most widely studied instance of graph coloring and of central importance in graph theory; major results include the Four Color Theorem and work on the Hadwiger-Nelson Problem. As an abstraction of classical combinatorial optimiz… ▽ More Node coloring is the task of assigning colors to the nodes of a graph such that no two adjacent nodes have the same color, while using as few colors as possible. It is the most widely studied instance of graph coloring and of central importance in graph theory; major results include the Four Color Theorem and work on the Hadwiger-Nelson Problem. As an abstraction of classical combinatorial optimization tasks, such as scheduling and resource allocation, it is also rich in practical applications. Here, we focus on a relaxed version, approximate $k$-coloring, which is the task of assigning at most $k$ colors to the nodes of a graph such that the number of edges whose vertices have the same color is approximately minimized. While classical approaches leverage mathematical programming or SAT solvers, recent studies have explored the use of machine learning. We follow this route and explore the use of graph neural networks (GNNs) for node coloring. We first present an optimized differentiable algorithm that improves a prior approach by Schuetz et al. with orthogonal node feature initialization and a loss function that penalizes conflicting edges more heavily when their endpoints have higher degree; the latter inspired by the classical result that a graph is $k$-colorable if and only if its $k$-core is $k$-colorable. Next, we introduce a lightweight greedy local search algorithm and show that it may be improved by recursively computing a $(k-1)$-coloring to use as a warm start. We then show that applying such recursive warm starts to the GNN approach leads to further improvements. Numerical experiments on a range of different graph structures show that while the local search algorithms perform best on small inputs, the GNN exhibits superior performance at scale. The recursive warm start may be of independent interest beyond graph coloring for local search methods for combinatorial optimization. △ Less

Submitted 8 January, 2026; originally announced January 2026.

Comments: 33 pages, 10 figures

Importance sampling of unbounded random stopping times: computing committor functions and exit rates without reweighting

Authors: Carsten Hartmann, Annika Jöster, Christof Schütte, Alexander Sikorski, Marcus Weber

Abstract: Rare events in molecular dynamics are often related to noise-induced transitions between different macroscopic states (e.g., in protein folding). A common feature of these rare transitions is that they happen on timescales that are on average exponentially long compared to the characteristic timescale of the system, with waiting time distributions that have (sub)exponential tails and infinite supp… ▽ More Rare events in molecular dynamics are often related to noise-induced transitions between different macroscopic states (e.g., in protein folding). A common feature of these rare transitions is that they happen on timescales that are on average exponentially long compared to the characteristic timescale of the system, with waiting time distributions that have (sub)exponential tails and infinite support. As a result, sampling such rare events can lead to trajectories that can be become arbitrarily long, with not too low probability, which makes the reweighting of such trajectories a real challenge. Here, we discuss rare event simulation by importance sampling from a variational perspective, with a focus on applications in molecular dynamics, in particular the computation of committor functions. The idea is to design importance sampling schemes that (a) reduce the variance of a rare event estimator while controlling the average length of the trajectories and (b) that do not require the reweighting of possibly very long trajectories. In doing so, we study different stochastic control formulations for committor and mean first exit times, which we compare both from a theoretical and a computational point of view, including numerical studies of some benchmark examples. △ Less

Submitted 4 January, 2026; originally announced January 2026.

Comments: 51 pages, 7 figures

MSC Class: 82M31 (Primary) 82M37; 93E20 (Secondary)

Pita factorisation in operadic categories

Authors: Michael Batanin, Joachim Kock, Mark Weber

Abstract: In strictly factorisable operadic categories, every morphism $f$ factors uniquely as $f=η_f \circ π_f$ where $η_f$ is order-preserving and $π_f$ is a quasibijection that is order-preserving on the fibres of $η_f$. We call it the pita factorisation. In this paper we develop some general theory to compensate for the fact that generally pita factorisations do not form an orthogonal factorisation syst… ▽ More In strictly factorisable operadic categories, every morphism $f$ factors uniquely as $f=η_f \circ π_f$ where $η_f$ is order-preserving and $π_f$ is a quasibijection that is order-preserving on the fibres of $η_f$. We call it the pita factorisation. In this paper we develop some general theory to compensate for the fact that generally pita factorisations do not form an orthogonal factorisation system. The main technical result states that a certain simplicial object in Cat, called the pita nerve, is oplax (rather than strict as it would be for an orthogonal factorisation system). The main application is the result that the so-called operadic nerve of any operadic category is coherent. This result is a key ingredient in the simplicial approach to operadic categories developed in the `main paper' [arXiv:2606.15671], which motivated the present paper. We also show that in the important case where quasibijections are invertible, the pita nerve is a decomposition space (a.k.a.~$2$-Segal space). △ Less

Submitted 22 June, 2026; v1 submitted 28 December, 2025; originally announced December 2025.

Comments: v2: More precise reference to Jardine's supercoherence and cleaner proof of Thm.9.5. Expository and typographical improvements throughout. 37pp

Report number: CPH-GEOTOP-DNRF151 MSC Class: 18M60 (Primary); 18N50 (Secondary)

Characterisation of the Bedretto Underground Site for Fundamental Physics Experiments

Authors: Björn Penning, Nicolas Angelides, Laura Baudis, Harvey Birch, Abigail Flowers, Florian Jörg, Alexander Kavner, Marcelle Soares-Santos, Aravind Sreekala, Johannes Wüthrich, Guandi Zhao, Chiara Capelli, John Clinton, Jose Cuenca García, Paolo Crivelli, Domenico Giardini, Evangelos-Leonidas Gkougkousis, Yacine Haddad, Marian Hertrich, Rebecca Hochreutener, Luisa Hötzsch, Philippe Jetzer, Ben Kilminster, Boris Korzh, Frederick Massin , et al. (11 additional authors not shown)

Abstract: Underground laboratories provide the ultra-low background and low-vibration environments essential for rare-event searches, gravitational-wave detection, and quantum-sensing technologies. We report a comprehensive environmental characterisation of the Bedretto tunnel in Ticino, Switzerland, a site offering horizontal access, excellent infrastructure, and the potential to be be Europe's second-deep… ▽ More Underground laboratories provide the ultra-low background and low-vibration environments essential for rare-event searches, gravitational-wave detection, and quantum-sensing technologies. We report a comprehensive environmental characterisation of the Bedretto tunnel in Ticino, Switzerland, a site offering horizontal access, excellent infrastructure, and the potential to be be Europe's second-deepest and quietest underground laboratory. At the prospective physics site, located beneath an overburden exceeding 1400 m, we measure the cosmic-muon, gamma-ray, and neutron fluxes, as well as the radon concentration, magnetic-field spectrum, and seismic backgrounds. The muon flux is suppressed by six orders of magnitude relative to the surface, consistent with an effective depth of about 4000 metre water equivalent, gamma-ray and neutron measurements reflect the local geology and guide shielding requirements for future particle and nuclear physics experiments. Magnetic and seismic noise levels are found to be exceptionally low, meeting or exceeding the criteria for next-generation atom-interferometric gravitational-wave detectors. These results establish the site as a highly competitive, accessible deep-underground location for fundamental-physics experiments. △ Less

Submitted 18 December, 2025; v1 submitted 16 December, 2025; originally announced December 2025.

Comments: 8 pages, 7 figures plus appendix

Journal ref: Eur. Phys. J. C 86, 866 (2026)

Achieving Approximate Symmetry Is Exponentially Easier than Exact Symmetry

Authors: Behrooz Tahmasebi, Melanie Weber

Abstract: Enforcing exact symmetry in machine learning models often yields significant gains in scientific applications, serving as a powerful inductive bias. However, recent work suggests that relying on approximate symmetry can offer greater flexibility and robustness. Despite promising empirical evidence, there has been little theoretical understanding, and in particular, a direct comparison between exac… ▽ More Enforcing exact symmetry in machine learning models often yields significant gains in scientific applications, serving as a powerful inductive bias. However, recent work suggests that relying on approximate symmetry can offer greater flexibility and robustness. Despite promising empirical evidence, there has been little theoretical understanding, and in particular, a direct comparison between exact and approximate symmetry is missing from the literature. In this paper, we initiate this study by asking: What is the cost of enforcing exact versus approximate symmetry? To address this question, we introduce averaging complexity, a framework for quantifying the cost of enforcing symmetry via averaging. Our main result is an exponential separation: under standard conditions, exact symmetry requires linear averaging complexity, whereas approximate symmetry can be attained with only logarithmic complexity in the group size. To the best of our knowledge, this provides the first theoretical separation of these two cases, formally justifying why approximate symmetry may be preferable in practice. Beyond this, our tools and techniques may be of independent interest for the broader study of symmetries in machine learning. △ Less

Submitted 14 May, 2026; v1 submitted 4 December, 2025; originally announced December 2025.

Comments: 33 pages, 2 figures. Published at ICLR 2026

Journal ref: International Conference on Learning Representations (ICLR) 2026

Cosmic Ray Measurements Using Charge and Light Readout in a Pixelated Liquid Argon Time Projection Chamber

Authors: SoLAr Collaboration, N. Anfimov, A. Branca, J. Bürgi, L. Calivers, P. Carniti, E. Calvo, E. Cristaldo, C. Cuesta, F. Declich, R. Diurba, P. Dunne, D. A. Dwyer, J. Evans, A. C. Ezeribe, A. Gauch, I. Gil-Botella, C. Gotti, S. Greenberg, D. Guffanti, A. Karcher, J. Kunzmann, N. Lane, S. Manthey Corchado, N. McConkey , et al. (18 additional authors not shown)

Abstract: Liquid argon time projection chambers have emerged as a competitive technology for detecting solar neutrinos. The SoLAr collaboration was formed to explore argon detectors with pixelated light and charge readout, aiming for high detection efficiency and improved energy resolution. Building on the success of an initial prototype, we present results obtained with a second SoLAr prototype (V2), a… ▽ More Liquid argon time projection chambers have emerged as a competitive technology for detecting solar neutrinos. The SoLAr collaboration was formed to explore argon detectors with pixelated light and charge readout, aiming for high detection efficiency and improved energy resolution. Building on the success of an initial prototype, we present results obtained with a second SoLAr prototype (V2), a $30 \times 30 \times 30$ cm$^{3}$ time projection chamber operated in a cryostat containing several hundred kilograms of liquid argon. We report measurements of cosmic-ray muons using both tracking and calorimetry from light and charge sensors, and we highlight the improved performance achieved through combined charge and light reconstruction. These results demonstrate the promise of dual-readout detectors and motivate future prototyping efforts toward kiloton-scale facilities. △ Less

Submitted 11 December, 2025; originally announced December 2025.

Surface image and activity-corrected orbit of the RS CVn binary HR 7275: Disentangling activity tracers

Authors: Ö. Adebali, M. Weber, K. G. Strassmeier, I. V. Ilyin, M. Steffen, Zs. Kovári

Abstract: Quantifying stellar parameters and magnetic activity for cool stars in double-lined spectroscopic binaries (SB2) is not straightforward, as both stars contribute to the observed composite spectra and are likely variable. Disentangled component spectra allow a detailed analysis of a component's magnetic activity. We aim at separating the spectra of the two stellar components of the HR\,7275 SB2 s… ▽ More Quantifying stellar parameters and magnetic activity for cool stars in double-lined spectroscopic binaries (SB2) is not straightforward, as both stars contribute to the observed composite spectra and are likely variable. Disentangled component spectra allow a detailed analysis of a component's magnetic activity. We aim at separating the spectra of the two stellar components of the HR\,7275 SB2 system. Our further aim is a more accurate orbital solution by cleaning the observed radial velocities (RV) from activity perturbations of the spotted primary ("RV jitter") and obtain a surface image of this component. The Doppler image of the primary shows two large cool spots of size $\approx$20\% of the visible hemisphere plus three smaller spots, each still $\approx$13\% in size. In total, HR\,7275a exhibited an impressive spottedness of $\approx$40\%\ of its entire surface in May-June 2022. The RV is modulated by the rotation of the primary with maximum amplitudes of 320\,\ms\ and 650\,\ms\ for two different modulation behaviors during the 250\,d of our observations. This jitter is primarily caused by the varying asymmetries of the apparent disk brightness due to the cool spots. Its removal resulted in roughly ten times higher precision of the orbital elements. Our snapshot magnetic-field measurements reveal phase-dependent (large-scale) surface fields between +0.6$\pm$2.0\,G at phase 0.1 and $-$15.2$\pm$2.7\,G at phase 0.6, indicating a complex magnetic morphology related to the location of the photospheric spots. We also obtain a logarithmic lithium abundance of 0.58$\pm$0.1 for HR\,7275a, indicating considerable mixing, and 0.16$^{+0.23}_{-0.63}$ for HR\,7275b, which is an extremely low value. } △ Less

Submitted 10 December, 2025; originally announced December 2025.

Comments: 15 pages, 12 Figures

Search for Light Sterile Neutrinos With Two Neutrino Beams at MicroBooNE

Authors: MicroBooNE collaboration, P. Abratenko, D. Andrade Aldana, L. Arellano, J. Asaadi, A. Ashkenazi, S. Balasubramanian, B. Baller, A. Barnard, G. Barr, D. Barrow, J. Barrow, V. Basque, J. Bateman, O. Benevides Rodrigues, S. Berkman, A. Bhat, M. Bhattacharya, M. Bishai, A. Blake, B. Bogart, T. Bolton, M. B. Brunetti, L. Camilleri, D. Caratelli , et al. (154 additional authors not shown)

Abstract: The existence of three distinct neutrino flavours, $ν_{e}$, $ν_μ$, and $ν_τ$, is a central tenet of the Standard Model of particle physics. Quantum-mechanical interference can allow a neutrino of one initial flavour to be detected some time later as a different flavour, a process called neutrino oscillation. Several anomalous observations inconsistent with this three-flavour picture have motivated… ▽ More The existence of three distinct neutrino flavours, $ν_{e}$, $ν_μ$, and $ν_τ$, is a central tenet of the Standard Model of particle physics. Quantum-mechanical interference can allow a neutrino of one initial flavour to be detected some time later as a different flavour, a process called neutrino oscillation. Several anomalous observations inconsistent with this three-flavour picture have motivated the hypothesis that an additional neutrino state exists which does not interact directly with matter, termed a "sterile" neutrino, $ν_s$. This includes anomalous observations from the LSND and MiniBooNE experiments, consistent with $ν_μ\rightarrowν_{e}$ transitions at a distance inconsistent with the three-neutrino picture. Here, we use data obtained from the MicroBooNE liquid-argon time projection chamber in two accelerator neutrino beams to exclude the single light sterile neutrino interpretation of the LSND and MiniBooNE anomalies at the 95\% confidence level (CL). Additionally, we rule out a significant portion of the parameter space that could explain the gallium anomaly. This is the first measurement to use two accelerator neutrino beams to break a degeneracy between $ν_{e}$ appearance and disappearance that would otherwise weaken the sensitivity to the sterile neutrino hypothesis. We find no evidence for either $ν_μ\rightarrowν_{e}$ flavour transitions or $ν_{e}$ disappearance that would indicate non-standard flavour oscillations. Our results show that previous anomalous observations consistent with $ν_μ\rightarrowν_{e}$ transitions cannot be explained by introducing a single sterile neutrino state. △ Less

Submitted 7 December, 2025; originally announced December 2025.

Comments: 17 pages, 6 figures

Report number: FERMILAB-PUB-24-0865-PPD

Journal ref: Nature 648, 64-69 (2025)