Showing 1–50 of 423 results for author: Jackson, M

The Fragility of Social Learning with Noisy Messages

Authors: Matthew O. Jackson, Suraj Malladi, David McAdams

Abstract: We examine how agents learn when information from original sources only reaches them after noisy relay. A receiver learns if and only if they have access to sufficiently many chains of noisy relay and they perfectly understand the noise process. However, even slight uncertainty over message mutation rates makes learning from long chains impossible, no matter how many independent sources are access… ▽ More We examine how agents learn when information from original sources only reaches them after noisy relay. A receiver learns if and only if they have access to sufficiently many chains of noisy relay and they perfectly understand the noise process. However, even slight uncertainty over message mutation rates makes learning from long chains impossible, no matter how many independent sources are accessed. △ Less

Submitted 18 August, 2026; originally announced August 2026.

How AI Prompts Can Teach Us About the Structure of Human Behavior

Authors: Matthew O. Jackson, Benjamin S. Manning, Yutong Xie, Walter Yuan, Qiaozhu Mei

Abstract: We introduce a general, easy-to-implement AI-based method for studying the structure and complexity of human behavior. We assign a large language model a ``type vector'' and then prompt it to choose actions across settings in which we observe human choices. For instance, the type vector (2,4) becomes ``You are a player characterized by the following profile: 2 out of 5 in Altruism, 4 out of 5 in R… ▽ More We introduce a general, easy-to-implement AI-based method for studying the structure and complexity of human behavior. We assign a large language model a ``type vector'' and then prompt it to choose actions across settings in which we observe human choices. For instance, the type vector (2,4) becomes ``You are a player characterized by the following profile: 2 out of 5 in Altruism, 4 out of 5 in Risk Aversion,'' after which it is prompted to make choices. We vary the dimensions (e.g., Altruism, Fairness, Trust, $\dots$) and values (e.g., 1--5) to minimize distance to human choices. Applying the method to 119,147 decisions made by 78,657 subjects from more than 35 countries across 10 classic economic game roles, we find that human behavior can be closely matched using three dimensions: Risk Aversion, Strategic Sophistication, and Trust. Moreover, the types needed to fit individuals across games cluster into fewer than a dozen groups, and can predict behavior in held-out games with different rules and available actions. The results suggest that behavior across diverse settings can be approximated by a low-dimensional, portable representation, supporting the possibility of general yet parsimonious theories across the behavioral sciences. More broadly, the method can provide insights into the structure of many human behaviors. △ Less

Submitted 18 August, 2026; originally announced August 2026.

The friendship paradox: Causal evidence of its behavioral consequences

Authors: Gary Charness, Francesco Feri, Matthew O. Jackson, Miguel A. Melendez-Jimenez, Matthias Sutter

Abstract: We provide a first causal analysis of the behavioral consequences of the friendship paradox-the fact that people's friends in a network have more connections than average. We find that people's behavior is biased by their network position: they do not best respond to what they should infer the average behavior of the population to be, but instead simply to the average behavior of their friends. Mo… ▽ More We provide a first causal analysis of the behavioral consequences of the friendship paradox-the fact that people's friends in a network have more connections than average. We find that people's behavior is biased by their network position: they do not best respond to what they should infer the average behavior of the population to be, but instead simply to the average behavior of their friends. Moreover, we find that they fail to learn to overcome such a bias when relocated within the network, varying their observational environment. In these games of complements, the friendship paradox generates a systematic upward distortion in actions, increases behavioral dispersion, and persists despite learning opportunities. △ Less

Submitted 7 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

Comparative qualification of advanced plasma-facing materials for fusion pilot plants through public- and private-sector experiments in DIII-D

Authors: Florian Effenberg, Jonathan D. Coburn, Luca Cappelli, Simon D. Corah, Amoolya Grandhi, Jerome Guterl, Charlie Hirst, Mike Jackson, Dylan A. Kohler, Rob Kolasinski, Erick Martinez-Loran, Ria Meston, Lauren Nuckols, Angelica Ottaviano, Zana Popovic, Sergey Tsurkan, Tessa Van Volkenburg, Daniel Velazquez, Aaliyah Zuniga, Arunodaya Bhattacharya, Jose Boedo, Kent Christian, Giacomo Dose, Eric Hollmann, Mykola Ialovega , et al. (22 additional authors not shown)

Abstract: A coordinated DIII-D campaign exposed and comparatively assessed 44 advanced plasma-facing materials from 12 institutions, including four public-private fusion partnerships, to support fusion pilot plant wall and divertor material down-selection. Samples were exposed using the Divertor Materials Evaluation System (DiMES) under Ohmic, L-mode, and H-mode conditions with edge-localized modes, at 0.2-… ▽ More A coordinated DIII-D campaign exposed and comparatively assessed 44 advanced plasma-facing materials from 12 institutions, including four public-private fusion partnerships, to support fusion pilot plant wall and divertor material down-selection. Samples were exposed using the Divertor Materials Evaluation System (DiMES) under Ohmic, L-mode, and H-mode conditions with edge-localized modes, at 0.2-2.5 MW m$^{-2}$ on flush geometries and 10-15 MW m$^{-2}$ on 10$^{\circ}$ angled geometries. Engineered tungsten architectures retained integrity; long-fiber Wf/W showed the clearest crack-arrest behavior. W-Re and K-doped W showed near-ITER-W-like responses, while additively manufactured W-Ta showed heat-flux-sensitive mass losses of 0.64 mg for the flat sample and 2.19-2.87 mg for angled samples. After irradiation to 0.3 dpa at 550$^{\circ}$C, neutron-irradiated ITER-grade W retained 2.8 times more deuterium than pristine W, while TiB$_2$ showed the lowest D$_2$ release in the Ohmic set. VTaHfMo was the most stable refractory multi-principal-element alloy. NbC and (Nb$_{0.5}$Ta$_{0.5}$)C retained integrity with 0.02-0.03 mg mass loss, whereas ZrC lost 7 mg. CVD SiC retained macroscopic integrity but exhibited an effective Si erosion yield of 0.5, about 5-10 times above prior DIII-D trends. Renewable boron pebble rods underwent controlled recession; 13% of released boron was ionized near the outer strike point and up to 50% was recovered locally. Initial in-situ chromium gross-erosion measurements yielded values of order $10^{-2}$. Together, these results provide cross-material benchmarks for fusion pilot plant down-selection and future AI/ML-assisted plasma-facing-material development. △ Less

Submitted 25 July, 2026; originally announced July 2026.

Comments: 20 pages, 16 figures, 3 tables

Energy-Energy Correlators at Strong Coupling

Authors: Max Jackson, Lecheng Ren, Bo Wang, Congkao Wen

Abstract: We study energy-energy correlators (EEC) in planar $\mathcal{N}=4$ super Yang-Mills theory at strong 't Hooft coupling $λ$. We consider the EEC in states created by half-BPS operators of arbitrary dimension $p$, and determine the corresponding event-shape function up to order $λ^{-3/2}$ from the worldsheet representation of the AdS Virasoro-Shapiro amplitude with Kaluza-Klein external states. For… ▽ More We study energy-energy correlators (EEC) in planar $\mathcal{N}=4$ super Yang-Mills theory at strong 't Hooft coupling $λ$. We consider the EEC in states created by half-BPS operators of arbitrary dimension $p$, and determine the corresponding event-shape function up to order $λ^{-3/2}$ from the worldsheet representation of the AdS Virasoro-Shapiro amplitude with Kaluza-Klein external states. For $p=2$ we compute the second curvature correction, which completes the EEC through order $λ^{-2}$; the new contribution improves the agreement with recently derived non-perturbative bounds at intermediate coupling. We further develop a complementary method in which the strong-coupling expansion coefficients of the EEC are extracted directly from the Wilson coefficients of low-energy expansion of the AdS Virasoro-Shapiro amplitude, and find the two approaches in perfect agreement. △ Less

Submitted 23 July, 2026; originally announced July 2026.

Comments: 28 pages + 4 appendices, 3 figures

Report number: QMUL-PH-26-26

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

The Economic Benefits and Costs of AI and Policies to Mitigate AI's Impact on Inequality

Authors: Matthew O. Jackson, Zafer Kanik

Abstract: We examine the economic impact of increasingly productive AI and policies that spread its benefits across the economy. Improvements in AI productivity trigger labor reallocation and changes in absolute and relative wages for different types of labor. Wages of labor that is essential for building AI increase faster than overall GDP. Wages of labor that is substituted for by AI decrease in both abso… ▽ More We examine the economic impact of increasingly productive AI and policies that spread its benefits across the economy. Improvements in AI productivity trigger labor reallocation and changes in absolute and relative wages for different types of labor. Wages of labor that is essential for building AI increase faster than overall GDP. Wages of labor that is substituted for by AI decrease in both absolute and relative terms. Wages of labor that is used only in final goods production and is not displaced by AI increase in line with overall GDP. We contrast the impact of productivity gains depending on whether AI production is competitive or monopolistic. Monopoly production of AI restricts its deployment, slowing the transition and impact of AI. Optimal tax and regulatory policies that achieve Pareto-improvements differ depending on whether there is competition in AI production. △ Less

Submitted 11 July, 2026; v1 submitted 1 July, 2026; originally announced July 2026.

BehaviorBench: Benchmarking Foundation Models for Behavioral Science Tasks

Authors: Jin Huang, Yutong Xie, Wanli Song, Xingjian Zhang, Walter Yuan, Matthew O. Jackson, Qiaozhu Mei

Abstract: Foundation models have been increasingly applied to behavioral science domains such as psychology, sociology, and economics. While these models show promise in individual tasks such as survey response prediction and human-subject experiment simulation, there remains no systematic understanding of how well they perform across diverse behavioral science tasks, contexts, and populations. We introduce… ▽ More Foundation models have been increasingly applied to behavioral science domains such as psychology, sociology, and economics. While these models show promise in individual tasks such as survey response prediction and human-subject experiment simulation, there remains no systematic understanding of how well they perform across diverse behavioral science tasks, contexts, and populations. We introduce BehaviorBench, a comprehensive benchmark that evaluates foundation models along four core capabilities: (1) behavior prediction and simulation, (2) strategic decision-making, (3) subject-trait inference, and (4) behavioral knowledge application. Crucially, BehaviorBench evaluates model outputs at both the individual and distributional levels, capturing not only per-subject accuracy but also population-level alignment, an essential requirement for behavioral validity. Leveraging the tasks in BehaviorBench, we further develop Be.FM-1.5, extending the Be.FM family of behavioral foundation models fine-tuned on behavioral data. Our results reveal a considerable gap: proprietary general-purpose models excel at individual-level prediction and knowledge-intensive tasks, whereas behavioral foundation models, fine-tuned on behavioral data, achieve substantially stronger distributional alignment. Notably, Be.FM-1.5 leads on distributional metrics and remains competitive on individual-level metrics, suggesting that proper behavioral adaptation can close the gap. Our results highlight the importance of distributional evaluation, establish BehaviorBench as a foundation for developing and assessing behaviorally aligned AI systems, and demonstrate Be.FM-1.5's potential for a broad range of behavioral science studies. Our BehaviorBench and Be.FM-1.5 models can be accessed via https://umich-foreseer.github.io/behaviorbench/. △ Less

Submitted 23 June, 2026; originally announced June 2026.

Even harder pseudovariety membership problem

Authors: Marcel Jackson

Abstract: We present a finite semigroup whose pseudovariety has membership problem hard for the class \emph{Difference P} We present a finite semigroup whose pseudovariety has membership problem hard for the class \emph{Difference P} △ Less

Submitted 19 June, 2026; originally announced June 2026.

MSC Class: 20M07

Molecular cloud dispersal traced by the ionized carbon 158 micron line

Authors: L. Bonne, N. Schneider, S. Dannhauer, E. Keilmann, J. M. Jackson, R. Simon, A. G. G. M. Tielens, E. Chambers, C. Buchbender, J. L. Verbena, S. Kabanovic, T. Faerber, L. D. Anderson, R. Guesten, A. M. Jacob, C. Guevara, F. Wyrowski

Abstract: Feedback from massive stars in the form of radiation and winds impacts the associated host molecular cloud. Feedback can disperse cloud material and lead to the destruction of the cloud. Recent observations of the ionized carbon CII 158 micron line in high-mass star-forming regions have demonstrated that this line is an excellent tracer of the gas dynamics in such environments. Expanding CII shell… ▽ More Feedback from massive stars in the form of radiation and winds impacts the associated host molecular cloud. Feedback can disperse cloud material and lead to the destruction of the cloud. Recent observations of the ionized carbon CII 158 micron line in high-mass star-forming regions have demonstrated that this line is an excellent tracer of the gas dynamics in such environments. Expanding CII shells have been detected, along with high-velocity gas escaping the natal cloud through low-density channels. Motivated by these results, we conducted a systematic analysis of spectrally resolved CII maps obtained with SOFIA towards ten high-mass star-forming regions hosting at least one O-type star. Across all regions, we identify high-velocity CII line wings with velocities that exceed the cloud escape velocity, indicating that this gas is not gravitationally confined. We show that the high-velocity gas exhibits a complex velocity structure and cannot be attributed solely to a single, coherent expanding CII bubble. The amount of material in these erosion flows depends on the evolutionary stage of the molecular cloud and its associated HII region. Once the initial bubble around the cluster ruptures, typically after 0.1 Myr, gas is expelled from the cloud. The resulting cloud erosion timescales based on these directly observed mass ejection rates typically vary between 2 and 10 Myr after the formation of the first O stars, similar to other indirect measures of molecular cloud life times. These results suggest that stellar feedback is able to remove enough molecular gas to terminate the star formation in the host cloud. △ Less

Submitted 18 June, 2026; originally announced June 2026.

Comments: Astronomy & Astrophysics in press, 19 pages

Goal-Conditioned Agents that Learn Everything All at Once

Authors: Michael Matthews, Matthew Jackson, Michael Beukman, Thomas Foster, Alistair Letcher, Scott Fujimoto, Cédric Colas, Jakob Foerster

Abstract: A goal-conditioned reinforcement learning agent exploring an environment will see a wealth of information throughout a trajectory, most of which is discarded when only performing on-policy updates with respect to the commanded goal. All-goals learning, where each transition is used for learning off-policy with respect to every goal, allows agents to extract maximal information, however it is usual… ▽ More A goal-conditioned reinforcement learning agent exploring an environment will see a wealth of information throughout a trajectory, most of which is discarded when only performing on-policy updates with respect to the commanded goal. All-goals learning, where each transition is used for learning off-policy with respect to every goal, allows agents to extract maximal information, however it is usually computationally infeasible when done via naive relabelling. This can be overcome by jointly outputting values and actions for every goal at once, allowing for efficient, parallel all-goals updates with a single pass through the network, in a process we call Learning Everything all at Once (LEO). We show that this approach significantly outperforms other methods on goal-conditioned Craftax and is competitive with existing baselines on continuous control environments, while achieving a >250x speed-up compared to all-goals relabelling. We then go on to show that this approach can be made even more powerful by using LEO as a teacher network, rather than a direct actor. We hope that, by unlocking all-goals learning at scale, LEO can serve as a useful tool for RL practitioners in complex environments. We open source our code. △ Less

Submitted 22 May, 2026; originally announced May 2026.

Global and Local Infall in the ASHES Sample (GLASHES). II. Asymmetric Line Profiles around Dense Cores in 70 $μ$m Dark Massive Clumps

Authors: Kaho Morii, Patricio Sanhueza, Qizhou Zhang, James M. Jackson

Abstract: Gravitational collapse is fundamental to star formation, yet direct kinematic evidence of infall at the core scale in high-mass star-forming regions remains poorly constrained. We present the first large-scale statistical study of infall signatures in 304 dense cores within 24 massive 70 $μ$m-dark clumps from the GLASHES (Global and Local Infall in the ASHES Sample) survey. Using ALMA Band 6 obser… ▽ More Gravitational collapse is fundamental to star formation, yet direct kinematic evidence of infall at the core scale in high-mass star-forming regions remains poorly constrained. We present the first large-scale statistical study of infall signatures in 304 dense cores within 24 massive 70 $μ$m-dark clumps from the GLASHES (Global and Local Infall in the ASHES Sample) survey. Using ALMA Band 6 observations of the optically thick tracers HCO$^+$ and HNC (J=3-2), we systematically characterize blue asymmetry line profiles indicative of infalling motions. We employ two complementary metrics, the velocity difference parameter ($δ_v$) and the asymmetry parameter ($A$), to quantify infall signatures, finding consistent results across both tracers. Blue asymmetry profiles are detected in $\sim$50-60% of cores ($δ_v<$0 or A>0). Spectral classification reveals that $\sim$60% of cores exhibit double-peaked profiles, and 34% and 39% show blue asymmetry profiles in HCO$^+$ and HNC, respectively, with the percentage increasing with core mass and surface density. Accounting for geometric effects that can obscure infall signatures, our results suggest that gravitational collapse is prevalent in and around the cores. Importantly, infall signatures are detected from the prestellar stage and become more dominant as cores' evolution proceeds. Even cores with virial parameters $α_{vir} > 2$ show infall signatures, suggesting that external compression may trigger collapse in addition to self-gravity or that linewidth may include inward motion in addition to turbulence. Furthermore, a moderate correlation between clump-scale and core-scale asymmetry supports a hierarchical collapse scenario, implying a dynamic and multi-scale process of high-mass star formation. △ Less

Submitted 12 May, 2026; originally announced May 2026.

Comments: Accepted for Publication in ApJ. 22 pages, 15 figures, 3 tables

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

Modulating Surface Acoustic Wave Generation through Superconductivity

Authors: Andrew Christy, Yuzan Xiong, Rui Sun, Yi Li, Kenneth O. Chua, Andrew H. Comstock, Junming Wu, Sidong Lei, Frank Tsui, Megan N. Jackson, Dali Sun, Valentine Novosad, James F. Cahoon, Wei Zhang

Abstract: Surface acoustic waves (SAWs), with their five orders-of-magnitude slower propagation velocity, allow for considerably shorter wavelengths at the same frequency compared to electromagnetic waves. The short wavelengths allow for device miniaturization and on-chip integration. The generic design of these devices involve piezoelectric substrates with comblike arrays of Al or Au electrodes known as in… ▽ More Surface acoustic waves (SAWs), with their five orders-of-magnitude slower propagation velocity, allow for considerably shorter wavelengths at the same frequency compared to electromagnetic waves. The short wavelengths allow for device miniaturization and on-chip integration. The generic design of these devices involve piezoelectric substrates with comblike arrays of Al or Au electrodes known as interdigitated transducers deposited on the surface. However, Al and Au both have shortcomings at the cryogenic temperatures required for quantum applications, namely the formation of two-level systems and the lack of superconductivity perpetuating Ohmic losses, respectively. In this work, SAWs are generated in the high-MHz to low-GHz range using niobium nitride (NbN) interdigitated transducers (IDTs) and Bragg reflectors. We demonstrate the fabrication of acoustic devices through photolithography and reactive ion etching (RIE). The sharp transition between superconducting and normal states and the corresponding change in SAW transmission allows for fine control of the 'on' (superconducting) and 'off' (normal) states of NbN, with a Δ_T = K separating the transmission minimum and maximum. We demonstrate a 16x difference in transmission between the 'on' and 'off' states of the device. The SAW transmission behavior mirrors the change in resistance of NbN at its Tc. These findings open up new possibilities for the integration of NbN SAW resonators into existing quantum architectures based on NbN and a method for adjusting transmission properties independent of applied voltage. △ Less

Submitted 2 March, 2026; originally announced March 2026.

Comments: 7 pages, 4 figures

Dense Molecular Clumps with Large Blue Asymmetries: Evidence for Collapse

Authors: James M. Jackson, J. Scott Whitaker, Edward Chambers, Robert Simon, Cristian Guevara, David Allingham, Philippa Patterson, Nicholas Killerby-Smith, Jacob Askew, Patricio Sanhueza, Ian W. Stephens, Anika Shmiedeke, Jacob Askew, Robert Loughnane

Abstract: An analysis of the Millimetre Astronomy Legacy Team 90 GHz (MALT90) survey has produced a sample of 27 candidate dense molecular clumps with large collapse motions, as revealed by large ``blue'' asymmetrical line profiles of the optically thick \hcop\, line. %with respect to the optically thin \nthp\, line. New, more sensitive molecular line observations of this sample, conducted with the Mopra 22… ▽ More An analysis of the Millimetre Astronomy Legacy Team 90 GHz (MALT90) survey has produced a sample of 27 candidate dense molecular clumps with large collapse motions, as revealed by large ``blue'' asymmetrical line profiles of the optically thick \hcop\, line. %with respect to the optically thin \nthp\, line. New, more sensitive molecular line observations of this sample, conducted with the Mopra 22-m telescope, confirm the blue asymmetries in the \hcop\, line profiles, with large, positive values of the asymmetry parameter $A$ ($\bar{A}_{HCO^+} = 0.69\pm0.01$), and positive, but smaller asymmetries in the \hcn\, and \hnc\, lines: ($\bar{A}_{HCN} = 0.35\pm0.01$ and $\bar{A}_{HNC} = 0.28\pm0.01$), as expected for a less optically thick tracer in collapsing clumps. The small, positive mean asymmetry parameters for \cch\, and \htcop, $\bar{A}_{C_2H} = 0.15\pm0.02$ and $\bar{A}_{H^{13}CO^+} = 0.18\pm0.03$, likely indicate slightly optically thick emission for at least some clumps. The hyperfine ratios for \nthp\, are in their optically thin, LTE, values, but for \hcn\ they are not; the $F=1 \to 1$ hyperfine line shows abnormally weak intensities. A simple two-component model shows that self-absorption of the background $F = 1 \to 1$ hyperfine line by the main $F = 2 \to 1$ hyperfine line of a cold, foreground, redshifted cloud can reproduce the observed \hcn\, hyperfine intensities and match the \hcn\, and \hcop\, line profiles. All of these results are consistent with self-absorption of the optically thick lines on the red side of the profile, as expected for collapsing clumps. A simple two-cloud model suggests that this sample represents dense clumps with extreme collapse velocities, $V_{inf} \sim 2.4$ \kms. △ Less

Submitted 15 February, 2026; originally announced February 2026.

Journal ref: ApJ, 998:167 2026

Adaptive Physics Transformer with Fused Global-Local Attention for Subsurface Energy Systems

Authors: Xin Ju, Nok Hei, Fung, Yuyan Zhang, Carl Jacquemyn, Matthew Jackson, Randolph Settgast, Sally M. Benson, Gege Wen

Abstract: The Earth's subsurface is a cornerstone of modern society, providing essential energy resources like hydrocarbons, geothermal, and minerals while serving as the primary reservoir for $CO_2$ sequestration. However, full physics numerical simulations of these systems are notoriously computationally expensive due to geological heterogeneity, high resolution requirements, and the tight coupling of phy… ▽ More The Earth's subsurface is a cornerstone of modern society, providing essential energy resources like hydrocarbons, geothermal, and minerals while serving as the primary reservoir for $CO_2$ sequestration. However, full physics numerical simulations of these systems are notoriously computationally expensive due to geological heterogeneity, high resolution requirements, and the tight coupling of physical processes with distinct propagation time scales. Here we propose the $\textbf{Adaptive Physics Transformer}$ (APT), a geometry-, mesh-, and physics-agnostic neural operator that explicitly addresses these challenges. APT fuses a graph-based encoder to extract high-resolution local heterogeneous features with a global attention mechanism to resolve long-range physical impacts. Our results demonstrate that APT outperforms state-of-the-art architectures in subsurface tasks across both regular and irregular grids with robust super-resolution capabilities. Notably, APT is the first architecture that learns directly from HR-adaptive mesh refinement simulations. We also demonstrate APT's favorable scaling behavior and cross-dataset learning capability, positioning it as a robust and scalable backbone for large-scale subsurface foundation model development. △ Less

Submitted 29 May, 2026; v1 submitted 10 February, 2026; originally announced February 2026.

Segment to Focus: Guiding Latent Action Models in the Presence of Distractors

Authors: Marcus Fechner, Hamza Adnan, Constantin C. Lüth, Matthew T. Jackson, Alexey Zakharov, J. Marius Zöllner

Abstract: Latent action models (LAMs) offer a promising path to pre-training embodied agents on large amounts of action-free video. They infer latent actions between consecutive observations that can later be decoded to ground-truth actions using a small number of labels. However, recent work has shown that this recipe fails in the presence of action-correlated visual distractors common in real-world video,… ▽ More Latent action models (LAMs) offer a promising path to pre-training embodied agents on large amounts of action-free video. They infer latent actions between consecutive observations that can later be decoded to ground-truth actions using a small number of labels. However, recent work has shown that this recipe fails in the presence of action-correlated visual distractors common in real-world video, such as dynamic backgrounds, camera shake, or other moving objects. In these scenarios, the standard reconstruction objective drives latent actions to encode exogenous motion instead of agent-controlled dynamics, resulting in policies that underperform when fine-tuned. We observe, however, that endogenous and exogenous factors are typically spatially separated in pixel space: control-relevant change is concentrated on the agent, while distractor motion occurs elsewhere. We exploit this observation by restricting the reconstruction objective to agent pixels, forcing latent actions to explain agent-controlled dynamics rather than exogenous ones. We call this method MaskLAM; it obtains the agent mask zero-shot from off-the-shelf segmentation foundation models (e.g., SAM) and requires no architectural changes, auxiliary losses, or action labels during pre-training. Across two continuous-control benchmarks (Distracting Control Suite, Distracting Meta-World), MaskLAM reduces normalized linear-probe MSE by up to $3.51\times$ and improves normalized return by up to $4.97\times$ over LAPO, while narrowing the gap to LAOM-Labels, which relies on ground-truth action supervision. △ Less

Submitted 27 May, 2026; v1 submitted 2 February, 2026; originally announced February 2026.

Social Learning with Endogenous Information and the Countervailing Effects of Homophily

Authors: Yunus C. Aybas, Matthew O. Jackson

Abstract: People learn about opportunities and actions by observing the experiences of their friends. We model how homophily -- the tendency to associate with similar others -- affects both the endogenous quality and diversity of the information accessible to decision makers. Homophily provides higher-quality information, since observing the payoffs of another person is more informative the more similar tha… ▽ More People learn about opportunities and actions by observing the experiences of their friends. We model how homophily -- the tendency to associate with similar others -- affects both the endogenous quality and diversity of the information accessible to decision makers. Homophily provides higher-quality information, since observing the payoffs of another person is more informative the more similar that person is to the decision maker. However, homophily can lead people to take actions that generate less information. We show how network connectivity influences the tradeoff between the endogenous quantity and quality of information. Although homophily hampers learning in sparse networks, it enhances learning in sufficiently dense networks. △ Less

Submitted 22 June, 2026; v1 submitted 31 January, 2026; originally announced February 2026.

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

SIMA 2: A Generalist Embodied Agent for Virtual Worlds

Authors: SIMA team, Adrian Bolton, Alexander Lerchner, Alexandra Cordell, Alexandre Moufarek, Andrew Bolt, Andrew Lampinen, Anna Mitenkova, Arne Olav Hallingstad, Bojan Vujatovic, Bonnie Li, Cong Lu, Daan Wierstra, Daniel P. Sawyer, Daniel Slater, David Reichert, Davide Vercelli, Demis Hassabis, Drew A. Hudson, Duncan Williams, Ed Hirst, Fabio Pardo, Felix Hill, Frederic Besse, Hannah Openshaw , et al. (41 additional authors not shown)

Abstract: We introduce SIMA 2, a generalist embodied agent that understands and acts in a wide variety of 3D virtual worlds. Built upon a Gemini foundation model, SIMA 2 represents a significant step toward active, goal-directed interaction within an embodied environment. Unlike prior work (e.g., SIMA 1) limited to simple language commands, SIMA 2 acts as an interactive partner, capable of reasoning about h… ▽ More We introduce SIMA 2, a generalist embodied agent that understands and acts in a wide variety of 3D virtual worlds. Built upon a Gemini foundation model, SIMA 2 represents a significant step toward active, goal-directed interaction within an embodied environment. Unlike prior work (e.g., SIMA 1) limited to simple language commands, SIMA 2 acts as an interactive partner, capable of reasoning about high-level goals, conversing with the user, and handling complex instructions given through language and images. Across a diverse portfolio of games, SIMA 2 substantially closes the gap with human performance and demonstrates robust generalization to previously unseen environments, all while retaining the base model's core reasoning capabilities. Furthermore, we demonstrate a capacity for open-ended self-improvement: by leveraging Gemini to generate tasks and provide rewards, SIMA 2 can autonomously learn new skills from scratch in a new environment. This work validates a path toward creating versatile and continuously learning agents for both virtual and, eventually, physical worlds. △ Less

Submitted 4 December, 2025; originally announced December 2025.

On efficient approximation of quadratic irrationals

Authors: Peter H. van der Kamp, Anthony Overmars, Marcel Jackson, Andrew N. W. Hone

Abstract: We provide efficient algorithms to compute convergents of quadratic irrationals. We show that for square roots, in settings where Galois' refinement of Lagrange's theorem holds, certain decimations of the sequence of convergents are signed Chebyshev sequences, which can be also be generated by a Householder method. We provide efficient algorithms to compute convergents of quadratic irrationals. We show that for square roots, in settings where Galois' refinement of Lagrange's theorem holds, certain decimations of the sequence of convergents are signed Chebyshev sequences, which can be also be generated by a Householder method. △ Less

Submitted 17 June, 2026; v1 submitted 26 November, 2025; originally announced November 2025.

Comments: 13 pages, 11 references, no figures, V2 contains two additional (multiplicative) algorithms (3.4 and 3.5) and an additional example (3.4)

MSC Class: 11A55; 41A50; 65D99

Measurement of Exclusive $π^+$--argon Interactions Using ProtoDUNE-SP

Authors: DUNE Collaboration, S. Abbaslu, 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, M. Andreotti , et al. (1304 additional authors not shown)

Abstract: We present the measurement of $π^{+}$--argon inelastic cross sections using the ProtoDUNE Single-Phase liquid argon time projection chamber in the incident $π^+$ kinetic energy range of 500 -- 800 MeV in multiple exclusive channels (absorption, charge exchange, and the remaining inelastic interactions). The results of this analysis are important inputs to simulations of liquid argon neutrino exper… ▽ More We present the measurement of $π^{+}$--argon inelastic cross sections using the ProtoDUNE Single-Phase liquid argon time projection chamber in the incident $π^+$ kinetic energy range of 500 -- 800 MeV in multiple exclusive channels (absorption, charge exchange, and the remaining inelastic interactions). The results of this analysis are important inputs to simulations of liquid argon neutrino experiments such as the Deep Underground Neutrino Experiment and the Short Baseline Neutrino program at Fermi National Accelerator Laboratory. They will be employed to improve the modeling of final state interactions within neutrino event generators used by these experiments, as well as the modeling of $π^{+}$--argon secondary interactions within the liquid argon. This is the first measurement of $π^+$--argon absorption at this kinetic energy range as well as the first ever measurement of $π^{+}$--argon charge exchange. △ Less

Submitted 17 November, 2025; originally announced November 2025.

Report number: CERN-EP-2025-268; FERMILAB-PUB-25-0732-LBNF

First Measurement of $π^+$-Ar and $p$-Ar Total Inelastic Cross Sections in the Sub-GeV Energy Regime with ProtoDUNE-SP Data

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, L. Aliaga Soplin, K. Allison, M. Alrashed, A. Alton, R. Alvarez, T. Alves, A. Aman, H. Amar, P. Amedo, J. Anderson, D. A. Andrade , et al. (1328 additional authors not shown)

Abstract: The ProtoDUNE-SP detector, a kiloton-scale prototype for the Deep Underground Neutrino Experiment (DUNE) far detector, is the largest liquid argon time projection chamber built to date. Operated at CERN from 2018 to 2020, it collected both cosmic-ray data and a beam consisting of positively-charged particles with discrete momentum settings across a range of 0.3 GeV/$c$ to 7 GeV/$c$. In this letter… ▽ More The ProtoDUNE-SP detector, a kiloton-scale prototype for the Deep Underground Neutrino Experiment (DUNE) far detector, is the largest liquid argon time projection chamber built to date. Operated at CERN from 2018 to 2020, it collected both cosmic-ray data and a beam consisting of positively-charged particles with discrete momentum settings across a range of 0.3 GeV/$c$ to 7 GeV/$c$. In this letter, we report the total inelastic cross section measurements for $π^+$--Ar and $p$--Ar interactions using selected $π^+$ and proton samples from the 1 GeV/$c$ beam data, spanning kinetic energies of 500--900~MeV and below 450~MeV, respectively. These energy ranges are directly relevant to hadrons produced in DUNE. The measured cross sections are consistent with predictions and provide a dataset that was previously unavailable for argon targets. These measurements are essential for constraining neutrino-argon interaction models and achieving the precision physics goals of the upcoming DUNE experiment. △ Less

Submitted 26 May, 2026; v1 submitted 14 November, 2025; originally announced November 2025.

Report number: FERMILAB-PUB-25-0814-LBNF, CERN-EP-2025-266

Supply Chain Disruptions, the Structure of Production Networks, and the Impact of Globalization

Authors: Matthew L. Elliott, Matthew O. Jackson

Abstract: We introduce a parsimonious multi-sector model of international production and use it to study the impact of a disruption in the production of some goods propagates to other goods and consumers, and how that impact depends on the goods' positions in, and overall structure of, the production network. We show that the short-run impact of a disruption can be dramatically larger than the long-run impa… ▽ More We introduce a parsimonious multi-sector model of international production and use it to study the impact of a disruption in the production of some goods propagates to other goods and consumers, and how that impact depends on the goods' positions in, and overall structure of, the production network. We show that the short-run impact of a disruption can be dramatically larger than the long-run impact. The short-run disruption depends on the value of all of the final goods whose supply chains involve a disrupted good, while by contrast the long-run disruption depends only on the cost of the disrupted goods. We use the model to show how increased complexity of supply chains leads to increased fragility in terms of the probability and expected short-run size of a disruption. We also show how decreased transportation costs can lead to increased specialization in production, lowering the chances for disruption but increasing the impact conditional upon disruption. We use the model to characterize the power that a country has over others via diversions of its production as well as quotas on imports and exports. △ Less

Submitted 15 January, 2026; v1 submitted 5 November, 2025; originally announced November 2025.

Response of wavelength-shifting and scintillating-wavelength-shifting fibers to ionizing radiation

Authors: W. Bae, J. Cesar, K. Chen, J. Cho, D. Du, J. Edgar, W. Earthman, O. M. Falana, M. Gajda, C. Hurlbut, M. Jackson, K. Lang, C. Lee, J. Y. Lee, E. Liang, J. Liu, C. Maxwell, C. Murthy, D. Myers, S. Nguyen, D. Phan, T. O'Brien, M. Proga, S. Syed, M. Zalikha , et al. (1 additional authors not shown)

Abstract: We report results of characterizing the response and light transport of wavelength-shifting (WLS) and scintillating-wavelength-shifting (Sci-WLS) fibers under irradiation by radioactive $α$, $β$, and $γ$ sources. Light yield and light transmission were measured for the WLS fiber BCF-91A from Saint-Gobain and for a new Sci-WLS fiber EJ-160 from Eljen Technology. The two variants with different fl… ▽ More We report results of characterizing the response and light transport of wavelength-shifting (WLS) and scintillating-wavelength-shifting (Sci-WLS) fibers under irradiation by radioactive $α$, $β$, and $γ$ sources. Light yield and light transmission were measured for the WLS fiber BCF-91A from Saint-Gobain and for a new Sci-WLS fiber EJ-160 from Eljen Technology. The two variants with different fluor mixtures, EJ-160I and EJ-160II, exhibited approximately five and seven times higher light yield than BCF-91A, respectively, while their attenuation lengths were 3.80\,m for BCF-91A, 4.00\,m for EJ-160I, and 2.50\,m for EJ-160II. △ Less

Submitted 15 March, 2026; v1 submitted 26 September, 2025; originally announced October 2025.

Comments: 13 pages, 13 figures, 3 tables; The source structure has been reorganized for journal submission compatibility

Identification of low-energy kaons in the ProtoDUNE-SP detector

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: The Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino experiment with a rich physics program that includes searches for the hypothetical phenomenon of proton decay. Utilizing liquid-argon time-projection chamber technology, DUNE is expected to achieve world-leading sensitivity in the proton decay channels that involve charged kaons in their final states. The first DUNE demo… ▽ More The Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino experiment with a rich physics program that includes searches for the hypothetical phenomenon of proton decay. Utilizing liquid-argon time-projection chamber technology, DUNE is expected to achieve world-leading sensitivity in the proton decay channels that involve charged kaons in their final states. The first DUNE demonstrator, ProtoDUNE Single-Phase, was a 0.77 kt detector that operated from 2018 to 2020 at the CERN Neutrino Platform, exposed to a mixed hadron and electron test-beam with momenta ranging from 0.3 to 7 GeV/c. We present a selection of low-energy kaons among the secondary particles produced in hadronic reactions, using data from the 6 and 7 GeV/c beam runs. The selection efficiency is 1\% and the sample purity 92\%. The initial energies of the selected kaon candidates encompass the expected energy range of kaons originating from proton decay events in DUNE (below $\sim$200 MeV). In addition, we demonstrate the capability of this detector technology to discriminate between kaons and other particles such as protons and muons, and provide a comprehensive description of their energy loss in liquid argon, which shows good agreement with the simulation. These results pave the way for future proton decay searches at DUNE. △ Less

Submitted 9 October, 2025; originally announced October 2025.

Report number: CERN-EP-2025-231, FERMILAB-PUB-25-0717-LBNF

Magnetic Fields in the Bones of the Milky Way

Authors: Ian W. Stephens, Simon Coude, Philip C. Myers, Catherine Zucker, James M. Jackson, B-G Andersson, Rowan Smith, Archana Soam, Patricio Sanhueza, Taylor Hogge, Howard A. Smith, Giles Novak, Sarah Sadavoy, Thushara Pillai, Zhi-Yun Li, Leslie W. Looney, Koji Sugitani, Andres E. Guzman, Alyssa Goodman, Takayoshi Kusune, Miaomiao Zhang, Nicole Karnath, Jessy Marin

Abstract: Stars primarily form in galactic spiral arms within dense, filamentary molecular clouds. The largest and most elongated of these molecular clouds are referred to as ``bones," which are massive, velocity-coherent filaments (lengths ~20 to >100 pc, widths ~1-2 pc) that run approximately parallel and in close proximity to the Galactic plane. While these bones have been generally well characterized, t… ▽ More Stars primarily form in galactic spiral arms within dense, filamentary molecular clouds. The largest and most elongated of these molecular clouds are referred to as ``bones," which are massive, velocity-coherent filaments (lengths ~20 to >100 pc, widths ~1-2 pc) that run approximately parallel and in close proximity to the Galactic plane. While these bones have been generally well characterized, the importance and structure of their magnetic fields (B-fields) remain largely unconstrained. Through the SOFIA Legacy program FIELDMAPS, we mapped the B-fields of 10 bones in the Milky Way. We found that their B-fields are varied, with no single preferred alignment along the entire spine of the bones. At higher column densities, the spines of the bones are more likely to align perpendicularly to the B-fields, although this is not ubiquitous, and the alignment shows no strong correlation with the locations of identified young stellar objects. We estimated the B-field strengths across the bones and found them to be ~30-150 $μ$G at pc scales. Despite the generally low virial parameters, the B-fields are strong compared to the local gravity, suggesting that B-fields play a significant role in resisting global collapse. Moreover, the B-fields may slow and guide gas flow during dissipation. Recent star formation within the bones may be due to high-density pockets at smaller scales, which could have formed before or simultaneously with the bones. △ Less

Submitted 7 October, 2025; originally announced October 2025.

Comments: Accepted to ApJ

HyperVLA: Efficient Inference in Vision-Language-Action Models via Hypernetworks

Authors: Zheng Xiong, Kang Li, Zilin Wang, Matthew Jackson, Jakob Foerster, Shimon Whiteson

Abstract: Built upon language and vision foundation models with strong generalization ability and trained on large-scale robotic data, Vision-Language-Action (VLA) models have recently emerged as a promising approach to learning generalist robotic policies. However, a key drawback of existing VLAs is their extremely high inference costs. In this paper, we propose HyperVLA to address this problem. Unlike exi… ▽ More Built upon language and vision foundation models with strong generalization ability and trained on large-scale robotic data, Vision-Language-Action (VLA) models have recently emerged as a promising approach to learning generalist robotic policies. However, a key drawback of existing VLAs is their extremely high inference costs. In this paper, we propose HyperVLA to address this problem. Unlike existing monolithic VLAs that activate the whole model during both training and inference, HyperVLA uses a novel hypernetwork (HN)-based architecture that activates only a small task-specific policy during inference, while still retaining the high model capacity needed to accommodate diverse multi-task behaviors during training. Successfully training an HN-based VLA is nontrivial so HyperVLA contains several key algorithm design features that improve its performance, including properly utilizing the prior knowledge from existing vision foundation models, HN normalization, and an action generation strategy. Compared to monolithic VLAs, HyperVLA achieves a similar or even higher success rate for both zero-shot generalization and few-shot adaptation, while significantly reducing inference costs. Compared to OpenVLA, a state-of-the-art VLA model, HyperVLA reduces the number of activated parameters at test time by $90\times$, and accelerates inference speed by $120\times$. Code is publicly available at https://github.com/MasterXiong/HyperVLA △ Less

Submitted 6 October, 2025; originally announced October 2025.

Optical characterization of wavelength-shifting and scintillating-wavelength-shifting fibers

Authors: W. Bae, J. Cesar, K. Chen, J. Cho, D. Du, J. Edgar, L. Earthman, O. M. Falana, M. Gajda, C. Hurlbut, M. Jackson, K. Lang, C. Lee, J. Y. Lee, E. Liang, J. Liu, C. Maxwell, C. Murthy, D. Myers, S. Nguyen, T. O'Brien, M. Proga, T. Rodriguez, S. Syed, M. Zalikha , et al. (1 additional authors not shown)

Abstract: We report results of optical characterizations of new wavelength-shifting and scintillating-wavelength-shifting fibers EJ-182 and EJ-160 from Eljen Technology and compare them to the wavelength-shifting fiber BCF-91A from Saint-Gobain. The wavelength-dependence of attenuation was derived from spectral measurements confirming that the long attenuation length increases with wavelength, while short a… ▽ More We report results of optical characterizations of new wavelength-shifting and scintillating-wavelength-shifting fibers EJ-182 and EJ-160 from Eljen Technology and compare them to the wavelength-shifting fiber BCF-91A from Saint-Gobain. The wavelength-dependence of attenuation was derived from spectral measurements confirming that the long attenuation length increases with wavelength, while short attenuation effects become less significant at longer wavelengths. The impact of the environmental refractive index was studied by immersing the EJ-160II fiber in water. Immersing the fiber in water reduced the overall light output and suppressed the short attenuation component, which can be explained by reduced light-collection efficiency due to the smaller refractive-index contrast between the fiber cladding and the surrounding medium. △ Less

Submitted 20 December, 2025; v1 submitted 22 September, 2025; originally announced September 2025.

Comments: 15 pages, 14 figures, 3 tables; The source structure has been reorganized for journal submission compatibility

Imagined Autocurricula

Authors: Ahmet H. Güzel, Matthew Thomas Jackson, Jarek Luca Liesen, Tim Rocktäschel, Jakob Nicolaus Foerster, Ilija Bogunovic, Jack Parker-Holder

Abstract: Training agents to act in embodied environments typically requires vast training data or access to accurate simulation, neither of which exists for many cases in the real world. Instead, world models are emerging as an alternative leveraging offline, passively collected data, they make it possible to generate diverse worlds for training agents in simulation. In this work, we harness world models t… ▽ More Training agents to act in embodied environments typically requires vast training data or access to accurate simulation, neither of which exists for many cases in the real world. Instead, world models are emerging as an alternative leveraging offline, passively collected data, they make it possible to generate diverse worlds for training agents in simulation. In this work, we harness world models to generate imagined environments to train robust agents capable of generalizing to novel task variations. One of the challenges in doing this is ensuring the agent trains on useful generated data. We thus propose a novel approach, IMAC (Imagined Autocurricula), leveraging Unsupervised Environment Design (UED), which induces an automatic curriculum over generated worlds. In a series of challenging, procedurally generated environments, we show it is possible to achieve strong transfer performance on held-out environments, having trained only inside a world model learned from a narrower dataset. We believe this opens the path to utilizing larger-scale, foundation world models for generally capable agents. △ Less

Submitted 28 September, 2025; v1 submitted 11 September, 2025; originally announced September 2025.

AI Behavioral Science

Authors: Matthew O. Jackson, Qiaozhu Me, Stephanie W. Wang, Yutong Xie, Walter Yuan, Seth Benzell, Erik Brynjolfsson, Colin F. Camerer, James Evans, Brian Jabarian, Jon Kleinberg, Juanjuan Meng, Sendhil Mullainathan, Asuman Ozdaglar, Thomas Pfeiffer, Moshe Tennenholtz, Robb Willer, Diyi Yang, Teng Ye

Abstract: We outline a foundation for a new field of ``AI Behavioral Science,'' covering three perspectives. First, as AI becomes ubiquitous and is increasingly proprietary and opaque, it becomes vital to develop techniques for assessing AI behavior. We outline how tools developed to assess people's behaviors by social scientists can be used to assess and infer AI's behaviors biases, tendencies, and heurist… ▽ More We outline a foundation for a new field of ``AI Behavioral Science,'' covering three perspectives. First, as AI becomes ubiquitous and is increasingly proprietary and opaque, it becomes vital to develop techniques for assessing AI behavior. We outline how tools developed to assess people's behaviors by social scientists can be used to assess and infer AI's behaviors biases, tendencies, and heuristics. Second, we also discuss how AI can change the ways in which we learn about human behavior. Beyond its computational power, AI offers new techniques for simulating, inferring, and predicting human behaviors that we outline and discuss. Third, as humans and AI are interacting in increasingly complex and intertwined systems, we need to understand the implications for the resulting economic and political outcomes. We outline issues that are increasingly pressing concerning the future of human-AI interactions and potential changes and disruptions that can ensue. △ Less

Submitted 29 May, 2026; v1 submitted 17 August, 2025; originally announced September 2025.

Towards mono-energetic virtual $ν$ beam cross-section measurements: A feasibility study of $ν$-Ar interaction analysis with DUNE-PRISM

Authors: DUNE Collaboration, S. Abbaslu, 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, M. Andreotti , et al. (1302 additional authors not shown)

Abstract: Neutrino-nucleus cross-section measurements are critical for future neutrino oscillation analyses. However, our models to describe them require further refinement, and a deeper understanding of the underlying physics is essential for future neutrino oscillation experiments to realize their ambitious physics goals. Current neutrino cross-section measurements provide clear deficiencies in neutrino i… ▽ More Neutrino-nucleus cross-section measurements are critical for future neutrino oscillation analyses. However, our models to describe them require further refinement, and a deeper understanding of the underlying physics is essential for future neutrino oscillation experiments to realize their ambitious physics goals. Current neutrino cross-section measurements provide clear deficiencies in neutrino interaction modeling, but almost all are reported averaged over broad neutrino fluxes, rendering their interpretation challenging. Using the DUNE-PRISM concept (Deep Underground Neutrino Experiment Precision Reaction Independent Spectrum Measurement) -- a movable near detector that samples multiple off-axis positions -- neutrino interaction measurements can be used to construct narrow virtual fluxes (less than 100 MeV wide). These fluxes can be used to extract charged-current neutrino-nucleus cross sections as functions of outgoing lepton kinematics within specific neutrino energy ranges. Based on a dedicated simulation with realistic event statistics and flux-related systematic uncertainties, but assuming an almost-perfect detector, we run a feasibility study demonstrating how DUNE-PRISM data can be used to measure muon neutrino charged-current integrated and differential cross sections over narrow fluxes. We find that this approach enables a model independent reconstruction of powerful observables, including energy transfer, typically accessible only in electron scattering measurements, but that large exposures may be required for differential cross-section measurements with few-\% statistical uncertainties. △ Less

Submitted 9 September, 2025; originally announced September 2025.

Report number: FERMILAB-PUB-25-0627-LBNF

Journal ref: Phys. Rev. D 114, 012018 (2026)

Operation of a Modular 3D-Pixelated Liquid Argon Time-Projection Chamber in a Neutrino Beam

Authors: DUNE Collaboration, S. Abbaslu, 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, M. Andreotti , et al. (1299 additional authors not shown)

Abstract: The 2x2 Demonstrator, a prototype for the Deep Underground Neutrino Experiment (DUNE) liquid argon (LAr) Near Detector, was exposed to the Neutrinos from the Main Injector (NuMI) neutrino beam at Fermi National Accelerator Laboratory (Fermilab). This detector prototypes a new modular design for a liquid argon time-projection chamber (LArTPC), comprised of a two-by-two array of four modules, each f… ▽ More The 2x2 Demonstrator, a prototype for the Deep Underground Neutrino Experiment (DUNE) liquid argon (LAr) Near Detector, was exposed to the Neutrinos from the Main Injector (NuMI) neutrino beam at Fermi National Accelerator Laboratory (Fermilab). This detector prototypes a new modular design for a liquid argon time-projection chamber (LArTPC), comprised of a two-by-two array of four modules, each further segmented into two optically-isolated LArTPCs. The 2x2 Demonstrator features a number of pioneering technologies, including a low-profile resistive field shell to establish drift fields, native 3D ionization pixelated imaging, and a high-coverage dielectric light readout system. The 2.4 tonne active mass detector is flanked upstream and downstream by supplemental solid-scintillator tracking planes, repurposed from the MINERvA experiment, which track ionizing particles exiting the argon volume. The antineutrino beam data collected by the detector over a 4.5 day period in 2024 include over 30,000 neutrino interactions in the LAr active volume-the first neutrino interactions reported by a DUNE detector prototype. During its physics-quality run, the 2x2 Demonstrator operated at a nominal drift field of 500 V/cm and maintained good LAr purity, with a stable electron lifetime of approximately 1.25 ms. This paper describes the detector and supporting systems, summarizes the installation and commissioning, and presents the initial validation of collected NuMI beam and off-beam self-triggers. In addition, it highlights observed interactions in the detector volume, including candidate muon anti-neutrino events. △ Less

Submitted 17 June, 2026; v1 submitted 6 September, 2025; originally announced September 2025.

Report number: FERMILAB-PUB-25-0537-LBNF

Journal ref: Instruments 2026, 10(1), 18

Predictive models for strain energy in condensed phase reactions

Authors: Baptiste Martin, Shukai Yao, Chunyu Li, Anthony Bocahut, Matthew Jackson, Alejandro Strachan

Abstract: Molecular modeling of thermally activated chemistry in condensed phases is essential to understand polymerization, depolymerization, and other processing steps of molecular materials. Current methods typically combine molecular dynamics (MD) simulations to describe short-time relaxation with a stochastic description of predetermined chemical reactions. Possible reactions are often selected on the… ▽ More Molecular modeling of thermally activated chemistry in condensed phases is essential to understand polymerization, depolymerization, and other processing steps of molecular materials. Current methods typically combine molecular dynamics (MD) simulations to describe short-time relaxation with a stochastic description of predetermined chemical reactions. Possible reactions are often selected on the basis of geometric criteria, such as a capture distance between reactive atoms. Although these simulations have provided valuable insight, the approximations used to determine possible reactions often lead to significant molecular strain and unrealistic structures. We show that the local molecular environment surrounding the reactive site plays a crucial role in determining the resulting molecular strain energy and, in turn, the associated reaction rates. We develop a graph neural network capable of predicting the strain energy associated with a cyclization reaction from the pre-reaction, local, molecular environment surrounding the reactive site. The model is trained on a large dataset of condensed-phase reactions during the activation of polyacrylonitrile (PAN) obtained from MD simulations and can be used to adjust relative reaction rates in condensed systems and advance our understanding of thermally activated chemical processes in complex materials △ Less

Submitted 7 January, 2026; v1 submitted 21 August, 2025; originally announced August 2025.

AI Telephone Surveying: Automating Quantitative Data Collection with an AI Interviewer

Authors: Danny D. Leybzon, Shreyas Tirumala, Nishant Jain, Summer Gillen, Michael Jackson, Cameron McPhee, Jennifer Schmidt

Abstract: With the rise of voice-enabled artificial intelligence (AI) systems, quantitative survey researchers have access to a new data-collection mode: AI telephone surveying. By using AI to conduct phone interviews, researchers can scale quantitative studies while balancing the dual goals of human-like interactivity and methodological rigor. Unlike earlier efforts that used interactive voice response (IV… ▽ More With the rise of voice-enabled artificial intelligence (AI) systems, quantitative survey researchers have access to a new data-collection mode: AI telephone surveying. By using AI to conduct phone interviews, researchers can scale quantitative studies while balancing the dual goals of human-like interactivity and methodological rigor. Unlike earlier efforts that used interactive voice response (IVR) technology to automate these surveys, voice AI enables a more natural and adaptive respondent experience as it is more robust to interruptions, corrections, and other idiosyncrasies of human speech. We built and tested an AI system to conduct quantitative surveys based on large language models (LLM), automatic speech recognition (ASR), and speech synthesis technologies. The system was specifically designed for quantitative research, and strictly adhered to research best practices like question order randomization, answer order randomization, and exact wording. To validate the system's effectiveness, we deployed it to conduct two pilot surveys with the SSRS Opinion Panel and followed-up with a separate human-administered survey to assess respondent experiences. We measured three key metrics: the survey completion rates, break-off rates, and respondent satisfaction scores. Our results suggest that shorter instruments and more responsive AI interviewers may contribute to improvements across all three metrics studied. △ Less

Submitted 23 July, 2025; originally announced July 2025.

Peer Influence on West Point Cadets' Civil War Allegiances

Authors: Yuchen Guo, Matthew O. Jackson, Ruixue Jia

Abstract: Do social networks and peer influence shape major life decisions in highly polarized settings? We explore this question by examining how peers influenced the allegiances of West Point cadets during the American Civil War. Leveraging quasi-random variations in the proportion of cadets from Free States, we analyze how cadets' decisions about which army to join depended on the composition of their pe… ▽ More Do social networks and peer influence shape major life decisions in highly polarized settings? We explore this question by examining how peers influenced the allegiances of West Point cadets during the American Civil War. Leveraging quasi-random variations in the proportion of cadets from Free States, we analyze how cadets' decisions about which army to join depended on the composition of their peers. We have three main findings. First, there was a strong and significant peer effect: a higher proportion of classmates from Free States significantly increased the likelihood that cadets from Slave States joined the Union Army. Second, the peer effect varies with geography, most notably with the slave population share in cadets' home states or counties, and with cadets' own slave ownership in 1860. Third, peer effects were amplified by shared experiences such as having served together in the Mexican-American War, continuous military service, and belonging to the same cohort, suggesting that sustained interaction is important. △ Less

Submitted 16 April, 2026; v1 submitted 12 July, 2025; originally announced July 2025.

Spatial and Temporal Evaluations of the Liquid Argon Purity in ProtoDUNE-SP

Authors: DUNE Collaboration, S. Abbaslu, 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, M. Andreotti , et al. (1301 additional authors not shown)

Abstract: Liquid argon time projection chambers (LArTPCs) rely on highly pure argon to ensure that ionization electrons produced by charged particles reach readout arrays. ProtoDUNE Single-Phase (ProtoDUNE-SP) was an approximately 700-ton liquid argon detector intended to prototype the Deep Underground Neutrino Experiment (DUNE) Far Detector Horizontal Drift module. It contains two drift volumes bisected by… ▽ More Liquid argon time projection chambers (LArTPCs) rely on highly pure argon to ensure that ionization electrons produced by charged particles reach readout arrays. ProtoDUNE Single-Phase (ProtoDUNE-SP) was an approximately 700-ton liquid argon detector intended to prototype the Deep Underground Neutrino Experiment (DUNE) Far Detector Horizontal Drift module. It contains two drift volumes bisected by the cathode plane assembly, which is biased to create an almost uniform electric field in both volumes. The DUNE Far Detector modules must have robust cryogenic systems capable of filtering argon and supplying the TPC with clean liquid. This paper will explore comparisons of the argon purity measured by the purity monitors with those measured using muons in the TPC from October 2018 to November 2018. A new method is introduced to measure the liquid argon purity in the TPC using muons crossing both drift volumes of ProtoDUNE-SP. For extended periods on the timescale of weeks, the drift electron lifetime was measured to be above 30 ms using both systems. A particular focus will be placed on the measured purity of argon as a function of position in the detector. △ Less

Submitted 27 August, 2025; v1 submitted 11 July, 2025; originally announced July 2025.

Report number: CERN-EP-2025-157, FERMILAB-PUB-25-0445-V

Journal ref: JINST (2025) 20 P09008

Interactions across multiple games: cooperation, corruption, and organizational design

Authors: Jonathan Bendor, Lukas Bolte, Nicole Immorlica, Matthew O. Jackson

Abstract: Teamwork is vital in many settings, and it is socially beneficial for teams to cooperate in some situations (``good games'') and not in others (``bad games;'' e.g., those that allow for corruption). A team's cooperation in any given game depends on expectations of cooperation in future iterations of both good and bad games. We identify when sustaining cooperation on good games necessitates coopera… ▽ More Teamwork is vital in many settings, and it is socially beneficial for teams to cooperate in some situations (``good games'') and not in others (``bad games;'' e.g., those that allow for corruption). A team's cooperation in any given game depends on expectations of cooperation in future iterations of both good and bad games. We identify when sustaining cooperation on good games necessitates cooperation on bad games. We then characterize how a designer should optimally assign workers to teams and teams to tasks that involve varying arrival rates of good and bad games. Our results show how organizational design can be used to promote cooperation while minimizing corruption. △ Less

Submitted 15 February, 2026; v1 submitted 2 July, 2025; originally announced July 2025.

RWESummary: A Framework and Test for Choosing Large Language Models to Summarize Real-World Evidence (RWE) Studies

Authors: Arjun Mukerji, Michael L. Jackson, Jason Jones, Neil Sanghavi

Abstract: Large Language Models (LLMs) have been extensively evaluated for general summarization tasks as well as medical research assistance, but they have not been specifically evaluated for the task of summarizing real-world evidence (RWE) from structured output of RWE studies. We introduce RWESummary, a proposed addition to the MedHELM framework (Bedi, Cui, Fuentes, Unell et al., 2025) to enable benchma… ▽ More Large Language Models (LLMs) have been extensively evaluated for general summarization tasks as well as medical research assistance, but they have not been specifically evaluated for the task of summarizing real-world evidence (RWE) from structured output of RWE studies. We introduce RWESummary, a proposed addition to the MedHELM framework (Bedi, Cui, Fuentes, Unell et al., 2025) to enable benchmarking of LLMs for this task. RWESummary includes one scenario and three evaluations covering major types of errors observed in summarization of medical research studies and was developed using Atropos Health proprietary data. Additionally, we use RWESummary to compare the performance of different LLMs in our internal RWE summarization tool. At the time of publication, with 13 distinct RWE studies, we found the Gemini 2.5 models performed best overall (both Flash and Pro). We suggest RWESummary as a novel and useful foundation model benchmark for real-world evidence study summarization. △ Less

Submitted 23 June, 2025; originally announced June 2025.

Comments: 24 pages, 2 figures

Optimal Regulation and Investment Incentives in Financial Networks

Authors: Matthew O. Jackson, Agathe Pernoud

Abstract: We examine optimal regulation of financial networks with debt interdependencies between financial firms. We first show that firms often have an incentive to choose excessively risky portfolios and overly correlate their portfolios with those of their counterparties. We then characterize how optimal regulation depends on a firm's financial centrality and its available investment opportunities. In s… ▽ More We examine optimal regulation of financial networks with debt interdependencies between financial firms. We first show that firms often have an incentive to choose excessively risky portfolios and overly correlate their portfolios with those of their counterparties. We then characterize how optimal regulation depends on a firm's financial centrality and its available investment opportunities. In standard core-periphery networks, optimal regulation depends non-monotonically on the correlation of banks' investments, with maximal restrictions for intermediate levels of correlation. Moreover, it can be uniquely optimal to treat banks asymmetrically: restricting the investments of one core bank while allowing an otherwise identical core bank (in all aspects, including network centrality) to invest freely. △ Less

Submitted 5 October, 2025; v1 submitted 19 June, 2025; originally announced June 2025.

Inequality's Economic and Social Roots: the Role of Social Networks and Homophily

Authors: Matthew O. Jackson

Abstract: I discuss economic and social sources of inequality and elaborate on the role of social networks in inequality, economic immobility, and economic inefficiencies. The lens of social networks clarifies how the entanglement of people's information, opportunities, and behaviors with those of their friends and family leads to persistent differences across communities, resulting in inequality in educati… ▽ More I discuss economic and social sources of inequality and elaborate on the role of social networks in inequality, economic immobility, and economic inefficiencies. The lens of social networks clarifies how the entanglement of people's information, opportunities, and behaviors with those of their friends and family leads to persistent differences across communities, resulting in inequality in education, employment, income, health, and wealth. The key role of homophily in separating groups within the network is highlighted. A network perspective's policy implications differ substantially from a narrower economic perspective that ignores social structure. I discuss the importance of ``policy cocktails'' that include aspects that are aimed at both the economic and social forces driving inequality. △ Less

Submitted 15 June, 2025; originally announced June 2025.

Experimenting with Networks

Authors: Arun G. Chandrasekhar, Matthew O. Jackson

Abstract: We provide an overview of methods for designing and implementing experiments (field, lab, hybrid, and natural) when there are networks of interactions between subjects. We provide an overview of methods for designing and implementing experiments (field, lab, hybrid, and natural) when there are networks of interactions between subjects. △ Less

Submitted 12 June, 2025; originally announced June 2025.

Accurate grain boundary plane distributions for textured microstructures from stereological analysis of orthogonal two-dimensional electron backscatter diffraction orientation maps

Authors: Martin Folwarczny, Ao Li, Rushvi Shah, Aaron Chote, Alexandra C. Austin, Yimin Zhu, Gregory S. Rohrer, Michael A. Jackson, Souhardh Kotakadi, Katharina Marquardt

Abstract: We present a method for obtaining qualitatively accurate grain boundary plane distributions (GBPD) for textured microstructures using a stereological calculation applied to two-dimensional electron backscatter diffraction (EBSD) orientation maps. Stereology, applied to 2D EBSD orientation maps, is currently the fastest method of obtaining GBPDs. Existing stereological methods are not directly appl… ▽ More We present a method for obtaining qualitatively accurate grain boundary plane distributions (GBPD) for textured microstructures using a stereological calculation applied to two-dimensional electron backscatter diffraction (EBSD) orientation maps. Stereology, applied to 2D EBSD orientation maps, is currently the fastest method of obtaining GBPDs. Existing stereological methods are not directly applicable to textured microstructures because of the biased viewing perspectives for different grain boundary types supplied from a single planar orientation map. The method presented in this work successfully removes part of this bias by combining data from three orthogonal EBSD orientation maps for stereology. This is shown here to produce qualitatively correct GBPDs for heavily textured synthetic microstructures with hexagonal and tetragonal crystal symmetries. Synthetic microstructures were generated to compare the stereological GBPD to a known ground truth, as the true GBPD could be obtained from a triangular mesh of the full grain boundary network in 3D. The triangle mesh data contained all five macroscopic parameters to fully describe the grain boundary structure. It was observed that our stereological method overestimated the GBPD anisotropy. However, qualitative analysis of the GBPD remains useful. Furthermore, it was found that combining data from three orthogonal sections gives reliable results when sectioning the texture's primary axes. △ Less

Submitted 30 May, 2025; originally announced May 2025.

Be.FM: Open Foundation Models for Human Behavior

Authors: Yutong Xie, Zhuoheng Li, Xiyuan Wang, Yijun Pan, Qijia Liu, Xingzhi Cui, Kuang-Yu Lo, Ruoyi Gao, Xingjian Zhang, Jin Huang, Walter Yuan, Matthew O. Jackson, Qiaozhu Mei

Abstract: Despite their success in numerous fields, the potential of foundation models for modeling and understanding human behavior remains largely unexplored. We introduce Be.FM, one of the first open foundation models designed for human behavior modeling. Built upon open-source large language models and fine-tuned on a diverse range of behavioral data, Be.FM can be used to understand and predict human de… ▽ More Despite their success in numerous fields, the potential of foundation models for modeling and understanding human behavior remains largely unexplored. We introduce Be.FM, one of the first open foundation models designed for human behavior modeling. Built upon open-source large language models and fine-tuned on a diverse range of behavioral data, Be.FM can be used to understand and predict human decision-making. We construct a comprehensive set of benchmark tasks for testing the capabilities of behavioral foundation models. Our results demonstrate that Be.FM can predict behaviors, infer characteristics of individuals and populations, generate insights about contexts, and apply behavioral science knowledge. △ Less

Submitted 29 May, 2025; originally announced May 2025.

An Optimisation Framework for Unsupervised Environment Design

Authors: Nathan Monette, Alistair Letcher, Michael Beukman, Matthew T. Jackson, Alexander Rutherford, Alexander D. Goldie, Jakob N. Foerster

Abstract: For reinforcement learning agents to be deployed in high-risk settings, they must achieve a high level of robustness to unfamiliar scenarios. One method for improving robustness is unsupervised environment design (UED), a suite of methods aiming to maximise an agent's generalisability across configurations of an environment. In this work, we study UED from an optimisation perspective, providing st… ▽ More For reinforcement learning agents to be deployed in high-risk settings, they must achieve a high level of robustness to unfamiliar scenarios. One method for improving robustness is unsupervised environment design (UED), a suite of methods aiming to maximise an agent's generalisability across configurations of an environment. In this work, we study UED from an optimisation perspective, providing stronger theoretical guarantees for practical settings than prior work. Whereas previous methods relied on guarantees if they reach convergence, our framework employs a nonconvex-strongly-concave objective for which we provide a provably convergent algorithm in the zero-sum setting. We empirically verify the efficacy of our method, outperforming prior methods in a number of environments with varying difficulties. △ Less

Submitted 9 July, 2025; v1 submitted 26 May, 2025; originally announced May 2025.

Comments: Reinforcement Learning Conference 2025

Measurement of reactor antineutrino oscillation at SNO+

Authors: SNO+ Collaboration, :, M. Abreu, V. Albanese, A. Allega, R. Alves, M. R. Anderson, S. Andringa, L. Anselmo, J. Antunes, E. Arushanova, S. Asahi, M. Askins, D. M. Asner, D. J. Auty, A. R. Back, S. Back, A. Bacon, T. Baltazar, F. Barão, Z. Barnard, A. Barr, N. Barros, D. Bartlett, R. Bayes , et al. (276 additional authors not shown)

Abstract: The SNO+ collaboration reports its second spectral analysis of reactor antineutrino oscillation using 286 tonne-years of new data. The measured energies of reactor antineutrino candidates were fitted to obtain the second-most precise determination of the neutrino mass-squared difference $Δm^2_{21}$ = ($7.96^{+0.48}_{-0.42}$) $\times$ 10$^{-5}$ eV$^2$. Constraining $Δm^2_{21}$ and $\sin^2θ_{12}$ wi… ▽ More The SNO+ collaboration reports its second spectral analysis of reactor antineutrino oscillation using 286 tonne-years of new data. The measured energies of reactor antineutrino candidates were fitted to obtain the second-most precise determination of the neutrino mass-squared difference $Δm^2_{21}$ = ($7.96^{+0.48}_{-0.42}$) $\times$ 10$^{-5}$ eV$^2$. Constraining $Δm^2_{21}$ and $\sin^2θ_{12}$ with measurements from long-baseline reactor antineutrino and solar neutrino experiments yields $Δm^2_{21}$ = ($7.58^{+0.18}_{-0.17}$) $\times$ 10$^{-5}$ eV$^2$ and $\sin^2θ_{12} = 0.308 \pm 0.013$. This fit also yields a first measurement of the flux of geoneutrinos in the Western Hemisphere, with $73^{+47}_{-43}$ TNU at SNO+. △ Less

Submitted 17 September, 2025; v1 submitted 7 May, 2025; originally announced May 2025.

Journal ref: Phys. Rev. Lett. 135, 121801 (2025)

Online learning to accelerate nonlinear PDE solvers: applied to multiphase porous media flow

Authors: Vinicius L S Silva, Pablo Salinas, Claire E Heaney, Matthew Jackson, Christopher C Pain

Abstract: We propose a novel type of nonlinear solver acceleration for systems of nonlinear partial differential equations (PDEs) that is based on online/adaptive learning. It is applied in the context of multiphase flow in porous media. The proposed method rely on four pillars: (i) dimensionless numbers as input parameters for the machine learning model, (ii) simplified numerical model (two-dimensional) fo… ▽ More We propose a novel type of nonlinear solver acceleration for systems of nonlinear partial differential equations (PDEs) that is based on online/adaptive learning. It is applied in the context of multiphase flow in porous media. The proposed method rely on four pillars: (i) dimensionless numbers as input parameters for the machine learning model, (ii) simplified numerical model (two-dimensional) for the offline training, (iii) dynamic control of a nonlinear solver tuning parameter (numerical relaxation), (iv) and online learning for real-time improvement of the machine learning model. This strategy decreases the number of nonlinear iterations by dynamically modifying a single global parameter, the relaxation factor, and by adaptively learning the attributes of each numerical model on-the-run. Furthermore, this work performs a sensitivity study in the dimensionless parameters (machine learning features), assess the efficacy of various machine learning models, demonstrate a decrease in nonlinear iterations using our method in more intricate, realistic three-dimensional models, and fully couple a machine learning model into an open-source multiphase flow simulator achieving up to 85\% reduction in computational time. △ Less

Submitted 25 April, 2025; originally announced April 2025.

Absorption of Fermionic Dark Matter in the PICO-60 C$_{3}$F$_{8}$ Bubble Chamber

Authors: E. Adams, B. Ali, R. Anderson-Dornan, I. J. Arnquist, M. Bai, D. Baxter, E. Behnke, B. Broerman, C. J. Chen, K. Clark, J. I. Collar, P. S. Cooper, D. Cranshaw, C. Cripe, M. Crisler, C. E. Dahl, M. Das, S. Das, S. Fallows, J. Farine, R. Filgas, A. García-Viltres, G. Giroux, O. Harris, H. Hawley-Herrera , et al. (36 additional authors not shown)

Abstract: Fermionic dark matter absorption on nuclear targets via neutral current interactions is explored using a non-relativistic effective field theory framework. An analysis of data from the PICO-60 C$_{3}$F$_{8}$ bubble chamber sets leading constraints on spin-independent absorption for dark matter masses below 23 MeV/$\textit{c}^2$ and establishes the first limits on spin-dependent absorptive interact… ▽ More Fermionic dark matter absorption on nuclear targets via neutral current interactions is explored using a non-relativistic effective field theory framework. An analysis of data from the PICO-60 C$_{3}$F$_{8}$ bubble chamber sets leading constraints on spin-independent absorption for dark matter masses below 23 MeV/$\textit{c}^2$ and establishes the first limits on spin-dependent absorptive interactions. These results demonstrate the sensitivity of bubble chambers to low-mass dark matter and underscore the importance of absorption searches in expanding the parameter space of direct detection experiments. △ Less

Submitted 24 June, 2025; v1 submitted 17 April, 2025; originally announced April 2025.

A Clean Slate for Offline Reinforcement Learning

Authors: Matthew Thomas Jackson, Uljad Berdica, Jarek Liesen, Shimon Whiteson, Jakob Nicolaus Foerster

Abstract: Progress in offline reinforcement learning (RL) has been impeded by ambiguous problem definitions and entangled algorithmic designs, resulting in inconsistent implementations, insufficient ablations, and unfair evaluations. Although offline RL explicitly avoids environment interaction, prior methods frequently employ extensive, undocumented online evaluation for hyperparameter tuning, complicating… ▽ More Progress in offline reinforcement learning (RL) has been impeded by ambiguous problem definitions and entangled algorithmic designs, resulting in inconsistent implementations, insufficient ablations, and unfair evaluations. Although offline RL explicitly avoids environment interaction, prior methods frequently employ extensive, undocumented online evaluation for hyperparameter tuning, complicating method comparisons. Moreover, existing reference implementations differ significantly in boilerplate code, obscuring their core algorithmic contributions. We address these challenges by first introducing a rigorous taxonomy and a transparent evaluation protocol that explicitly quantifies online tuning budgets. To resolve opaque algorithmic design, we provide clean, minimalistic, single-file implementations of various model-free and model-based offline RL methods, significantly enhancing clarity and achieving substantial speed-ups. Leveraging these streamlined implementations, we propose Unifloral, a unified algorithm that encapsulates diverse prior approaches within a single, comprehensive hyperparameter space, enabling algorithm development in a shared hyperparameter space. Using Unifloral with our rigorous evaluation protocol, we develop two novel algorithms - TD3-AWR (model-free) and MoBRAC (model-based) - which substantially outperform established baselines. Our implementation is publicly available at https://github.com/EmptyJackson/unifloral. △ Less

Submitted 15 April, 2025; originally announced April 2025.