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The prevailing paradigm in AI for physical systems (scaling general-purpose foundation models toward universal multimodal reasoning) confronts a fundamental barrier at the control interface. Recent benchmarks show that even frontier…

Artificial Intelligence · Computer Science 2026-05-21 Yoon Pyo Lee , Samrendra Roy , Jay Yoo , Kazuma Kobayashi , Sajedul Talukder , Seid Koric , Souvik Chakraborty , Syed Bahauddin Alam

For decades, physicists have used neutrinos from nuclear reactors to advance basic science. These pursuits have inspired many ideas for application of neutrino detectors in nuclear energy and security. While developments in neutrino…

Artificial intelligence (AI) technologies are increasingly used in modern weapons systems. Notably, these systems have recently been involved in mass killings and destruction at scale. Furthermore, there is currently a strong interest and…

Artificial Intelligence · Computer Science 2026-04-21 Alexandra Volokhova , Alex Hernandez-Garcia

Proceedings of the AAAI Fall Symposium on Artificial Intelligence in Government and Public Sector, Arlington, Virginia, USA, November 7-8, 2019

Artificial Intelligence · Computer Science 2019-12-02 Frank Stein , Alun Preece

Many leading AI researchers expect AI development to exceed the transformative impact of all previous technological revolutions. This belief is based on the idea that AI will be able to automate the process of AI research itself, leading to…

Computers and Society · Computer Science 2026-03-09 Severin Field , Raymond Douglas , David Krueger

Several reports in education have called for transforming physics learning environments by promoting sensemaking of real-world scenarios in light of curricular ideas. Recent advancements in Generative-Artificial Intelligence has garnered…

We present an AI agentic measurement of the thrust distribution in $e^{+}e^{-}$ collisions at $\sqrt{s}=91.2$~GeV using archived ALEPH data. The analysis and all note writing is carried out entirely by AI agents (OpenAI Codex and Anthropic…

High Energy Physics - Experiment · Physics 2026-04-02 Anthony Badea , Yi Chen , Marcello Maggi , Yen-Jie Lee , Electron-Positron Alliance

Recent advances in machine-learning interatomic potentials have enabled the efficient modeling of complex atomistic systems with an accuracy that is comparable to that of conventional quantum mechanics based methods. At the same time, the…

Materials Science · Physics 2021-05-06 April M. Miksch , Tobias Morawietz , Johannes Kästner , Alexander Urban , Nongnuch Artrith

This document was prepared as part of the briefing material for the Workshop of the CERN Council Strategy Group, held in DESY Zeuthen from 2nd to 6th May 2006. It gives an overview of the physics issues and of the technological challenges…

We present an overview of the evolution of ab initio methods for few-nucleon systems with A \ge 4, tracing the progress made that today allows precision calculations for these systems. First a succinct description of the diverse approaches…

Nuclear Theory · Physics 2015-06-04 Winfried Leidemann , Giuseppina Orlandini

This article is a summary of four introductory lectures on ``Neutrino Experiments,'' given at the 2006 TASI summer school. The purposes were to sketch out the present questions in neutrino physics and to discuss the experimental challenges…

High Energy Physics - Experiment · Physics 2007-08-21 J. M. Conrad

This document describes a two-day meeting held for the Principal Investigators (PIs) of NSF CyberTraining grants. The report covers invited talks, panels, and six breakout sessions. The meeting involved over 80 PIs and NSF program managers…

Educational dialogue -- the collaborative exchange of ideas through talk -- is widely recognized as a catalyst for deeper learning and critical thinking in and across contexts. At the same time, artificial intelligence (AI) has rapidly…

Large language model-based AI agents are now able to autonomously execute substantial portions of a high energy physics (HEP) analysis pipeline with minimal expert-curated input. Given access to a HEP dataset, an execution framework, and a…

High Energy Physics - Experiment · Physics 2026-04-02 Eric A. Moreno , Samuel Bright-Thonney , Andrzej Novak , Dolores Garcia , Philip Harris

We describe an approach to learning optimal control policies for a large, linear particle accelerator using deep reinforcement learning coupled with a high-fidelity physics engine. The framework consists of an AI controller that uses deep…

Artificial Intelligence · Computer Science 2020-12-22 Xiaoying Pang , Sunil Thulasidasan , Larry Rybarcyk

A neutrino community workshop was held at Fermilab in Jan 2020, with the aim of developing an implementation plan for a set of common interfaces to Neutrino Event Generators. This white paper summarizes discussions at the workshop and the…

This report summarizes the present status of neutrino non-standard interactions (NSI). After a brief overview, several aspects of NSIs are discussed, including connection to neutrino mass models, model-building and phenomenology of large…

A Collaboration comprising Taiwan and mainland Chinese scientists has been built up since 1996 to pursue a experimental program in neutrino and astro-particle physics in Taiwan. A pilot experiment to be performed at the Nuclear Power…

High Energy Physics - Experiment · Physics 2009-10-31 Henry T. Wong , Jin Li

Computational materials science and chemistry span vast knowledge domains and fractured software ecosystems. Although large language models (LLMs) have demonstrated research capabilities, scaling monolithic agents to manage the rigor and…

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