Tootfinder

Application Of Large Language Models For The Extraction Of Information From Particle Accelerator Technical Documentation
Qing Dai, Rasmus Ischebeck, Maruisz Sapinski, Adam Grycner
https://arxiv.org/abs/2509.02227

Application Of Large Language Models For The Extraction Of Information From Particle Accelerator Technical Documentation
The large set of technical documentation of legacy accelerator systems, coupled with the retirement of experienced personnel, underscores the urgent need for efficient methods to preserve and transfer specialized knowledge. This paper explores the application of large language models (LLMs), to automate and enhance the extraction of information from particle accelerator technical documents. By exploiting LLMs, we aim to address the challenges of knowledge retention, enabling the retrieval of do…

CP violation in $K\to\mu^ \mu^-$ with and without time dependence through a tagged analysis
Giancarlo D'Ambrosio, Avital Dery, Yuval Grossman, Teppei Kitahara, Radoslav Marchevski, Diego Mart\'inez Santos, Stefan Schacht
https://arxiv.org/abs/2507.13445

CP violation in $K\toμ^+μ^-$ with and without time dependence through a tagged analysis
We point out that using current knowledge of ${\cal B}(K^0_L\toμ^+μ^-)$ and $ {\cal B}(K^0_L\to γγ)$, one can extract short-distance information from the combined measurement of the time-integrated CP asymmetry, $A_{\rm CP}(K^0\toμ^+μ^-)$, and of ${\cal B}(K^0_S\toμ^+μ^-)$. We discuss the interplay between this set of observables, and demonstrate that determining ${\rm sign}[A_{\rm CP}(K^0\toμ^+μ^-)]$ would eliminate the discrete ambiguity in the Standard Model prediction for ${\cal B…

Replaced article(s) found for econ.GN. https://arxiv.org/list/econ.GN/new
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- Public Support for Environmental Regulation: When Ideology Trumps Knowledge
Markus Dertwinkel-Kalt, Max R. P. Grossmann