6 papers
HepScript: A Dual-Use DSL for Human-AI Collaborative Data Analysis Workflows in High-Energy Physics
Junkun Jiao, Tong Liu, Ke Li +6
The escalating data scale in High-Energy Physics (HEP) fuels a growing aspiration for higher analytical efficiency. While Large Language Models (LLMs) offer a path toward automatio…
Dr.Sai: An agentic AI for real-world physics analysis at BESIII
Mingfeng He, Fayu Jiang, Junkun Jiao +16
High Energy Physics (HEP) experiments like BESIII produce petabyte-scale data. Extracting physics results requires complex workflows (simulation, reconstruction, statistical analys…
AI Agents, Language, Deep Learning and the Next Revolution in Science
Ke Li, Beijiang Liu, Bruce Mellado +2
Modern science is reaching a critical inflection point. Instruments across disciplines, from particle physics and astronomy to genomics and climate modeling, now produce data of su…
DCTracks: An Open Dataset for Machine Learning-Based Drift Chamber Track Reconstruction
Qian Liyan, Zhang Yao, Yuan Ye +11
We introduce a Monte Carlo (MC) dataset of single- and two-track drift chamber events to advance Machine Learning (ML)-based track reconstruction. To enable standardized and compar…
Machine-Learning-Based Method for Goodness-of-Fit Test in Amplitude Analysis
Huoyi Hou, Beijiang Liu
\textbf{Purpose:} Amplitude analysis is a pivotal tool in hadron spectroscopy, fundamentally involving a series of likelihood fits to multi-dimensional experimental distributions.…
Search for in decays
BESIII Collaboration, M. Ablikim, M. N. Achasov +689
Based on a sample of events collected by the BESIII detector operating at the BEPCII collider, an analysis of the decay $Ï(3686)\toγÏ_{cJ}, Ï_{cJ}\…