.png){kind=icon}
.png){kind=icon}
Return
An online data analysis framework for small-scale physics experiments
.png){kind=icon}
OA
AI
DOI：10.1016/j.nima.2025.171269.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
A robust and flexible architecture capable of providing real-time analysis on diagnostic data is of crucial importance to physics experiments. In this paper, we present such an online framework, used in June 2025 as part of the HRMT-68 experiment, performed at the HiRadMat facility at CERN, using the Super Proton Synchrotron (SPS) beam line. HRMT-68 was a fixed-target laboratory astrophysics experiment aiming to identify plasma instabilities generated by a relativistic electron-positron beam during traversal of an argon plasma. This framework was essential for experimental data acquisition and analysis, and can be adapted for a broad range of similar-scale experiments with a variety of experimental diagnostics, even those without a standard direct network communication interface. The developed framework's customizable design enabled us to rapidly observe and extract emergent features from a diverse range of diagnostic data. Simultaneously, its modularity allowed for a quick introduction of new diagnostic devices and the modification of our analysis as features of interest were identified. As a result, we were able to effectively diagnose equipment malfunction, and infer the beam's response to varying bunch duration, beam intensity, and the plasma state without resorting to offline analysis, at which time adjustment or improvement would have been impossible. We present the features of this agile framework, whose codebase we have made publicly available so that it may be adapted for future experiments with minimal modification.
Keywords:
HiRadMat
Super proton synchrotron
Laboratory astrophysics
Accelerator physics
Data collection
Data analysis
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
View more organizations