Streaming readout for next generation electron scattering experiments
Sezione di Roma, Istituto Nazionale di Fisica Nucleare, 00185, Roma, Italy
2 Thomas Jefferson National Accelerator Facility, Newport News, 23606, Virginia, USA
3 Sezione di Genova, Istituto Nazionale di Fisica Nucleare, 16146, Genova, Italy
4 Catholic University of America, 20064, Washington, DC, USA
5 Istituto Nazionale di Fisica Nucleare, CNAF, 40127, Bologna, Italy
6 Sezione di Bologna, Istituto Nazionale di Fisica Nucleare, 40127, Bologna, Italy
7 Massachusetts Institute of Technology, 02139-4307, Cambridge, MA, USA
8 The NSF AI Institute for Artificial Intelligence and Fundamental Interactions, 02139-4307, Cambridge, MA, USA
9 Dipartimento di Scienze Matematiche e Informatiche, Scienze Fisiche e Scienze della Terra, Università degli Studi di Messina, 98166, Messina, Italy
10 Sezione di Catania, Istituto Nazionale di Fisica Nucleare, 95123, Catania, Italy
11 Sezione di Ferrara, Istituto Nazionale di Fisica Nucleare, 44122, Ferrara, Italy
Accepted: 4 August 2022
Published online: 24 August 2022
Current and future experiments at the high-intensity frontier are expected to produce an enormous amount of data that needs to be collected and stored for offline analysis. Thanks to the continuous progress in computing and networking technology, it is now possible to replace the standard ‘triggered’ data acquisition systems with a new, simplified and outperforming scheme. ‘Streaming readout’ (SRO) DAQ aims to replace the hardware-based trigger with a much more powerful and flexible software-based one, that considers the whole detector information for efficient real-time data tagging and selection. Considering the crucial role of DAQ in an experiment, validation with on-field tests is required to demonstrate SRO performance. In this paper, we report results of the on-beam validation of the Jefferson Lab SRO framework. We exposed different detectors (PbWO-based electromagnetic calorimeters and a plastic scintillator hodoscope) to the Hall-D electron-positron secondary beam and to the Hall-B production electron beam, with increasingly complex experimental conditions. By comparing the data collected with the SRO system against the traditional DAQ, we demonstrate that the SRO performs as expected. Furthermore, we provide evidence of its superiority in implementing sophisticated AI-supported algorithms for real-time data analysis and reconstruction.
© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2022. Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.