Sprecher
Beschreibung
The PALLAS project aims to develop an laser-plasma injector (LPI) prototype delivering 150-200 MeV, 10-50 pC, 1 mm.mrad, at 10 Hz with reliability and control performance at the level of conventional RF accelerator. The LPI is driven by the 40 TW laser of the Université Paris-Saclay LaseriX facility. The project is built as accelerator test facility with state of the art accelerator control command system, data acquisition system and open data sharing.
We present the approach and design of the control command and data acquisition system (CCSA) for PALLAS currently in development and deployment for some subsystems. PALLAS is composed by around 100 different network components from ‘simple’ motor to high quality (and therefore high bandwidth) camera. And to qualify this LPI prototype, control command system have to manage this large variety of instrument, with pertinent and consistent data archiving whereas data acquisition system have to handle a consolidated raw data bandwidth of ~10Gbs coming from multiple source with non trivial time coordination.
To reach these goals, the CCSA is based on the open source distributed control system Tango Controls [1] for the accelerator part and ElliOOs [2] system for the laser. The graphical user interfaces are based on webpage thanks to Ada Web Server [3] and the online monitoring of the laser system and accelerator subsystems is based on Grafana [4].
The data collected by CCSA will be described with details on the data timestamping and readiness for application for machine learning will be discussed. The definition of the project's data management plan will be reviewed from an open science perspective [5] for the community.
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[1] Tango controls, https://www.tango-controls.org/
[2] ElliOOs, monitoring and control library based on a distributed multi-client and multi-server architecture used by Amplitude Laser
[3] An Ada-Based Framework to Develop Web-Based Applications, https://www.adacore.com/gnatpro/toolsuite/ada-web-server
[4] Grafana, open source monitoring and analytics platform https://grafana.com/oss/grafana/
[5] CNRS data management plan,link Recommendations for Services in a FAIR data ecosystem 
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