Data Compression in the NEXT-100 Data Acquisition System
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- Polytechnic University of Valencia (UPV) (Spain)
- Ben Gurion University of the Negev, Beer Sheva (Israel); University of Chicago, IL (United States). Enrico Fermi Institute; Donostia International Physics Center (DIPC), San Sebastian (Spain)
- Donostia International Physics Center (DIPC), San Sebastian (Spain)
NEXT collaboration detectors are based on energy measured by an array of photomultipliers (PMT) and topological event filtering based on an array of silicon photomultipliers (SiPMs). The readout of the PMT sensors for low-frequency noise effects and detector safety issues requires a grounded cathode connection that makes the readout AC-couple with variations in the signal baseline. Strict detector requirements of energy resolution better than 1% FWHM require a precise baseline reconstruction that is performed offline for data analysis and detector performance characterization. Baseline variations make it inefficient to apply traditional lossy data compression techniques, such as zero-suppression, that help to minimize data throughput and, therefore, the dead time of the system. However, for the readout of the SiPM sensors with less demanding requirements in terms of accuracy, a traditional zero-suppression is currently applied with a configuration that allows for a compression ratio of around 71%. The third stage in the NEXT detectors program, the NEXT-100 detector, is a 100 kg detector that instruments approximately five times more PMT sensors and twice the number of SiPM sensors than its predecessor, the NEXT-White detector, putting more pressure in the DAQ throughput, expected to be over 900 MB/s with the current configuration, which will worsen the dead time of the acquisition data system. This paper describes the data compression techniques applied to the sensor data in the NEXT-100 detector, which reduces data throughput and minimizes dead time while maintaining the event rate to the level of its predecessor, around 50 Hz.
- Research Organization:
- Argonne National Lab. (ANL), Argonne, IL (United States); Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC); European Research Council (ERC); Innovation Horizon 2020; Severo Ochoa Program; María de Maeztu Program; Generalitat Valenciana of Spain; National Science Foundation (NSF); Portuguese FCT; Robert A Welch Foundation; Ben-Gurion University; Marie Skłodowska-Curie grant
- Contributing Organization:
- NEXT Collaboration
- Grant/Contract Number:
- SC0010813; SC0019054; SC0019223; AC02-06CH11357; AC02-07CH11359; 951281-BOLD; 101039048-GanESS; 957202-HIDDEN; RTI2018-095979; CEX2018-000867-S; MDM-2016-0692; PROMETEO/2021/087; CIDEGENT/2019/049
- OSTI ID:
- 1904473
- Journal Information:
- Sensors, Vol. 22, Issue 14; ISSN 1424-8220
- Publisher:
- MDPI AGCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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