Data Compression in the NEXT-100 Data Acquisition System

Authors:
Open Access
Publisher website
Google Scholar
Abstract
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.
Funding Information
  • European Research Council (951281-BOLD, 101039048-GanESS, 957202-HIDDEN, RTI2018-095979, MDM-2016-0692, PROMETEO/2021/087, CIDEGENT/2019/049, UID/FIS/04559/2020, 877040, 877041, DE-AC02-06CH11357, DE-AC02-07CH11359, DE-FG02-13ER42020, DE-SC0019054, DE-SC0019223, NSF CHE 2004111, Y-2031-20200401, 101026628)
  • European Union’s Framework Program for Research and Innovation Horizon 2020 (951281-BOLD, 101039048-GanESS, 957202-HIDDEN, RTI2018-095979, MDM-2016-0692, PROMETEO/2021/087, CIDEGENT/2019/049, UID/FIS/04559/2020, 877040, 877041, DE-AC02-06CH11357, DE-AC02-07CH11359, DE-FG02-13ER42020, DE-SC0019054, DE-SC0019223, NSF CHE 2004111, Y-2031-20200401, 101026628)
  • MCIN/AEI/10.13039/501100011033 of Spain and ERDF A way of making Europe (951281-BOLD, 101039048-GanESS, 957202-HIDDEN, RTI2018-095979, MDM-2016-0692, PROMETEO/2021/087, CIDEGENT/2019/049, UID/FIS/04559/2020, 877040, 877041, DE-AC02-06CH11357, DE-AC02-07CH11359, DE-FG02-13ER42020, DE-SC0019054, DE-SC0019223, NSF CHE 2004111, Y-2031-20200401, 101026628)
  • Severo Ochoa Program grant CEX2018-000867-S and the María de Maeztu Program (951281-BOLD, 101039048-GanESS, 957202-HIDDEN, RTI2018-095979, MDM-2016-0692, PROMETEO/2021/087, CIDEGENT/2019/049, UID/FIS/04559/2020, 877040, 877041, DE-AC02-06CH11357, DE-AC02-07CH11359, DE-FG02-13ER42020, DE-SC0019054, DE-SC0019223, NSF CHE 2004111, Y-2031-20200401, 101026628)
  • Generalitat Valenciana (951281-BOLD, 101039048-GanESS, 957202-HIDDEN, RTI2018-095979, MDM-2016-0692, PROMETEO/2021/087, CIDEGENT/2019/049, UID/FIS/04559/2020, 877040, 877041, DE-AC02-06CH11357, DE-AC02-07CH11359, DE-FG02-13ER42020, DE-SC0019054, DE-SC0019223, NSF CHE 2004111, Y-2031-20200401, 101026628)
  • Portuguese FCT (951281-BOLD, 101039048-GanESS, 957202-HIDDEN, RTI2018-095979, MDM-2016-0692, PROMETEO/2021/087, CIDEGENT/2019/049, UID/FIS/04559/2020, 877040, 877041, DE-AC02-06CH11357, DE-AC02-07CH11359, DE-FG02-13ER42020, DE-SC0019054, DE-SC0019223, NSF CHE 2004111, Y-2031-20200401, 101026628)
  • Pazy Foundation (Israel) (951281-BOLD, 101039048-GanESS, 957202-HIDDEN, RTI2018-095979, MDM-2016-0692, PROMETEO/2021/087, CIDEGENT/2019/049, UID/FIS/04559/2020, 877040, 877041, DE-AC02-06CH11357, DE-AC02-07CH11359, DE-FG02-13ER42020, DE-SC0019054, DE-SC0019223, NSF CHE 2004111, Y-2031-20200401, 101026628)
  • US Department of Energy (951281-BOLD, 101039048-GanESS, 957202-HIDDEN, RTI2018-095979, MDM-2016-0692, PROMETEO/2021/087, CIDEGENT/2019/049, UID/FIS/04559/2020, 877040, 877041, DE-AC02-06CH11357, DE-AC02-07CH11359, DE-FG02-13ER42020, DE-SC0019054, DE-SC0019223, NSF CHE 2004111, Y-2031-20200401, 101026628)
  • US National Science Foundation (951281-BOLD, 101039048-GanESS, 957202-HIDDEN, RTI2018-095979, MDM-2016-0692, PROMETEO/2021/087, CIDEGENT/2019/049, UID/FIS/04559/2020, 877040, 877041, DE-AC02-06CH11357, DE-AC02-07CH11359, DE-FG02-13ER42020, DE-SC0019054, DE-SC0019223, NSF CHE 2004111, Y-2031-20200401, 101026628)
  • Robert A Welch Foundation (951281-BOLD, 101039048-GanESS, 957202-HIDDEN, RTI2018-095979, MDM-2016-0692, PROMETEO/2021/087, CIDEGENT/2019/049, UID/FIS/04559/2020, 877040, 877041, DE-AC02-06CH11357, DE-AC02-07CH11359, DE-FG02-13ER42020, DE-SC0019054, DE-SC0019223, NSF CHE 2004111, Y-2031-20200401, 101026628)
  • Marie Skłodowska-Curie (951281-BOLD, 101039048-GanESS, 957202-HIDDEN, RTI2018-095979, MDM-2016-0692, PROMETEO/2021/087, CIDEGENT/2019/049, UID/FIS/04559/2020, 877040, 877041, DE-AC02-06CH11357, DE-AC02-07CH11359, DE-FG02-13ER42020, DE-SC0019054, DE-SC0019223, NSF CHE 2004111, Y-2031-20200401, 101026628)

This publication has 23 references indexed in Scilit: