====== IF4: Trigger and DAQ ======
Co-Conveners:
^Name ^Institution ^email |
|Darin Acosta|University of Florida|dea6[at]rice.edu|
|Allison Deiana|Southern Methodist University|adeiana[at]mail.smu.edu|
|Wes Ketchum|Fermi National Accelerator Laboratory|wketchum[at]fnal.gov|

=====Communication =====
Please sign-up for our email list: SNOWMASS-IF-04-TDAQ[at]FNAL.GOV

Please join our slack channel at snowmass2021.slack.com, #if04-tdaq 

===== Upcoming TDAQ events=====
  * 9 Nov 2021 -- White paper organization workshop: https://indico.fnal.gov/event/51566/

===== Previous TDAQ/IF events=====
  * TDAQ virtual workshop (Aug 6, 2020): https://indico.fnal.gov/event/44741/
  * First TDAQ community virtual meeting: https://indico.fnal.gov/event/44402/
  * Instrumentation Frontier Kick-off Workshop (June 19, 2020): https://indico.fnal.gov/event/43730/

===== Description=====

Trigger and Data Acquisition (TDAQ) systems are responsible for collecting data at the very front-end of detectors, reducing the volume of data through use of selection algorithms and summarizing data into high-level quantities, and storing the data for later transfer and processing. The next generation of physics detectors will encounter many new challenges, including requirements to handle an enormous throughput of data, have high reliability and uptime in extreme environments, and accommodate fast timing and precise synchronization.

We invite Letters Of Interest and White Papers to outline developments in the area of TDAQ across the science frontiers of high-energy particle physics. In particular, we welcome contributions that touch on the following areas:
  * High-speed data links and transfers, including radiation-hard and low-power links
  *  Real-time processing hardware, like low-power hardware capable of working in extreme environments like high radiation or cryogenic temperatures, and real-time hardware capable of real-time feature extraction, including fast inference for machine-learning algorithms
  * Online processing and high-level trigger and reconstruction algorithms, including use of heterogeneous computing in commodity hardware for both triggered and 'streaming' DAQ systems
  * Autonomous operation, control, and calibration of detector systems, including fast anomaly detection and fault recovery
  * Precise timing synchronization, for both improved triggering and event reconstruction and for distribution across large areas


===== Handy references/links =====
(Please let us know if you have suggestions to add!)
  * M/S pledge to end problematic and unnecessary language in technology: https://sites.google.com/view/mspledge
  * European Strategy Physics Book (see Secs. 11.1 and 11.2): https://cds.cern.ch/record/2691414/files/Briefing_Book_Final.pdf
  * CPAD 2018 Report (see Secs. 4.7, 4.10.5-7): https://arxiv.org/pdf/1908.00194.pdf
  * 2017 CPAD DAQ Workshop: https://indico.fnal.gov/event/14744/
  * TDAQ Community Meeting for DOE Basic Research Needs (2019): https://agenda.hep.wisc.edu/event/1430/
  * Presentation to HEPAP on BRN: https://science.osti.gov/-/media/hep/hepap/pdf/202007/11-Fleming_Shipsey-Basic_Research_Needs_Study_on_HEP_Detector_Research_and_Development.pdf?la=en&hash=1D6CE7C7AEFCE124E6AA3A6914332B3F4D78A525

===== Submitted LOI =====
Here is the list of submitted LOIs to this topical group.   First index before "/"  corresponds to the primary frontier used for the submission.
 {{url>https://www.snowmass21.org/docs/files/list.php?frontier=IF4  noborder 95%,600px}}