sPHENIX is a new detector at RHIC.

[Anthony Frawley <afrawley AT fsu.edu>]

Hi Cameron,

I suggest a more specific wording of the situation before the ML demonstrator. Maybe something like:

Due to data volume limitations, sPHENIX is capable of recording, in addition to hardware triggered rare events, 10% of the minimum-bias collisions at RHIC. This demonstrator will use machine-learning algorithms on FPGAs to sample the remaining 90% of the minimum bias collisions, determine the event topology and send a decision to the data acquisition system to record events of interest.

Cheers

Tony

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From: sPHENIX-l <sphenix-l-bounces AT lists.bnl.gov> on behalf of Liu, Ming Xiong via sPHENIX-l <sphenix-l AT lists.bnl.gov>
Sent: Monday, November 13, 2023 10:30 AM
To: Cameron Thomas Dean <cameron.dean AT cern.ch>; sPHENIX-HF-Trigger (sPHENIX HF Trigger Discussions) <sPHENIX-HF-Trigger AT cern.ch>; Maxim Potekhin via sPHENIX-l <sphenix-l AT lists.bnl.gov>
Subject: Re: [Sphenix-l] [EXTERNAL] Abstract for AI4EIC

 

Hi Cameron,

Nice abstract. You may also mention at the end that we are applying similar approach to EIC/ePIC for HF and DIS-electron tagging.  

 

Cheers,

Ming

 

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Dr. Ming Xiong Liu P-3, MS H846 Physics Division   Office: 505.667.7125 Mobile: 505.412.7396 Los Alamos National Laboratory

 

 

From: Cameron Dean <cameron.dean AT cern.ch>
Date: Monday, November 13, 2023 at 8:23 AM
To: "sPHENIX-HF-Trigger (sPHENIX HF Trigger Discussions)" <sPHENIX-HF-Trigger AT cern.ch>, sPHENIX-l <sphenix-l AT lists.bnl.gov>
Subject: [EXTERNAL] Abstract for AI4EIC

 

Dear collaborators,

I’ve been invited to give a talk at the next AI4EIC workshop at CUA at the end of November. The title I proposed was:

 

Autonomous selection of physics events: A RHIC demonstrator for EIC physics

 

And the abstract is:

 

With ever-increasing collision rates producing larger data volumes and the search for rarer physics processes, it is becoming apparent that autonomic decision making can play a key role in tagging physics events of interest to specific groups or filtering data streams to manageable levels. A demonstrator for separating events with a heavy flavor decay from background events in proton-proton collisions at the Relativistic Heavy Ion Collider (RHIC) with the sPHENIX detector is presented. Due to data volume limitations, sPHENIX is only capable of recording 10% of the minimum-bias collisions at RHIC. This demonstrator will use machine-learning algorithms on FPGAs to sample the remaining 90% of the collisions, determine the event topology and send a decision to the data acquisition system to record events of interest.

Please let me know if you have any comments or questions.

Cheers,
Cameron