sPHENIX is a new detector at RHIC.

["Go, Yeonju" <ygo AT bnl.gov>]

Dear all,

 

We are pleased to introduce a new AI paper titled "Variable Neural Compression for Sparse Time Projection Chamber Data." This study focuses on online data compression/size reduction using machine learning, which has promising applications for future streaming data taking. This work is part of a BNL LDRD project in collaboration with computer scientists from the BNL Department of Artificial Intelligence. To demonstrate our AI/ML technique, we used the sPHENIX MDC simulation samples.

 

Yi Huang (BNL staff, computer scientist) will present this work at today’s sPHENIX General Meeting: https://indico.bnl.gov/event/25213/. You can also find the draft of the paper in the indica page [1].

 

We welcome your valuable input by Nov. 4th, 2024 (Mon.) and look forward to fruitful discussions during and after the presentation.

 

Thank you,

Yeonju Go on behalf of the AI analysis team

 

[1] https://indico.bnl.gov/event/25213/contributions/98186/attachments/58120/99826/paperDraft_Variable%20Neural%20Compression%20for%20Sparse%20TPC%20data_2024Oct24.pdf