Autoencoders on FPGAs for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider

التفاصيل البيبلوغرافية
العنوان: Autoencoders on FPGAs for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider
المؤلفون: Govorkova, Ekaterina, Puljak, Ema, Aarrestad, Thea, James, Thomas, Loncar, Vladimir, Pierini, Maurizio, Pol, Adrian Alan, Ghielmetti, Nicolò, Graczyk, Maksymilian, Summers, Sioni, Ngadiuba, Jennifer, Nguyen, Thong Q., Duarte, Javier, Wu, Zhenbin
المصدر: Nature Machine Intelligence 4, 154 (2022)
سنة النشر: 2021
المجموعة: High Energy Physics - Experiment
Physics (Other)
مصطلحات موضوعية: Physics - Instrumentation and Detectors, High Energy Physics - Experiment
الوصف: In this paper, we show how to adapt and deploy anomaly detection algorithms based on deep autoencoders, for the unsupervised detection of new physics signatures in the extremely challenging environment of a real-time event selection system at the Large Hadron Collider (LHC). We demonstrate that new physics signatures can be enhanced by three orders of magnitude, while staying within the strict latency and resource constraints of a typical LHC event filtering system. This would allow for collecting datasets potentially enriched with high-purity contributions from new physics processes. Through per-layer, highly parallel implementations of network layers, support for autoencoder-specific losses on FPGAs and latent space based inference, we demonstrate that anomaly detection can be performed in as little as $80\,$ns using less than 3% of the logic resources in the Xilinx Virtex VU9P FPGA. Opening the way to real-life applications of this idea during the next data-taking campaign of the LHC.
نوع الوثيقة: Working Paper
DOI: 10.1038/s42256-022-00441-3
URL الوصول: http://arxiv.org/abs/2108.03986
رقم الأكسشن: edsarx.2108.03986
قاعدة البيانات: arXiv
الوصف
DOI:10.1038/s42256-022-00441-3