3 papers
physics.ins-det2026
Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)
Julia Gonski, Jenni Ott, Shiva Abbaszadeh +118
The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environmen…
cs.LG2026
Towards Tensor Network Models for Low-Latency Jet Tagging on FPGAs
Alberto Coppi, Ema Puljak, Lorenzo Borella +6
We present a systematic study of Tensor Network (TN) models $\unicode{x2013}$ Matrix Product States (MPS) and Tree Tensor Networks (TTN) $\unicode{x2013}$ for real-time jet tagging…
hep-ex2024
Ultra-low latency quantum-inspired machine learning predictors implemented on FPGA
Lorenzo Borella, Alberto Coppi, Jacopo Pazzini +4
Tensor Networks (TNs) are a computational paradigm used for representing quantum many-body systems. Recent works have shown how TNs can also be applied to perform Machine Learning…