1 citations · 1 across the 1 of their papers we have counts for
5 papers
Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)
Julia Gonski, Jenni Ott, Shiva Abbaszadeh +117
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…
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…
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…
Potential to identify neutrino mass ordering with reactor antineutrinos at JUNO
JUNO Collaboration, Angel Abusleme, Thomas Adam +622
The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose neutrino experiment under construction in South China. This paper presents an updated estimate of JUNO's sen…
JUNO Sensitivity to Invisible Decay Modes of Neutrons
JUNO Collaboration, Angel Abusleme, Thomas Adam +651
We explore the decay of bound neutrons into invisible particles (e.g., or ) in the JUNO liquid scintillator detector, which do not produce an…