6 papers
Real-Time Plasma State Prediction via FPGA-Accelerated Quantized Recurrent Probabilistic Neural Networks
Daniel Gaytan-Villarreal, Aiken Xie, Tu Pham +5
Real time plasma state estimation for control of Tokamak devices are challenging due to the stringent latency requirements of the plasma control system (PCS). We present an end-to-…
Probing light axion-like particles in vector boson fusion at CMS with data parking and scouting
Sena Durgut, Mariel Peczak, Gonzalo Alonso-Álvarez +4
Axion-like particles (ALPs) with masses between 10 MeV and 10 GeV and moderately small couplings sit in an experimental blind spot. They decay too fast for intensity-frontier exper…
Real-Time SiPM Pulse Deconvolution for a High-granularity Dual-readout Calorimeter with Neutral Networks
Spencer Allen, Matteo Cremonesi, Jordan Damgov +6
The High-Granularity Dual-Readout Calorimeter (HG-DREAM) designed for FCC-ee aims to achieve unprecedented energy resolution through fine three-dimensional shower imaging, simultan…
Real-Time Detection of Charge Jumps in Superconducting Qubits with a Convolutional Neural Network
Daniel Gaytan-Villarreal, Peter Meiring, Daniel Baxter +6
Ionizing radiation from cosmic rays and gammas can induce discontinuous jumps in the environmental charge of superconducting qubits (charge jumps), causing correlated errors that c…
Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision
Thea Klaeboe Aarrestad, Alaa Abdelhamid, Haider Abidi +457
Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape co…
Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)
Julia Gonski, Jennifer Ott, Jenni Ott +129
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…