Search Results for author: Cristiano Fanelli

Found 8 papers, 1 papers with code

Physics Event Classification Using Large Language Models

1 code implementation5 Apr 2024 Cristiano Fanelli, James Giroux, Patrick Moran, Hemalata Nayak, Karthik Suresh, Eric Walter

The 2023 AI4EIC hackathon was the culmination of the third annual AI4EIC workshop at The Catholic University of America.

Chatbot Classification +2

Towards a RAG-based Summarization Agent for the Electron-Ion Collider

no code implementations23 Mar 2024 Karthik Suresh, Neeltje Kackar, Luke Schleck, Cristiano Fanelli

The complexity and sheer volume of information encompassing documents, papers, data, and other resources from large-scale experiments demand significant time and effort to navigate, making the task of accessing and utilizing these varied forms of information daunting, particularly for new collaborators and early-career scientists.

Language Modelling Large Language Model +1

ELUQuant: Event-Level Uncertainty Quantification in Deep Inelastic Scattering

no code implementations4 Oct 2023 Cristiano Fanelli, James Giroux

We introduce a physics-informed Bayesian Neural Network (BNN) with flow approximated posteriors using multiplicative normalizing flows (MNF) for detailed uncertainty quantification (UQ) at the physics event-level.

Anomaly Detection Decision Making +1

Design of Detectors at the Electron Ion Collider with Artificial Intelligence

no code implementations9 Mar 2022 Cristiano Fanelli

Artificial Intelligence (AI) for design is a relatively new but active area of research across many disciplines.

Machine Learning for Imaging Cherenkov Detectors

no code implementations9 Jun 2020 Cristiano Fanelli

Imaging Cherenkov detectors are largely used in modern nuclear and particle physics experiments where cutting-edge solutions are needed to face always more growing computing demands.

BIG-bench Machine Learning

DeepRICH: Learning Deeply Cherenkov Detectors

no code implementations26 Nov 2019 Cristiano Fanelli, Jary Pomponi

Imaging Cherenkov detectors are largely used for particle identification (PID) in nuclear and particle physics experiments, where developing fast reconstruction algorithms is becoming of paramount importance to allow for near real time calibration and data quality control, as well as to speed up offline analysis of large amount of data.

Double Polarization Observables in Pentaquark Photoproduction

no code implementations22 Jul 2019 JPAC Collaboration, Daniel Winney, Cristiano Fanelli, Alessandro Pilloni, Astrid N. Hiller Blin, Cesar Fernandez-Ramirez, Miguel Albaladejo, Vincent Mathieu, Victor I. Mokeev, Adam P. Szczepaniak

We investigate the properties of the hidden charm pentaquark-like resonances first observed by LHCb in 2015, by measuring the polarization transfer KLL between the incident photon and the outgoing proton in the exclusive photoproduction of J/psi near threshold.

High Energy Physics - Phenomenology High Energy Physics - Experiment Nuclear Experiment

Cannot find the paper you are looking for? You can Submit a new open access paper.