Workshop: Probing the Frontiers of Nuclear Physics with AI at the EIC

US/Eastern
CFNS

CFNS

Description

Over the last decade, there have been significant developments in machine learning and artificial intelligence, which are now used frequently in scientific applications. Building on this progress, the focus of this workshop is on the use and future impact of machine learning in nuclear theory and experiments related to the future Electron-Ion Collider (EIC). The EIC is the main effort of the U.S. nuclear physics program where the structure of nucleons/nuclei in terms of quark and gluon degrees of freedom will be explored in great detail. To realize this ambitious program, many challenges in data science and theory remain where AI applications can advance scientific discoveries. Our goal is to bring together machine learning experts and researchers with a focus on hadron and nuclear structure, lattice QCD, nuclear many-body theory, quantum computing, experiment design, and data analysis at collider experiments to discuss recent progress and explore common interests in machine learning tools and applications. The workshop will also focus on connections to AI applications in high-energy physics and heavy-ion collisions at the LHC & RHIC. There are limited slots available for contributed talks. Please contact the organizers with a proposed topic by Friday, September 8th if you would like to attend in person and deliver a talk. The workshop will be primarily in person and limited travel support is available for junior participants.

Specific topics:

  • Inverse problems of physics extractions at the EIC
  • AI for calculations in lattice gauge theory
  • Jet physics and interpretable AI
  • Neural network quantum states and nuclear matter
  • Generative modeling for parton showers and event generators
  • Experimental challenges in nuclear tomography at the EIC

Organizing committee:

Prerit Jaiswal 
Dima Kharzeev (SBU/BNL & local CFNS member) 
James Mulligan (UCB/LBNL) 
Felix Ringer (JLab/ODU) 
Nobuo Sato (JLab) 
Phiala Shanahan (MIT)

This event is part of the CFNS workshop/ad-hoc meeting series. See the CFNS conferences page for other events.

 

 

Registration
Registration
Participants
  • Adrien Florio
  • Anindita Maiti
  • Anja Butter
  • Ankan Banerjee
  • Ankan Banerjee
  • Bartosz Pyszkowski
  • Benjamin Nachman
  • Bishnu Karki
  • Bryce Fore
  • Charles-Joseph Naïm
  • Chenxi Ma
  • Cristiano Fanelli
  • Daniel Hackett
  • Daniel Lersch
  • Debasish Das
  • Denis Boyda
  • Dennis Perepelitsa
  • Dimitrios Athanasakos
  • Ding Chen
  • Dmitri Kharzeev
  • Evgeny Shulga
  • Felix Ringer
  • Fernando Torales Acosta
  • Jack Araz
  • James Mulligan
  • Jaydeep Datta
  • Jin Huang
  • Joseph Karpie
  • Megha Lahiri
  • Natalie Isenberg
  • Nathan Urban
  • Niseem (Magdy) Abdelrahman
  • nobuo sato
  • Parada Hutauruk
  • Peter Devlin
  • Phiala Shanahan
  • Pietro Dall'Olio
  • Prithwish Tribedy
  • Raymond Ehlers
  • shanjin wu
  • Tapasi Ghosh
  • Tianji Cai
  • Vinicius Mikuni
  • Yeonju Go
  • Yihui Ren
  • Yukari Yamauchi
  • Monday, September 25
    • Morning session 1
      Convener: Felix Ringer (JLab/ODU)
      • 1
        Introduction
        Speaker: Felix Ringer (JLab/ODU)
      • 2
        How uncertain your DIS events are? Event-level UQ with Bayesian DL
        Speaker: Cristiano Fanelli (W&M)
      • 3
        Challenges and Progress towards Applying AI/ML methods on Experimental Data
        Speaker: Yihui Ren (BNL)
      • 4
        Machine Learning assisted Lepton-Jet asymmetries at H1 & AI Detector Co-Design for the EIC
        Speaker: Fernando Torales - Acosta (LBNL)
    • 10:30 AM
      coffee break
    • Morning session 2
      Convener: James Mulligan (UC Berkeley)
    • 12:30 PM
      Lunch
    • Afternoon session
      Convener: nobuo sato (Jefferson Lab)
    • 3:30 PM
      coffee break
    • Afternoon session
      Convener: Dimitri Kharzeev (Stonybrook)
      • 10
        Entanglement and thermalization in pair creation
        Speaker: Adrien Florio (BNL)
      • 11
        Multi-differential Jet Substructure Measurement in electron-proton Collisions
        Speaker: Vinicius Mikuni (LBNL)
    • 6:30 PM
      Dinner: Curry Club @ Saghar

      111 West Broadway
      Port Jefferson, NY 11777

  • Tuesday, September 26
    • Morning session 2
      Convener: James Mulligan (UC Berkeley)
      • 12
        Boostin Loop Amplitudes and Event Generation with Precision Networks
        Speaker: Anja Butter (Heidelberg)
      • 13
        Optimal Transport: From Jet Physics to Quark-Gluon Plasma
        Speaker: Tianji Cai (SLAC)
      • 14
        Extracting physics and examining observable sensitivity via Bayesian Inference
        Speaker: Raymond Ehlers (Lawrence Berkeley National Laboratory/UC Berkeley)
    • 10:30 AM
      coffee break
    • Morning session 2
      Convener: nobuo sato (Jefferson Lab)
      • 15
        Accelerated Monte Carlo methods from machine learning
        Speaker: Yukari Yamauchi (University of Washington)
      • 16
        Simulating EIC electron-proton events with diffusion models
        Speaker: Peter Devlin (JLab)
      • 17
        Is IRC safe information all you need for jet classification?
        Speaker: Dimitris Athanasakos (Stony Brook)
    • 12:30 PM
      Lunch
    • Afternoon session
      Convener: Felix Ringer (JLab/ODU)
      • 18
        Reconstructing Parton Structure from Lattice QCD
        Speaker: Joe Karpie (JLab)
      • 19
        Covariant Extension of Generalized Parton Distributions using Artificial Neural Networks
        Speaker: Pietro Dall’Olio (UNAM)
      • 20
        The QuantOM Event-Level Inference Framework
        Speaker: Daniel Lersch (JLab)
    • 4:00 PM
      coffee break