COLLECTION OF PAPERS

AI/ML applications for the EIC

S. Furletov et al 2022 JINST 17 C06009

JINST

Machine learning on FPGA for event selection (link to JINST 17 C06009)

AI4EIC proceeding, Sep 2021

T.S. Humble et al 2022 JINST 17 C03037

JINST

Frontiers in computing for artificial intelligence (link to JINST 17 C03037)

AI4EIC proceeding, Sep 2021

C. Fanelli et al (ECCE consortium) (2022)

physics.ins-det

AI-assisted Optimization of the ECCE Tracking System at the Electron Ion Collider (link to arXiv:2205.09185 [physics.ins-det])

Jefferson Lab Angular Momentum (JAM) (2022)

JHEP

New tool for kinematic regime estimation in semi-inclusive deep-inelastic scattering (link to 2201.12197 [hep-ph])

JHEP 04 (2022) 084 DOI: 10.1007/JHEP04(2022)084

M. Arratia, D. Britzger, O. Long, B. Nachman (2022)

NIM-A

Reconstructing the Kinematics of Deep Inelastic Scattering with Deep Learning (link to arXiv:2110.05505)

NIM-A 1025 (2022) 166164, 10.1016/j.nima.2021.166164

C. Fanelli, A. Mahmood (2022)

physics.ins-det

Artificial Intelligence for Imaging Cherenkov Detectors at the EIC (link to arXiv:2204.08645)

AI4EIC proceeding, Sep 2021

T. Jeske et al., JINST 17 C03043 (2022)

JINST

AI for Experimental Controls at Jefferson Lab, (link to 2022_JINST_17_C03043)

AI4EIC proceeding, Sep 2021

L.-G. Gagnon JINST 17 C02026 (2022)

JINST

Machine learning for track reconstruction at the LHC (link to 2022 JINST 17 C02026)

AI4EIC proceeding, Sep 2021

D. Higinbotham JINST 17 C02018 (2022)

physics.ins-det

EIC Detector Overview (link to 2022 JINST 17 C02018, arXiv:2202.13970)

AI4EIC proceeding, Sep 2021

C. Fanelli arXiv:2203.04530v2 (2022)

physics.ins-det

Design of Detectors at the Electron Ion Collider with Artificial Intelligence (link to arXiv:2203.04530v2)

AI4EIC proceeding, Sep 2021

L. Anderlini arXiv:2110.07925 (2021)

HEP-Ex

Machine Learning for the LHCb Simulation (link to arXiv:2110.07925

AI4EIC proceeding, Sep 2021

T. Britton and B. Nachman JINST 17 C02022 (2022)

JINST

Accelerator and detector control for the EIC with machine learning (link to 2022 JINST 17 C02022)

AI4EIC proceeding, Sep 2021

M. Diefenthaler, A. Farhat, A. Verbytskyi, Y. Xu, arXiv:2108.11638 (2021)

HEP-PH

Deeply Learning Deep Inelastic Scattering Kinematics (link to arXiv:2108.11638v2)

J. Arrington et al., J.Phys.G 48 (2021)7, 075106

HEP-PH, NUCL-TH

Revealing the structure of light pseudoscalar mesons at the electron–ion collider (link to arXiv:2102.11788v1, paper)

E. Cisbani, A. Del Dotto, C. Fanelli, M. Williams, et al, JINST 15.05(2020)

physics.ins-det, cs.LG, hep-ex

AI-optimized detector design for the future Electron-Ion Collider: the dual-radiator RICH case (link to arXiv, paper)

C. Fanelli, J. Pomponi, Mach. Learn.: Sci. Technol. (2020): 015010

physics.DATA-AN

DeepRICH: learning deeply Cherenkov detectors (link to arXiv:1911.11717, paper)

Alanazi, Y. et al, arXiv:2008.03151v1 [hep-ph] JLAB-THY-20-3230 (2020)

HEP-PH, HEP-EX, NUCL-TH

AI-based Monte Carlo event generator for electron-proton scattering, Alanazi, Y. et al., (link to arXiv:2008.03151v1 [hep-ph])

Khalek, R. A., Jacob J. E., and Rojo J. , Eur. Phys. J. C 79.6 (2019) 1-35

HEP-PH, HEP-EX, NUCL-TH

Nuclear Parton Distributions from Lepton-Nucleus Scattering and the Impact of an Electron-Ion Collider (link to arXiv 1904.00018, EPJ C)

In progress (contact: support@eic.ai)

Artificial Intelligence for the Electron Ion Collider

Artificial Intelligence for the Electron Ion Collider

COLLECTION OF PAPERS

AI/ML applications for the EIC

S. Furletov et al 2022 JINST 17 C06009

T.S. Humble et al 2022 JINST 17 C03037

C. Fanelli et al (ECCE consortium) (2022)

Jefferson Lab Angular Momentum (JAM) (2022)

M. Arratia, D. Britzger, O. Long, B. Nachman (2022)

C. Fanelli, A. Mahmood (2022)

T. Jeske et al., JINST 17 C03043 (2022)

L.-G. Gagnon JINST 17 C02026 (2022)

D. Higinbotham JINST 17 C02018 (2022)

C. Fanelli arXiv:2203.04530v2 (2022)

L. Anderlini arXiv:2110.07925 (2021)

T. Britton and B. Nachman JINST 17 C02022 (2022)

M. Diefenthaler, A. Farhat, A. Verbytskyi, Y. Xu, arXiv:2108.11638 (2021)

J. Arrington et al., J.Phys.G 48 (2021)7, 075106

E. Cisbani, A. Del Dotto, C. Fanelli, M. Williams, et al, JINST 15.05(2020)

C. Fanelli, J. Pomponi, Mach. Learn.: Sci. Technol. (2020): 015010

Alanazi, Y. et al, arXiv:2008.03151v1 [hep-ph] JLAB-THY-20-3230 (2020)

Khalek, R. A., Jacob J. E., and Rojo J. , Eur. Phys. J. C 79.6 (2019) 1-35

Artificial Intelligence for the Electron Ion Collider

COLLECTION OF PAPERS

AI/ML applications for the EIC

S. Furletov et al 2022 JINST 17 C06009

T.S. Humble et al 2022 JINST 17 C03037

C. Fanelli et al (ECCE consortium) (2022)

Jefferson Lab Angular Momentum (JAM) (2022)

M. Arratia, D. Britzger, O. Long, B. Nachman (2022)

C. Fanelli, A. Mahmood (2022)

T. Jeske et al., JINST 17 C03043 (2022)

L.-G. Gagnon JINST 17 C02026 (2022)

D. Higinbotham JINST 17 C02018 (2022)

C. Fanelli arXiv:2203.04530v2 (2022)

L. Anderlini arXiv:2110.07925 (2021)

T. Britton and B. Nachman JINST 17 C02022 (2022)

M. Diefenthaler, A. Farhat, A. Verbytskyi, Y. Xu, arXiv:2108.11638 (2021)

J. Arrington et al., J.Phys.G 48 (2021)7, 075106

E. Cisbani, A. Del Dotto, C. Fanelli, M. Williams, et al, JINST 15.05(2020)

C. Fanelli, J. Pomponi, Mach. Learn.: Sci. Technol. (2020): 015010

Alanazi, Y. et al, arXiv:2008.03151v1 [hep-ph] JLAB-THY-20-3230 (2020)

Khalek, R. A., Jacob J. E., and Rojo J. , Eur. Phys. J. C 79.6 (2019) 1-35

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