Name: AI and Quantum Information for Particle Physics
Start: 2023-11-14T09:00:00+09:00
End: 2023-11-17T21:50:00+09:00
Location: No location set

AI and Quantum Information for Particle Physics

from Tuesday, 14 November 2023 (09:00) to Friday, 17 November 2023 (21:50)

Monday, 13 November 2023
Tuesday, 14 November 2023
10:00
10:00 - 12:30
Contributions

10:00 Welcome - Minho SON (KAIST)

10:10 Entanglement Theory - Joonwoo Bae (KAIST)

11:30 Quantum Position Verification and Time-Constrained Nonlocal Computation - Eric Chitambar (UIUC)
12:30 Lunch
Lunch
12:30 - 14:00
14:00
14:00 - 17:30
Contributions

14:00 Theory-driven Quantum Machine Learning for HEP - Jack Y. Araz (Jefferson Lab.)

15:30 Digitizaiton and Propagation in quantum computing for lattice gauge theories - Ying-Ying Li (University of Science and Technology of China)
Wednesday, 15 November 2023
10:00
10:00 - 12:30
Contributions

10:00 Combinatorial optimization using QC for collider physics - Myeonghun Park (Seoul National University of Science and Technology)

11:30 Expressing non-Abelian gauge-field dynamics in the quantum age - Jesse R. Stryker (LBNL, Berkeley)
12:30 Lunch
Lunch
12:30 - 14:00
14:00
14:00 - 16:30
Contributions

14:00 Constructing Novel Nonparametric Estimators for f-divergences and Its Applications to High-energy Physics - Yung-Kyun Noh (Hanyang University)

15:30 Scalar and Grassmann Neural Network Field Theories - Anindita Maiti (Perimeter Institute)
18:30 Workshop dinner
Workshop dinner
18:30 - 21:00
Thursday, 16 November 2023
10:00
10:00 - 12:30
Contributions

10:00 Towards Building Large HEP Models with Self-Supervised Learning - Michael A. Kagan (SLAC)

11:30 The Vision of End-to-End ML models in HEP - Lukas Heinrich (echnical University Munich)
12:30 Lunch
Lunch
12:30 - 14:00
14:00
14:00 - 15:00
Contributions

14:00 Why autoencoders fail at anomaly detection and what we can do about it - Sangwoong Yoon (KIAS-AI)
15:00
15:00 - 17:30
Contributions

15:00 Quantum computing for high-energy physics - Michael Spannowsky (University of Durham)
Friday, 17 November 2023
10:00
10:00 - 11:50
Contributions

10:00 Mixture Density Network for Neutrino Reconstruction in Collider Physics - SeungJin Yang (Kyung Hee University)

10:40 Exploring local and global feature integration in Multi-Model Deep Neural Networks - Kayoung Ban (Yonsei University)
11:50
11:50 - 12:30
Contributions

11:50 Quantum Amplitude Amplification Operators: Quantum Search in the NISQ era - Hyeokjea Kwon (KAIST)
12:30

12:30 - 14:00
14:00
14:00 - 16:30
Contributions

14:00 TBA - Minho SON (Korea Advanced Institute of Science and Technology)

15:30 Summary and Future prospective - Minho SON (Korea Advanced Institute of Science and Technology) Myeonghun Park (Seoul National University of Science and Technology)
16:30 Break
Break
16:30 - 17:00

17:00

17:00 - 18:00