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AI and Quantum Information for Particle Physics

14–17 Nov 2023
Asia/Seoul timezone

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Contribution List

31 out of 31 displayed
  1. 2. Welcome
    Minho SON (KAIST)
    14/11/2023, 10:00
  2. 3. Entanglement Theory
    Dr Joonwoo Bae (KAIST)
    14/11/2023, 10:10

    Entanglement, that is, quantum correlations that do not have a classical counterpart, is a resource for quantum information processing. I provide an overview on the entanglement theory by focusing on the structure of entangled states. I also discuss the experimental verification of entangled states given assumptions made on sources and measurements.

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  3. 4. Quantum Position Verification and Time-Constrained Nonlocal Computation
    Dr Eric Chitambar (UIUC)
    14/11/2023, 11:30

    Quantum position verification (QPV) is a cryptographic task in which the spatial location of an untrusted agent is certified using the principles of quantum mechanics and special relativity. The problem of QPV has deep connections to computational complexity and the AdS/CFT correspondence. In this talk I will introduce the general task of QPV and review some results. I will then turn to...

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  4. 11. Theory-driven Quantum Machine Learning for HEP
    Dr Jack Y. Araz (Jefferson Lab.)
    14/11/2023, 14:00

    Machine Learning is, in most cases, powerful but a black-box application. In this talk, we will tackle this very problem from a quantum mechanics point of view, arguing that an optimisation problem, such as classification or anomaly detection, can be studied by “rephrasing" the problem as a quantum many-body system or a mixed state. Such an approach allows us to employ the entire arsenal of...

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  5. 12. Digitizaiton and Propagation in quantum computing for lattice gauge theories
    Dr Ying-Ying Li (University of Science and Technology of China)
    14/11/2023, 15:30
  6. 29. Combinatorial optimization using QC for collider physics
    Myeonghun Park (Seoul National University of Science and Technology)
    15/11/2023, 10:00
  7. 6. Expressing non-Abelian gauge-field dynamics in the quantum age
    Dr Jesse R. Stryker (LBNL, Berkeley)
    15/11/2023, 11:30
  8. 9. Constructing Novel Nonparametric Estimators for f-divergences and Its Applications to High-energy Physics
    Dr Yung-Kyun Noh (Hanyang University)
    15/11/2023, 14:00

    Nonparametric methods, such as nearest neighbor and kernel methods, can offer simple and parallelizable algorithms without the need for manual structure tunning. However, these methods may suffer from severe performance degradation due to biases from the high-dimensionality of data. I will introduce recently derived equations for understanding and addressing the high-dimensional bias and...

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  9. 10. Scalar and Grassmann Neural Network Field Theories
    Dr Anindita Maiti (Perimeter Institute)
    15/11/2023, 15:30

    Neural Networks (NN), the backbones of Deep Learning, define field theories through output ensembles at initialization. Certain limits of NN architecture give rise to free field theories via Central Limit Theorem (CLT), whereas other regimes give rise to weakly coupled, and non-perturbative field theories, via small, and large deviations from CLT, respectively. I will present a systematic...

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  10. 7. Towards Building Large HEP Models with Self-Supervised Learning
    Dr Michael A. Kagan (SLAC)
    16/11/2023, 10:00
  11. 8. The Vision of End-to-End ML models in HEP
    Dr Lukas Heinrich (echnical University Munich)
    16/11/2023, 11:30
  12. 27. Why autoencoders fail at anomaly detection and what we can do about it
    Dr Sangwoong Yoon (KIAS-AI)
    16/11/2023, 14:00
  13. 5. Quantum computing for high-energy physics
    Dr Michael Spannowsky (University of Durham)
    16/11/2023, 15:00
  14. 22. Mixture Density Network for Neutrino Reconstruction in Collider Physics
    Dr SeungJin Yang (Kyung Hee University)
    17/11/2023, 10:00
  15. 23. Exploring local and global feature integration in Multi-Model Deep Neural Networks
    Ms Kayoung Ban (Yonsei University)
    17/11/2023, 10:40
  16. 28. Quantum Amplitude Amplification Operators: Quantum Search in the NISQ era
    Hyeokjea Kwon (KAIST)
    17/11/2023, 11:50
  17. 30. TBA
    Minho SON (Korea Advanced Institute of Science and Technology)
    17/11/2023, 14:00
  18. 31. Summary and Future prospective
    Minho SON (Korea Advanced Institute of Science and Technology), Myeonghun Park (Seoul National University of Science and Technology)
    17/11/2023, 15:30
  19. 1. Quantum World
    Myeonghun Park (Seoul National University of Science and Technology)
  20. 13. TBA
  21. 14. TBA
    Dr Minho Son (KAIST)
  22. 15. TBA
    Dr Jong-Wan Lee (CTPU-IBS)
  23. 16. TBA
    Myeonghun Park (Seoul National University of Science and Technology)
  24. 17. TBA
    Dr Lee Jong-Wan (IBS-CTPU)
  25. 18. TBA
    Myeonghun Park (Seoul National University of Science and Technology)
  26. 19. TBA
  27. 20. TBA
    Sangwoon Yoon (KIAS AI)
  28. 21. TBA
    Dr Myeonghun Park (Seoul National University of Science and Technology)
  29. 24. TBA
  30. 25. TBA
  31. 26. TBA
    Minho SON (Korea Advanced Institute of Science and Technology)