Name: Quantum Computing and Quantum Machine Learning Algorithms for High Energy Physics
Start: 2022-06-01T09:00:00-04:00
End: 2022-06-02T16:00:00-04:00
Location: No location set

Quantum Computing and Quantum Machine Learning Algorithms for High Energy Physics

from Wednesday, 1 June 2022 (09:00) to Thursday, 2 June 2022 (16:00)

Monday, 30 May 2022
Tuesday, 31 May 2022
Wednesday, 1 June 2022
09:00
09:00 - 13:00
Contributions

09:00 Quantum Compiling, Black Holes, and a Quantum LHC - Andrew Sornborger (Los Alamos National Laboratory)

10:00 Quantum Computing: Challenges and Prospects - Simone Severini (University College London and Amazon Web Service)

11:00 Overview of Classical Machine Learning - Benjamin Nachman (Lawrence Berkley National Laboratory) Benjamin Nachman

12:00 Overview of Quantum Machine Learning - Iordanis Kerenidis (QC Ware and CNRS)
13:00 Lunch
Lunch
13:00 - 14:00
14:00
14:00 - 17:00
Contributions

14:00 Quantum Neural Networks and their application to generative learning - Christa Zoufal Francesco Tacchino

14:50 Introduction to Hybrid Quantum-Classical Machine Learning - Yen-Chi Chen
Thursday, 2 June 2022
09:00
09:00 - 11:05
Contributions

09:00 Application of Quantum Machine Learning at the LHC - Shaojun sun (University of Wisconsin)

09:20 Quantum K-Means Algorithm for Signal Processing and Quantum Entanglement in Higgs Boson Decay to Four Leptons - Daniel Qenani (Yale University)

09:40 Implementation and Analysis of Quantum Search Methods for Higgs Boson Reconstruction at the LHC - Anthony Armenakas (Harvard University)

10:00 Matrix Model simulations using Quantum Computing, Deep Learning, and Lattice Monte Carlo - Yuan Feng (UC Berkeley)

10:20 Quantum Anomaly Detection for Collider Physics - Avli Sulaiman (Berkeley Laboratoy)
11:05

11:05 - 12:05

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