`2021-04-12 10:00:00``2021-04-12 11:00:00``Quantum Matter Seminar - Hui Zhai, (Institute for Advanced Study, Tsinghua University) - Machine Learning and Quantum Physics``In this talk, I will first give a brief overview of three different aspects of the connection between machine learning and quantum physics. Then, the central part of this talk will focus on quantum neural networks, and especially, I will discuss how to analyze quantum neural networks from the quantum information scrambling perspective. Quantum information scrambling can be described by quantities such as the out-of-time-ordered correlator, the tripartite information, and the operator size. I will show that both the learning dynamics and the design of network architecture can be understood with the help of these quantities. Link to talk: https://osu.zoom.us/rec/share/DLI5eI1yX2qNoPAs3mZoAa-gW0bIQV2zLf0WPpqBnjRRxxwzYDLWQFjNjA3NrgRN.t9Hab7iGhF_wqnkf``Zoom webinar``OSU ASC Drupal 8``ascwebservices@osu.edu``America/New_York``public`

`2021-04-12 11:00:00``2021-04-12 12:00:00``Quantum Matter Seminar - Hui Zhai, (Institute for Advanced Study, Tsinghua University) - Machine Learning and Quantum Physics``In this talk, I will first give a brief overview of three different aspects of the connection between machine learning and quantum physics. Then, the central part of this talk will focus on quantum neural networks, and especially, I will discuss how to analyze quantum neural networks from the quantum information scrambling perspective. Quantum information scrambling can be described by quantities such as the out-of-time-ordered correlator, the tripartite information, and the operator size. I will show that both the learning dynamics and the design of network architecture can be understood with the help of these quantities. Link to talk: https://osu.zoom.us/rec/share/DLI5eI1yX2qNoPAs3mZoAa-gW0bIQV2zLf0WPpqBnjRRxxwzYDLWQFjNjA3NrgRN.t9Hab7iGhF_wqnkf``Zoom webinar``Department of Physics``physics@osu.edu``America/New_York``public`In this talk, I will first give a brief overview of three different aspects of the connection between machine learning and quantum physics. Then, the central part of this talk will focus on quantum neural networks, and especially, I will discuss how to analyze quantum neural networks from the quantum information scrambling perspective. Quantum information scrambling can be described by quantities such as the out-of-time-ordered correlator, the tripartite information, and the operator size. I will show that both the learning dynamics and the design of network architecture can be understood with the help of these quantities.

Link to talk: https://osu.zoom.us/rec/share/DLI5eI1yX2qNoPAs3mZoAa-gW0bIQV2zLf0WPpqBnjRRxxwzYDLWQFjNjA3NrgRN.t9Hab7iGhF_wqnkf