Sabre Kais: Quantum Machine-Learning for Complex Many-Body Systems on Quantum Devices
Abstract : In this talk, I will give a general introduction to quantum algorithms for electronic structure calculations. Then, focus on quantum machine learning, particularly the Restricted Boltzmann Machine (RBM), as it emerged to be a promising alternative approach leveraging the power of quantum computers. The workhorse of our technique is a shallow neural network encoding the desired state of the system with the amplitude computed by sampling the Gibbs−Boltzmann distribution using a quantum circuit and the phase information obtained classically from the nonlinear activation of a separate set of neurons. In Addition to present successful applications for electronic structure of 2D-materials I will discuss the training dynamics by unraveling how quantum information is scrambled through such a network introducing correlation among its constituent sub-systems. Finally, I will discuss possible applications of RBM in the field of open quantum dynamics.
Bio: Sabre Kais is a distinguished professor of chemistry with a courtesy appointments in computer science, physics and electrical and computer engineering at Purdue. The research in his group is mainly devoted to quantum information and quantum computing for complex chemical systems. He is a Fellow of the American Physical Society, Fellow of the American Association for the Advancement of Science, Guggenheim Fellow, Purdue University Faculty Scholar, National Science Foundation Career Award Fellow, 2012 Sigma Xi Research Award, and 2019 Herbert Newby McCoy Award, Purdue university.
“Quantum Machine Learning for Electronic Structure Calculations”
Rongxin Xia and Sabre Kais, Nature Comm. 9, 4195 (2018)
“Quantum Machine-Learning for Eigenstate Filtration in Two-Dimensional Materials”, Manas Sajjan, Shree Hari Sureshbabu and Sabre Kais, JACS 143, 44, 18426 (2021).
“Quantum Machine Learning for Chemistry and Physics”
Manas Sajjan, Junxu Li, Raja Selvarajan, Shree Hari Sureshbabu, Sumit Suresh Kale, Rishabh Gupta, Vinit Singh and Sabre Kais, Chemical Society Reviews, 51, 6475 (2022).
“Imaginary components of out-of-time-order correlator and information scrambling for navigating the learning landscape of a quantum machine learning model”, Manas Sajjan, Vinit Singh, Raja Selvarajan and Sabre Kais, PHYSICAL REVIEW RESEARCH 5, 013146 (2023).
