Pan Zhang, Computation with Tensor Networks

Описание: Abstract
In this talk, Pan Zhang will present methods and algorithms for solving statistical mechanics problems, combinatorial optimization problems, and quantum circuit simulations, in an integrated framework based on tensor networks.


In statistical mechanics problems, the partition function (i.e. the normalization factor of the Boltzmann distribution) at a finite temperature can be obtained by contracting a tensor network that is converted from the stat. mech. problem. When equipped with the "Tropical" algebra, the tensor network contraction can be used to obtain ground state energy and entropy of the model directly at zero temperature. When the interactions in the stat. mech. model are complex, computing the partition function acts as estimating the amplitude of an end state basis vector of a quantum circuit, thus tensor network contractions can be used to simulate quantum circuits. Pan Zhang will introduce approximate and exact algorithms for contracting tensor networks, and their wide applications, particularly in simulating Google's Sycamore quantum circuits.


About CFCS Quantum Day
CFCS Quantum Day, organized by Center on Frontiers of Computing Studies (CFCS), Peking University, is a one-day seminar focusing on pioneering works on supremacy, quantum simulation, and applications with near-term quantum computing hardware. Given continued uncertainty surrounding the future of COVID-19 and worldwide travel precautions, CFCS Quantum Day was held online on May 12th, 2021.