Tech Talks @ Horizon

Compilation by Stochastic Hamiltonian Sparsification

Tech Talks @ Horizon Quantum is our forum for staying up to date with quantum computing developments from across the research community. We host invited speakers, provide the platform, and benefit from exchanging ideas with those who are advancing both the technology and the industry.

In this talk, Dr Yingkai Ouyang, Research Fellow at the National University of Singapore, discusses compilation by stochastic Hamiltonian sparsification (work he completed while at the University of Sheffield). He introduces a stochastic Hamiltonian sparsification method that approximates an actual Hamiltonian with a sparser Hamiltonian containing fewer terms.

Estimated time
40 min 42
Published
July 18, 2021

Tech Talks @ Horizon Quantum

Compilation by stochastic Hamiltonian sparsification


Dr Yingkai Ouyang
Research fellow at the National University of Singapore


Abstract
"In quantum simulation, a complicated Hamiltonian describing the dynamics of a quantum system is decomposed into its constituent terms, where the effect of each term during time-evolution is individually computed. For many physical systems, the Hamiltonian has a large number of terms, constraining the scalability of established simulation methods. To address this limitation we introduce a scheme that approximates the actual Hamiltonian with a sparser Hamiltonian containing fewer terms. By stochastically sparsifying weaker Hamiltonian terms, we benefit from a quadratic suppression of errors relative to deterministic approaches."