Jul 26 – 30, 2021
US/Eastern timezone

Quantum Algorithms for Simulating the Lattice Schwinger Model

Jul 26, 2021, 2:15 PM
15m
Oral presentation Algorithms (including Machine Learning, Quantum Computing, Tensor Networks) Algorithms (including Machine Learning, Quantum Computing, Tensor Networks)

Speaker

Alexander Shaw (University of Maryland College Park)

Description

The Schwinger model is a testbed for the study of quantum gauge field theories. We give scalable, explicit digital quantum algorithms to simulate the lattice Schwinger model in both NISQ and fault-tolerant settings. In particular, we analyze low-order Trotter formula simulations of the Schwinger model, using recently derived commutator bounds, and give upper bounds on the resources needed for simulations. We give scalable measurement schemes and algorithms to estimate observables which we cost in both settings by assuming a simple target observable: the mean pair density. Finally, we bound the root-mean-square error in estimating this observable via simulation as a function of the diamond distance between the ideal and actual CNOT channels. This work provides a rigorous analysis of simulating the Schwinger model, while also providing benchmarks against which subsequent simulation algorithms can be tested.

Primary authors

Alexander Shaw (University of Maryland College Park) Jesse Stryker (University of Maryland) Dr Pavel Lougovski (Amazon Braket) Prof. Wiebe Nathan (University of Toronto)

Presentation materials