Classical Quantum Monte Carlo (QMC) methods leverage High Performance Computing (HPC) resources to simulate complex quantum many-body systems. Quantum computation has the potential to provide new routes to tackling these problems. Recently, a series of hybrid quantum-classical QMC methods have been proposed. These approaches seek to advance classical QMC by augmenting the classical algorithm with a quantum processing unit.
In this tutorial, we demonstrate a solution to an exemplary quantum many-body problem using distributed heterogeneous classical and quantum compute resources on Amazon Web Services (AWS). To solve the problem, we use cloud-based batch and quantum computing capabilities to run classical and quantum versions of a QMC algorithm in parallel. We then combine outputs of these runs to produce an estimate of the ground state energy of the problem Hamiltonian.
The tutorial introduces QMC and QC basics to the participants and enables them to utilize cloud-native HPC and QC technologies for hybrid workloads. During the tutorial, participants will get free access to temporary AWS accounts and can follow along the guided steps in the QMC workflow. All attendees leave with code examples they can use as a foundation for their own projects.
Targeted Audience
This tutorial is aimed at diverse audiences including students, researchers and engineers in computer science, quantum physics and chemistry, quantum computing, and HPC. Attendees from academia and industry gain practical understanding of QC and QMC, and hands-on experience running hybrid HPC-QC applications using real quantum computers in could-based HPC environments.
