Towards scalable quantum chemistry in quantum computers through localized domain ansatze for unitary coupled cluster.

This project will develop a more efficient way to run quantum-computing simulations of molecules, an important step toward faster discovery of new materials and catalysts. Today, many quantum chemistry methods on quantum computers become too expensive as molecules grow, requiring large numbers of circuit operations and measurements. We will adapt a proven “local” strategy from classical quantum chemistry (which focuses computation only on the most important electron interactions) to build smaller, shallower quantum circuits, and we will test mappings that better preserve chemical locality on quantum hardware. The work will be carried out through a research internship, sending a PhD candidate from McMaster University to the University of Augsburg, combining McMaster’s strengths in scalable quantum algorithms and measurement-efficient methods with Augsburg’s expertise in quantum chemistry circuit design and the Tequila quantum software ecosystem. The outcomes from this project include an open-source implementation of our localized method on quantum devices, aiming to use it in the near future to train machine learning models for reducing quantum resource utilization, bringing to Canada highly qualified personnel prepared to develop scalable quantum algorithms, adapt highly specific quantum chemistry workflows, and perform high-impact international research.

Faculty Supervisor:

Rodrigo A. Vargas-Hernández

Student:

Partner:

Universität Augsburg

Discipline:

Physics

Sector:

Quantum Science

University:

McMaster University

Program: