Perimeter QuInterships – Symmetric Ansatz for the Kagome HAF

Haiqu Inc. focuses on building a quantum software stack enabling more efficient development and execution of quantum applications on near-term and early fault tolerant quantum computers. Simulations of quantum chemistry and condensed matter models are one of the primary early uses cases for quantum processors (QPUs), with benefits for chemistry and materials science. Important open questions in this domain concern the physics of magnetic systems on geometrically frustrated lattices. A particular example is the Heisenberg antiferromagnet (HAF) on the Kagome lattice. The primary challenge is the difficulty in classical simulations using e.g. exact diagonalization or DMRG methods, when applied to larger systems. The key objective of the project is to demonstrate the utility of quantum computers in simulating such systems, overcoming classical limitations. The intern will work with to study in detail, implement and simulate on simulated noiseless and noisy quantum devices the ground state properties of the HAF model using symmetric quantum machine learning (QML). Haiqu has been developing SU(2) symmetric QML ansaetze and studying their applications to quantum condensed matter problems. Through this project we aim to validate the use of such equivariant QML approaches and chart the path to their applications in materials science.

Faculty Supervisor:

Roger Melko

Student:

Partner:

Haiqu

Discipline:

Physics

Sector:

Professional, scientific and technical services

University:

University of Waterloo

Program: