What Symmetry Buys on Hardware: Compressing an SU(2)-Equivariant Ansatz for the Kagome Heisenberg Antiferromagnet

Working with researchers at the Perimeter Institute, we asked what a quantum circuit's built-in symmetry is actually worth on today's noisy hardware, rather than on paper. Exploiting the rotational symmetry of a frustrated magnet, we cut a trained circuit's most expensive gates by nearly three quarters, turned the symmetry into a free filter against measurement noise, and reached excited states by re-initialising the same circuit. We then ran it on an IBM processor. Pushing demanding condensed-matter problems inside the limits of the machines that exist today is how quantum computers start doing useful science before full fault tolerance arrives. 

Date: 13 September 2026
Journal/conference link and reference: Paper link not yet available.
4th International Workshop on Quantum Machine Learning,  in 2026 IEEE International Conference on Quantum computing and Engineering (QCE’26)