Jul 26 – 30, 2021
US/Eastern timezone

Quantum computing for lattice supersymmetry

Jul 28, 2021, 1:15 PM
Oral presentation Algorithms (including Machine Learning, Quantum Computing, Tensor Networks) Algorithms (including Machine Learning, Quantum Computing, Tensor Networks)


Chris Culver (University of Liverpool)


Quantum computing allows for the study of real-time dynamics of non-perturbative quantum field theories while avoiding the sign problem in conventional lattice approaches. Current and near-future quantum devices are severely limited by noise, making investigations of simple low-dimensional lattice systems ideal testbeds for algorithm development. Considering simple supersymmetric systems, such as supersymmetric quantum mechanics with different superpotentials, allows for the analysis of phenomena like dynamical supersymmetry breaking. I will present ongoing work applying quantum computing techniques to study such theories, targeting real-time dynamics and supersymmetry breaking effects.

Primary author

Chris Culver (University of Liverpool)

Presentation materials