Novel (Quantum) Computational Methods for Quantum Field Theories

Novel (Quantum) Computational Methods for Quantum Field Theories I will discuss novel approaches for the task of finding a solution to a quantum field theoretical problem, e.g. tunnelling, in terms of an optimisation problem that can be solved either classically using machine learning methods or through a quantum computational ansatz. The general method we use is a discretisation of the field theory problem into a general Ising model, with the continuous field values being encoded into Ising spin chains. To illustrate the method, and as a simple proof of principle, we have used a quantum annealer to recover the correct profile of various tunnelling solutions. I will discuss this as well as outlining future possibilities. These methods are applicable to many nonperturbative problems. Presented by Michael Spannowsky 04-11-2020