Neural Networks Might Make Computations Easier for Quantum Systems
(Physics.aps) Simulating a quantum system that exchanges energy with the outside world is notoriously hard, but the necessary computations might be easier with the help of neural networks.
International research groups have collaborated to report on the use of neural network tools to tackle one of the most computationally challenging problems in condensed-matter physics—simulating the behavior of an open many-body quantum system [2–5]. This scenario describes a collection of particles—such as the qubits in a quantum computer—that both interact with each other and exchange energy with their environment. For certain open systems, the new work might allow accurate simulations to be performed with less computer power than existing methods.
The international research groups include: Maria Schuld, Xanadu, Toronto, Canada, and Quantum Research Group, University of KwaZulu-Natal, Durban, South Africa.
Ilya Sinayskiy, Quantum Research Group, University of KwaZulu-Natal, Durban, South Africa.
Francesco Petruccione, Quantum Research Group, University of KwaZulu-Natal, Durban, South Africa, and National Institute of Theoretical Physics, Durban, South Africa, and KAIST, Daejeon, Korea