Optimization schemes for unitary tensornetwork circuit
Abstract
An efficient representation of a quantum circuit is of great importance in achieving a quantum advantage on current noisy intermediate scale quantum (NISQ) devices and the classical simulation of quantum manybody systems. The quantum circuits are playing the key ingredient in the performance of variational quantum algorithms and quantum dynamics in problems of physics and chemistry. In this paper, we study the role of the network structure of a quantum circuit in its performance. We discuss the variational optimization of quantum circuit (a unitary tensornetwork circuit) with different network structures. The ansatz is performed based on a generalization of welldeveloped multiscale entanglement renormalization algorithm and also the conjugategradient method with an effective line search. We present the benchmarking calculations for different network structures by studying the Heisenberg model in a strongly disordered magnetic field and a tensornetwork Q R decomposition. Our work can contribute to achieve the most out of NISQ hardware and to classically develop isometric tensor network states.
 Publication:

Physical Review Research
 Pub Date:
 May 2021
 DOI:
 10.1103/PhysRevResearch.3.023148
 arXiv:
 arXiv:2009.02606
 Bibcode:
 2021PhRvR...3b3148H
 Keywords:

 Condensed Matter  Strongly Correlated Electrons;
 Condensed Matter  Statistical Mechanics;
 Quantum Physics
 EPrint:
 9 pages, 6 figures, sample source codes are available at https://github.com/rezah/unitarytensornetworkoperator