학술논문

Explicit demonstration of initial state construction in artificial neural networks using NetKet and IBM Q experience platform.
Document Type
Article
Source
Quantum Information Processing. Jan2020, Vol. 19 Issue 1, p1-15. 15p.
Subject
*QUANTUM computing
*ARTIFICIAL neural networks
*QUANTUM computers
*BOLTZMANN machine
*QUANTUM states
*QUANTUM gates
Language
ISSN
1570-0755
Abstract
Quantum neural networks have gained significant interest in recent times for the representation of many-body states and classical simulation of quantum computation. Here, we discuss the methods to generate specific initial states in the Restricted Boltzmann Machines analogous to those used as the initial states while performing quantum computation in quantum computers such as IBM Q. We validate our approach by applying the Pauli X gate to the single-qubit and two-qubit initial states using NetKet and compare the results to that obtained by performing the same task in the IBM quantum computer. We find that using this approach, the RBM neural networks can represent desired quantum states with high accuracy. Thus, this method is promising to mimic quantum computation classically in neural networks by using specific initial states. [ABSTRACT FROM AUTHOR]