Unsupervised Quantum Gate Control for Gate-Model Quantum Computers

Abstract

In near-term quantum computers, the operations are realized by unitary quantum gates. The precise and stable working mechanism of quantum gates is essential for the implementation of any complex quantum computations. Here, we define a method for the unsupervised control of quantum gates in near-term quantum computers. We model a scenario in which a tensor product structure of non-stable quantum gates is not controllable in terms of control theory. We prove that the non-stable quantum gate becomes controllable via a machine learning method if the quantum gates formulate an entangled gate structure.

Personalized Extractive Summarization Using an Ising Machine Towards Real-time Generation of Efficient and Coherent Dialogue Scenarios

“…Quantum computing technologies are categorized into two types: quantum gate computers (Arute et al, 2019;Gyongyosi, 2020) and Ising machines. Quantum gate computers are for universal computing, whereas Ising machines specialize in searching for solutions of combinatorial optimization problems.…”

Objective function estimation for solving optimization problems in gate-model quantum computers

“…A method for the evaluation of objective function connectivity in gate-model quantum computers has been proposed in 33 . An unsupervised machine learning method for quantum gate control in gate-model quantum computers has been defined in 34 . In 35 , a framework has been defined for the circuit depth reduction of gate-model quantum computers.…”

A Novel Modulation Scheme for Homodyne Detection Control

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