Quantum computers are expected to surpass the computational capabilities of classical
computers and have a transformative impact on numerous industry sectors. We present a …

Quantum computing holds substantial potential for applications in biology and medicine,
spanning from the simulation of biomolecules to machine learning methods for subty** …

With the rapid advance of quantum machine learning, several proposals for the quantum-
analogue of convolutional neural network (CNN) have emerged. In this work, we benchmark …

With the rapid development of quantum neural networks (QNN), several quantum
simulations of convolutional neural networks (CNN) have been proposed. Among them …

The quantum state preparation problem aims to prepare an-qubit quantum state from the
initial state, for a given unit vector with. The problem is of fundamental importance in …

Variational quantum circuits have been widely employed in quantum simulation and
quantum machine learning in recent years. However, quantum circuits with random …

The past decade has witnessed significant advancements in quantum hardware,
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …

Nowadays, quantum-enhanced methods have been widely studied to solve machine
learning related problems. This article presents the application of a Variational Quantum …

A crucial subroutine in quantum computing is to load the classical data of N complex
numbers into the amplitude of a superposed n=⌈ log 2 N⌉-qubit state. It has been proven …

Quantum state preparation is a vital routine in many quantum algorithms, including solution
of linear systems of equations, Monte Carlo simulations, quantum sampling, and machine …