Quantum machine learning has recently attracted much attention from the community of
quantum computing. In this paper, we explore the ability of generative adversarial networks …

Abstract The Harrow-Hassidim-Lloyd (HHL) algorithm is a method to solve the quantum
linear system of equations that may be found at the core of various scientific applications …

Data compression can be achieved by reducing the dimensionality of high-dimensional but
approximately low-rank datasets, which may in fact be described by the variation of a much …

Quantum machine learning aims to execute machine learning algorithms in quantum
computers by utilizing powerful laws like superposition and entanglement for solving …

Anomaly detection, as an important branch of machine learning, plays a critical role in fraud
detection, health care, intrusion detection, military surveillance, etc. An anomaly detection …

Quantum information science is an interdisciplinary subject spanning physics, mathematics,
and computer science. It involves finding new ways to apply natural quantum-mechanical …

We propose an effective protocol for the implementation of nonadiabatic geometric quantum
gates of cat-state qubits in Kerr-nonlinear resonators driven by two-photon squeezing drives …

A quantum circuit learning approach is studied to carry out the fast-fitting of Gaussian
functions. First, a parameterized structure is designed for quantum circuits based on the …

Anomaly detection, an important branch of machine learning, plays a critical role in fraud
detection, health care, intrusion detection, military surveillance, etc. As one of the most …

Dimensionality reduction algorithms, which reduce the dimensionality of a given data set
whereas preserving the information of the original data set as well as possible, play an …