The variational quantum eigensolver (or VQE), first developed by Peruzzo et al.(2014), has
received significant attention from the research community in recent years. It uses the …

Abstract Machine learning has achieved dramatic success in a broad spectrum of
applications. Its interplay with quantum physics may lead to unprecedented perspectives for …

We describe Qiskit, a software development kit for quantum information science. We discuss
the key design decisions that have shaped its development, and examine the software …

Sentiment and sarcasm detection in social media contribute to assessing social opinion
trends. Over the years, most artificial intelligence (AI) methods have relied on real values to …

Quantum architecture Search (QAS) is a promising direction for optimization and automated
design of quantum circuits towards quantum advantage. Recent techniques in QAS …

With the arrival of the Noisy Intermediate-Scale Quantum (NISQ) era and the fast
development of machine learning, variational quantum algorithms (VQA) including …

As one of the latest fields of interest in both academia and industry, quantum computing has
garnered significant attention. Among various topics in quantum computing, variational …

A bstract We study the spectral properties of two classes of random matrix models: non-
Gaussian RMT with quartic and sextic potentials, and RMT with Gaussian noise. We …

In the current AI era, mobile devices such as smartphones are tasked with executing a
myriad of deep neural networks (DNNs) locally. It presents a complex landscape, as these …

Parameterized Quantum Circuits (PQC) are promising towards quantum advantage on near-
term quantum hardware. However, due to the large quantum noises (errors), the …