Digital quantum computers provide a computational framework for solving the Schrödinger
equation for a variety of many‐particle systems. Quantum computing algorithms for the …

Quantum computing is a game-changing technology for global academia, research centers
and industries including computational science, mathematics, finance, pharmaceutical …

Quantum machine learning is expected to be one of the first practical applications of near-
term quantum devices. Pioneer theoretical works suggest that quantum generative …

Implementing a gate-based quantum algorithm on an noisy intermediate scale quantum
(NISQ) device has several challenges that arise from the fact that such devices are noisy …

Variational quantum circuits are becoming tools of choice in quantum optimization and
machine learning. In this paper we investigate a class of variational circuits for the purposes …

The variational quantum eigensolver is one of the most promising approaches for
performing chemistry simulations using noisy intermediate-scale quantum (NISQ) …

The pressure of fundamental limits on classical computation and the promise of exponential
speedups from quantum effects have recently brought quantum circuits to the attention of the …

In quantum computation every unitary operation can be decomposed into quantum circuits—
a series of single-qubit rotations and a single type entangling two-qubit gates, such as …

Adversarial machine learning is an emerging field that focuses on studying vulnerabilities of
machine learning approaches in adversarial settings and developing techniques …

Multiclass classification is of great interest for various applications, for example, it is a
common task in computer vision, where one needs to categorize an image into three or …