The unprecedented outbreak of the novel coronavirus (COVID-19), during early December
2019 in Wuhan, China, has quickly evolved into a global pandemic, became a matter of …

With the advent of real-world quantum computing, the idea that parametrized quantum
computations can be used as hypothesis families in a quantum-classical machine learning …

Recent advances in quantum computers are demonstrating the ability to solve problems at a
scale beyond brute force classical simulation. As such, a widespread interest in quantum …

Abstract Despite advances in Deep Learning, the Convolutional Neural Networks methods
still manifest limitations in medical applications because datasets are usually restricted in …

Preparing ground states and thermal states is essential for simulating quantum systems on
quantum computers. Despite the hope for practical quantum advantage in quantum …

We report a proof-of-concept demonstration of a quantum order-finding algorithm for
factoring the integer 21. Our demonstration involves the use of a compiled version of the …

We describe algorithms to obtain an approximate classical description of ad-dimensional
quantum state when given access to a unitary (and its inverse) that prepares it. For pure …

This is a set of lecture notes used in a graduate topic class in applied mathematics
called``Quantum Algorithms for Scientific Computation''at the Department of Mathematics …

Heterogeneous catalysis plays a critical role in many industrial processes, including the
production of fuels, chemicals, and pharmaceuticals, and research to improve current …

The Self-Attention Mechanism (SAM) excels at distilling important information from the
interior of data to improve the computational efficiency of models. Nevertheless, many …