Quantum annealing (QA) is a heuristic quantum optimization algorithm that can be used to
solve combinatorial optimization problems. In recent years, advances in quantum …

One of the most promising suggested applications of quantum computing is solving
classically intractable chemistry problems. This may help to answer unresolved questions …

Quantum simulation of chemical systems is one of the most promising near-term
applications of quantum computers. The variational quantum eigensolver, a leading …

A formal analysis is conducted on the exactness of various forms of unitary coupled cluster
(UCC) theory based on particle-hole excitation and de-excitation operators. Both the …

Designing quantum algorithms for simulating quantum systems has seen enormous
progress, yet few studies have been done to develop quantum algorithms for open quantum …

Considering recent advancements and successes in the development of efficient quantum
algorithms for electronic structure calculations—alongside impressive results using machine …

We explore the potential of D-Wave's quantum annealers for computing some of the basic
components required for quantum simulations of standard model physics. By implementing …

We present a quantum algorithm based on the generalized quantum master equation
(GQME) approach to simulate open quantum system dynamics on noisy intermediate-scale …

Restricted Boltzmann Machine (RBM) is an energy-based, undirected graphical model. It is
commonly used for unsupervised and supervised machine learning. Typically, RBM is …

Image recognition is one of the primary applications of machine learning algorithms.
Nevertheless, machine learning models used in modern image recognition systems consist …