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 …

A universal fault-tolerant quantum computer that can efficiently solve problems such as
integer factorization and unstructured database search requires millions of qubits with low …

As we begin to reach the limits of classical computing, quantum computing has emerged as
a technology that has captured the imagination of the scientific world. While for many years …

Computational models are an essential tool for the design, characterization, and discovery
of novel materials. Computationally hard tasks in materials science stretch the limits of …

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

Among the many computational challenges faced across different disciplines, quantum-
mechanical systems pose some of the hardest ones and offer a natural playground for the …

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 holds substantial potential for applications in biology and medicine,
spanning from the simulation of biomolecules to machine learning methods for subty** …

Recent advances in quantum computing devices have brought attention to hybrid quantum-
classical algorithms like the variational quantum eigensolver (VQE) as a potential route to …

Many applications of quantum simulation require one to prepare and then characterize
quantum states by efficiently estimating k-body reduced density matrices (k-RDMs), from …