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 …

We present a review of the Unitary Coupled Cluster (UCC) ansatz and related ansätze
which are used to variationally solve the electronic structure problem on quantum …

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 …

The variational quantum eigensolver (VQE) is a method that uses a hybrid quantum-
classical computational approach to find eigenvalues of a Hamiltonian. VQE has been …

Variational quantum algorithms rely on gradient based optimization to iteratively minimize a
cost function evaluated by measuring output (s) of a quantum processor. A barren plateau is …

We propose a tomographic protocol for estimating any k-body reduced density matrix (k-
RDM) of an n-mode fermionic state, a ubiquitous step in near-term quantum algorithms for …

Obtaining precise estimates of quantum observables is a crucial step of variational quantum
algorithms. We consider the problem of estimating expectation values of quantum …

We introduce a multireference selected quantum Krylov (MRSQK) algorithm suitable for
quantum simulation of many-body problems. MRSQK is a low-cost alternative to the …

Molecular simulations with the variational quantum eigensolver (VQE) are a promising
application for emerging noisy intermediate-scale quantum computers. Constructing …