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 …

We present a self-consistent field (SCF) approach within the adaptive derivative-assembled
problem-tailored ansatz variational quantum eigensolver (ADAPT-VQE) framework for …

Adaptive quantum variational algorithms are particularly promising for simulating strongly
correlated systems on near-term quantum hardware, but they are not yet viable due, in large …

ADAPT-VQE is one of the leading VQE algorithms which circumvents the choice-of-ansatz
conundrum by iteratively growing compact and arbitrarily accurate problem-tailored ans\" …

We formulate and implement the Variational Quantum Eigensolver Self Consistent Field
(VQE-SCF) algorithm in combination with polarizable embedding (PE), thereby extending …

The near-term utility of quantum computers is hindered by hardware constraints in the form
of noise. One path to achieving noise resilience in hybrid quantum algorithms is to decrease …

Physics is living an era of unprecedented cross-fertilization among the different areas of
science. In this perspective review, we discuss the manifold impact that state-of-the-art cold …

Physics is living an era of unprecedented cross-fertilization among the different areas of
science. In this perspective review, we discuss the manifold impact that ultracold-atom …

Quantum chemistry is one of the most promising applications for which quantum computing
is expected to have a significant impact. Despite considerable research in the field of …

Achieving high-precision measurements on near-term quantum devices is critical for
advancing quantum computing applications. In this paper, we explore several practical …