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 …

During the last ten years, superconducting circuits have passed from being interesting
physical devices to becoming contenders for near-future useful and scalable quantum …

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 …

Quantum computing has recently exhibited great potential in predicting chemical properties
for various applications in drug discovery, material design, and catalyst optimization …

Imaginary-time evolution (ITE) on a quantum computer is a promising formalism for
obtaining the ground state of a quantum system. The probabilistic ITE (PITE) exploits …

Conical intersections (CIs) are pivotal in many photochemical processes. Traditional
quantum chemistry methods, such as the state-average multiconfigurational methods, face …

Simulating response properties of molecules is crucial for interpreting experimental
spectroscopies and accelerating materials design. However, it remains a long-standing …

We propose a quantum inverse algorithm (QInverse) to directly determine general
eigenstates by repeatedly applying the inverse power of a shifted Hamiltonian to an arbitrary …

Quantitative descriptions of strongly correlated materials pose a considerable challenge in
condensed matter physics and chemistry. A promising approach to address this problem is …

In this work, we present a detailed analysis of statistical errors in reduced density matrices
(RDMs) of active space wavefunctions sampled from quantum circuit simulation and the …