For quantum computers to successfully solve real-world problems, it is necessary to tackle
the challenge of noise: the errors that occur in elementary physical components due to …

This Perspective focuses on the several overlaps between quantum algorithms and Monte
Carlo methods in the domains of physics and chemistry. We will analyze the challenges and …

Variational quantum eigensolvers (VQE) are among the most promising approaches for
solving electronic structure problems on near-term quantum computers. A critical challenge …

Classical shadows enable us to learn many properties of a quantum state ρ with very few
measurements. However, near-term and early fault-tolerant quantum computers will only be …

The utility of quantum computers for simulating lattice gauge theories is currently limited by
the noisiness of the physical hardware. Various quantum error mitigation strategies exist to …

Estimating expectation values is a key subroutine in quantum algorithms. Near-term
implementations face two major challenges: a limited number of samples required to learn a …

Quantum computing, with its superior computational capabilities compared to classical
approaches, holds the potential to revolutionize numerous scientific domains, including …

Determining the ground and excited state properties of materials is considered one of the
most promising applications of quantum computers. On near-term hardware, the limiting …

We propose to use wave function overlaps obtained from a quantum computer as inputs for
the classical split-amplitude techniques, tailored and externally corrected coupled cluster, to …

A balanced description of both static and dynamic correlations in electronic systems with
nearly degenerate low-lying states presents a challenge for multiconfigurational methods on …