Quantum random sampling is the leading proposal for demonstrating a computational
advantage of quantum computers over classical computers. Recently the first large-scale …

In order to characterize and benchmark computational hardware, software, and algorithms, it
is essential to have many problem instances on-hand. This is no less true for quantum …

Although molecular vibronic spectra generation is pivotal for chemical analysis, tackling
such exponentially complex tasks on classical computers remains inefficient. Quantum …

Spectroscopy is one of the most accurate probes of the molecular world. However,
predicting molecular spectra accurately is computationally difficult because of the presence …

Plausible claims for quantum advantage have been made using sampling problems such as
random circuit sampling in superconducting qubit devices, and Gaussian boson sampling in …

Computations of chemical systems' equilibrium properties and non-equilibrium dynamics
have been suspected of being a" killer app" for quantum computers. This review highlights …

We present a quantum-inspired classical algorithm that can be used for graph-theoretical
problems, such as finding the densest k subgraph and finding the maximum weight clique …

Transition amplitudes and transition probabilities are relevant to many areas of physics
simulation, including the calculation of response properties and correlation functions. These …

An accurate description of electron transport at a molecular level requires a precise
treatment of quantum effects. These effects play a crucial role in determining the electron …

Spectroscopy is an indispensable tool for understanding the structures and dynamics of
molecular systems. However, computational modeling of spectroscopy is challenging due to …