Quantum computers can in principle solve certain problems exponentially more quickly than
their classical counterparts. We have not yet reached the advent of useful quantum …

Quantum computing holds substantial potential for applications in biology and medicine,
spanning from the simulation of biomolecules to machine learning methods for subty** …

Motivation. Predicting the native state of a protein has long been considered a gateway
problem for understanding protein folding. Recent advances in structural modeling driven by …

Highlights•Quantum computing and its use for computer-aided product design is discussed
and perspectives for several types of problems are provided.•Hybrid QC methods are likely …

Transcorrelated methods provide an efficient way of partially transferring the description of
electronic correlations from the ground-state wave function directly into the underlying …

We propose digitized-counterdiabatic quantum optimization (DCQO) to achieve polynomial
enhancement over adiabatic quantum optimization for the general Ising spin-glass model …

We develop quantum computational tools to predict the 3D structure of proteins, one of the
most important problems in current biochemical research. We explain how to combine …

Quantum annealing is a promising approach for obtaining good approximate solutions to
difficult optimization problems. Folding a protein sequence into its minimum-energy structure …

The field of quantum computing (QC) is expanding, with efforts being made to apply it to
areas previously covered by classical algorithms and methods. Bioinformatics is one such …

Transcorrelated methods provide an efficient way of partially transferring the description of
electronic correlations from the ground state wavefunction directly into the underlying …