Quantum machine learning for chemistry and physics
133 Citations•2022•
Manas Sajjan, Junxu Li, Raja Selvarajan
A brief overview of the well-known techniques is presented but also their learning strategies using statistical physical insight to empower and promote cross-pollination among future research in all areas of chemistry which can benefit from ML and in turn can potentially accelerate the growth of such algorithms.
Abstract
<jats:p>Quantum variants of machine learning algorithms are discussed with emphasis on methodology, learning techniques and applications in broad and distinct domains of chemical physics.</jats:p>