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arXiv · 2112.00760

Biology and medicine in the landscape of quantum advantages

Benjamin A. Cordier·Nicolas P. D. Sawaya·Gian G. Guerreschi·Shannon K. McWeeney
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Abstract

Quantum computing holds significant potential for applications in biology and medicine, spanning from the simulation of biomolecules to machine learning approaches for subtyping cancers on the basis of clinical features. This potential is encapsulated by the concept of a quantum advantage, which is typically contingent on a reduction in the consumption of a computational resource, such as time, space, or data. Here, we distill the concept of a quantum advantage into a simple framework that we hope will aid researchers in biology and medicine pursuing the development of quantum applications. We then apply this framework to a wide variety of computational problems relevant to these domains in an effort to i) assess the potential of quantum advantages in specific application areas and ii) identify gaps that may be addressed with novel quantum approaches. Bearing in mind the rapid pace of change in the fields of quantum computing and classical algorithms, we aim to provide an extensive survey of applications in biology and medicine that may lead to practical quantum advantages.

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BibTeXRIS

Benjamin A. Cordier, Nicolas P. D. Sawaya, Gian G. Guerreschi, Shannon K. McWeeney. 2021-12-01. Biology and medicine in the landscape of quantum advantages. https://doi.org/10.1098/rsif.2022.0541

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