The role of experimental noise in a hybrid classical-molecular computer to solve combinatorial optimization problems

Krasecki, V. K. et al. (2023) The role of experimental noise in a hybrid classical-molecular computer to solve combinatorial optimization problems. ACS Central Science, 9(7), 1453–1465. (doi: 10.1021/acscentsci.3c00515) (PMID:37521801)

Abstract

Chemical and molecular-based computers may be promising alternatives to modern silicon-based computers. In particular, hybrid systems, where tasks are split between a chemical medium and traditional silicon components, may provide access and demonstration of chemical advantages such as scalability, low power dissipation, and genuine randomness. This work describes the development of a hybrid classical-molecular computer (HCMC) featuring an electrochemical reaction on top of an array of discrete electrodes with a fluorescent readout. The chemical medium, optical readout, and electrode interface combined with a classical computer generate a feedback loop to solve several canonical optimization problems in computer science such as number partitioning and prime factorization. Importantly, the HCMC makes constructive use of experimental noise in the optical readout, a milestone for molecular systems, to solve these optimization problems, as opposed to in silico random number generation. Specifically, we show calculations stranded in local minima can consistently converge on a global minimum in the presence of experimental noise. Scalability of the hybrid computer is demonstrated by expanding the number of variables from 4 to 7, increasing the number of possible solutions by 1 order of magnitude. This work provides a stepping stone to fully molecular approaches to solving complex computational problems using chemistry.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Sharma, Mr Abhishek and Cronin, Professor Lee
• Authors: Krasecki, V. K., Sharma, A., Cavell, A. C., Forman, C., Guo, S. Y., Jensen, E. T., Smith, M. A., Czerwinski, R., Friederich, P., Hickman, R. J., Gianneschi, N., Aspuru-Guzik, A., Cronin, L., and Goldsmith, R. H.
• College/School: College of Science and Engineering > School of Chemistry
• Journal Name: ACS Central Science
• Publisher: American Chemical Society
• ISSN: 2374-7951
• ISSN (Online): 2374-7951
• Published Online: 14 July 2023
• Copyright Holders: Copyright © 2023 The Authors
• First Published: First published in ACS Central Science 9(7):1453-1465
• Publisher Policy: Reproduced under a Creative Commons licence