Quantum Vertex Model For Reversible Classical Computing
Abstract
Mappings of classical computation onto statistical mechanics models have led to remarkable successes in addressing some complex computational problems. However, such mappings display thermodynamic phase transitions that may prevent reaching solution even for easy problems known to be solvable in polynomial time. Here we map universal reversible classical computations onto a planar vertex model that exhibits no bulk classical thermodynamic phase transition, independent of the computational circuit. Within our approach the solution of the computation is encoded in the ground state of the vertex model and its complexity is reflected in the dynamics of the relaxation of the system to its ground state. We use thermal annealing with and without 'learning' to explore typical computational problems. We also construct a mapping of the vertex model into the Chimera architecture of the D-Wave machine, initiating an approach to reversible classical computation based on state-of-the-art implementations of quantum annealing.
Publication Date
5-12-2017
Publication Title
Nature Communications
Volume
8
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1038/ncomms15303
Copyright Status
Unknown
Socpus ID
85019209253 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85019209253
STARS Citation
Chamon, C.; Mucciolo, E. R.; Ruckenstein, A. E.; and Yang, Z. C., "Quantum Vertex Model For Reversible Classical Computing" (2017). Scopus Export 2015-2019. 4995.
https://stars.library.ucf.edu/scopus2015/4995