Content area

Abstract

Recently, there has been an increasing interest in employing dynamical systems as solvers of NP-complete problems. In this paper, we present accurate implementations of two continuous-time dynamical solvers, known in the literature as analog SAT and digital memcomputing, using advanced numerical integration algorithms of SPICE circuit simulators. For this purpose, we have developed Python scripts that convert Boolean satisfiability (SAT) problems into electronic circuits representing the analog SAT and digital memcomputing dynamical systems. Our Python scripts process conjunctive normal form (CNF) files and create netlists that can be directly imported into LTspice. We explore the SPICE implementations of analog SAT and digital memcomputing solvers by applying these to a selected set of problems and present some interesting and potentially useful findings related to digital memcomputing and analog SAT.

Details

1009240
Title
Accurate modeling of continuous-time SAT solvers in SPICE
Publication title
arXiv.org; Ithaca
Publication year
2024
Publication date
Dec 19, 2024
Section
Computer Science; Nonlinear Sciences
Publisher
Cornell University Library, arXiv.org
Source
arXiv.org
Place of publication
Ithaca
Country of publication
United States
University/institution
Cornell University Library arXiv.org
e-ISSN
2331-8422
Source type
Working Paper
Language of publication
English
Document type
Working Paper
Publication history
 
 
Online publication date
2024-12-20
Milestone dates
2024-12-19 (Submission v1)
Publication history
 
 
   First posting date
20 Dec 2024
ProQuest document ID
3147568924
Document URL
https://www.proquest.com/working-papers/accurate-modeling-continuous-time-sat-solvers/docview/3147568924/se-2?accountid=208611
Full text outside of ProQuest
Copyright
© 2024. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2024-12-21
Database
2 databases
  • ProQuest One Academic
  • ProQuest One Academic