Affiliation:
1. Institute for Informatics, LMU Munich, 80538 Munich, Germany
2. Quantum & Computer Engineering, Delft University of Technology, 2628 CD Delft, The Netherlands
Abstract
One way of solving 3sat instances on a quantum computer is to transform the 3sat instances into instances of Quadratic Unconstrained Binary Optimizations (QUBOs), which can be used as an input for the QAOA algorithm on quantum gate systems or as an input for quantum annealers. This mapping is performed by a 3sat-to-QUBO transformation. Recently, it has been shown that the choice of the 3sat-to-QUBO transformation can significantly impact the solution quality of quantum annealing. It has been shown that the solution quality can vary up to an order of magnitude difference in the number of correct solutions received, depending solely on the 3sat-to-QUBO transformation. An open question is: what causes these differences in the solution quality when solving 3sat-instances with different 3sat-to-QUBO transformations? To be able to conduct meaningful studies that assess the reasons for the differences in the performance, a larger number of different 3sat-to-QUBO transformations would be needed. However, currently, there are only a few known 3sat-to-QUBO transformations, and all of them were created manually by experts, who used time and clever reasoning to create these transformations. In this paper, we will solve this problem by proposing an algorithmic method that is able to create thousands of new and different 3sat-to-QUBO transformations, and thus enables researchers to systematically study the reasons for the significant difference in the performance of different 3sat-to-QUBO transformations. Our algorithmic method is an exhaustive search procedure that exploits properties of 4×4 dimensional pattern QUBOs, a concept which has been used implicitly in the creation of 3sat-to-QUBO transformations before, but was never described explicitly. We will thus also formally and explicitly introduce the concept of pattern QUBOs in this paper.
Funder
German Federal Ministry of Education and Research
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
Reference35 articles.
1. Cook, S.A. (1971, January 3–5). The complexity of theorem-proving procedures. Proceedings of the Third Annual ACM Symposium on Theory of Computing, Shaker Heights, OH, USA.
2. Arora, S., and Barak, B. (2009). Computational Complexity: A Modern Approach, Cambridge University Press.
3. Nüßlein, J., Zielinski, S., Gabor, T., Linnhoff-Popien, C., and Feld, S. (2023). Solving (Max) 3-SAT via Quadratic Unconstrained Binary Optimization. arXiv.
4. Kautz, H.A., and Selman, B. (1992, January 3–7). Planning as Satisfiability. Proceedings of the ECAI, Vienna, Austria.
5. A survey of recent advances in SAT-based formal verification;Prasad;Int. J. Softw. Tools Technol. Transf.,2005
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Using an Evolutionary Algorithm to Create (MAX)-3SAT QUBOs;Proceedings of the Genetic and Evolutionary Computation Conference Companion;2024-07-14
2. SATQUBOLIB: A Python Framework for Creating and Benchmarking (Max-)3SAT QUBOs;Communications in Computer and Information Science;2024