In this paper, we demonstrate that the logic computation performed by the DNA-based algorithm for solving general cases of the satisfiability problem can be implemented more efficiently by our proposed quantum algorithm on the quantum machine proposed by Deutsch. To test our theory, we carry out a three-quantum bit nuclear magnetic resonance experiment for solving the simplest satisfiability problem.
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http://dx.doi.org/10.1109/TNB.2008.2002286 | DOI Listing |
bioRxiv
November 2024
Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA 16802, USA.
Reducing into a satisfiability (SAT) formulation has been proven effective in solving certain NP-hard problems. In this work, we extend this research by presenting a novel SAT formulation for computing the double-cut-and-join (DCJ) distance between two genomes with duplicate genes. The DCJ distance serves as a crucial metric in studying genome rearrangement.
View Article and Find Full Text PDFEntropy (Basel)
October 2024
Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC 27695, USA.
This paper aims to outline the effectiveness of modern universal gate quantum computers when utilizing different configurations to solve the B-SAT (Boolean satisfiability) problem. The quantum computing experiments were performed using Grover's search algorithm to find a valid solution. The experiments were performed under different variations to demonstrate their effects on the results.
View Article and Find Full Text PDFPhys Rev E
September 2024
School of Fundamental Physics and Mathematical Sciences, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China.
Nat Commun
October 2024
Department of Electrical and Computer Engineering, University of California, Santa Barbara, Santa Barbara, CA, 93106, USA.
Domain-specific hardware to solve computationally hard optimization problems has generated tremendous excitement. Here, we evaluate probabilistic bit (p-bit) based Ising Machines (IM) on the 3-Regular 3-Exclusive OR Satisfiability (3R3X), as a representative hard optimization problem. We first introduce a multiplexed architecture that emulates all-to-all network functionality while maintaining highly parallelized chromatic Gibbs sampling.
View Article and Find Full Text PDFNat Commun
September 2024
Department of Electrical and Computer Engineering, University of California at Santa Barbara, Santa Barbara, CA, USA.
Specialized function gradient computing hardware could greatly improve the performance of state-of-the-art optimization algorithms. Prior work on such hardware, performed in the context of Ising Machines and related concepts, is limited to quadratic polynomials and not scalable to commonly used higher-order functions. Here, we propose an approach for massively parallel gradient calculations of high-degree polynomials, which is conducive to efficient mixed-signal in-memory computing circuit implementations and whose area scales proportionally with the product of the number of variables and terms in the function and, most importantly, independent of its degree.
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