Solving the B-SAT Problem Using Quantum Computing: Smaller Is Sometimes Better
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 experime...
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| Abstract | 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. Changing the number of shots, qubit mapping, and using a different quantum processor were all among the experimental variables. The study also branched into a dedicated experiment highlighting a peculiar behavior that IBM quantum processors exhibit when running circuits with a certain number of shots. |
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| AbstractList | 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. Changing the number of shots, qubit mapping, and using a different quantum processor were all among the experimental variables. The study also branched into a dedicated experiment highlighting a peculiar behavior that IBM quantum processors exhibit when running circuits with a certain number of shots.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. Changing the number of shots, qubit mapping, and using a different quantum processor were all among the experimental variables. The study also branched into a dedicated experiment highlighting a peculiar behavior that IBM quantum processors exhibit when running circuits with a certain number of shots. 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. Changing the number of shots, qubit mapping, and using a different quantum processor were all among the experimental variables. The study also branched into a dedicated experiment highlighting a peculiar behavior that IBM quantum processors exhibit when running circuits with a certain number of shots. |
| Audience | Academic |
| Author | Franzon, Paul Byrd, Gregory T. Bennakhi, Ahmad |
| AuthorAffiliation | Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC 27695, USA; gbyrd@ncsu.edu (G.T.B.); paulf@ncsu.edu (P.F.) |
| AuthorAffiliation_xml | – name: Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC 27695, USA; gbyrd@ncsu.edu (G.T.B.); paulf@ncsu.edu (P.F.) |
| Author_xml | – sequence: 1 givenname: Ahmad orcidid: 0000-0002-4269-2856 surname: Bennakhi fullname: Bennakhi, Ahmad – sequence: 2 givenname: Gregory T. orcidid: 0000-0003-3647-8738 surname: Byrd fullname: Byrd, Gregory T. – sequence: 3 givenname: Paul orcidid: 0000-0002-6048-5770 surname: Franzon fullname: Franzon, Paul |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/39451951$$D View this record in MEDLINE/PubMed |
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| References | Vinod (ref_11) 2021; 2 Cheng (ref_10) 2007; 73 ref_13 ref_12 Lin (ref_18) 2022; 4 ref_20 Nation (ref_19) 2023; 4 ref_1 Glover (ref_15) 2022; 314 ref_2 Kochenberger (ref_14) 2014; 28 ref_17 ref_16 Zalka (ref_3) 1999; 60 ref_9 ref_8 Zecchina (ref_7) 2002; 66 ref_5 ref_4 ref_6 |
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| SubjectTerms | Algorithms B-SAT Boolean Boolean satisfiability problem Circuits conjunctive normal form (CNF) electronic design automation (EDA) Grover’s search Logic Microprocessors Quantum computers Quantum computing Qubits (quantum computing) Search algorithms Variables |
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| Title | Solving the B-SAT Problem Using Quantum Computing: Smaller Is Sometimes Better |
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