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Quantum Algorithm for Variant Maximum Satisfiability.
Alasow, Abdirahman; Jin, Peter; Perkowski, Marek.
Afiliação
  • Alasow A; Department of Electrical & Computer Engineering, Portland State University, Portland, OR 97207, USA.
  • Jin P; Department of Electrical & Computer Engineering, Portland State University, Portland, OR 97207, USA.
  • Perkowski M; Department of Electrical & Computer Engineering, Portland State University, Portland, OR 97207, USA.
Entropy (Basel) ; 24(11)2022 Nov 05.
Article em En | MEDLINE | ID: mdl-36359704
In this paper, we proposed a novel quantum algorithm for the maximum satisfiability problem. Satisfiability (SAT) is to find the set of assignment values of input variables for the given Boolean function that evaluates this function as TRUE or prove that such satisfying values do not exist. For a POS SAT problem, we proposed a novel quantum algorithm for the maximum satisfiability (MAX-SAT), which returns the maximum number of OR terms that are satisfied for the SAT-unsatisfiable function, providing us with information on how far the given Boolean function is from the SAT satisfaction. We used Grover's algorithm with a new block called quantum counter in the oracle circuit. The proposed circuit can be adapted for various forms of satisfiability expressions and several satisfiability-like problems. Using the quantum counter and mirrors for SAT terms reduces the need for ancilla qubits and realizes a large Toffoli gate that is then not needed. Our circuit reduces the number of ancilla qubits for the terms T of the Boolean function from T of ancilla qubits to ≈⌈log2⁡T⌉+1. We analyzed and compared the quantum cost of the traditional oracle design with our design which gives a low quantum cost.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Entropy (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Entropy (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos