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Quantum Search Algorithms for Constr...

Alasow, Abdirahman Sheikh Hassan,

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Quantum Search Algorithms for Constraint Satisfaction and Optimization Problems Using Grover's Search and Quantum Walk Algorithms With Advanced Oracle Design /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Quantum Search Algorithms for Constraint Satisfaction and Optimization Problems Using Grover's Search and Quantum Walk Algorithms With Advanced Oracle Design // Abdirahman Sheikh Hassan Alasow.
Author:	Alasow, Abdirahman Sheikh Hassan,
Description:	1 electronic resource (326 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-12, Section: B.
Contained By:	Dissertations Abstracts International85-12B.
Subject:	Engineering. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31139788
ISBN:	9798383045954

Quantum Search Algorithms for Constraint Satisfaction and Optimization Problems Using Grover's Search and Quantum Walk Algorithms With Advanced Oracle Design /
Alasow, Abdirahman Sheikh Hassan,

Quantum Search Algorithms for Constraint Satisfaction and Optimization Problems Using Grover's Search and Quantum Walk Algorithms With Advanced Oracle Design /Abdirahman Sheikh Hassan Alasow. - 1 electronic resource (326 pages)

Source: Dissertations Abstracts International, Volume: 85-12, Section: B.

The field of quantum computing has emerged as a powerful tool for solving and optimizing combinatorial optimization problems. To solve many real-world problems with many variables and possible solutions for constraint satisfaction and optimization problems, the required number of qubits of scalable hardware for quantum computing is the bottleneck in the current generation of quantum computers. In this dissertation, we will demonstrate advanced, scalable building blocks for the quantum search algorithms that have been implemented in Grover's search algorithm and the quantum walk algorithm. The scalable building blocks are used to reduce the required number of qubits in the design. The proposed architecture effectively scales and optimizes the number of qubits needed to solve large problems with a limited number of qubits. Thus, scaling and optimizing the number of qubits that can be accommodated in quantum algorithm design directly reflect on performance. Also, accuracy is a key performance metric related to how accurately one can measure quantum states.The search space of quantum search algorithms is traditionally created by using the Hadamard operator to create superposition. However, creating superpositions for problems that do not need all superposition states decreases the accuracy of the measured states. We present an efficient quantum circuit design that the user has control over to create the subspace superposition states for the search space as needed. Using only the subspace states as superposition states of the search space will increase the rate of correct solutions.In this dissertation, we will present the implementation of practical problems for Grover's search algorithm and quantum walk algorithm in logic design, logic puzzles, and machine learning problems such as SAT, MAX-SAT, XOR-SAT, and like SAT problems in EDA, and mining frequent patterns for association rule mining.

English

ISBN: 9798383045954Subjects--Topical Terms:

586835
Engineering.
Subjects--Index Terms:

Grover search algorithm

Quantum Search Algorithms for Constraint Satisfaction and Optimization Problems Using Grover's Search and Quantum Walk Algorithms With Advanced Oracle Design /
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520 $a The field of quantum computing has emerged as a powerful tool for solving and optimizing combinatorial optimization problems. To solve many real-world problems with many variables and possible solutions for constraint satisfaction and optimization problems, the required number of qubits of scalable hardware for quantum computing is the bottleneck in the current generation of quantum computers. In this dissertation, we will demonstrate advanced, scalable building blocks for the quantum search algorithms that have been implemented in Grover's search algorithm and the quantum walk algorithm. The scalable building blocks are used to reduce the required number of qubits in the design. The proposed architecture effectively scales and optimizes the number of qubits needed to solve large problems with a limited number of qubits. Thus, scaling and optimizing the number of qubits that can be accommodated in quantum algorithm design directly reflect on performance. Also, accuracy is a key performance metric related to how accurately one can measure quantum states.The search space of quantum search algorithms is traditionally created by using the Hadamard operator to create superposition. However, creating superpositions for problems that do not need all superposition states decreases the accuracy of the measured states. We present an efficient quantum circuit design that the user has control over to create the subspace superposition states for the search space as needed. Using only the subspace states as superposition states of the search space will increase the rate of correct solutions.In this dissertation, we will present the implementation of practical problems for Grover's search algorithm and quantum walk algorithm in logic design, logic puzzles, and machine learning problems such as SAT, MAX-SAT, XOR-SAT, and like SAT problems in EDA, and mining frequent patterns for association rule mining.
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650 4 $a Engineering. $3 586835
650 4 $a Computer engineering. $3 621879
650 4 $a Electrical engineering. $3 649834
650 4 $a Quantum physics. $3 726746
653 $a Grover search algorithm
653 $a Quantum counter
653 $a Quantum walk algorithm
653 $a Machine learning problems
690 $a 0537
690 $a 0464
690 $a 0544
690 $a 0599
710 2 $a Portland State University. $b Electrical and Computer Engineering. $e degree granting institution. $3 3816325
720 1 $a Perkowski, Marek $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 85-12B.
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791 $a Ph.D.
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