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Mathematics

Using a Simplified Quantum Counter to Implement Quantum Circuits Based on Grover’s Algorithm to Tackle the Exact Cover Problem

Jehn‐Ruey Jiang, Yujie Wang

Published Dec 29, 2024• 9 citations
Publisher

Abstract

In this paper, we use a simplified quantum counter to implement Grover’s algorithm-based quantum circuits to tackle the NP-hard exact cover problem (ECP). The ECP seeks a subcollection of sets such that every element is covered by exactly one set. Leveraging Grover’s algorithm, our quantum circuits achieve a quadratic speedup, querying the oracle O(N) times, compared to O(N) for classical methods, where N=2n is the total number of unstructured input instances and n is the number of input (quantum) bits. For the whole quantum circuit, the simplified quantum counter saves (4mb−4m)⌊π/4N/M⌋ quantum gates and reduces the quantum circuit depth by (2mb)⌊π/4N/M⌋ compared to Heidari et al.’s design, where b=⌊logn⌋+1 is the number of counting qubits used in a counter. Experimental results obtained using IBM Qiskit packages confirm the effectiveness of our quantum circuits.

DOI
10.3390/math13010090

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In this paper, we use a simplified quantum counter to implement Grover’s algorithm-based quantum circuits to tackle the NP-hard exact cover problem (ECP). The ECP seeks a subcollection of sets such that every element is covered by exactly one set. Leveraging Grover’s algorithm, our quantum circuits achieve a quadratic speedup, querying the oracle O(N) times, compared to O(N) for classical methods, where N=2n is the total number of unstructured input instances and n is the number of input (quantum) bits. For the whole quantum circuit, the simplified quantum counter saves (4mb−4m)⌊π/4N/M⌋ quantum gates and reduces the quantum circuit depth by (2mb)⌊π/4N/M⌋ compared to Heidari et al.’s design, where b=⌊logn⌋+1 is the number of counting qubits used in a counter. Experimental results obtained using IBM Qiskit packages confirm the effectiveness of our quantum circuits.
In this paper, we propose a quantum circuit based on Grover’s algorithm to solve the exact cover problem (ECP), which is NP-hard. A novel controlled counter is designed and used to implement the ECP oracle to check if every element is covered by a set exactly once. If so, a feasible solution is found. The phase of the qubit state representing a feasible solution is flipped by calling the oracle, and the state’s amplitude is amplified through the diffusion operator o(2n\sqrt{2^{n}}2n​) times, where n is the number of sets given in the ECP. Thanks to Grover’s algorithm, the proposed quantum circuit achieves quadratic speedup compared with the classical algorithm that needs to call the oracle O(2n2^{n}2n) times. To validate our approach, we execute the proposed quantum circuit using the IBM Quantum Lab service.
We propose new quantum circuit designs for the Grover oracle, i.e., the oracle of Grover’s algorithm, to solve the vertex cover problem (VCP) efficiently. Grover’s algorithm is an unstructured quantum search algorithm to search a target data item out of N data pieces by calling the oracle O(N)\mathrm{O}(\sqrt{N})O(N​) times. It represents a quadratic speedup compared to the classical unstructured data sequential search algorithm, which requires O(N) oracle calls. We are in the noisy intermediate-scale quantum (NISQ) era in which quantum computers have a limited number of qubits, short decoherence time, and low gate fidelity. It is thus desirable to design quantum circuits with three properties: (1) a reduced number of qubits, (2) shorter quantum depth, and (3) fewer gates. We created novel designs of a quantum counter and a quantum semaphore to be applied to the Grover oracle to have the three properties. Through the IBM Quantum Lab service, we executed Grover’s algorithm with the novel quantum circuit designs to solve the VCP to validate the design correctness.
Grover's algorithm is a well-known unstructured quantum search algorithm run on quantum computers. It constructs an oracle and calls the oracle O(N\sqrt NN​) times to locate specific data out of N unsorted data. This represents a quadratic speedup compared to the classical unstructured data sequential search algorithm, which requires to call the oracle O(N) times. We are currently in the noisy intermediate-scale quantum (NISQ) era in which quantum computers have a limited number of qubits, short decoherence time, and low gate fidelity. It is thus desirable to design quantum components with three good properties: (i) a reduced number of qubits, (ii) shorter quantum depth, and (iii) fewer gates. This paper utilizes novel quantum counters with the above-mentioned three good properties to construct the oracle of Grover's algorithm to efficiently solve the dominating set problem (DSP), as defined below. For a given graph G=(V, E), a dominating set (DS) D is a subset of the vertex set V, such that every vertex is in D or has an adjacent vertex in D. The DSP is to decide for a given graph G and an integer k whether there exists a DS with size k. Algorithms solving the DSP have many applications. For example, they can be applied to check whether k routers suffice to connect all computers in a computer network. The DSP is an NP-complete problem, indicating that no classical algorithm exists to solve the DSP with polynomial time complexity in the worst case. Therefore, using quantum algorithms, such as Grover's algorithm, to exploit the potent computational capabilities of quantum computers to solve the DSP is highly promising. We execute the whole quantum circuit of Grover's algorithm using novel quantum counters through the IBM Quantum Lab service to validate that the circuit can solve the DSP efficiently and correctly.
Quantum computing offers an accelerated mechanism for solving combinatorial optimization problems that could be hardly solvable with classical tools, in this context, this paper highlights the utility of quantum computing in solving NP-complete problems efficiently and shows up the importance of employing quantum algorithms achieving parallel calculation in the purpose of reducing the algorithmic complexity and simplifying the development of optimization applications. Within this publication, an optimized version of quantum circuit conception for developing the oracle of the Grover's search algorithm is introduced for solving the vertex cover problem, and it was also tested using the Qiskit library and applied to a set of instances to evaluate its performance.
The Hamiltonian cycle problem (HCP) is related to the decision of whether there exists a cycle in a graph that visits every vertex exactly once. It is a well-known NP-complete problem, and thus there currently exists no classical algorithm solving it with polynomial time complexity in the worst case. With the emergence of quantum computers, the introduction of Grover’s algorithm has suggested new possibilities for solving the HCP more efficiently. In this article, we propose three novel quantum circuit designs of quantum counters to be embedded in the oracle of Grover’s algorithm to check if the input instance satisfies the HCP constraints to solve the HCP. We executed Grover’s algorithm with the novel quantum circuit designs, through the IBM Quantum Lab service, to solve the HCP to validate the design correctness.
This study explores how well Grover's Algorithm performs in solving the Boolean Satisfiability Problem (SAT) using quantum circuits. The algorithm is implemented with IBM's Qiskit framework and compared to classical brute-force methods. Experiments focus on 3-SAT, 4-SAT, and 5-SAT problems, using quantum simulators and IBM quantum hardware. The results show that Grover's Algorithm is more efficient, offering a theoretical quadratic speedup over classical methods. However, practical issues like limited qubit availability, hardware noise, and optimization challenges impact its current performance. The data highlights the potential for quantum computing to scale and solve NP-complete problems. This research shows how quantum computing can improve problem-solving and lays the groundwork for future studies on more complex SAT problems and advanced quantum hardware.