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Optimum Design of Quantum Teleportation Circuit

Guangjun Xie

Published Jan 1, 2010• 1 citation
OpenAlex

Abstract

Optimum design of quantum teleportation circuit is achieved based on genetic algorithm,and a novel one-dimensional quantum coding mode is proposed to store the location information of quantum gates using the location information of codes.The method is more convenient than previous ones for coding and de-coding,and has high coding efficiency.It can well express the circuit structure,and is easy to be extended to multi-bit quantum circuits.A fitness function of the genetic algorithm is also presented with two parts to determine the function and performance of the quantum circuit.Experimental results are given to show that a better circuit structure has been obtained.

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Optimizing quantum teleportation circuit using genetic algorithm

Fei Peng, Guangjun Xie, Tianhao Wu

This paper applies a standard genetic algorithm to the optimization of the quantum circuits. We propose a new coding scheme, which encodes quantum gates as integers and stores circuit topology information in the position of the integers. The design of the corresponding fitness function and genetic operators are also discussed. The quantum teleportation circuit, a typical quantum computation process, is chosen as our optimization target. Finally, the experiment results are discussed, and an optimized teleportation circuit has been obtained.

IEEE International Conference on Granular Computing (GrC)•Aug 1, 2009•3 citations

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Genetic Algorithm Based Optimisation Framework for Quantum Circuit Mapping GAQCM

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Abstract Most of the existing qubit mapping algorithms are deterministic, resulting in a lack of diversity in the generated quantum circuit mappings, which makes it difficult to strike a balance between quality and diversity, and prevents them from being flexibly adapted to different quantum computing tasks. To solve this problem, this paper proposes the Genetic Algorithm-based Quantum Circuit Mapping (GAQCM) framework, which is based on the idea of genetic algorithm, evaluates the quality of mapping by the fitness function, and continuously improves the mapping scheme through several iterations. The GAQCM framework is designed to be flexible, providing a variety of choices, crossover operations and several unique mutation methods are designed to improve the performance of the algorithm. The framework also introduces a neighbourhood gate-based initialisation strategy to improve the algorithm efficiency and convergence speed. Experimental results show that the GAQCM framework reduces the number of SWAP gates by an average of 44.6% and 62.0%, and reduces the hardware gate overhead by 13.8% and 14.9% in the t|ket > and Qiskit compilers, respectively, compared to 2QAN. The framework allows users to customise the fitness function and parameter settings according to their specific needs, and is suitable for a variety of quantum computing tasks.

•Sep 11, 2024•0 citations
Optimum design of quantum teleportation circuit is achieved based on genetic algorithm,and a novel one-dimensional quantum coding mode is proposed to store the location information of quantum gates using the location information of codes.The method is more convenient than previous ones for coding and de-coding,and has high coding efficiency.It can well express the circuit structure,and is easy to be extended to multi-bit quantum circuits.A fitness function of the genetic algorithm is also presented with two parts to determine the function and performance of the quantum circuit.Experimental results are given to show that a better circuit structure has been obtained.
This paper applies a standard genetic algorithm to the optimization of the quantum circuits. We propose a new coding scheme, which encodes quantum gates as integers and stores circuit topology information in the position of the integers. The design of the corresponding fitness function and genetic operators are also discussed. The quantum teleportation circuit, a typical quantum computation process, is chosen as our optimization target. Finally, the experiment results are discussed, and an optimized teleportation circuit has been obtained.
Quantum Teleportation is the process of transmitting Quantum information from one place to another by performing Quantum mechanical operations like entanglement, Bell measurement and classical communication.Unlike the commonly used term teleportation, Quantum teleportation involves only transfer of information rather than particles or objects.Quantum teleportation allows transmission of quantum information despite the impossibility of measuring or broadcasting the information to be transmitted.This paper evolves some new simpler Quantum teleportation circuits which use only Quantum entanglement and a set of Hadamard and CNOT gates.Further, each of the circuits performs teleportation even if Alice does not perform measurement on her qubits.Keeping the feasibility of physical realization in mind, circuits using only adjacent CNOT gates along with Hadamard gates have also been constructed.All these circuits have been evolved using Genetic Algorithms which has been designed with appropriate representation and search operations towards faster convergence.
Quantum computing is a new way of data processing based on the concept of quantum mechanics. Quantum circuit design is a process of converting a quantum gate to a series of basic gates and is divided into two general categories based on the decomposition and composition. In the second group, using evolutionary algorithms and especially genetic algorithms, multiplication of matrix gates was used to achieve the final characteristic of quantum circuit. Genetic programming is a subfield of evolutionary computing in which computer programs evolve to solve studied problems. In past research that has been done in the field of quantum circuits design, only one cost metrics (usually quantum cost) has been investigated. In this paper for the first time, a multi-objective approach has been provided to design quantum circuits using genetic programming that considers the depth and the cost of nearest neighbor metrics in addition to quantum cost metric. Another innovation of this article is the use of two-step fitness function and taking into account the equivalence of global phase in quantum gates. The results show that the proposed method is able to find a good answer in a short time.
The synthesis method of quantum reversible logic circuits based on the genetic algorithm was studied.The multi-objective optimal design of reversible logic circuit's function,the number of quantum gates,the number of garbage bits and quantum cost was achieved by new synthesis method.The mathematical model for quantum reversible logic circuit synthesis was established,the matrix encoding method of quantum reversible logic circuits was proposed,the evolution operations and the multi-objective evolutionary algorithm for quantum reversible logic circuit design were developed.The 8 bits reversible multiplier was designed as an example,the experimental results show that the proposed multi-objective evolutionary design method for quantum reversible logic circuit synthesis is correct and effective.
Abstract Most of the existing qubit mapping algorithms are deterministic, resulting in a lack of diversity in the generated quantum circuit mappings, which makes it difficult to strike a balance between quality and diversity, and prevents them from being flexibly adapted to different quantum computing tasks. To solve this problem, this paper proposes the Genetic Algorithm-based Quantum Circuit Mapping (GAQCM) framework, which is based on the idea of genetic algorithm, evaluates the quality of mapping by the fitness function, and continuously improves the mapping scheme through several iterations. The GAQCM framework is designed to be flexible, providing a variety of choices, crossover operations and several unique mutation methods are designed to improve the performance of the algorithm. The framework also introduces a neighbourhood gate-based initialisation strategy to improve the algorithm efficiency and convergence speed. Experimental results show that the GAQCM framework reduces the number of SWAP gates by an average of 44.6% and 62.0%, and reduces the hardware gate overhead by 13.8% and 14.9% in the t|ket > and Qiskit compilers, respectively, compared to 2QAN. The framework allows users to customise the fitness function and parameter settings according to their specific needs, and is suitable for a variety of quantum computing tasks.