Evolutionary Approach to Quantum and Reversible Circuits Synthesis (original) (raw)
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This paper illustrates the application of a Hybrid Quantum Inspired Evolutionary Algorithm (HQIEA) in evolving a variety of Quantum equivalents of classical circuits. Taking the matrix corresponding to an oracle as input, this HIQEA designs classical circuits using quantum gates. A library consisting of single, two and three qubit Quantum gates and the desired circuit matrix were given as input and algorithm was able to successfully design half adder, full adder and binary-gray conversion circuits apart from circuits for two, three and four qubit Boolean functions, using Quantum gates. The circuits obtained compare favorably with earlier attempts in terms of number of gates, ancillary inputs and garbage outputs required for constructing these circuits and the time taken to evolve them.
arXiv (Cornell University), 2011
It has been experimentally proven that realizing universal quantum gates using higher-radices logic is practically and technologically possible. We developed a Parallel Genetic Algorithm that synthesizes Boolean reversible circuits realized with a variety of quantum gates on qudits with various radices. In order to allow synthesizing circuits of medium sizes in the higher radix quantum space we performed the experiments using a GPU accelerated Genetic Algorithm. Using the accelerated GA we compare heuristic improvements to the mutation process based on cost minimization, on the adaptive cost of the primitives and improvements due to Baldwinian vs. Lamarckian GA. We also describe various fitness function formulations that allowed for various realizations of well known universal Boolean reversible or quantum-probabilistic circuits.
Application of Genetic Algorithms for Evolution of Quantum Equivalents of Boolean Circuits
Due to the non-intuitive nature of Quantum algorithms, it becomes difficult for a classically trained person to efficiently construct new ones. So rather than designing new algorithms manually, lately, Genetic algorithms (GA) are being implemented for this purpose. GA is a technique to automatically solve a problem using principles of Darwinian evolution. This has been implemented in this paper to explore the possibility of evolving an n-qubit circuit when the circuit matrix has been provided using a set of single, two and three qubit gates. Using a variable length population and universal stochastic selection procedure, a number of possible solution circuits, with different number of gates can be obtained for the same input matrix during different runs of GA. The given algorithm has also been successfully implemented to obtain two and three qubit Boolean circuits using Quantum gates. The results demonstrate the relative effectiveness of the GA procedure in providing better solutions in a reasonable computation time even when the search spaces are large.
Synthesis of Quantum Circuits Using Genetic Algorithm
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The need of efficient technique for synthesis of quantum circuits is of immense importance in defining efficient hardware for quantum computers. In this work, a new automated approach for quantum circuit synthesis using genetic algorithm has been presented. The methodology of building a quantum circuit corresponding to a given quantum operation, expressed in terms of a unitary transform matrix, utilizing a specified quantum gate library has been proposed in this paper. Experimental results show that this technique using GA is better than other methods used for this purpose.
IEEE Congress on Evolutionary Computation, 2010
It has been experimentally proven that realizing universal quantum gates using higher-radices logic is practically and technologically possible. We developed a Parallel Genetic Algorithm that synthesizes Boolean reversible circuits realized with a variety of quantum gates on qudits with various radices. In order to allow synthesizing circuits of medium sizes in the higher radix quantum space we performed the experiments using a GPU accelerated Genetic Algorithm. Using the accelerated GA we compare heuristic improvements to the mutation process based on cost minimization, on the adaptive cost of the primitives and improvements due to Baldwinian vs. Lamarckian GA. We also describe various fitness function formulations that allowed for various realizations of well known universal Boolean reversible or quantum-probabilistic circuits.
Genetic Algorithm based synthesis of ternary Reversible/Quantum circuit
Reversible / Quantum circuits are believed to be one of the future computer technologies. In this paper, a Genetic Algorithm (GA) based synthesis of ternary reversible / quantum circuits using Muthukrishnan-Stroud gates is presented. The circuit generated by GA may contain redundant gates. We have used post GA reduction to eliminate these redundant gates. We have experimented with ternary half-adder circuit. The proposed GA converges for many combinations of crossover and mutation.. Index Terms — Reversible logic, half-adder, quantum circuit, post GA reduction..
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This paper proposes an automated quantum circuit synthesis approach, using a genetic algorithm. We consider the circuit as a successive rippling of the so-called gate sections; also, the usage of a database is proposed in order to specify the gates that will be used in the synthesis process. Details are presented for an appropriate comparison with previous approaches, along with experimental results that prove the convergence and the effectiveness of the algorithm.
Quantum encoded quantum evolutionary algorithm for the design of quantum circuits
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In this paper we present Quanrum Encoded Quantum Evolutionary Algorithm (QEQEA) and compare its performance against a a classical GPU accelerated Genetic Algorithm (GPUGA). The proposed QEQEA differs from existing quantum evolutionary algorithms in several points: representation of candidates circuits is using qubits and qutrits and the proposed evolutionary operators can theoretically be implemented on quantum computer provided a classical control exists. The synthesized circuits are obtained by a set of measurements performed on the encoding units of quantum representation. Both algorithms are accelerated using (general purpose graphic processing unit) GPGPU. The main target of this paper is not to propose a completely novel quantum genetic algorithm but to rather experimentally estimate the advantages of certain components of genetic algorithm being encoded and implemented in a quantum compatible manner. The algorithms are compared and evaluated on several reversible and quantum ...
A Genetic Algorithm Framework Applied to Quantum Circuit Synthesis
Studies in Computational Intelligence, 2008
This paper proposes an object oriented framework for genetic algorithm implementations. Software methods and design patterns are applied in order to create the necessary abstract levels for the genetic algorithm. The architecture is presented in UML terms, while several genetic algorithm schemes are already implemented. The framework allows for different configurations, thus the comparison between the characteristics of the emerged solutions becomes straightforward. This design creates incentives for practical solutions, because the inheritance from the defined abstract classes makes the creation of new genetic schemes possible. This framework was tested for the GA quantum circuit synthesis on several benchmark circuits. The genetic algorithm created with our framework proved to be faster than other available similar solutions used for quantum circuit synthesis.