Synthesis of Quantum Circuits Using Genetic Algorithm (original) (raw)
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Automatic Synthesis for Quantum Circuits Using Genetic Algorithms
Lecture Notes in Computer Science, 2007
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.
The task of this report is to present the proposed re- search program, and to review the literature describing the main characteristics of quantum computing, genetic algorithms and cir- cuit synthesis. We also present selected parts from a submitted ar- ticle, which proposes a solution for quantum circuit synthesis using genetic algorithms. Our goal is to perform automatic quantum cir- cuit synthesis for a given functional description using rippled steps. We propose and will pursue the usage of a parser which will create an internal data structure for the provided description. Also, we employ simulation in order to determine the flnal quantum state, and we encourage the usage of an optimizer that will allow a better handling of data, and in the last step foster the usage of genetic algorithms in order to perform the synthesis tasks.
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.
Quantum Circuit Design by Means of Genetic Programming Ê
2007
Research in quantum technology has shown that quantum computers can provide dramatic advantages over classical computers for some problems. The efficiency of quantum computing is considered to become so significant that the study of quantum algorithms has attracted widespread interest. Development of quantum algorithms and circuits is difficult for a human researcher, so automatic induction of computer programs by means of genetic programming, which uses almost no auxiliary information on the search space, proved to be useful in generating new quantum algorithms. This approach takes advantage of the intrinsic parallelism of the genetic algorithm and quantum computing parallelism. The paper begins with a brief review on some basic concepts in genetic algorithms and quantum computation. Next, it describes an application of genetic programming for evolving quantum computing circuits.
Quantum encoded quantum evolutionary algorithm for the design of quantum circuits
2019
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 ...
Quantum Circuit Design by Means of Genetic Programming
Romanian Physics, 2007
Research in quantum technology has shown that quantum computers can provide dramatic advantages over classical computers for some problems. The effi-ciency of quantum computing is considered to become so significant that the study of quantum algorithms has attracted widespread ...
A Hierarchical Approach to Computer-Aided Design of Quantum Circuits
2003
A new approach to synthesis of permutation class of quantum logic circuits has been proposed in this paper. This approach produces better results than the previous approaches based on classical reversible logic and can be easier tuned to any particular quantum technology such as nuclear magnetic resonance (NMR). First we synthesize a library of permutation (pseudobinary) gates using a Computer-Aided-Design approach that links evolutionary and combinatorics approaches with human experience and creativity. Next the circuit is designed using these gates and standard 1*1 and 2*2 quantum gates and finally the optimizing tautological transforms are applied to the circuit, producing a sequence of quantum operations being close to operations practically realizable. These hierarchical stages can be compared to standard gate library design, generic logic synthesis and technology mapping stages of classical CAD systems, respectively. We use an informed genetic algorithm to evolve arbitrary quantum circuit specified by a (target) unitary matrix, specific encoding that reduces the time of calculating the resultant unitary matrices of chromosomes, and an evolutionary algorithm specialized to permutation circuits specified by truth tables. We outline interactive CAD approach in which the designer is a part of feedback loop in evolutionary program and the search is not for circuits of known specifications, but for any gates with high processing power and small cost for given constraints. In contrast to previous approaches, our methodology allows synthesis of both: small quantum circuits of arbitrary type (gates), and permutation class circuits that are well realizable in particular technology.
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.
Machine invention of quantum computing circuits by means of genetic programming
AI EDAM, 2008
We demonstrate the use of genetic programming in the automatic invention of quantum computing circuits that solve problems of potential theoretical and practical significance. We outline a developmental genetic programming scheme for such applications; in this scheme the evolved programs, when executed, build quantum circuits and the resulting quantum circuits are then tested for "fitness" using a quantum computer simulator. Using the PushGP genetic programming system and the QGAME quantum computer simulator we demonstrate the invention of a new, better than classical quantum circuit for the two-oracle AND/OR problem.
An Extended Approach for Generating Unitary Matrices for Quantum Circuits
Computers, Materials & Continua, 2019
In this paper, we do research on generating unitary matrices for quantum circuits automatically. We consider that quantum circuits are divided into six types, and the unitary operator expressions for each type are offered. Based on this, we propose an algorithm for computing the circuit unitary matrices in detail. Then, for quantum logic circuits composed of quantum logic gates, a faster method to compute unitary matrices of quantum circuits with truth table is introduced as a supplement. Finally, we apply the proposed algorithm to different reversible benchmark circuits based on NCT library (including NOT gate, Controlled-NOT gate, Toffoli gate) and generalized Toffoli (GT) library and provide our experimental results.