• Corpus ID: 3265351

Genetic Algorithms and Quantum Computation

  title={Genetic Algorithms and Quantum Computation},
  author={Gilson Antonio Giraldi and Renato Portugal and Ricardo N. Thess},
Recently, researchers have applied genetic algorithms (GAs) to address some problems in quantum computation. Also, there has been some works in the designing of genetic algorithms based on quantum theoretical concepts and techniques. The so called Quantum Evolutionary Programming has two major sub-areas: Quantum Inspired Genetic Algorithms (QIGAs) and Quantum Genetic Algorithms (QGAs). The former adopts qubit chromosomes as representations and employs quantum gates for the search of the best… 
Implementing quantum genetic algorithms: a solution based on Grover's algorithm
It turns out that the genetic strategy is not particularly helpful in the quantum computation approach; therefore the solution consists of designing a special-purpose oracle that will work with a modified version of an already known algorithm (maximum finding [1]), in order to reduce the QGAs to a Grover search.
Grover ’ s Algorithm and the Evolutionary Approach of Quantum Computation
In the recent years we were witnesses of an intense research activity, trying to find some common ground for quantum computation and genetic programming [4][19]. The use of genetic algorithms
Semiclassical genetic algorithm with quantum crossover and mutation operations
A novel semiclassical quantum genetic algorithm that has both of quantum crossover and quantum mutation procedures unlike conventional quantum genetic algorithms is introduced.
Quantum Behaved Genetic Algorithm: Constraints-Handling and GPU Computing
Main concepts behind the intersection between evolutionary algorithms and quantum computing, such as quantum-bit, superposition feature, quantum gate, quantum measurement and quantum interference, are introduced.
Evolving quantum circuits at the gate level with a hybrid quantum-inspired evolutionary algorithm
This paper proposes an approach to evolve quantum circuits at the gate level, based on a hybrid quantum-inspired evolutionary algorithm. This approach encodes quantum gates as integers and combines
A new Quantum Inspired Genetic Algorithm for Evolvable Hardware
  • R. Popa, V. Nicolau, S. Epure
  • Mathematics
    2010 3rd International Symposium on Electrical and Electronics Engineering (ISEEE)
  • 2010
The developments in the area of Evolvable Quantum Hardware (QEHW) are based on successful quantum genetic algorithms (QGAs) that take advantage of both the Genetic Algorithms (GAs) and Quantum
A review of procedures to evolve quantum algorithms
  • A. Gepp, P. Stocks
  • Computer Science, Physics
    Genetic Programming and Evolvable Machines
  • 2009
This paper provides an introduction into quantum and evolutionary algorithms for the computer scientist not familiar with these fields and the exciting field of using evolutionary algorithms to evolve quantum algorithms is reviewed.
A Review of Procedure to Evolve Quantum Procedures
There exist quantum algorithms that are more efficient than their classical counterparts; such algorithms were invented by Shor in 1994 and then Grover in 1996. A lack of invention since Grover's
Developing Automatic Synthesis Methodologies for Quantum Circuits using Genetic Algorithms Ph
The task of this report is to present the proposed research program, and to review the literature describing the main characteristics of quantum computing, genetic algorithms and circuit synthesis.
Quantum Genetic Optimization
It is shown that the complexity of the quantum genetic optimization algorithm (QGOA) is in terms of number of oracle calls in the selection procedure, which is confirmed by the simulations of the algorithm.


Parallel quantum-inspired genetic algorithm for combinatorial optimization problem
Results show that PQGA is superior to QGA as well as other conventional genetic algorithms, and is able to possess the two characteristics of exploration and exploitation simultaneously.
Quantum evolutionary programming
Recent developments in quantum technology have shown that quantum computers can provide dramatic advantages over classical computers for some problems [1] [2]. These quantum algorithms rely upon the
Genetic quantum algorithm and its application to combinatorial optimization problem
  • Kuk-Hyun Han, Jong-Hwan Kim
  • Mathematics
    Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)
  • 2000
This paper proposes a novel evolutionary computing method called a genetic quantum algorithm (GQA). GQA is based on the concept and principles of quantum computing such as qubits and superposition of
Quantum-inspired genetic algorithms
  • A. Narayanan, Mark Moore
  • Mathematics, Computer Science
    Proceedings of IEEE International Conference on Evolutionary Computation
  • 1996
It is informally shown that the quantum inspired genetic algorithm performs better than the classical counterpart for a small domain.
Automated Design of Quantum Circuits
An automated approach to quantum circuit design using search heuristics based on principles abstracted from evolutionary genetics, i.e. using a genetic programming algorithm adapted specially for this problem, is proposed.
Evolving quantum circuits using genetic programming
  • Benjamin I. P. Rubinstein
  • Mathematics
    Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546)
  • 2001
The paper presents a new representation and corresponding set of genetic operators for a scheme to evolve quantum circuits with various properties. The scheme is a variant on the techniques of
A Practical Architecture for Reliable Quantum Computers
A proposed architecture is described that uses code teleportation, quantum memory refresh units, dynamic compilation of quantum programs, and scalable error correction to achieve system-level efficiencies and indicates the underlying technology's reliability is crucial.
Genetic Algorithms for Quantum Circuit Design –Evolving a Simpler Teleportation Circuit–
It is shown by experiments that without any deep knowledge of the problem it is possible to evolve a circuit for the quantum teleportation simpler than ever known.
Genetic programming - on the programming of computers by means of natural selection
  • J. Koza
  • Computer Science
    Complex adaptive systems
  • 1993
This book discusses the evolution of architecture, primitive functions, terminals, sufficiency, and closure, and the role of representation and the lens effect in genetic programming.
An Introduction to Genetic Algorithms.
An Introduction to Genetic Algorithms is one of the rare examples of a book in which every single page is worth reading. The author, Melanie Mitchell, manages to describe in depth many fascinating