Quantum Computing Applications of Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Lee Spector and Howard Barnum and 
                 Herbert J. Bernstein and Nikhil Swamy",
  title =        "Quantum Computing Applications of Genetic
  booktitle =    "Advances in Genetic Programming 3",
  publisher =    "MIT Press",
  year =         "1999",
  editor =       "Lee Spector and William B. Langdon and 
                 Una-May O'Reilly and Peter J. Angeline",
  chapter =      "7",
  pages =        "135--160",
  address =      "Cambridge, MA, USA",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "0-262-19423-6",
  URL =          "http://www.cs.bham.ac.uk/~wbl/aigp3/ch07.pdf",
  abstract =     "Quantum computers are computational devices that use
                 the dynamics of atomic-scale objects to store and
                 manipulate information. Only a few, small-scale quantum
                 computers have been built to date, but quantum
                 computers can in principle outperform all possible
                 classical computers in significant ways. Quantum
                 computation is therefore a subject of considerable
                 theoretical interest that may also have practical
                 applications in the future.

                 Genetic programming can automatically discover new
                 algorithms for quantum computers [spector:1998:GPqc].
                 We describe how to simulate a quantum computer so that
                 the fitness of a quantum algorithm can be determined on
                 classical hardware. We then describe ways in which
                 three different genetic programming approaches can
                 drive the simulator to evolve new quantum algorithms.
                 The approaches are standard tree-based genetic
                 programming, stack-based linear genome genetic
                 programming, and stackless linear genome genetic
                 programming. We demonstrate the techniques on four
                 different problems: the two-bit early promise problem,
                 the scaling majority-on problem, the four-item database
                 search problem, and the two-bit and-or problem. For
                 three of these problems (all but majority-on) the
                 automatically discovered algorithms are more efficient
                 than any possible classical algorithms for the same
                 problems. One of the better-than-classical algorithms
                 (for the two-bit and-or problem) is in fact more
                 efficient than any previously known quantum algorithm
                 for the same problem, suggesting that genetic
                 programming may be a valuable tool in the future study
                 of quantum programming.",
  notes =        "AiGP3 See http://cognet.mit.edu",

Genetic Programming entries for Lee Spector Howard Barnum Herbert J Bernstein Nikhil Swamy