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Human-competitive evolution of quantum computing artefacts by Genetic Programming.

Paul Massey1, John A Clark, Susan Stepney

  • 1Department of Computer Science, University of York, York, YO10 5DD, UK. psm111@cs.york.ac.uk

Evolutionary Computation
|March 16, 2006
PubMed
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Genetic Programming (GP) evolves sophisticated quantum computing tools, including circuits, programs, and algorithms. A human-competitive Quantum Fourier Transform algorithm was successfully evolved using GP.

Area of Science:

  • Quantum Computing
  • Artificial Intelligence
  • Evolutionary Computation

Background:

  • Quantum computing leverages quantum-mechanical phenomena to perform computations.
  • Genetic Programming (GP) is an evolutionary computation technique that evolves computer programs.

Purpose of the Study:

  • To demonstrate the capability of Genetic Programming (GP) in evolving quantum computing artifacts.
  • To evolve increasingly complex quantum computing elements, from circuits to algorithms.

Main Methods:

  • Utilized Genetic Programming (GP) to automatically design and optimize quantum computing components.
  • Applied GP to evolve specific quantum circuits, quantum programs, and system-independent quantum algorithms.

Main Results:

Related Experiment Videos

  • Successfully evolved useful quantum computing artifacts of increasing sophistication.
  • Developed a Quantum Fourier Transform (QFT) algorithm using GP that achieves human-competitive performance.

Conclusions:

  • Genetic Programming (GP) is a powerful tool for evolving quantum computing solutions.
  • The evolved QFT algorithm demonstrates the potential of automated methods in quantum algorithm design.