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This is an old revision of this page, as edited by ColeDU (talk | contribs) at 23:55, 8 October 2020 (I copied the background section from the Quantum complexity theory Wikipedia page and added a paragraph describing how quantum computation may violate the Church-Turing thesis as a motivation for the study of quantum complexity theory. I also added a reference section and one source that I used for in-text citation. Lastly, I also added a link to the Church-Turing thesis Wikipedia page when I first mentioned it.). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.
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Background[edit]

See also: Computational complexity and Complexity class

A complexity class is a collection of computational problems that can be solved by a computational model under certain resource constraints. For instance, the complexity class P is defined as the set of problems solvable by a Turing machine in polynomial time. Similarly, quantum complexity classes may be defined using quantum models of computation, such as the quantum circuit model or the equivalent quantum Turing machine. One of the main aims of quantum complexity theory is to find out how these classes relate to classical complexity classes such as P, NP, BPP, and PSPACE.

One of the reasons quantum complexity theory is studied are the implications of quantum computing for the modern Church-Turing thesis. In short the modern Church-Turing thesis states that any computational model can be simulated in polynomial time with a probabilistic Turing machine.[1] However, questions around the Church-Turing thesis arise in the context of quantum computing. It is unclear whether the Church-Turing thesis holds for the quantum computation model. There is much evidence that the thesis does not hold and that it may not be possible for a probabilistic Turing machine to simulate quantum computation models in polynomial time.[1]


References

  1. ^ a b Vazirani, Umesh V. (2002). "A survey of quantum complexity theory". Proceedings of Symposia in Applied Mathematics: 193–217. doi:10.1090/psapm/058/1922899. ISSN 2324-7088.