On the Impossibility of a Quantum Sieve Algorithm for Graph Isomorphism

Abstract

It is known that any quantum algorithm for Graph Isomorphism that works within the framework of the hidden subgroup problem (HSP) must perform highly entangled measurements across (n log n) coset states. One of the only known models for how such a measurement could be carried out efficiently is Kuperberg's algorithm for the HSP in the dihedral group, in which quantum states are adaptively combined and measured according to the decomposition of tensor products into irreducible representations. This "quantum sieve" starts with coset states, and works its way down towards representations whose probabilities differ depending on, for example, whether the hidden subgroup is trivial or nontrivial. In this paper we show that no such approach can produce a polynomial-time quantum algorithm for Graph Isomorphism. Specifically, we consider the natural reduction of Graph Isomorphism to the HSP over the wreath product Sn - Z2. Using a recently proved bound on the irreducible characters of Sn, we show that no algorithm in this family can solve Graph Isomorphism in less than e(n) time, no matter what adaptive rule it uses to select and combine quantum states. In particular, algorithms of this type can offer essentially no improvement over the best known classical algorithms, which run in time eO((n log n)).

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2007
Accession Number
ADA572849

Entities

People

  • Alexander Russell
  • Cristopher Moore
  • Piotr Sniady

Organizations

  • University of New Mexico

Tags

Communities of Interest

  • Advanced Electronics

DTIC Thesaurus Topics

  • Algorithms
  • Computations
  • Computer Science
  • Computers
  • Decomposition
  • Electronic Mail
  • Fourier Analysis
  • Geometry
  • Mathematics
  • New Mexico
  • Permutations
  • Polynomials
  • Probability
  • Probability Distributions
  • Quantum Algorithms
  • Quantum Computing
  • Quantum States

Fields of Study

  • Computer science
  • Mathematics

Readers

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  • Graph Algorithms and Convex Optimization.
  • Quantum Dot Semiconductor Device Photonics and Graphene Optoelectronic Materials and THz Physics.

Technology Areas

  • Quantum Computing