Boson sampling from a Gaussian state.

@article{Lund2014BosonSF,
  title={Boson sampling from a Gaussian state.},
  author={Austin P. Lund and Anthony Laing and Saleh Rahimi-Keshari and Terry Rudolph and Jeremy Lloyd O'Brien and Timothy C. Ralph},
  journal={Physical review letters},
  year={2014},
  volume={113 10},
  pages={
          100502
        }
}
We pose a randomized boson-sampling problem. Strong evidence exists that such a problem becomes intractable on a classical computer as a function of the number of bosons. We describe a quantum optical processor that can solve this problem efficiently based on a Gaussian input state, a linear optical network, and nonadaptive photon counting measurements. All the elements required to build such a processor currently exist. The demonstration of such a device would provide empirical evidence that… 

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References

SHOWING 1-10 OF 16 REFERENCES

A Guide To Experiments In Quantum Optics

Quantum computation and quantum information

This chapter discusses quantum information theory, public-key cryptography and the RSA cryptosystem, and the proof of Lieb's theorem.

The complexity of approximate counting

The complexity of computing approximate solutions to problems in #P is classified in terms of the polynomial-time hierarchy (for short, P-hierarchy) in order to study a class of restricted, but very natural, probabilistic sampling methods motivated by the particular counting problems.

The Polynomial-Time Hierarchy

  • L. Stockmeyer
  • Computer Science, Mathematics
    Theor. Comput. Sci.
  • 1976

Et al

A large population-based survey of veterans and nondeployed controls found evidence of a deployment-related Gulf War syndrome by factor analysis in Air Force veterans and controls.

Proceedings of the fifteenth annual ACM symposium on Theory of computing

Phys

  • Rev. Lett. 104, 250503
  • 2010

Theory Comput

  • 9, 143
  • 2013

Phys

  • Rev. A 85, 022332 (2012). PRL 113, 100502
  • 2014

Phys

  • Rev. A 66, 053805
  • 2002