# Testing permanent oracles - Revisited

## Author(s): Arora, Sanjeev; Bhattacharyya, A; Manokaran, R; Sachdeva, S

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Abstract: | Suppose we are given an oracle that claims to approximate the permanent for most matrices X, where X is chosen from the Gaussian ensemble (the matrix entries are i.i.d. univariate complex Gaussians). Can we test that the oracle satisfies this claim? This paper gives a polynomial-time algorithm for the task. The oracle-testing problem is of interest because a recent paper of Aaronson and Arkhipov showed that if there is a polynomial-time algorithm for simulating boson-boson interactions in quantum mechanics, then an approximation oracle for the permanent (of the type described above) exists in BPP NP. Since computing the permanent of even 0/1 matrices is #P-complete, this seems to demonstrate more computational power in quantum mechanics than Shor's factoring algorithm does. However, unlike factoring, which is in NP, it was unclear previously how to test the correctness of an approximation oracle for the permanent, and this is the contribution of the paper. The technical difficulty overcome here is that univariate polynomial self-correction, which underlies similar oracle-testing algorithms for permanent over -and whose discovery led to a revolution in complexity theory-does not seem to generalize to complex (or even, real) numbers. We believe that this tester will motivate further progress on understanding the permanent of Gaussian matrices. |

Publication Date: | 2012 |

Citation: | Arora, S, Bhattacharyya, A, Manokaran, R, Sachdeva, S. (2012). Testing permanent oracles - Revisited. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7408 LNCS (362 - 373. doi:10.1007/978-3-642-32512-0_31 |

DOI: | doi:10.1007/978-3-642-32512-0_31 |

Pages: | 362 - 373 |

Type of Material: | Conference Article |

Journal/Proceeding Title: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |

Version: | Author's manuscript |

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