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arXiv 1610.04670quant-phcs.CC
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使用线性光学的永久硬度的新结果

New Hardness Results for the Permanent Using Linear Optics

Daniel Grier, Luke Schaeffer

摘要:

2011年,Aaronson给出了一个基于量子线性光学的惊人证明,表明计算矩阵的积和式的问题是#P-hard的。Aaronson的证明自然导致了对恒量的近似结果的困难,并且可以说它比Valiant在1979年对同一事实的开创性证明更简单。然而,它并没有证明计算永久式对于任何以前不知道的矩阵类都是P-困难的。在本文中,我们提出了一个新的结果,主要是来自通过这些线性光学技术的矩阵永久。首先,我们证明了计算实正交矩阵的积和式的问题是P-困难的。就像Aaronson的原始证明一样,这将表明即使是乘法近似仍然是#P-难以计算的。硬度结果甚至转化为有限域上的积和式,其中计算正交矩阵的积和式的问题在有限域F_{p^4}中对于所有不等于2或3的素数p是Modpp-困难的。有趣的是,这个特征是紧密的:在特征2的域中,积和行列式重合;在特征3的域中,可以通过Kogan的一个非平凡结果有效地计算正交矩阵的积和。最后,我们用更初等的论证证明了半正定矩阵的积和式的P-困难性,这表明尽管经典计算机可以有效地对热态玻色子抽样实验的某些概率进行抽样,但它们很难精确计算.

英文摘要:

In 2011, Aaronson gave a striking proof, based on quantum linear optics, showing that the problem of computing the permanent of a matrix is #P-hard. Aaronson's proof led naturally to hardness of approximation results for the permanent, and it was arguably simpler than Valiant's seminal proof of the same fact in 1979. Nevertheless, it did not prove that computing the permanent was #P-hard for any class of matrices which was not previously known. In this paper, we present a collection of new results about matrix permanents that are derived primarily via these linear optical techniques. First, we show that the problem of computing the permanent of a real orthogonal matrix is #P-hard. Much like Aaronson's original proof, this will show that even a multiplicative approximation remains #P-hard to compute. The hardness result even translates to permanents over finite fields, where the problem of computing the permanent of an orthogonal matrix is ModpP-hard in the finite field F_{p^4} for all primes p not equal to 2 or 3. Interestingly, this characterization is tight: in fields of characteristic 2, the permanent coincides with the determinant; in fields of characteristic 3, one can efficiently compute the permanent of an orthogonal matrix by a nontrivial result of Kogan. Finally, we use more elementary arguments to prove #P-hardness for the permanent of a positive semidefinite matrix, which shows that certain probabilities of boson sampling experiments with thermal states are hard to compute exactly despite the fact that they can be efficiently sampled by a classical computer.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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