Near invariance of the hypercube
classification
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math.PR
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matriceshypercubeorthogonalalmost-completeapplicationsbooleancharacterizingclose
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We give an almost-complete description of orthogonal matrices $M$ of order $n$ that "rotate a non-negligible fraction of the Boolean hypercube $C_n=\{-1,1\}^n$ onto itself," in the sense that $$P_{x\in C_n}(Mx\in C_n) \ge n^{-C},\mbox{ for some positive constant } C,$$ where $x$ is sampled uniformly over $C_n$. In particular, we show that such matrices $M$ must be very close to products of permutation and reflection matrices. This result is a step toward characterizing those orthogonal and unitary matrices with large permanents, a question with applications to linear-optical quantum computing.
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