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A nonlinear lower bound for constant depth arithmetical circuits via the discrete uncertainty principle

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Abstract

We prove a superlinear lower bound on the size of a bounded depth bilinear arithmetical circuit computing cyclic convolution. Our proof uses the strengthening of the Donoho-Stark uncertainty principle [D.L. Donoho, P.B. Stark, Uncertainty principles and signal recovery, SIAM Journal of Applied Mathematics 49 (1989) 906-931] given by Tao [T. Tao, An uncertainty principle for cyclic groups of prime order, Mathematical Research Letters 12 (2005) 121-127], and a combinatorial lemma by Raz and Shpilka [R. Raz, A. Shpilka, Lower bounds for matrix product, in arbitrary circuits with bounded gates, SIAM Journal of Computing 32 (2003) 488-513]. This combination and an observation on ranks of circulant matrices, which we use to give a much shorter proof of the Donoho-Stark principle, may have other applications.

Original languageEnglish
Pages (from-to)617-622
Number of pages6
JournalTheoretical Computer Science
Volume409
Issue number3
DOIs
StatePublished - Dec 28 2008

Keywords

  • Arithmetical circuits
  • Computational complexity
  • Constant depth bilinear circuits
  • Lower bounds

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