2018
DOI: 10.1016/j.acha.2017.08.002
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On sets of large Fourier transform under changes in domain

Abstract: A function f : Z n → C can be represented as a linear combination f (where f is the (discrete) Fourier transform of f . Clearly, the basis {χ α,n (x) := exp(2πiαx/n)} depends on the value n.We show that if f has "large" Fourier coefficients, then the function f : Z m → C, given byalso has "large" coefficients. Moreover, they are all contained in a "small" interval around ⌊ m n α⌉ for each α ∈ Z n such that f (α) is large. One can use this result to recover the large Fourier coefficients of a function f by rede… Show more

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Cited by 3 publications
(6 citation statements)
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“…In Section 4 we outline our recent work [28] on applying modulus switching to this subject (namely to re-cast a function on Z p to a function on Z 2 n for the nearest power of 2 to p). These ideas are very similar to the approach taken in Shor's (period-finding) algorithm [42].…”
Section: Roadmapmentioning
confidence: 99%
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“…In Section 4 we outline our recent work [28] on applying modulus switching to this subject (namely to re-cast a function on Z p to a function on Z 2 n for the nearest power of 2 to p). These ideas are very similar to the approach taken in Shor's (period-finding) algorithm [42].…”
Section: Roadmapmentioning
confidence: 99%
“…Specifically, significant coefficients are "preserved" even when the time domain representation of the function is extended (by "preserved" we mean that there is a clear relation between the significant coefficients of both functions). We refer to Laity and Shani [28] for the technical details.…”
Section: Simplifications: Modulus Switchingmentioning
confidence: 99%
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