Paraunitary Matrices, Entropy, Algebraic Condition Number and Fourier Computation
Nir Ailon

TL;DR
This paper investigates the limitations of algebraic condition numbers in Fourier computation, establishing bounds on speedup and connecting algebraic and standard condition numbers through complex analysis.
Contribution
It introduces the algebraic condition number for Fourier computation, providing bounds on speedup and linking it to the standard condition number using complex analysis techniques.
Findings
Algebraic condition number bounds the speedup in Fourier computation.
Algebraic condition number is related to the degree of polynomials in the computation.
It upper bounds the standard condition number and equals it in certain cases.
Abstract
The Fourier Transform is one of the most important linear transformations used in science and engineering. Cooley and Tukey's Fast Fourier Transform (FFT) from 1964 is a method for computing this transformation in time . From a lower bound perspective, relatively little is known. Ailon shows in 2013 an bound for computing the normalized Fourier Transform assuming only unitary operations on two coordinates are allowed at each step, and no extra memory is allowed. In 2014, Ailon then improved the result to show that, in a -well conditioned computation, Fourier computation can be sped up by no more than . The main conjecture is that Ailon's result can be exponentially improved, in the sense that -well condition cannot admit speedup. The main result here is that `algebraic' -well condition admits no…
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