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 O(nlogn). From a lower bound perspective, relatively little is known. Ailon shows in 2013 an Ω(nlogn) 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 κ-well conditioned computation, Fourier computation can be sped up by no more than O(κ). The main conjecture is that Ailon's result can be exponentially improved, in the sense that κ-well condition cannot admit ω(logκ) speedup.The main result here is that ‘algebraic’ κ-well condition cannot admit ω(κ) speedup. One equivalent definition of algebraic condition number is related to the degree of polynomials naturally arising as the computation evolves. Using the maximum modulus theorem from complex analysis, we show that algebraic condition number upper bounds standard condition number, and equals it in certain cases. Algebraic condition number is an interesting measure of numerical computation stability in its own right, and provides a novel computational lens. Moreover, based on evidence from other recent related work, we believe that the approach of algebraic condition number has a good chance of establishing an algebraic version of the main conjecture.
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