Latest

Theoretical computer science

Exact Fourier transforms below nlog n

OpenAI research collection · 2 manuscripts · Source checked 2026-10-19

OpenAI's result summary

Gives a deterministic length-n discrete Fourier transform algorithm using O(n(log n)^{1-δ}) operations for every n, with explicit δ=10^{-13}. The model uses exact complex arithmetic, unrestricted coefficients and a supplied root of unity, and counts scalar preparation and logarithmic-word indexing.

Read the manuscripts

Short excerpts below come from OpenAI's abstracts. The full abstract and original PDF preserve the paper's precise scope.

MANUSCRIPT 01

An explicit power saving for the exact discrete Fourier transform

We give a deterministic algorithm that computes the discrete Fourier transform at every length n in O(n(log n)^{1-10^{-13}}) operations. The model uses exact complex arithmetic, unrestricted coefficients, specified Fourier roots, and unit-cost logarithmic-size indexing; scalar preparation and array organization are included.

This PDF is listed in OpenAI's formalization catalogue. See the scope and dependencies before interpreting coverage.

MANUSCRIPT 02

Finite tensor savings and exact Fourier circuits

We construct exact nonuniform Fourier circuits of size o(nlog n) along an unbounded sequence of lengths, counting every addition, subtraction, and scalar multiplication. This refutes the \Omega(nlog n) lower bound in the unrestricted complex linear-circuit model. The construction uses a finite tensor saving: a tensor power of…

Full source abstract

We construct exact nonuniform Fourier circuits of size o(nlog n) along an unbounded sequence of lengths, counting every addition, subtraction, and scalar multiplication. This refutes the \Omega(nlog n) lower bound in the unrestricted complex linear-circuit model. The construction uses a finite tensor saving: a tensor power of some invertible nonmonomial complex matrix can be computed with fewer matrix calls than the standard tensor-axis algorithm on the same coordinates, when invertible monomial maps are allowed freely between calls.

This PDF is listed in OpenAI's formalization catalogue. See the scope and dependencies before interpreting coverage.

One signal in the wider AGI picture

New mathematical reasoning could help AI tackle harder scientific and computational problems. How reliably these skills transfer beyond mathematics will determine how much they contribute to general intelligence.

Explore the AGI Clock ↗