🤖 AI Summary
This work addresses the noisy $k$XOR problem—where $k$ is a large constant—and presents the first classical algorithm achieving quadratic speedup, thereby substantially narrowing the quantum advantage from prior quartic to quadratic. Methodologically, it introduces a novel integration of sublinear-time algorithmic frameworks with polynomial anti-concentration phenomena, while strategically leveraging the birthday paradox to design an efficient solver tailored to semi-random noise settings. The resulting algorithm improves upon the best prior classical time complexity by a quadratic factor. Although quantum algorithms retain asymptotic advantages in space complexity, their temporal superiority is materially diminished. This work advances the understanding of the classical–quantum boundary for the $k$XOR problem, offering new insights into the interplay between noise structure, algorithmic primitives, and computational hardness.
📝 Abstract
A recent work of Schmidhuber et al (QIP, SODA, & Phys. Rev. X 2025) exhibited a quantum algorithm for the noisy planted $k$XOR problem running quartically faster than all known classical algorithms. In this work, we design a new classical algorithm that is quadratically faster than the best previous one, in the case of large constant $k$. Thus for such $k$, the quantum speedup of Schmidhuber et al. becomes only quadratic (though it retains a space advantage). Our algorithm, which also works in the semirandom case, combines tools from sublinear-time algorithms (essentially, the birthday paradox) and polynomial anticoncentration.