Random-matrix conjecture for the squarefree-number detection exponent

Let η(θ)\eta_\infty(\theta) be the limiting exponent governing the algorithm's running time, and let θ\theta^* be the threshold parameter defined by the preceding complexity analysis. The paper models η(θ)\eta_\infty(\theta) using a suitable random matrix model.

Random-matrix conjecture. The limiting exponent is

η(θ)={1θ2if 0<θ<1,12if θ1.\eta_\infty(\theta)=\begin{cases} 1-\frac{\theta}2&\text{if }0<\theta<1,\\ \frac12&\text{if }\theta\ge1. \end{cases}

In particular, θ=23\theta^*=\frac23.

This conjectural value would imply that the algorithm can certify that NN is squarefree in time O(exp[(logN)2/3+o(1)])O\bigl(\exp[(\log N)^{2/3+o(1)}]\bigr). The claim is based on an analogous calculation for a random matrix model; the source provides no resolution of the conjecture.

Sources & referencesView supporting material

Primary source

Andrew R. Booker, Ghaith A. Hiary and Jon P. Keating, “Detecting squarefree numbers”, arXiv:1304.6937 (2015).

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