Polynomial rejection under square-root rational approximation

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Let S{\mathscr{S}} be a step multiset and let \textscHθ(S){\textsc{H}}_{\theta}({\mathscr{S}}) be a half-plane model, with hn(θ)h_n(\theta) denoting the number of walks of length nn in this model. Let θ∗\theta^* be the optimal slope, and let a (1/n)(1/\sqrt{n})-rational approximation mean a half-plane model whose slope tangent differs from tan⁡θ∗\tan\theta^* by at most 1/n1/\sqrt{n} and whose tangent is rational. Polynomial-rejection conjecture. There exists an infinite sequence of angles {θn}n≤0\{\theta_n\}_{n\le 0} such that, for all n≥0n\ge 0, \textscHθn(S){\textsc{H}}_{\theta_n}({\mathscr{S}}) is a (1/n)(1/\sqrt{n})-rational approximation of \textscHθ∗(S){\textsc{H}}_{\theta^*}({\mathscr{S}}), and

∃p∈R,lim⁡n→+∞hn(θn)hn(θ)∈O(np).\exists p\in\mathbb{R},\qquad \lim_{n\to+\infty}\frac{h_n(\theta_n)}{h_n(\theta)}\in\mathcal{O}(n^p).

This would imply that the rejection count in the associated sampling algorithm remains polynomial in nn when the irrational optimal slope is approximated at precision 1/n1/\sqrt{n}. The surrounding discussion establishes polynomial-time rejection for precision 1/(n+1)1/(n+1), while the conjectured square-root precision would provide a substantially more efficient approximation; no resolution is supplied here.

References

Primary source

Jeremie Lumbroso, Marni Mishna and Yann Ponty, “Taming Reluctant Random Walks in the Positive Quadrant”, arXiv:1603.06321 (2016).

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