Archimedes configuration conjecture for uniform sorting networks

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Let ωn\omega_n be an nn-element uniform sorting network. For t∈(0,1)t\in(0,1), define the scaled configuration by

μt(ωn):=1n∑i=1nδ(2in−1  ,  2σ⌊tN⌋(i)n−1).\mu_t(\omega_n):=\frac 1n \sum_{i=1}^n \delta\Big(\frac {2i}{n}-1\;,\;\frac {2\sigma_{\lfloor tN\rfloor}(i)}{n}-1\Big).

For t∈(0,1)t\in(0,1), define the Archimedes measure by

Archt(dx×dy):=12π[sin⁡2(πt)+2xycos⁡(πt)−x2−y2]−1∨0  dx  dy.\mathfrak{Arch}_t(dx\times dy):=\frac{1}{2\pi}\sqrt{\Big[\sin^2(\pi t) +2xy\cos(\pi t)-x^2-y^2\Big]^{-1}\vee 0}\;dx\;dy.

Archimedes configurations. For all t∈(0,1)t\in(0,1), the scaled configuration converges in distribution to the Archimedes measure in the vague topology for random Borel measures on R2\mathbb{R}^2:

μt(ωn)⟹Archtasn→∞.\mu_t(\omega_n) \Longrightarrow \mathfrak{Arch}_t \qquad\text{as}\quad n\to\infty.

The conjecture describes the limiting particle density inside the asymptotic ellipses suggested by simulations. The supplied text gives no resolution evidence.

References

Primary source

Omer Angel, Alexander E. Holroyd, Dan Romik and Balint Virag, “Random Sorting Networks”, arXiv:math/0609538 (2006).

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