PreprintCC BY 4.0arXiv
Latin Eulerian Numbers
Abstract
We introduce \emph{Latin Eulerian numbers} LEnatop k1,…,kn, a multivariate refinement of classical Eulerian numbers counting order-n Latin squares by column ascents. We establish their fundamental symmetries, univariate marginals, and an exact multiplicity divisibility property. For the total ascent statistic Σ(L)=∑i ki(L), we prove the sharp, isolated bounds n−1 ≤ Σ(L) ≤ (n−1)2, demonstrating that the adjacent values n and (n−1)2−1 are strictly unattainable. To analyze intermediate values, we show that symbol permutations typically ignored in classical enumeration directly govern Σ via an exact formula. This insight yields explicit constructions for the interior range, motivates a unimodality conjecture for the total ascent distribution.
Related
BibTeX
@misc{mirzavaziri2026latin,
title = {{Latin Eulerian Numbers}},
author = {Madjid Mirzavaziri and Daniel Yaqubi},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.25100},
eprint = {2609.25100},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.25100},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Latin Eulerian Numbers
AU - Madjid Mirzavaziri
AU - Daniel Yaqubi
PY - 2026
DA - 2026/09/19
PB - arXiv
DO - 10.48550/arxiv.2609.25100
UR - https://arxiv.org/abs/2609.25100
AB - We introduce \emph{Latin Eulerian numbers} LEnatop k_1,…,k_n, a multivariate refinement of classical Eulerian numbers counting order-n Latin squares by column ascents. We establish their fundamental symmetries, univariate marginals, and an exact multiplicity divisibility property. For the total ascent statistic Σ(L)=∑_i k_i(L), we prove the sharp, isolated bounds n−1 ≤ Σ(L) ≤ (n−1)^2, demonstrating that the adjacent values n and (n−1)^2−1 are strictly unattainable. To analyze intermediate values, we show that symbol permutations typically ignored in classical enumeration directly govern Σ via an exact formula. This insight yields explicit constructions for the interior range, motivates a unimodality conjecture for the total ascent distribution.
ER -