SearcharxivSearch

arXiv · 2609.07949

Improved Integrality Gap for Multicommodity Flow on Trees

Abstract

We improve the best known lower bound on the integrality gap for weighted unit-demand multicommodity flow on trees from $1/4$ to $2/5$, improving on the long-standing bound of Chekuri, Mydlarz, and Shepherd~\cite{CMS}. We give the proof in two stages. First, a surprisingly simple packing lemma and an inductive coloring argument give an intermediate bound of $4/11$. We then refine the argument to obtain $2/5$.

Explore related subjects

Keep this discovery

BibTeXRIS

Elfarouk Harb. 2026-09-07. Improved Integrality Gap for Multicommodity Flow on Trees. https://arxiv.org/abs/2609.07949

Cite the original work for its findings. Save a collection to share your selection of sources.

Discover connections

Connections use source metadata and explicit phrase matches, not verified experimental comparisons.

KEEP EXPLORING

Related papers

Oracle-free Boltzmann Sampling for Powersets

We propose an approach for sampling powersets under the Boltzmann distribution in an oracle-free way, i.e. without numerically evaluating the associated generating function. Our approach relies on a Poissonised infinite occupancy model and thinning. It yields an explicit sampler for bounded counting sequences and extends under mild growth conditions. We implement the sampler and find runtimes comparable to existing Boltzmann samplers.

cs.DM

An Exposition of the $\widetilde{O}(\log^{1/4} n)$ Bound for the Komlós Problem

A conjecture of Komlós states that the combinatorial discrepancy of any matrix $A\in\mathbb R^{m\times n}$ whose columns have Euclidean norm at most one is bounded by a universal constant. We prove that the combinatorial discrepancy of every such matrix is at most $O((\log n)^{1/4}(\log\log n)^{7/4})$. This is the first asymptotic improvement over the $O(\sqrt{\log n})$ bound established by Banaszczyk [Banaszczyk, Random Struct.\ Algorithms, 1998], and it refutes a conjecture of Hajela [Hajela, European J.\ Combin., 1988] that a lower bound of order $Ω(\sqrt{\log n})$ should hold.

math.CO

Analysis of Polynomial Threshold Functions on Random Regular Graphs: Computational Complexity of Detecting Noisy Random Lifts

In this work, we present the first analysis of low-degree polynomial threshold functions for the natural hypothesis testing problem of detecting the noisy random lift of a base $d$-regular graph from a uniformly random $d$-regular graph. Along the way, we obtain a new result for the distribution of short cycle counts in noisy random lift up to logarithmic lengths, which generalizes results by McKay, Wormald, and Wysocka and by Johnson in the case of random regular graphs, and results by Greenhill, Janson, and Ruciński and by Fortin and Rudinsky in the case of random lifts.

math.CO