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THE PHASE TRANSITION OF DISCREPANCY IN RANDOM HYPERGRAPHS

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A10473965" target="_blank" >RIV/00216208:11320/23:10473965 - isvavai.cz</a>

  • Result on the web

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=OqAHyfWnwN" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=OqAHyfWnwN</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1137/21M1451427" target="_blank" >10.1137/21M1451427</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    THE PHASE TRANSITION OF DISCREPANCY IN RANDOM HYPERGRAPHS

  • Original language description

    Motivated by the Beck-Fiala conjecture, we study the discrepancy problem in two related models of random hypergraphs on n vertices and m edges. In the first model, each of the m edges is constructed by placing each vertex into the edge independently with probability d/m, where d is a parameter satisfying d -&gt; infinity and dn/m -&gt; infinity. In the second model, each vertex independently chooses a subset of d edge labels from [m] uniformly at random. Edge i is then defined to be exactly those vertices whose d-subsets include label i. In the sparse regime, i.e., when m = O(n), we show that with high probability a random hypergraph from either model has discrepancy at least Omega(2(-n/m) root dn/m). In the dense regime, i.e., when m &gt;&gt; n, we show that with high probability a random hypergraph from either model has discrepancy at least Omega(root(dn/m) log gamma), where gamma = min{m/n, dn/m}. Furthermore, we obtain nearly matching asymptotic upper bounds on the discrepancy. Specifically, we apply the partial coloring lemma of Lovett and Meka to show that, in the dense regime, with high probability the two random hypergraph models each have discrepancy O(root dn/m log(m/n)). In fact, in a significant parameter range we can tighten our analysis to get an upper bound which matches our lower bound up to a constant factor. This result is algorithmic, and together with the work of Bansal and Meka [On the discrepancy of random low degree set systems, in Proceedings of the 2019 Annual ACM-SIAM Symposium on Discrete Algorithms, 2019, pp. 2557-2564] characterizes how the discrepancy of each random hypergraph transitions from Theta (surd d) to o(surd d) as m increases from m= Theta (n) to m &gt;&gt; n.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    SIAM Journal on Discrete Mathematics

  • ISSN

    0895-4801

  • e-ISSN

    1095-7146

  • Volume of the periodical

    37

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    24

  • Pages from-to

    1818-1841

  • UT code for WoS article

    001071676800016

  • EID of the result in the Scopus database

    2-s2.0-85171614345