145,164 research outputs found
Ramsey-nice families of graphs
For a finite family of fixed graphs let be
the smallest integer for which every -coloring of the edges of the
complete graph yields a monochromatic copy of some . We
say that is -nice if for every graph with
and for every -coloring of there exists a
monochromatic copy of some . It is easy to see that if
contains no forest, then it is not -nice for any . It seems
plausible to conjecture that a (weak) converse holds, namely, for any finite
family of graphs that contains at least one forest, and for all
(or at least for infinitely many values of ),
is -nice. We prove several (modest) results in support of this
conjecture, showing, in particular, that it holds for each of the three
families consisting of two connected graphs with 3 edges each and observing
that it holds for any family containing a forest with at most 2
edges. We also study some related problems and disprove a conjecture by
Aharoni, Charbit and Howard regarding the size of matchings in regular
3-partite 3-uniform hypergraphs.Comment: 20 pages, 2 figure
Derandomization and Group Testing
The rapid development of derandomization theory, which is a fundamental area
in theoretical computer science, has recently led to many surprising
applications outside its initial intention. We will review some recent such
developments related to combinatorial group testing. In its most basic setting,
the aim of group testing is to identify a set of "positive" individuals in a
population of items by taking groups of items and asking whether there is a
positive in each group.
In particular, we will discuss explicit constructions of optimal or
nearly-optimal group testing schemes using "randomness-conducting" functions.
Among such developments are constructions of error-correcting group testing
schemes using randomness extractors and condensers, as well as threshold group
testing schemes from lossless condensers.Comment: Invited Paper in Proceedings of 48th Annual Allerton Conference on
Communication, Control, and Computing, 201
Unconstraining Graph-Constrained Group Testing
In network tomography, one goal is to identify a small set of failed links in a network using as little information as possible. One way of setting up this problem is called graph-constrained group testing. Graph-constrained group testing is a variant of the classical combinatorial group testing problem, where the tests that one is allowed are additionally constrained by a graph. In this case, the graph is given by the underlying network topology.
The main contribution of this work is to show that for most graphs, the constraints imposed by the graph are no constraint at all. That is, the number of tests required to identify the failed links in graph-constrained group testing is near-optimal even for the corresponding group testing problem with no graph constraints. Our approach is based on a simple randomized construction of tests. To analyze our construction, we prove new results about the size of giant components in randomly sparsified graphs.
Finally, we provide empirical results which suggest that our connected-subgraph tests perform better not just in theory but also in practice, and in particular perform better on a real-world network topology
Regular spanning subgraphs of bipartite graphs of high minimum degree
Let G be a simple balanced bipartite graph on vertices, , and . If then it has a -regular spanning subgraph. The
statement is nearly tight.Comment: submitte
The Chromatic Number of Random Regular Graphs
Given any integer d >= 3, let k be the smallest integer such that d < 2k log
k. We prove that with high probability the chromatic number of a random
d-regular graph is k, k+1, or k+2, and that if (2k-1) \log k < d < 2k \log k
then the chromatic number is either k+1 or k+2
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