29 research outputs found
Hypergraph Independent Sets
The study of extremal problems related to independent sets in hypergraphs is a problem that has generated much interest. There are a variety of types of independent sets in hypergraphs depending on the number of vertices from an independent set allowed in an edge. We say that a subset of vertices is j-independent if its intersection with any edge has size strictly less than j. The Kruskal–Katona theorem implies that in an r-uniform hypergraph with a fixed size and order, the hypergraph with the most r-independent sets is the lexicographic hypergraph. In this paper, we use a hypergraph regularity lemma, along with a technique developed by Loh, Pikhurko and Sudakov, to give an asymptotically best possible upper bound on the number of j-independent sets in an r-uniform hypergraph
Hypergraph Independent Sets
The study of extremal problems related to independent sets in hypergraphs is a problem that has generated much interest. There are a variety of types of independent sets in hypergraphs depending on the number of vertices from an independent set allowed in an edge. We say that a subset of vertices is j-independent if its intersection with any edge has size strictly less than j. The Kruskal–Katona theorem implies that in an r-uniform hypergraph with a fixed size and order, the hypergraph with the most r-independent sets is the lexicographic hypergraph. In this paper, we use a hypergraph regularity lemma, along with a technique developed by Loh, Pikhurko and Sudakov, to give an asymptotically best possible upper bound on the number of j-independent sets in an r-uniform hypergraph
Rapid mixing of hypergraph independent sets
We prove that the mixing time of the Glauber dynamics for sampling independent sets on n-vertex k-uniform hypergraphs is 0(n log n) when the maximum degree Δ satisfies Δ ≤ c2k/2, improving on the previous bound Bordewich and co-workers of Δ ≤ k − 2. This result brings the algorithmic bound to within a constant factor of the hardness bound of Bezakova and co-workers which showed that it is NP-hard to approximately count independent sets on hypergraphs when Δ ≥ 5·2k/2.Financial support by the EPSRC grant EP/L018896/1 (J.H.)
Metric Construction, Stopping Times and Path Coupling
In this paper we examine the importance of the choice of metric in path
coupling, and the relationship of this to \emph{stopping time analysis}. We
give strong evidence that stopping time analysis is no more powerful than
standard path coupling. In particular, we prove a stronger theorem for path
coupling with stopping times, using a metric which allows us to restrict
analysis to standard one-step path coupling. This approach provides insight for
the design of non-standard metrics giving improvements in the analysis of
specific problems.
We give illustrative applications to hypergraph independent sets and SAT
instances, hypergraph colourings and colourings of bipartite graphs.Comment: 21 pages, revised version includes statement and proof of general
stopping times theorem (section 2.2), and additonal remarks in section
Counting hypergraph matchings up to uniqueness threshold
We study the problem of approximately counting matchings in hypergraphs of
bounded maximum degree and maximum size of hyperedges. With an activity
parameter , each matching is assigned a weight .
The counting problem is formulated as computing a partition function that gives
the sum of the weights of all matchings in a hypergraph. This problem unifies
two extensively studied statistical physics models in approximate counting: the
hardcore model (graph independent sets) and the monomer-dimer model (graph
matchings).
For this model, the critical activity
is the threshold for the uniqueness of Gibbs measures on the infinite
-uniform -regular hypertree. Consider hypergraphs of maximum
degree at most and maximum size of hyperedges at most . We show that
when , there is an FPTAS for computing the partition
function; and when , there is a PTAS for computing the
log-partition function. These algorithms are based on the decay of correlation
(strong spatial mixing) property of Gibbs distributions. When , there is no PRAS for the partition function or the log-partition
function unless NPRP.
Towards obtaining a sharp transition of computational complexity of
approximate counting, we study the local convergence from a sequence of finite
hypergraphs to the infinite lattice with specified symmetry. We show a
surprising connection between the local convergence and the reversibility of a
natural random walk. This leads us to a barrier for the hardness result: The
non-uniqueness of infinite Gibbs measure is not realizable by any finite
gadgets
Path Coupling Using Stopping Times and Counting Independent Sets and Colourings in Hypergraphs
We give a new method for analysing the mixing time of a Markov chain using
path coupling with stopping times. We apply this approach to two hypergraph
problems. We show that the Glauber dynamics for independent sets in a
hypergraph mixes rapidly as long as the maximum degree Delta of a vertex and
the minimum size m of an edge satisfy m>= 2Delta+1. We also show that the
Glauber dynamics for proper q-colourings of a hypergraph mixes rapidly if m>= 4
and q > Delta, and if m=3 and q>=1.65Delta. We give related results on the
hardness of exact and approximate counting for both problems.Comment: Simpler proof of main theorem. Improved bound on mixing time. 19
page
Towards derandomising Markov chain Monte Carlo
We present a new framework to derandomise certain Markov chain Monte Carlo
(MCMC) algorithms.
As in MCMC, we first reduce counting problems to sampling from a sequence of
marginal distributions.
For the latter task,
we introduce a method called coupling towards the past that can, in
logarithmic time,
evaluate one or a constant number of variables from a stationary Markov chain
state.
Since there are at most logarithmic random choices, this leads to very simple
derandomisation.
We provide two applications of this framework, namely efficient deterministic
approximate counting algorithms for hypergraph independent sets and hypergraph
colourings,
under local lemma type conditions matching, up to lower order factors, their
state-of-the-art randomised counterparts.Comment: 57 page
Approximate Counting, the Lovasz Local Lemma and Inference in Graphical Models
In this paper we introduce a new approach for approximately counting in
bounded degree systems with higher-order constraints. Our main result is an
algorithm to approximately count the number of solutions to a CNF formula
when the width is logarithmic in the maximum degree. This closes an
exponential gap between the known upper and lower bounds.
Moreover our algorithm extends straightforwardly to approximate sampling,
which shows that under Lov\'asz Local Lemma-like conditions it is not only
possible to find a satisfying assignment, it is also possible to generate one
approximately uniformly at random from the set of all satisfying assignments.
Our approach is a significant departure from earlier techniques in approximate
counting, and is based on a framework to bootstrap an oracle for computing
marginal probabilities on individual variables. Finally, we give an application
of our results to show that it is algorithmically possible to sample from the
posterior distribution in an interesting class of graphical models.Comment: 25 pages, 2 figure
Positive independence densities of finite rank countable hypergraphs are achieved by finite hypergraphs
The independence density of a finite hypergraph is the probability that a
subset of vertices, chosen uniformly at random contains no hyperedges.
Independence densities can be generalized to countable hypergraphs using
limits. We show that, in fact, every positive independence density of a
countably infinite hypergraph with hyperedges of bounded size is equal to the
independence density of some finite hypergraph whose hyperedges are no larger
than those in the infinite hypergraph. This answers a question of Bonato,
Brown, Kemkes, and Pra{\l}at about independence densities of graphs.
Furthermore, we show that for any , the set of independence densities of
hypergraphs with hyperedges of size at most is closed and contains no
infinite increasing sequences.Comment: To appear in the European Journal of Combinatorics, 12 page