Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Random sampling of colourings of sparse random graphs with a constant
  number of colours   In this work we present a simple and efficient algorithm which, with high
probability, provides an almost uniform sample from the set of proper
k-colourings on an instance of a sparse random graph G(n,d/n), where k=k(d) is
a sufficiently large constant. Our algorithm is not based on the Markov Chain
Monte Carlo method (M.C.M.C.). Instead, we provide a novel proof of correctness
of our Algorithm that is based on interesting "spatial mixing" properties of
colourings of G(n,d/n). Our result improves upon previous results (based on
M.C.M.C.) that required a number of colours growing unboundedly with n.

3
The categories of this paper are: physics
6
The categories of this paper are: astro-ph
30
The categories of this paper are: q-alg
25
The categories of this paper are: patt-sol
34
The categories of this paper are: chem-ph
36
The categories of this paper are: cmp-lg
24
The categories of this paper are: dg-ga
8
The categories of this paper are: hep-ex
35
The categories of this paper are: mtrl-th
13
The categories of this paper are: quant-ph
23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph
18
The categories of this paper are: econ
7
The categories of this paper are: hep-th
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat