14,629 research outputs found
Faster Replacement Paths
The replacement paths problem for directed graphs is to find for given nodes
s and t and every edge e on the shortest path between them, the shortest path
between s and t which avoids e. For unweighted directed graphs on n vertices,
the best known algorithm runtime was \tilde{O}(n^{2.5}) by Roditty and Zwick.
For graphs with integer weights in {-M,...,M}, Weimann and Yuster recently
showed that one can use fast matrix multiplication and solve the problem in
O(Mn^{2.584}) time, a runtime which would be O(Mn^{2.33}) if the exponent
\omega of matrix multiplication is 2.
We improve both of these algorithms. Our new algorithm also relies on fast
matrix multiplication and runs in O(M n^{\omega} polylog(n)) time if \omega>2
and O(n^{2+\eps}) for any \eps>0 if \omega=2. Our result shows that, at least
for small integer weights, the replacement paths problem in directed graphs may
be easier than the related all pairs shortest paths problem in directed graphs,
as the current best runtime for the latter is \Omega(n^{2.5}) time even if
\omega=2.Comment: the current version contains an improved resul
Almost Shortest Paths with Near-Additive Error in Weighted Graphs
Let be a weighted undirected graph with vertices and
edges, and fix a set of sources . We study the problem of
computing {\em almost shortest paths} (ASP) for all pairs in in
both classical centralized and parallel (PRAM) models of computation. Consider
the regime of multiplicative approximation of , for an arbitrarily
small constant . In this regime existing centralized algorithms
require time, where is the
matrix multiplication exponent. Existing PRAM algorithms with polylogarithmic
depth (aka time) require work .
Our centralized algorithm has running time , and its PRAM
counterpart has polylogarithmic depth and work , for an
arbitrarily small constant . For a pair , it
provides a path of length that satisfies , where is the weight of the
heaviest edge on some shortest path. Hence our additive term depends
linearly on a {\em local} maximum edge weight, as opposed to the global maximum
edge weight in previous works. Finally, our .
We also extend a centralized algorithm of Dor et al. \cite{DHZ00}. For a
parameter , this algorithm provides for {\em unweighted}
graphs a purely additive approximation of for {\em all pairs
shortest paths} (APASP) in time . Within the same
running time, our algorithm for {\em weighted} graphs provides a purely
additive error of , for every vertex pair , with defined as above.
On the way to these results we devise a suit of novel constructions of
spanners, emulators and hopsets
Superdiffusion in a class of networks with marginal long-range connections
A class of cubic networks composed of a regular one-dimensional lattice and a
set of long-range links is introduced. Networks parametrized by a positive
integer k are constructed by starting from a one-dimensional lattice and
iteratively connecting each site of degree 2 with a th neighboring site of
degree 2. Specifying the way pairs of sites to be connected are selected,
various random and regular networks are defined, all of which have a power-law
edge-length distribution of the form with the marginal
exponent s=1. In all these networks, lengths of shortest paths grow as a power
of the distance and random walk is super-diffusive. Applying a renormalization
group method, the corresponding shortest-path dimensions and random-walk
dimensions are calculated exactly for k=1 networks and for k=2 regular
networks; in other cases, they are estimated by numerical methods. Although,
s=1 holds for all representatives of this class, the above quantities are found
to depend on the details of the structure of networks controlled by k and other
parameters.Comment: 10 pages, 9 figure
Evolution of networks
We review the recent fast progress in statistical physics of evolving
networks. Interest has focused mainly on the structural properties of random
complex networks in communications, biology, social sciences and economics. A
number of giant artificial networks of such a kind came into existence
recently. This opens a wide field for the study of their topology, evolution,
and complex processes occurring in them. Such networks possess a rich set of
scaling properties. A number of them are scale-free and show striking
resilience against random breakdowns. In spite of large sizes of these
networks, the distances between most their vertices are short -- a feature
known as the ``small-world'' effect. We discuss how growing networks
self-organize into scale-free structures and the role of the mechanism of
preferential linking. We consider the topological and structural properties of
evolving networks, and percolation in these networks. We present a number of
models demonstrating the main features of evolving networks and discuss current
approaches for their simulation and analytical study. Applications of the
general results to particular networks in Nature are discussed. We demonstrate
the generic connections of the network growth processes with the general
problems of non-equilibrium physics, econophysics, evolutionary biology, etc.Comment: 67 pages, updated, revised, and extended version of review, submitted
to Adv. Phy
Algebraic Methods in the Congested Clique
In this work, we use algebraic methods for studying distance computation and
subgraph detection tasks in the congested clique model. Specifically, we adapt
parallel matrix multiplication implementations to the congested clique,
obtaining an round matrix multiplication algorithm, where
is the exponent of matrix multiplication. In conjunction
with known techniques from centralised algorithmics, this gives significant
improvements over previous best upper bounds in the congested clique model. The
highlight results include:
-- triangle and 4-cycle counting in rounds, improving upon the
triangle detection algorithm of Dolev et al. [DISC 2012],
-- a -approximation of all-pairs shortest paths in
rounds, improving upon the -round -approximation algorithm of Nanongkai [STOC 2014], and
-- computing the girth in rounds, which is the first
non-trivial solution in this model.
In addition, we present a novel constant-round combinatorial algorithm for
detecting 4-cycles.Comment: This is work is a merger of arxiv:1412.2109 and arxiv:1412.266
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