Examples of using Sparse graphs in English and their translations into Russian
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Many natural families of sparse graphs have bounded expansion.
Therefore, the graphs with bounded Hadwiger number are sparse graphs.
Thus, the pseudoforests are the(1,0)-sparse graphs, and the maximal pseudoforests are the(1,0)-tight graphs. .
In this way, the biclique-free graph families unify two of the most general classes of sparse graphs.
For sparse graphs, it may be more efficient to repeatedly apply a single-source widest path algorithm.
A family of graphs is said to have bounded expansion if all of its shallow minors are sparse graphs.
Therefore, for every family of sparse graphs, having bounded treewidth is equivalent to having bounded clique-width.
In graph theory, isoperimetric inequalities are at the heart of the study of expander graphs, which are sparse graphs that have strong connectivity properties.
Pseudoforests are exactly the(1,0)-sparse graphs, and the Laman graphs arising in rigidity theory are exactly the(2,3)-tight graphs. .
The time per maximal independent set is proportional to that for matrix multiplication in dense graphs, orfaster in various classes of sparse graphs.
In graph theory, the Laman graphs are a family of sparse graphs describing the minimally rigid systems of rods and joints in the plane.
Some sparse graphs do not have separators of sublinear size: in an expander graph, deleting up to a constant fraction of the vertices still leaves only one connected component.
The same notation can be used to describe other important families of sparse graphs, including trees, pseudoforests, and graphs of bounded arboricity.
Thus, in their notation, the Laman graphs are exactly the(2,3)-tight graphs, andthe subgraphs of the Laman graphs are exactly the(2,3)-sparse graphs.
Thus trees are exactly the(1,1)-tight graphs, forests are exactly the(1,1)-sparse graphs, and graphs with arboricity k are exactly the(k, k)-sparse graphs.
Graphs with low queue number are sparse graphs: 1-queue graphs with n vertices have at most 2n- 3 edges, and more generally graphs with queue number q have at most 2qn- q(2q+ 1) edges.
Biclique-free graphs have been used in parameterized complexity to develop algorithms that are efficient for sparse graphs with suitably small input parameter values.
Pseudoforests are sparse graphs- they have very few edges relative to their number of vertices- and their matroid structure allows several other families of sparse graphs to be decomposed as unions of forests and pseudoforests.
A faster implementation of the algorithm due to Robert Tarjan runs in time O( E log V){\displaystyle O(E\log V)} for sparse graphs and O( V 2){\displaystyle O(V^{2})} for dense graphs. .
A shallow minor of a k-planar graph, with depth d, is itself a(2d+ 1)k-planar graph, so the shallow minors of 1-planar graphs andof k-planar graphs are also sparse graphs, implying that the 1-planar and k-planar graphs have bounded expansion.
Several other important families of graphs may be defined from other values of k and l, and when l≤ k the(k,l)-sparse graphs may be characterized as the graphs formed as the edge-disjoint union of l forests and k- l pseudoforests.
However, not every(3,6)-sparse graph is planar.
The biclique-free graph families form one of the most general types of sparse graph family.
More generally, for any graph with degeneracy d and maximum degree Δ, the degeneracy of the square of the graph is O(dΔ),so many types of sparse graph other than the planar graphs also have squares whose chromatic number is proportional to Δ.
Every shallow minor of a graph of bounded book thickness is a sparse graph, whose ratio of edges to vertices is bounded by a constant that depends only on the depth of the minor and on the book thickness.
For instance, Cook& Seymour(2003)apply branchwidth-based dynamic programming to a problem of merging multiple partial solutions to the travelling salesman problem into a single global solution, by forming a sparse graph from the union of the partial solutions, using a spectral clustering heuristic to find a good branch-decomposition of this graph, and applying dynamic programming to the decomposition.
Graphs that are the complement of a sparse graph have small intersection numbers: the intersection number of any n-vertex graph G is at most 2e2(d+ 1)2ln n, where e is the base of the natural logarithm and d is the maximum degree of the complement graph of G. Testing whether a given graph G has intersection number at most a given number k is NP-complete.
The distinction between sparse and dense graphs is rather vague, and depends on the context.
Gamarnik et al. use a linear time algorithm for solving the problem on trees to study the asymptotic number of edges that must be added for sparse random graphs to make them Hamiltonian.