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In
graph theory In mathematics, graph theory is the study of '' graphs'', which are mathematical structures used to model pairwise relations between objects. A graph in this context is made up of '' vertices'' (also called ''nodes'' or ''points'') which are conn ...
, a branch of mathematics, the linear arboricity of an undirected graph is the smallest number of linear forests its edges can be partitioned into. Here, a linear forest is an acyclic graph with maximum
degree Degree may refer to: As a unit of measurement * Degree (angle), a unit of angle measurement ** Degree of geographical latitude ** Degree of geographical longitude * Degree symbol (°), a notation used in science, engineering, and mathemati ...
two; that is, it is a
disjoint union In mathematics, a disjoint union (or discriminated union) of a family of sets (A_i : i\in I) is a set A, often denoted by \bigsqcup_ A_i, with an injection of each A_i into A, such that the images of these injections form a partition of A ...
of
path graph In the mathematical field of graph theory, a path graph or linear graph is a graph whose vertices can be listed in the order such that the edges are where . Equivalently, a path with at least two vertices is connected and has two terminal ...
s. Linear arboricity is a variant of
arboricity The arboricity of an undirected graph is the minimum number of forests into which its edges can be partitioned. Equivalently it is the minimum number of spanning forests needed to cover all the edges of the graph. The Nash-Williams theorem pro ...
, the minimum number of forests into which the edges can be partitioned. The linear arboricity of any graph of maximum degree \Delta is known to be at least \lceil\Delta/2\rceil and is conjectured to be at most \lceil(\Delta+1)/2\rceil. This conjecture would determine the linear arboricity exactly for graphs of odd degree, as in that case both expressions are equal. For graphs of even degree it would imply that the linear arboricity must be one of only two possible values, but determining the exact value among these two choices is
NP-complete In computational complexity theory, a problem is NP-complete when: # it is a problem for which the correctness of each solution can be verified quickly (namely, in polynomial time) and a brute-force search algorithm can find a solution by tryin ...
.


Relation to degree

The linear arboricity of a graph G with maximum degree \Delta is always at least \lceil\Delta/2\rceil, because each linear forest can use only two of the edges at a maximum-degree vertex. The linear arboricity conjecture of is that this lower bound is also tight: according to their conjecture, every graph has linear arboricity at most \lceil(\Delta+1)/2\rceil. However, this remains unproven, with the best proven
upper bound In mathematics, particularly in order theory, an upper bound or majorant of a subset of some preordered set is an element of that is greater than or equal to every element of . Dually, a lower bound or minorant of is defined to be an elem ...
on the linear arboricity being somewhat larger, \Delta/2 + O(\Delta^) for some constant c> 0 due to Ferber, Fox and Jain. In order for the linear arboricity of a graph to equal \Delta/2, \Delta must be even and each linear forest must have two edges incident to each vertex of degree \Delta. But at a vertex that is at the end of a path, the forest containing that path has only one incident edge, so the degree at that vertex cannot equal \Delta. Thus, a graph whose linear arboricity equals \Delta/2 must have some vertices whose degree is less than maximum. In a
regular graph In graph theory, a regular graph is a graph where each vertex has the same number of neighbors; i.e. every vertex has the same degree or valency. A regular directed graph must also satisfy the stronger condition that the indegree and outdegre ...
, there are no such vertices, and the linear arboricity cannot equal \Delta/2. Therefore, for regular graphs, the linear arboricity conjecture implies that the linear arboricity is exactly \lceil(\Delta+1)/2\rceil.


Related problems

Linear arboricity is a variation of
arboricity The arboricity of an undirected graph is the minimum number of forests into which its edges can be partitioned. Equivalently it is the minimum number of spanning forests needed to cover all the edges of the graph. The Nash-Williams theorem pro ...
, the minimum number of forests that the edges of a graph can be partitioned into. Researchers have also studied linear -arboricity, a variant of linear arboricity in which each path in the linear forest can have at most edges. Another related problem is Hamiltonian decomposition, the problem of decomposing a
regular graph In graph theory, a regular graph is a graph where each vertex has the same number of neighbors; i.e. every vertex has the same degree or valency. A regular directed graph must also satisfy the stronger condition that the indegree and outdegre ...
of even degree \Delta into exactly \Delta/2 Hamiltonian cycles. A given graph has a Hamiltonian decomposition if and only if the subgraph formed by removing an arbitrary vertex from the graph has linear arboricity \Delta/2.


Computational complexity

Unlike arboricity, which can be determined in
polynomial time In computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated by counting the number of elementary operations performed by ...
, linear arboricity is
NP-hard In computational complexity theory, NP-hardness ( non-deterministic polynomial-time hardness) is the defining property of a class of problems that are informally "at least as hard as the hardest problems in NP". A simple example of an NP-hard pr ...
. Even recognizing the graphs of linear arboricity two is
NP-complete In computational complexity theory, a problem is NP-complete when: # it is a problem for which the correctness of each solution can be verified quickly (namely, in polynomial time) and a brute-force search algorithm can find a solution by tryin ...
. However, for cubic graphs and other graphs of maximum degree three, the linear arboricity is always two, and a decomposition into two linear forests can be found in
linear time In computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm. Time complexity is commonly estimated by counting the number of elementary operations performed by t ...
using an algorithm based on
depth-first search Depth-first search (DFS) is an algorithm for traversing or searching tree or graph data structures. The algorithm starts at the root node (selecting some arbitrary node as the root node in the case of a graph) and explores as far as possible alo ...
.


References

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