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Graph of the Kempner function In number theory , the Kempner function S ( n ) {\displaystyle S(n)} [ 1 ] is defined for a given positive integer n {\displaystyle n} to be the smallest number s {\displaystyle s} such that n {\displaystyle n} divides the factorial s ! {\displaystyle s!} .
In mathematics, the floor function is the function that takes as input a real number x, and gives as output the greatest integer less than or equal to x, denoted ⌊x⌋ or floor(x). Similarly, the ceiling function maps x to the least integer greater than or equal to x, denoted ⌈x⌉ or ceil(x). [1]
Example graph that has a vertex cover comprising 2 vertices (bottom), but none with fewer. In graph theory, a vertex cover (sometimes node cover) of a graph is a set of vertices that includes at least one endpoint of every edge of the graph. In computer science, the problem of finding a minimum vertex cover is a classical optimization problem.
However, specialized cases (such as bounded/integer weights, directed acyclic graphs etc.) can be improved further. If preprocessing is allowed, algorithms such as contraction hierarchies can be up to seven orders of magnitude faster. Dijkstra's algorithm is commonly used on graphs where the edge weights are positive integers or real numbers.
Carmichael λ function: λ(n) for 1 ≤ n ≤ 1000 (compared to Euler φ function) In number theory, a branch of mathematics, the Carmichael function λ(n) of a positive integer n is the smallest positive integer m such that holds for every integer a coprime to n.
Specifically, he considered functions of the form = + (), where a 0, b 0, ..., a P − 1, b P − 1 are rational numbers which are so chosen that g(n) is always an integer. The standard Collatz function is given by P = 2, a 0 = 1 / 2 , b 0 = 0, a 1 = 3, b 1 = 1. Conway proved that the problem
If n is the smallest nonnegative integer, such that for some i, j, the element (i, j) of A n is positive, then n is the distance between vertex i and vertex j. A great example of how this is useful is in counting the number of triangles in an undirected graph G , which is exactly the trace of A 3 divided by 3 or 6 depending on whether the graph ...
For a graph with E edges and V vertices, Kruskal's algorithm can be shown to run in time O(E log E) time, with simple data structures. Here, O expresses the time in big O notation , and log is a logarithm to any base (since inside O -notation logarithms to all bases are equivalent, because they are the same up to a constant factor).