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  2. Kruskal–Szekeres coordinates - Wikipedia

    en.wikipedia.org/wiki/Kruskal–Szekeres_coordinates

    The Kruskal–Szekeres coordinates also apply to space-time around a spherical object, but in that case do not give a description of space-time inside the radius of the object. Space-time in a region where a star is collapsing into a black hole is approximated by the Kruskal–Szekeres coordinates (or by the Schwarzschild coordinates). The ...

  3. Kruskal's algorithm - Wikipedia

    en.wikipedia.org/wiki/Kruskal's_algorithm

    Kruskal's algorithm [1] finds a minimum spanning forest of an undirected edge-weighted graph. If the graph is connected , it finds a minimum spanning tree . It is a greedy algorithm that in each step adds to the forest the lowest-weight edge that will not form a cycle . [ 2 ]

  4. Korteweg–De Vries equation - Wikipedia

    en.wikipedia.org/wiki/Korteweg–De_Vries_equation

    Cnoidal wave solution to the Korteweg–De Vries equation, in terms of the square of the Jacobi elliptic function cn (and with value of the parameter m = 0.9). Numerical solution of the KdV equation u t + uu x + δ 2 u xxx = 0 (δ = 0.022) with an initial condition u(x, 0) = cos(πx). Time evolution was done by the Zabusky–Kruskal scheme. [1]

  5. Parallel algorithms for minimum spanning trees - Wikipedia

    en.wikipedia.org/wiki/Parallel_algorithms_for...

    Similarly to Prim's algorithm there are components in Kruskal's approach that can not be parallelised in its classical variant. For example, determining whether or not two vertices are in the same subtree is difficult to parallelise, as two union operations might attempt to join the same subtrees at the same time.

  6. Reverse-delete algorithm - Wikipedia

    en.wikipedia.org/wiki/Reverse-delete_algorithm

    It is the reverse of Kruskal's algorithm, which is another greedy algorithm to find a minimum spanning tree. Kruskal’s algorithm starts with an empty graph and adds edges while the Reverse-Delete algorithm starts with the original graph and deletes edges from it. The algorithm works as follows: Start with graph G, which contains a list of ...

  7. Multidimensional scaling - Wikipedia

    en.wikipedia.org/wiki/Multidimensional_scaling

    An R-square of 0.6 is considered the minimum acceptable level. [citation needed] An R-square of 0.8 is considered good for metric scaling and .9 is considered good for non-metric scaling. Other possible tests are Kruskal’s Stress, split data tests, data stability tests (i.e., eliminating one brand), and test-retest reliability.

  8. Schwarzschild coordinates - Wikipedia

    en.wikipedia.org/wiki/Schwarzschild_coordinates

    Depending on context, it may be appropriate to regard a and b as undetermined functions of the radial coordinate (for example, in deriving an exact static spherically symmetric solution of the Einstein field equation). Alternatively, we can plug in specific functions (possibly depending on some parameters) to obtain a Schwarzschild coordinate ...

  9. Distributed minimum spanning tree - Wikipedia

    en.wikipedia.org/wiki/Distributed_minimum...

    Example of a MST: The minimum spanning tree of a planar graph.Each edge is labeled with its weight, which here is roughly proportional to its length. The distributed minimum spanning tree (MST) problem involves the construction of a minimum spanning tree by a distributed algorithm, in a network where nodes communicate by message passing.