A Computational Approach to Finding the Diameter of a Cayley Digraph of Sn Jordan Almeter April 16, 2015 Basic definitions A Cayley digraph is defined on a group G with a generator set S ⊆ G such that, for every s ∈ S and a, b ∈ G , if as = b, then there is an edge from a to b. Note that this does not mean there is a path from b to a. The distance between two vertices in a graph is the length of the shortest path between these vertices, and the diameter is the largest distance in a graph. Importance of diameter In any Cayley digraph, we may write that a path from the identity to some element x gives us a factorization of x, where every element in the factorization is from the generator set. In the case of sorting algorithms, the diameter gives us the maximum number of steps necessary to sort a list of values. A Computational Approach How do we go about computing with permutations in a Cayley digraph?? I We need a function T : Sn → Zn! to use as a hash function, for indexing I We need a data structure which can be stored on a typical hard drive I Given the size of these graphs, a by hand analysis of the entire graph is impractical. Can we generate a smaller graph which gives us the information we need yet is still easily understood? The function T : Sn → Zn! Consider that, from a combinatorics perspective, there are n choices for the first element in x, n − 1 choices for the second element, and so on. Conceptually, we can say that T (x) is equal to (n − 1)! times the first choice, plus T of the rest of the permutation. We can say T ([a1 , a2 , . . . , an ]) = a1 (n − 1)! + T ([g (a2 , x), g (a3 , x), . . . g (an , x)]), where g (a, b) = a if a < b, and g (a, b) = a − 1 if a ≥ b. There is an inverse function, T −1 , which we can find computationally. Unfortunately, there are no isomorphisms between Sn and Zn! , so operations like T (x1 ) ∗ T (x2 ) do not give meaningful results. Computational limits of data structures The largest integer that can be stored in 32-bit is 231 − 1 = 2147483647. The largest factorial standard math packages can handle is 12!. For n > 12, we must use 64 bit integers. The smallest possible representation for a k-regular (each vertex has k neighbors) Cayley digraph is n! indices, each with k 64 bit digit integers representing its neighbors. For n = 13, this representation would require ≈ 400k gigabytes. For k > 1, this becomes an unfeasible amount of space for a consumer-level hard drive, and n > 13 is an order of magnitude higher. An adjacency matrix can be constructed with n!2 bits, which would require over 16 GB when n = 9, and is unreasonably large for n > 9. Computational limits: Array of distances Assuming that the diameter of a graph is a reasonable number, say less than 256, then we can create an array of length n! which has one byte per entry. Each entry stores the distance between that vertex and the identity. For n = 12, this requires almost 0.5 GB, and for n = 13, over 6 GB. In addition, it is possible to calculate this array without a separate data structure for depth-first search; set every element to a value of −1, and use this as a control value for a breadth-first search. This is computationally expensive, and requires about 15 minutes for n = 12 on my personal computer, but it minimizes memory storage. Digraphs of interest: hL, S, L−1 i and hL, Si In Sn , we define L = (0 1 2 . . . n − 1), and S = (0 1). Values for the diameter of each graph are determined as follows. Note that the value 87 is not available on oeis; the relevant sequences are A039745 and A186783 on the online encyclopedia of integer sequences. Also note that the values in the second row follow n2 . It is a conjecture shared by Professor Li and others that this is true for all n. Diameter for Sn hL, Si hL, S, L−1 i S2 1 1 S3 2 2 S4 6 6 S5 11 10 S6 18 15 S7 25 21 S8 35 28 S9 45 36 S10 58 45 S11 71 55 S12 87 66 New conjectures on the diameter of hL, Si From the numbers we have, we can make the following observations, and hypothesize that the pattern will continue: I For L, S and L, S, L−1 , most patterns treat S3 as an exception. I For L, S, the even and odd values fall on different parabolas for n 6= 3, 4 and n ≤ 12. For odd values of n we can d = 3n2 /4 − 2n + 9/4, and for even values of n, we know d = 3n2 /4 − 2n + 3. The proposed conjecture is that this pattern continues. I For n > 4, we can say d = b3n2 /4 − 2n + 3c = d3n2 /4 − 2n + 9/4e I Another n > 4, the diameter of L, S is formula: for n−4 cb d = n2 + b n−1 2 2 c + 1 for n > 4 hL, S, L−1 i and hL, Si For these graphs, we can ask how many different vertices are the maximum distance away from the identity? The graph below shows computed values for these. Number of vertices with maximum distance from identity hL, Si hL, S, L−1 i S2 1 1 S3 3 2 S4 3 1 S5 2 1 S6 1 1 S7 2 1 S8 1 1 S9 2 1 S10 1 1 S11 2 1 S12 1 1 Creating simple metrics For any n greater than 24, a list of the distance of each vertex from 0 becomes difficult to analyze by hand, so we can attempt to generate more useful metrics. Of interest are the permutations which are of maximum distance from the identity, as well as the paths that connect the identity to these vertices, and the factorizations that each represents. A metric which combines all of these is presented for select values of n. Paths of incrementing distance A path of incrementing distance is defined here as one where the distance from the identity for each vertex is one greater than the vertex preceding it. A maximum incrementing path is one whose final vertex v is the maximum possible distance from the identity. If we take the union of all maximum incrementing distance paths, we have a subgraph showing the paths leading to the vertices furthest from the identity. Call this subgraph the distance incrementing subgraph. Distance Incrementing Subgraph visualization This is a simple case, where n = 3. LSL−1 , n = 3 3 0 LS, n = 3 5 2 4 0 1 2 1 3 4 5 LS, n = 4 6 3 17 23 14 7 4 21 8 12 1 11 13 0 18 9 16 22 LS,n = 4 Factorizations: SLLSLL, LLSLLS, LLSLLL, SLSLLS, LLLSLS, SLSLLL, LLLSLL, SLLSLS LS, n = 5 0 64 90 96 18 105 45 112 60 57 40 82 42 99 8 50 13 113 62 33 73 4 79 28 32 21 91 98 20 111 56 37 LS, n = 5 Maximum factorizations: LLLLSLSLLLL, LSLSLLLSLSL, LSLSLLSLLLL, LSLLLSLLLSL, LLLLSLLSLSL LS, n = 6 0 263 LS, n = 6 Maximum factorizations: SLSLLSLLSLSLSLLLLL, SLSLLSLSLLLLLSLLLL, SLLLSLSLLLSLLSLLLL, LLLSLSLLSLSLLSLLLL, SLSLLLLSLSLSLLSLLL, SLSLLLSLLLLLSLSLLL, SLLLLSLLLSLLSLSLLL, LLLLSLLSLSLLSLSLLL, SLLSLSLLSLSLLSLLSL, SLLLSLLSLSLLSLSLSL, SLLLSLLSLSLSLLLLLS, SLLLSLSLLLLLSLLLLS, LLLSLSLLSLLLSLLLLS, LSLSLSLLSLSLLSLLLS, SLLLLLSLSLSLLSLLLS, SLLLLSLLLLLSLSLLLS, LLLLSLLSLLLSLSLLLS, LSLLSLLSLSLLSLSLLS, LLLSLLSLSLSLLLLSLS, LLLSLSLLLLLSLLLSLS, LLLLLSLSLSLLSLLSLS, LLLLSLLLLLSLSLLSLS LSL−1 , n = 4 6 0 18 9 3 17 20 13 23 4 21 8 16 22 11 15 2 12 10 19 14 1 5 7 LSL−1 , n = 4 The following is a list of all factorizations of the maximum value (1 0 3 2 ): SLLSLL, SRRSLL, RSLLSL, SLSRSL, RSRRSL, LLSLLS, RRSLLS, LSRSLS, RSLSRS, LLSRRS, RRSRRS, LSLLSR, SRSLSR, LSRRSR, SLLSRR, SRRSRR LSL−1 , n = 5 0 24 102 42 99 21 113 62 86 55 96 9 92 116 71 117 80 31 5 33 18 51 16 93 38 53 49 23 90 76 61 85 11 84 47 57 105 45 112 60 7 101 64 114 70 115 74 107 119 40 91 35 59 118 88 66 97 19 43 6 48 108 94 14 65 89 68 103 95 82 63 87 30 54 110 29 LSL−1 , n = 5 SRSLSLLSLL, SRRSRSLSLL, SLSLLSLLSL, RSRSLSLLSL, RSRRSRSLSL, SRRSRRSRSL, RSLSLLSLLS, RRSRSLSLLS, LSLLSLLSLS, RRSRRSRSLS, LLSLLSLSRS, RSRRSRRSRS, LLSLSRSRRS, LSRSRRSRRS, SLLSLLSLSR, LSLLSLSRSR, LSLSRSRRSR, SRSRRSRRSR, SLLSLSRSRR, SLSRSRRSRR Swapping adjacent vertices, n = 4 The graph here is using the generating set of permutations swapping adjacent values. While this set’s behavior is well understood, its inclusion here illustrates that this metric applies to all Cayley digraphs on Sn . 0 6 8 9 15 17 2 12 14 16 21 1 3 13 11 22 7 10 20 4 18 19 5 23 Conclusion I The extreme size of Sn makes a Cayley digraph impossible to compute for large values of n. I Even when n is less than 12, understanding the structure of a Cayley digraph difficult to understand I I propose the distance incrementing subgraph as a new metric for understanding the structure of a Cayley digraph
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