Succinct Representations of Permutations and Functions
J. Ian Munro, Rajeev Raman, Venkatesh Raman, S. Srinivasa Rao

TL;DR
This paper introduces space-efficient data structures for representing permutations and functions that enable quick computation of their powers, achieving near-optimal space and time complexities with minimal redundancy.
Contribution
It presents novel succinct representations for permutations and functions that support fast power computations, improving space efficiency and challenging existing lower bounds.
Findings
Achieves constant-time power computation with near-optimal space for permutations.
Provides a representation for functions supporting fast positive and negative power computations.
Demonstrates that some data structures surpass recent theoretical lower bounds on redundancy.
Abstract
We investigate the problem of succinctly representing an arbitrary permutation, \pi, on {0,...,n-1} so that \pi^k(i) can be computed quickly for any i and any (positive or negative) integer power k. A representation taking (1+\epsilon) n lg n + O(1) bits suffices to compute arbitrary powers in constant time, for any positive constant \epsilon <= 1. A representation taking the optimal \ceil{\lg n!} + o(n) bits can be used to compute arbitrary powers in O(lg n / lg lg n) time. We then consider the more general problem of succinctly representing an arbitrary function, f: [n] \rightarrow [n] so that f^k(i) can be computed quickly for any i and any integer power k. We give a representation that takes (1+\epsilon) n lg n + O(1) bits, for any positive constant \epsilon <= 1, and computes arbitrary positive powers in constant time. It can also be used to compute f^k(i), for any negative…
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Taxonomy
TopicsAlgorithms and Data Compression · Genome Rearrangement Algorithms · Coding theory and cryptography
