Polynomial Time Computable Triangular Arrays For Almost Sure Convergence
Vladimir Dobric, Marina Skyers, Lee J. Stanley

TL;DR
This paper introduces a polynomial-time method to construct triangular arrays representing the almost sure convergence of normalized polarized binary expansions to the normal distribution, providing explicit, computationally feasible representations.
Contribution
It presents a novel construction of i.i.d. families that sum to quantile functions, classifies these by admissible permutations, and establishes their computational complexity bounds.
Findings
Constructed polynomial-time computable arrays for convergence representation
Established lower bounds on the complexity of admissible permutations
Provided explicit sequences with complexity bounded by SBC
Abstract
For 0 < x < 1, take the binary expansion with infinitely many 0's, replace each 0 with -1, this gives the polarized binary expansion of x. Let R_i(x) be the ith "polarized bit" and let S_n(x) be the sum of the first n R_i(x). {S_n} is the Z-valued random walk on (0,1). Normalize, by dividing each S_n by the square root of n: the resulting sequence converges weakly to the standard normal distribution on (0,1). The quantiles of S_n are random variables on (0,1), denoted S*_n, which are equal in distribution to the S_n, Skorokhod showed that the sequence of normalized quantiles converges almost surely to the standard normal distribution on (0,1). For n > 2, S*_n cannot be represented as the sum of the first n terms of a fixed sequence, R*_i, of random variables with the properties of the R_i. We introduce a method of constructing, for each n, an i.i.d family, R*_(n,1), ... R*_(n,n) which…
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