Rank Distribution and Dynamics of Gram Matrices from Binary m-Sequences with Applications to LCD Codes
Hengfeng Liu, Chunming Tang, Cuiling Fan, Zhengchun Zhou

TL;DR
This paper analyzes the rank distribution and dynamic behavior of Gram matrices derived from binary m-sequences, revealing structural properties and applications to LCD codes.
Contribution
It provides an explicit formula for the rank of Gram matrices from m-sequences and characterizes their global distribution and local dynamics.
Findings
Full rank occurs for about half of the t values.
Rank-deficient states are strictly unstable.
Full-rank states persist over intervals of t.
Abstract
The Gram matrix is a classical object formed from the pairwise inner products of a collection of vectors, with fundamental roles in functional analysis, statistics, combinatorics, and coding theory. In the realm of sequence design, maximum-length sequences (m-sequences) are among the most fundamental classes of sequences, traditionally characterized by their span, decimation, shift-and-add, balance, run, and ideal autocorrelation properties. In this paper, we bridge the two foundational concepts by uncovering novel structural features of m-sequences through the lens of a family of Gram matrices. Specifically, for each , we extract consecutive subsequences of length from an m-sequence of period , construct their corresponding Gram matrix, and investigate its rank, denoted by . Utilizing semilinear representation of Galois…
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