The "art of trellis decoding" is fixed-parameter tractable
Jisu Jeong, Eun Jung Kim, Sang-il Oum

TL;DR
This paper introduces a fixed-parameter tractable algorithm for constructing linear layouts of subspaces, which generalizes trellis decoding, matroid path-width, and graph linear rank-width, providing practical tools for these problems.
Contribution
It presents the first fixed-parameter tractable algorithm to explicitly construct linear layouts of width at most k for subspaces, matroids, and graphs, surpassing previous decision-only algorithms.
Findings
Algorithm constructs linear layouts efficiently for given width k.
Extends fixed-parameter tractability to explicit decompositions, not just decision.
Applicable to coding theory, matroid theory, and graph theory problems.
Abstract
Given n subspaces of a finite-dimensional vector space over a fixed finite field , we wish to find a linear layout of the subspaces such that for all i, such a linear layout is said to have width at most k. When restricted to 1-dimensional subspaces, this problem is equivalent to computing the trellis-width (or minimum trellis state-complexity) of a linear code in coding theory and computing the path-width of an -represented matroid in matroid theory. We present a fixed-parameter tractable algorithm to construct a linear layout of width at most k, if it exists, for input subspaces of a finite-dimensional vector space over . As corollaries, we obtain a fixed-parameter tractable algorithm to produce a path-decomposition of width at most k for an input -represented…
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