Stack-sorting with Stacks Avoiding Vincular Patterns
William Zhao

TL;DR
This paper introduces a new stack-sorting map avoiding vincular patterns, characterizes the sorted permutation classes, and explores properties like maximum preimage size and periodic points, extending previous pattern-avoidance sorting frameworks.
Contribution
It defines and analyzes a novel vincular pattern-avoiding stack-sorting map, characterizes sorted classes for specific patterns, and investigates key dynamical properties.
Findings
Characterized and enumerated sorting classes for seven length 3 patterns.
Determined when sorting classes form permutation classes.
Computed maximum preimage sizes and identified periodic points.
Abstract
We introduce the stack-sorting map that sorts, in a right-greedy manner, an input permutation through a stack that avoids some vincular pattern . The stack-sorting maps of Cerbai et al. in which the stack avoids a pattern classically and Defant and Zheng in which the stack avoids a pattern consecutively follow as special cases. We first characterize and enumerate the sorting class , the set of permutations sorted by , for seven length patterns . We also decide when is a permutation class. Next, we compute and characterize the periodic points of for several length patterns . We end with several conjectures and open problems.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAlgorithms and Data Compression · Image Retrieval and Classification Techniques · Machine Learning and Data Classification
