Succinct Planar Encoding with Minor Operations
Frank Kammer, Johannes Meintrup

TL;DR
This paper introduces a space-efficient data structure for planar graphs that supports minor operations like edge contractions and vertex deletions in linear time, enabling fast queries and modifications.
Contribution
It combines existing techniques with novel ideas to create a succinct encoding supporting minor operations efficiently, partially answering prior open questions.
Findings
Supports induced-minor operations in O(n) time
Provides constant time neighborhood and degree queries
Supports edge deletions with expected O(n) time
Abstract
Let be an unlabeled planar and simple -vertex graph. Unlabeled graphs are graphs where the label-information is either not given or lost during the construction of data-structures. We present a succinct encoding of that provides induced-minor operations, i.e., edge contractions and vertex deletions. Any sequence of such operations is processed in time in the word-RAM model. At all times the encoding provides constant time (per element output) neighborhood access and degree queries. Optional hash tables extend the encoding with constant expected time adjacency queries and edge-deletion (thus, all minor operations are supported) such that any number of edge deletions are computed in expected time. Constructing the encoding requires bits and time. The encoding requires bits of space with being the entropy of…
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