What is the purpose of Cohomological Obstructions (H⁰)?

H⁰ detects failures in local-to-global gluing, identifying cases where snapshots of temporal data cannot be merged into a consistent global narrative.

How does the Adhesion Filter improve performance?

It uses a Fixed-Parameter Tractable (FPT) algorithm to reduce complexity from exponential to linear (O(f(w) · n)) for data structured via tree decompositions.

Can this skill be used for data visualization?

Yes, it integrates with Gay.jl to apply deterministic color-coding to temporal intervals, making complex diagrams and narratives easier to interpret.

What are Bumpus Narratives in the context of data modeling?

Bumpus Narratives represent time-varying data as sheaves on time categories, allowing for formal, compositional reasoning about how data structures change over discrete or continuous intervals.

How does it handle triadic balance?

It implements GF(3) naturality, ensuring that narrative operations like restriction and extension satisfy triadic equations to maintain compositional coherence.

Bumpus Narratives

Name: Bumpus Narratives
Author: plurigrid

byplurigrid

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Data Science & ML

Models and analyzes time-varying data using sheaves on time categories for compositional temporal reasoning.

About

Bumpus Narratives is a highly specialized skill designed for advanced temporal data modeling and analysis within the Claude Code environment. Based on the categorical research of B.M. Bumpus, it implements sheaves on time categories to facilitate structured reasoning about data that evolves across intervals. The skill utilizes sophisticated mathematical techniques such as the Adhesion Filter (FPT algorithm) for efficient tree decompositions and Cech cohomology to detect local-to-global consistency obstructions. It is an essential tool for developers and data scientists working with complex, time-dependent systems that require formal verification and compositional coherence.

Key Features

Sheaf-based modeling for structured temporal data intervals
Cohomological obstruction detection via H⁰ analysis
2 GitHub stars
Deterministic narrative visualization with Gay.jl color chains
Adhesion Filter (FPT) for efficient data consistency checking
Triadic composition support for GF(3) conservation and balance

Use Cases

Verifying consistency across distributed time-varying datasets
Modeling organizational transitions like mergers, acquisitions, and supply chain evolutions
Implementing compositional algorithms on complex tree-structured decompositions

About

Key Features

Sheaf-based modeling for structured temporal data intervals
Cohomological obstruction detection via H⁰ analysis
2 GitHub stars
Deterministic narrative visualization with Gay.jl color chains
Adhesion Filter (FPT) for efficient data consistency checking
Triadic composition support for GF(3) conservation and balance

Use Cases

Verifying consistency across distributed time-varying datasets
Modeling organizational transitions like mergers, acquisitions, and supply chain evolutions
Implementing compositional algorithms on complex tree-structured decompositions