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January 20, 20260 citationsOpen Access

Invariant Density in Mathematical Representations: A Syntactic Framework for Presentation Reduction

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DTDavid Gérard Tonnel

Key Points

  • The goal is to present a framework that reduces equational presentations by removing redundancies while maintaining important properties.
  • Developed a framework for syntactic reduction of equational presentations.
  • Identified and eliminated redundant relations to preserve derivable invariants.
  • Formalized invariant density as a key concept using measurable ratios.
  • Demonstrated monotonic density gains through invariant-preserving transforms.
  • Provided a framework that is constructive, deterministic, and relative to grammar.

Abstract

This work introduces a purely syntactic framework for reducing equational presentations by identifying and eliminating redundant relations while preserving all derivable invariants. It formalizes invariant density as a ratio between derivable relations and syntactic description length, and demonstrates how invariant-preserving transforms induce monotonic density gains under explicit derivability bounds. The framework is constructive, deterministic, and grammar-relative: all reductions are mechanically witnessed, no semantic interpretation is assumed, and no claims of optimality or completeness are made.

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Cite This Study

David Gérard Tonnel (2026) studied this question.

synapsesocial.com/papers/696f1a629e64f732b51eea7fhttps://doi.org/10.5281/zenodo.18283944
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