Structural Depth Theory: Constraint Geometry of Complex System Evolution

Structural Depth Theory (SDT) is a constraint-geometric framework for analyzing the long-run evolution of complex systems, including economic, thermodynamic, and information-based structures. The model formalizes system dynamics through three core state variables: constraint density (Θ), accessible state-space volume (Ω), and internal coordination time (τ). These variables describe how structural constraints accumulate over time, reducing configurational freedom and degrading signal clarity within bounded systems. Unlike equilibrium-based or stochastic models, SDT treats system evolution as a geometric contraction process driven by endogenous constraint accumulation. As constraint density increases, systems exhibit nonlinear contraction of accessible state-space, increased synchronization friction, and asymptotic movement toward critical phase transition thresholds. The framework is intended as a structural and asymptotic description of complex system behavior, not a short-term predictive model. It provides a unified way to interpret structural collapse, regime shifts, and long-horizon systemic transitions across multiple domains. This work is part of the Structural Depth Theory research series developed under the broader marketalchemy.io framework.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-29
DOI
https://doi.org/10.5281/zenodo.20451871
Primary Topic
Complex Systems and Decision Making
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Structural Depth Theory: Constraint Geometry of Complex System Evolution

Halil İbrahim GÜVEN
Zenodo (CERN European Organization for Nuclear Research)
Complex Systems and Decision Making
preprint

Structural Depth Theory: Constraint Geometry of Complex System Evolution

Halil İbrahim GÜVEN
preprint en

Abstract

Structural Depth Theory (SDT) is a constraint-geometric framework for analyzing the long-run evolution of complex systems, including economic, thermodynamic, and information-based structures. The model formalizes system dynamics through three core state variables: constraint density (Θ), accessible state-space volume (Ω), and internal coordination time (τ). These variables describe how structural constraints accumulate over time, reducing configurational freedom and degrading signal clarity within bounded systems. Unlike equilibrium-based or stochastic models, SDT treats system evolution as a geometric contraction process driven by endogenous constraint accumulation. As constraint density increases, systems exhibit nonlinear contraction of accessible state-space, increased synchronization friction, and asymptotic movement toward critical phase transition thresholds. The framework is intended as a structural and asymptotic description of complex system behavior, not a short-term predictive model. It provides a unified way to interpret structural collapse, regime shifts, and long-horizon systemic transitions across multiple domains. This work is part of the Structural Depth Theory research series developed under the broader marketalchemy.io framework.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Complex Systems and Decision Making
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.