An Informational Perspective on Geometric Phase Transitions and Polymorphism

This repository contains the finalized manuscript and the accompanying computational models for "An Informational Perspective on Geometric Phase Transitions and Polymorphism." This work proposes a complementary theoretical framework to classical thermodynamics, treating the local thermal environment as a continuous Shannon channel. By applying Landauer’s Principle and introducing the Landauer Inverse, the models demonstrate how pressure-induced polymorphism and macroscopic phase boundaries (such as the anomalous transitions of water) can be mathematically mapped as the continuous minimization of Shannon entropy under environmental constraint. Repository Contents: Informational_Polymorphism.pdf: The full master manuscript detailing the theoretical framework, the 6-bit geometric constraint for capacity collapse, and tectonic warping. 01 Geometric Relaxation Lambda.ipynb: A Python Jupyter Notebook detailing the rigid 6-bit geometric capacity collapse of a non-linear molecule (benzene), including ideal tensor mapping and N=10,000 statistical ensemble simulations. 02_Water_Polymorphism.ipynb: A Python Jupyter Notebook mapping the complex thermodynamic routing of Ice Ih, Liquid Water, and Ice VII under extreme scaling pressure. Instructions for Reproducibility: To ensure methodological transparency, the computational models provided herein are fully deterministic, mathematically falsifiable, and designed for rapid independent replication. Researchers are encouraged to download the native .ipynb files and run them in a standard Python environment (requiring only numpy and matplotlib libraries). The code is structured sequentially. By executing the cells in order, users can immediately verify the ideal mathematical phase boundaries and independently manipulate the localized thermal variance (noise) parameters to observe the resulting macroscopic sigmoidal transitions.