The Shape of Chocolate: A Topological Perspective on Food Microstructure
Matteo Rucco

TL;DR
This paper introduces a topological data analysis framework to characterize cocoa butter microstructure during chocolate tempering, revealing distinctive topological signatures for optimal crystallization phases.
Contribution
It applies persistent homology and entropy measures to molecular simulations, providing a novel, non-invasive method to identify phase transitions in chocolate tempering.
Findings
Form V shows a local minimum in persistent entropy and beta_1, indicating optimal tempering.
Topological metrics successfully distinguish between different cocoa butter phases.
Persistent entropy correlates with phase transitions, validating TDA as a quality indicator.
Abstract
We present a computational framework for characterizing the molecular self-organization of cocoa butter (Theobroma cacao) during dark chocolate tempering through the lens of Topological Data Analysis (TDA). A physics-inspired particle simulation models N=100 triglyceride molecules across the full temperature range 15--60 degrees C, spanning all six crystalline polymorphs of cocoa butter (Forms I--VI) as well as the melt and superheating regimes. At each temperature tick, we construct a Vietoris-Rips filtration and compute the persistent homology groups H0 (connected components), H1 (independent cycles), and H2 (3D voids). The resulting persistence diagrams are analyzed via persistent entropy E = -sum_i p_i log2(p_i), where p_i = l_i / sum_j l_j and l_i = death_i - birth_i denotes feature lifetime; essential classes are assigned death = m+1 (m = eps_max) following the standard persistent…
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