This synthesis paper presents Dawn Field Theory--a framework that began as speculative exploration of cosmic information mining and evolved into systematic investigation across physics, artificial intelligence, and complex systems. What started as exploring "mining information from the universe" has become seven specialized research papers, working computational frameworks, and a novel approach to understanding reality's structure. The path from the original Cosmic Information Mining (CIM) thought experiment to these seven preprints has been unpredictable. Our framework proposes that information might drive reality's formation through recursive collapse events in dual energy-information fields, rather than merely describing existing structures. We test these ideas through computational studies in quantum systems, biological evolution, fluid dynamics, and AI architectures. Results suggest intriguing patterns warranting investigation. We work under an "imperfection engine" methodology--treating this repository as a living experiment designed to evolve through scrutiny and collaboration. We explicitly seek arXiv endorsement and global collaboration to help validate, extend, or properly refute these concepts. *Note: This work represents ongoing theoretical and computational exploration. While our results are promising, they require independent validation, peer review, and extension beyond computational studies. We present this framework as a research program for community investigation rather than established science.*

Version 2.0 Update - December 2025 This updated version adds a complete reproducibility package including executable code, raw data, and publication-quality figures. The theoretical content remains unchanged from v1.0. Original Abstract:This paper presents Dawn Field Theory as a unified framework synthesizing Symbolic Entropy Collapse (SEC), Recursive Balance Fields (RBF), and Potential-Actualization Conservation (PAC). Beginning with the Cosmic Information Mining Model (CIMM) and evolving through the Quantum Balance Equation (QBE), the framework addresses how structure emerges from information dynamics rather than the reverse. What's New in v2.0: Complete Python codebase for all simulations Raw experimental data in JSON format Publication-quality figures with generation scripts Reproducibility instructions and environment specification Package Contains: Paper (PDF + Markdown) Code/ - All simulation and analysis scripts Data/ - Raw experimental outputs Figures/ - All paper figures with source README with reproduction instructions