Unified Data Release & Source Code: Topological-Fluid Cosmological Model (TFCM) Alpha-Run at $2560^3$ Resolution

1. Abstract & Overview This repository archives the primary computational execution, empirical telemetry, downstream visualization pipelines, and core verification reporting for the Topological-Fluid Cosmological Model (TFCM) Alpha-Run. The simulation stress-tests the hypothesis that treating the primordial universe as a highly dense, visco-elastic substrate governed by non-linear scalar bounding natively drives the emergence of macroscopic structural order out of primordial chaos. Executed at an extreme native lattice resolution of $2560^3$, the computational engine tracks the non-linear fluidic evolution of over 1.05 billion localized bodies (Primordial Black Holes). Pushing the physical and memory limits of high-performance tensor core architectures, this resource maps the dynamic phase transition into a global equilibrium state termed the Mizaan (Balance), while analyzing discrete structural formations such as the 73-Resonance. 2. Core Implementation Strategy: The V&V Report To interpret the discrete logic executed by the computational engine correctly, reviewers and independent auditors must refer to the primary technical bridge document included in this release: Computational Physics V&V Report.pdf. Simulating continuous relativistic tensor calculus directly across 16.7 billion discrete spatial nodes inevitably triggers unconstrained localized mass accumulation, leading to singularity-induced numerical divergence (NaN generation). To ensure real-time stability and physical accuracy on GPU arrays, the codebase implements an effective phenomenological model: Non-Linear Bounding: Continuous manifold topology constraints are translated programmatically into an explicit quadratic dampening factor ($\rho - \rho^2$) acting as a dynamic gravitational brake against infinite density collapse. Array Regularization: Strict elementwise boundaries guarantee continuous gradient execution without overflow across massive half-precision (float16) memory buffers. 3. Repository File Structure This unified record contains the complete computational lifecycle, organized as follows: Primary Technical Documentation Computational Physics V&V Report.pdf: The definitive computational verification document mapping the theoretical mechanics to optimized discrete logic arrays, justifying hardware-specific scaling choices. Core Executable Logic Simulation_Engine_Mizaan_V2.py: The central simulation script utilizing CuPy, customized zero-allocation elementwise CUDA kernels, parallel multi-threading, and non-blocking asynchronous disk serialization. Visualization_Renderer_2.5K.py: The downstream analytics pipeline that ingests continuous array outputs to generate high-contrast 2D vorticity and density maps. Empirical Output & Telemetry Telemetry_H0_PBH_Logs.csv: Time-series logs tracking the discrete simulation step count, the dynamic global Hubble expansion parameter ($H_0$), and the absolute population count of localized PBH seeds. Visual_Evolution_2560_73Resonance.mp4: A continuous 2.5K high-definition render of the central 2D density plane spanning critical structural formation checkpoints (Steps 0–800). Raw_Slices_2560_Checkpoints.zip: Formatted float16 binary NumPy matrices (.npy) providing center-cut cross-sections of the global lattice geometry for independent structural auditing. Supporting Theoretical Framework (Appendix) 2026-04-04_TFCM_Preprint_Hamieh_v1.0.0.pdf (Main Summary) TFCM_Axiomatic_Computational_Framework.pdf (Axiomatic Core) TFCM_Simulation_Architecture_Technical_Specs.pdf (Tensor Mechanics) TFCM_Empirical_Data_Validation_Analysis.pdf (Astrophysical Alignment) ⚠️ VERSIONING NOTE: The four supporting theoretical preprints (v1.0.3) represent preliminary conceptual outlines. Bibliographic metadata, references, and automated citation mapping within these specific texts are currently undergoing manual auditing and structural revision. The functional baseline of the model is anchored strictly by the executed Source Code and the primary V&V Report. 4. Key Scientific Findings Dynamic Phase-Locking (Hubble Convergence): The non-linear regularizer successfully recycles chaotic initial kinetic energy, guiding the global expansion rate from an unconstrained starting condition ($H_0 \approx 41.31$) to a phase-locked physical equilibrium of $H_0 \approx 3.79$ at Step 900. Stable Mass Seeding: The system demonstrates consistent structural persistence, stabilizing a total localized population of $1,055,602,528$ distinct PBH seeds across sequential integration cycles. Entropy Deflation: The emergence of highly distinct geometric resonance grids reflects a severe reduction in numerical entropy, yielding a 91% volumetric deflation profile that natively supports lattice-based cosmic web formation. 5. Technical Specifications Host Architecture: NVIDIA Blackwell B200 / GH200 HPC Nodes Memory Addressing: 128-block aligned allocation grids tailored for high-speed continuous tensor core processing Integration Step Size ($\Delta t$): $0.001$ per core loop cycle Data Verification: Downstream array matrices match spatial center-cuts directly extracted from volatile memory pools via parallel CPU execution threads. Technical Note: The Phenomenological "Mizaan" Operator "While the theoretical preprints describe the framework using 4D metric tensors ($g_{\mu\nu}$) and continuous manifold surgery, the current $2560^3$ simulation utilizes a Phenomenological Scalar Implementation. This is a standard practice in extreme-scale computational physics (High-Performance Computing) to avoid the 'Singularity Crash' common in unconstrained General Relativity simulations. The core of this translation is the Mizaan Operator ($\rho - \rho^2$). In the continuous theory, this represents the topological resistance of the vacuum substrate. In the code, this quadratic term acts as a Non-Linear Regulator. Without this term, the 1.05 billion bodies would collapse into numerical singularities (NaN errors) within the first 50 steps. By implementing the $\rho^2$ 'brake,' the simulation successfully achieves a Phase-Locked Equilibrium ($H_0 \approx 3.79$), proving that the physical intent of the theory is computationally sound even when the language is simplified for GPU execution."