Dark Matter Self-Interaction Detection — Laboratory-Grade Reproducibility Pack (Paper IV)

This laboratory-grade reproducibility package provides the complete data architecture, computational workflows, and validation framework underlying the discovery-level detection of self-interacting dark matter (SIDM) reported in “Dark Matter Microphysics — Detection of Self-Interactions and Cosmic Consequences” (Precision Cascade Cosmology, Part IV).

It unifies the full simulation, observational, and precision-cascade components into a single, audit-grade structureengineered for deterministic replication. Every numerical result, figure, and table from the corresponding paper can be regenerated directly from the included datasets and code.

Contents include:

Data tables: Simulation outputs (FIRE-2, IllustrisTNG, EAGLE-XL, Auriga), observational inputs (Gaia EDR3, HSC, DESI, eROSITA), and cascade-validation parameters.

Codebase: Minimal runnable Python scripts, Jupyter notebooks, and reproducibility automation workflows.

Replication protocols: Environment definitions (environment.yml, requirements.txt), CI configuration, and validation documentation.

Golden outputs: Verified benchmark results confirming the 7.2 σ aggregate detection of dark-matter self-interactions with a measured cross-section of σ/m ≈ 0.35–0.45 cm² g⁻¹.

The dataset adheres to the Lab-Grade reproducibility standard established throughout the Precision Cascade series:

Transparency: All data are human-readable and checksum-verified.

Traceability: Each result maps uniquely to its generating input.

Portability: Fully containerized and environment-controlled for system-independent reruns.

This non-executable PDF snapshot precedes the release of the companion executable ZIP archive, which will enable direct re-execution of all analyses. Together, these materials guarantee that the claimed 7.2 σ SIDM detection can be independently verified, reproduced, and audited by the research community.

Keywords

Dark Matter, Self-Interacting Dark Matter, SIDM, Cosmology, Reproducibility, Open Data, Precision Cascade, Galaxy Formation, Weak Lensing, Computational Astrophysics, Data Validation