Welcome to SpaceLab, a project that explores the interplay between dark matter, black holes, and higher-dimensional spacetime. This repository contains the theoretical framework, numerical implementation, and observational tests for a model that bridges speculative theoretical physics with empirical science.
SpaceLab aims to develop a testable theoretical framework that incorporates:
- Axion-like dark matter.
- Dynamical dark energy (quintessence).
- Higher-dimensional spacetime (Kaluza-Klein theory).
- Numerical simulations of black hole dynamics and dark matter distributions.
The project combines theoretical models with observational data to provide insights into the nature of dark matter, black holes, and the structure of spacetime.
- Higher-Dimensional Metric: Incorporates a 5D spacetime metric with a compactified extra dimension.
- Dark Matter Lagrangian: Describes axion-like dark matter with couplings to the dilaton and graviphoton.
- Dynamical Dark Energy: Uses a quintessence field with a potential ( V(\phi_{\text{DE}}) )
- Stress-Energy Tensor: Includes bulk terms from higher dimensions.
- PDE Solvers: Solves coupled partial differential equations for black hole dynamics and dark matter distributions.
- Global Fits: Uses Markov Chain Monte Carlo (MCMC) methods to fit model parameters to observational data.
- Parallelization: Optimized for high-performance computing (HPC) environments.
- Galactic Rotation Curves: Compares predicted rotation velocities with SPARC data.
- Gravitational Waves: Simulates black hole mergers and compares waveforms with LIGO/Virgo data.
- Gamma-Ray Flux: Computes dark matter annihilation signals and compares with Fermi-LAT data.
- Install development dependencies:
pip install -r requirements-dev.txt
- Set up pre-commit hooks for code formatting:
pre-commit install
- Install Miniconda or Anaconda.
- Create the environment:
conda env create -f environment.yml
- Activate the environment:
conda activate spacelab
- Install Docker.
- Build the Docker image:
docker build -t spacelab . - Run the container:
docker run -it spacelab
- Clone the repository:
git clone https://github.com/junkwax/spacelab.git cd spacelab - Install Python dependencies:
pip install -r requirements.txt
To run a simulation of black hole dynamics and dark matter distributions:
python src/black_hole_simulation.py --config configs/simulation_config.yamlTo perform global fits using MCMC:
python src/global_fits.py --data data/observational_data.h5 --output results/fit_results.h5To analyze the results of simulations or fits:
python src/analyze_results.py --input results/fit_results.h5 --plot output/plots/Example input and output files are provided in the examples/ directory to help you get started.
We welcome contributions from the open-source community! Here’s how you can help:
- Report Issues: If you find a bug or have a feature request, please open an issue.
- Submit Pull Requests: Fork the repository, make your changes, and submit a pull request.
- Improve Documentation: Help us improve the documentation by submitting edits or additions.
Please read our Contributing Guidelines for more details.
This project is licensed under the MIT License. See the LICENSE file for details.
We thank the open-source community for their invaluable contributions to scientific software. Special thanks to:
- The developers of NumPy, SciPy, emcee, and PETSc.
- The LIGO/Virgo Collaboration for providing gravitational wave data.
- The SPARC and Fermi-LAT teams for their observational datasets.
For questions or collaborations, please contact:
- Email: spl@junkwax.nl