A Unified Multi-Wavelength Data Analysis Workflow with gammapy.
<p>Repository containing multi-wavelength (MWL) data of the distant quasar OP 313 (z=0.997) taken during the nights of MJD 60373 (3-4 March 2024) and MJD 60384 (14-15 March 2024) using <em>Fermi</em>-LAT, <em>Swift</em>-XRT, <em>Swift</em>-UVOT, and the Liverpool IO:O photometric data.</p> <div> <h3>Directory structure:</h3> <a href="https://github.com/mireianievas/gammapy_mwl_workflow/tree/main#directory-structure"></a></div> <ul> <li>Notebooks/DatasetGenerator: Notebooks (one per instrument) that summarize the steps to generate gammapy-compliant 1D and 3D binned datasets.</li> <li>Notebooks/DatasetAnalysis: Notebooks (one per instrument) to analyse each dataset independently and one notebook to perform the MWL joint analysis.</li> <li>Helpers: Auxiliary functions to generate native multiplicative models for dust extinction (out of xspec's redden), neutral hydrogen (out of xspec's tbabs), EBL absorption, and utility functions for file handling and plotting.</li> <li>Models: multiplicative models in tabular format for easy 2d interpolation.</li> <li>Figures: collection of figures for the paper.</li> </ul> <p>Link: <a href="https://github.com/mireianievas/gammapy_mwl_workflow">https://github.com/mireianievas/gammapy_mwl_workflow/ </a></p> <p>Based on the original work from <a href="https://github.com/luca-giunti/gammapyXray">https://github.com/luca-giunti/gammapyXray</a></p>
ShareScore
32/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0