WM-AGN Analysis Code

This record contains the analysis code and lightweight machine-readable tables associated with the manuscript “When the Shadow Meets Its Measure: Assessing the Feasibility of Submillimeter Black Hole Shadow Imaging in Megamaser Disk AGN.” The release supports the paper’s analysis of water-megamaser disk AGN as targets for future submillimeter/millimeter space-VLBI black-hole-shadow imaging. It includes scripts and notebooks for SMA calibration and imaging, archival ALMA/VLA continuum-product fitting, continuum flux compilation and 230 GHz reference scaling, black-hole-shadow angular-size calculations, VLBI baseline and sensitivity calculations, and thermal-dust and extended-jet contamination estimates. Included products comprise the 501-row continuum-fitting table, the audited 21-source black-hole parameter table and canonical inputs, explicit model-sensitivity and conditional non-adopted-fit sidecars, deterministic renderers for manuscript Tables 1 and 2, six SED figures, and the black-hole-shadow-size versus 230 GHz flux figure. Machine-readable values retain full precision, while publication renderers apply documented display rounding. Version v1.0.10 supersedes v1.0.9 for reproduction of the corrected manuscript results. The black-hole workflow now distinguishes six sources evaluated from paired mass–distance posterior information, thirteen sources for which a shared distance factor cancels from the shadow-size ratio, and two sources without robust adopted primary masses or shadow sizes. Statistical intervals, numerical systematics, reported undecomposed uncertainties, non-probabilistic model-sensitivity checks, and unquantified caveats remain separate. The release also incorporates the final continuum-product provenance audit, corrected anchor selections and contamination treatments, and regenerated manuscript tables and figures. These revisions preserve the paper’s overall scientific interpretation and conclusions. The archive intentionally excludes raw SMA data, ALMA or VLA archival FITS files, CASA products and logs, and measurement sets. DATA_ACCESS.md explains how to retrieve the external observations. Primary dependencies include Python, NumPy, SciPy, pandas, Matplotlib, Astropy, Astroquery, Requests, PyUVData, Jupyter, and CASA 6.