Reconstructing Multi-frequency Movies of Supermassive Black Holes with PRIMO with Lia Medeiros

The sparse interferometric coverage of the Event Horizon Telescope (EHT) makes reconstruction of black-hole images challenging. The dictionary learning algorithm principal component interferometric modeling (PRIMO) builds a principal component basis from high-fidelity numerical simulations of low-luminosity accretion flows. This basis enables reconstruction of images that are both consistent with the interferometric data and that live in the space spanned by the simulations. So far, the EHT has only published images at 230 GHz, but recent and upcoming campaigns will also include simultaneous observations at 345 GHz. The EHT is also interested in probing the temporal variability of image morphology through a series of intermittent observations spanning several weeks to months (i.e., reconstruct a movie of matter swirling around the black hole). I will review the PRIMO algorithm and its application to EHT M87 data. I will then introduce the new multi-wavelength and multi-epoch version of PRIMO. This new version can simultaneously reconstruct multi-frequency images while accounting for correlations between the frequencies. The algorithm can therefore produce a single mass over distance measurement for multiple frequencies and/or observational epochs.

This lecture was made possible by the William C. Ferguson Fund