Multi-frequency Black Hole Imaging for the Next-Generation Event Horizon Telescope

TL;DR

This paper introduces a new multi-frequency imaging method for the next-generation Event Horizon Telescope, enabling improved black hole images and spectral maps by reconstructing data across multiple frequencies simultaneously.

Contribution

The paper presents a novel multi-frequency image reconstruction technique based on Regularized Maximum Likelihood methods, integrated into the eht-imaging library, enhancing EHT data analysis.

Findings

Multi-frequency reconstruction yields higher-quality images.

Simultaneous spectral index maps constrain plasma properties.

Method outperforms independent frequency reconstructions.

Abstract

The Event Horizon Telescope (EHT) has produced images of the plasma flow around the supermassive black holes in Sgr A* and M87* with a resolution comparable to the projected size of their event horizons. Observations with the next-generation Event Horizon Telescope (ngEHT) will have significantly improved Fourier plane coverage and will be conducted at multiple frequency bands (86, 230, and 345 GHz), each with a wide bandwidth. At these frequencies, both Sgr A* and M87* transition from optically thin to optically thick. Resolved spectral index maps in the near-horizon and jet-launching regions of these supermassive black hole sources can constrain properties of the emitting plasma that are degenerate in single-frequency images. In addition, combining information from data obtained at multiple frequencies is a powerful tool for interferometric image reconstruction, since gaps in spatial scales in single-frequency observations can be filled in with information from other frequencies. Here we present a new method of simultaneously reconstructing interferometric images at multiple frequencies along with their spectral index maps. The method is based on existing Regularized Maximum Likelihood (RML) methods commonly used for EHT imaging and is implemented in the eht-imaging Python software library. We show results of this method on simulated ngEHT data sets as well as on real data from the VLBA and ALMA. These examples demonstrate that simultaneous RML multi-frequency image reconstruction produces higher-quality and more scientifically useful results than is possible from combining independent image reconstructions at each frequency.