SynCOM: The training data for flow tracking algorithms

Authors: Valmir Moraes Filho (Catholic University of America at NASA/GSFC), Vadim Uritsky (Catholic University of America at NASA/GSFC), Barbara Thompson (NASA Goddard Space Flight Center), Sarah Gibson (University Corporation for Atmospheric Research), Craig DeForest (Southwest Institute Research)

The Synthetic Coronal Outflow Model (SynCOM) is an empirical data-driven model that simulates the outflow dynamics of the solar corona based on high-resolution observations. It reproduces the transient and quasi-periodic behavior observed in previous STEREO-A/COR2 observations. SynCOM generates synthetic images with realistic radial scaling of polarized brightness, accounting for physical fluctuations of plasma outflow and instrumental noise through stochastic elements. SynCOM offers a predefined flow velocity distribution for each position angle and an adjustable signal-to-noise ratio, facilitating accurate testing of flow velocity measuring techniques. Its customizable settings accommodate specific coronal conditions and instrument parameters, allowing for accurate performance comparisons across various flow measuring methods. Moreover, the validation of these flow velocity algorithms is crucial for understanding the origin of the solar wind and supporting future missions like the Polarimeter to Unify the Corona and Heliosphere (PUNCH) mission. In our study, we present updated applications of SynCOM that satisfy the observational requirements for detecting coronal flows beyond the altitudes covered by prior observations. Furthermore, we are exploring the feasibility of implementing our methods using FORWARD modeling. Our aim is to establish benchmarks for widely used flow tracking methods and cross-validate their outcomes, thereby contributing to advancements in flow measurement techniques within the field of solar physics.