The SynCOM Flow Tracking Challenge

TL;DR

This paper introduces the Flow Tracking Challenge using SynCOM synthetic data to evaluate and improve solar wind flow tracking algorithms, aiding space weather prediction and future mission planning.

Contribution

It establishes a synthetic data benchmark for testing solar wind flow tracking methods, providing a platform for systematic evaluation and development.

Findings

SynCOM data effectively benchmarks flow tracking accuracy.

Initial results show improved velocity estimation with SynCOM.

The challenge guides future algorithm enhancements.

Abstract

Understanding solar wind flows is crucial for unraveling the dynamics of the Sun's corona and improving space weather forecasting. However, the complex nature of the solar wind and the absence of reliable ground-truth data present significant challenges to current tracking methods. To address this, the Flow Tracking Challenge was established, providing a platform for testing and refining flow tracking algorithms using synthetic images generated by the Synthetic Coronal Outflow Model (SynCOM). The challenge is divided into two phases: a preliminary phase focusing on simpler flow scenarios and a main phase featuring more complex synthetic images that mimic solar outflows. These phases allow researchers to evaluate their methods under various simulated conditions. SynCOM's synthetic data benchmark improves accuracy in velocity estimations. This paper presents the preliminary results of the Flow Tracking Challenge, where the synthetic images from SynCOM are used to test solar wind velocity tracking methods. Initial findings demonstrate SynCOM's value as a benchmark, guiding improvements for upcoming missions like PUNCH.