# Electron Density Reconstruction of Solar Coronal Mass Ejections Based on a Genetic Algorithm: Method and Application

## TL;DR

This paper introduces a genetic algorithm-based method for three-dimensional electron density reconstruction of solar coronal mass ejections, validated with synthetic and real observational data, improving understanding of CME structures.

## Contribution

The paper presents the first application of a genetic algorithm for CME electron density reconstruction, demonstrating its effectiveness with synthetic and actual observational data.

## Key findings

- GRM accurately reconstructs synthetic CMEs with various orientations.
- The method performs well even with brightness incompleteness and noise.
- Application to real data shows promising results for CME analysis.

## Abstract

We present a new method to reconstruct the three-dimensional electron density of coronal mass ejections (CMEs) based on a genetic algorithm, namely the genetic reconstruction method (GRM). GRM is first applied to model CMEs with different orientations and shapes. A set of analytic model CMEs from Gibson and Low is employed to produce synthetic CME images for GRM reconstruction. Model CMEs with longitudes of 0, 45, 90, 135, 180 degrees and latitudes of 0, 15, 30, 45 degrees are used to test the performance of GRM. The model CMEs are obscured with a simulated occulter of a coronagraph to determine the influence of CME brightness incompleteness. We add random noise to some synthetic CME images to test the performance of GRM. The CME reconstructions are carried out using synthetic data from Solar Terrestrial Relations Observatory (STEREO) A and B with a separation angle of 90 degrees and from STEREO A and the Solar and Heliospheric Observatory (SOHO) with a separation angle of 73 degrees. The Pearson correlation coefficient and the mean relative absolute deviation are calculated to analyze the similarities in brightness and electron density between the model and reconstructed CMEs. Comparisons based on the similarity analysis under various conditions stated above give us valuable insights into the advantages and limitations of GRM reconstruction. The method is then applied to real coronagraph data from STEREO A and B, and SOHO on 2013 September 30.