Analysis of coronal mass ejection flux rope signatures using 3DCORE and approximate Bayesian Computation

TL;DR

This paper introduces an enhanced 3DCORE model combined with an Approximate Bayesian Computation algorithm to accurately fit coronal mass ejection flux rope structures to in situ magnetic field data, enabling uncertainty estimation from single observations.

Contribution

The paper presents a novel integration of 3DCORE with ABC-SMC for flux rope modeling, allowing large ensemble simulations and uncertainty quantification from limited data.

Findings

Validated the fitting procedure with synthetic data.

Applied model to Parker Solar Probe event from 2018.

Demonstrated potential for multi-spacecraft event analysis.

Abstract

We present a major update to the 3D coronal rope ejection (3DCORE) technique for modeling coronal mass ejection flux ropes in conjunction with an Approximate Bayesian Computation (ABC) algorithm that is used for fitting the model to in situ magnetic field measurements. The model assumes an empirically motivated torus-like flux rope structure that expands self-similarly within the heliosphere, is influenced by a simplified interaction with the solar wind environment, and carries along an embedded analytical magnetic field. The improved 3DCORE implementation allows us to generate extremely large ensemble simulations which we then use to find global best-fit model parameters using an ABC sequential Monte Carlo (SMC) algorithm. The usage of this algorithm, under some basic assumptions on the uncertainty of the magnetic field measurements, allows us to furthermore generate estimates on the uncertainty of model parameters using only a single in situ observation. We apply our model to synthetically generated measurements to prove the validity of our implementation for the fitting procedure. We also present a brief analysis, within the scope of our model, of an event captured by Parker Solar Probe (PSP) shortly after its first fly-by of the Sun on 2018 November 12 at 0.25 AU. The presented toolset is also easily extendable to the analysis of events captured by multiple spacecraft and will therefore facilitate future multi-point studies.