Modelling Solar Orbiter Dust Detection Rates in Inner Heliosphere as a Poisson Process
Abstract
Solar Orbiter provides dust detection capability in inner heliosphere, but estimating physical properties of detected dust from the collected data is far from straightforward. First, a physical model for dust collection considering a Poisson process is formulated. Second, it is shown that dust on hyperbolic orbits is responsible for the majority of dust detections with Solar Orbiter's Radio and Plasma Waves (SolO/RPW). Third, the model for dust counts is fitted to SolO/RPW data and parameters of the dust are inferred, namely: radial velocity, hyperbolic meteoroids predominance, and solar radiation pressure to gravity ratio as well as uncertainties of these. Non-parametric model fitting is used to get the difference between inbound and outbound detection rate and dust radial velocity is thus estimated. A hierarchical Bayesian model is formulated and applied to available SolO/RPW data. The model uses the methodology of Integrated Nested Laplace Approximation, estimating parameters of dust and their uncertainties. SolO/RPW dust observations can be modelled as a Poisson process in a Bayesian framework and observations up to this date are consistent with the hyperbolic dust model with an additional background component. Analysis suggests a radial velocity of the hyperbolic component around with the predominance of hyperbolic dust about . The results are consistent with hyperbolic meteoroids originating between and and showing substantial deceleration, which implies effective solar radiation pressure to gravity ratio . The flux of hyperbolic component at is found to be and the flux of background component at is found to be .
Keywords
Cite
@article{arxiv.2210.03562,
title = {Modelling Solar Orbiter Dust Detection Rates in Inner Heliosphere as a Poisson Process},
author = {Samuel Kočiščák and Andreas Kvammen and Ingrid Mann and Sigrunn Holbek Sørbye and Audun Theodorsen and Arnaud Zaslavsky},
journal= {arXiv preprint arXiv:2210.03562},
year = {2023}
}