Modelling Solar Orbiter Dust Detection Rates in Inner Heliosphere as a Poisson Process
Samuel Ko\v{c}i\v{s}\v{c}\'ak (1), Andreas Kvammen (1), Ingrid Mann, (1), Sigrunn Holbek S{\o}rbye (2), Audun Theodorsen (1), Arnaud Zaslavsky (3), ((1) Department of Physics, Technology, UiT The Arctic University of, Norway, 9037, Troms\o, Norway, (2) Department of Mathematics

TL;DR
This paper models dust detection rates by Solar Orbiter as a Poisson process, inferring properties of hyperbolic dust particles and their origins using Bayesian hierarchical modeling of observational data.
Contribution
It introduces a Bayesian Poisson process model for dust detection data, estimating dust parameters and their uncertainties, and confirms hyperbolic meteoroids' characteristics and origins.
Findings
Hyperbolic dust radial velocity around 63 km/s
Hyperbolic dust constitutes about 78% of detections
Flux of hyperbolic dust at 1 AU is approximately 1.1e-4 m^-2 s^-1
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.…
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Taxonomy
TopicsSolar and Space Plasma Dynamics · Astro and Planetary Science · Gamma-ray bursts and supernovae
