{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/modelling-solar-orbiter-dust-detection-rates","title":"Modelling Solar Orbiter Dust Detection Rates in Inner Heliosphere as a Poisson Process","arxiv_id":"2210.03562","date":"2022-10-07","proceeding":null,"authors":["Samuel Kočiščák","Andreas Kvammen","Ingrid Mann","Sigrunn Holbek Sørbye","Audun Theodorsen","Arnaud Zaslavsky"],"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 $(63 \\pm 7) \\mathrm{km/s}$ with the predominance of hyperbolic dust about $(78 \\pm 4) \\%$. The results are consistent with hyperbolic meteoroids originating between $0.02 \\mathrm{AU}$ and $0.1 \\mathrm{AU}$ and showing substantial deceleration, which implies effective solar radiation pressure to gravity ratio $\\gtrsim 0.5$. The flux of hyperbolic component at $1 \\mathrm{AU}$ is found to be $(1.1 \\pm 0.2) \\times 10^{-4} \\mathrm{m^{-2}s^{-1}}$ and the flux of background component at $1 \\mathrm{AU}$ is found to be $(5.4 \\pm 1.5) \\times 10^{-5} \\mathrm{m^{-2}s^{-1}}$.","url_abs":"https://arxiv.org/abs/2210.03562v1","url_pdf":"https://arxiv.org/pdf/2210.03562v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"modelling-solar-orbiter-dust-detection-rates","repo_url":"https://github.com/samuelko1607/solo_dust_2022","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}