English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  On the trail of a comet's tail: A particle tracking algorithm for comet 67P/Churyumov-Gerasimenko

Pfeifer, M., Agarwal, J., & Schröter, M. (2022). On the trail of a comet's tail: A particle tracking algorithm for comet 67P/Churyumov-Gerasimenko. Astronomy and Astrophysics, 659, A171. doi:10.1051/0004-6361/202141953.

Item is

Files

show Files

Locators

show
hide
Description:
-
OA-Status:
Not specified

Creators

show
hide
 Creators:
Pfeifer, Marius1, Author           
Agarwal, J.1, Author           
Schröter, M., Author
Affiliations:
1Planetary Science Department, Max Planck Institute for Solar System Research, Max Planck Society, ou_1832288              

Content

show
hide
Free keywords: comets: general; comets: individual: 67P/Churyumov-Gerasimenko; zodiacal dust; Astrophysics - Earth and Planetary Astrophysics; Astrophysics - Instrumentation and Methods for Astrophysics
 Abstract: Context. During the post-perihelion phase of the European Space Agency's Rosetta mission to comet <ASTROBJ>67P</ASTROBJ>, the Optical, Spectroscopic, and Infrared Remote Imaging System on board the spacecraft took numerous image sequences of the near-nucleus coma, with many showing the motion of individual pieces of debris ejected from active surface areas into space.
Aims: We aim to track the motion of individual particles in these image sequences and derive their projected velocities and accelerations. This should help us to constrain their point of origin on the surface, understand the forces that influence their dynamics in the inner coma, and predict whether they will fall back to the surface or escape to interplanetary space.
Methods: We have developed an algorithm that tracks the motion of particles appearing as point sources in image sequences. Our algorithm employs a point source detection software to locate the particles and then exploits the image sequences' pair-nature to reconstruct the particle tracks and derive the projected velocities and accelerations. We also constrained the particle size from their brightness.
Results: Our algorithm identified 2268 tracks in a sample image sequence. Manual inspection not only found that 1187 (∼52%) of them are likely genuine, but in combination with runs on simulated data it also revealed a simple criterion related to the completeness of a track to single out a large subset of the genuine tracks without the need for manual intervention. A tentative analysis of a small (n = 89) group of particles exemplifies how our data can be used, and provides first results on the particles' velocity, acceleration, and radius distributions, which agree with previous work.

Details

show
hide
Language(s):
 Dates: 2022
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1051/0004-6361/202141953
ISSN: 0004-6361
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Astronomy and Astrophysics
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 659 Sequence Number: - Start / End Page: A171 Identifier: -