Presenter Information

Jenna Syposs, SUNY GeneseoFollow

Submission Type

Poster

Start Date

4-26-2021

Abstract

In the Cassini-Huygens mission, the Cassini spacecraft left Earth in 1997 and reached Saturn in 2004, where it orbited and collected data from the planet for 13 years. Cassini collected magnetic field data from a plasma spectrometer instrument known as CHarge Energy Mass Spectrometer (CHEMS). Gases are released from Saturn’s icy moon known as Enceladus. These gases become plasma when approaching Saturn’s magnetic field. Collaborators built a Python model to analyze 816 plasma events to evaluate their geometry. This study analyzed these events to determine if our model accurately aligns with the plasma injections discovered by CHEMS. We filtered the events to find a subset that occurred within a fixed distance to the satellite (0.25 Saturn radii). By comparing the model’s predictions with CHEMS spectrogram data, we found that a majority (181 injections) were determined to be “channel-like”, or radially extended, because they aligned with an observed dispersed ion signature, while 62 did not match a channel-like morphology. Most of the events required slight adjustments to the model’s drift speeds which improved our fit to the modeled particles on the spectrogram. A best-fit co-rotation rate was on average 8.9% faster than our nominal setting.

Comments

Sponsored by Scott Giorgis. This project as funded through a grant fom the National Science Foundation's Research Eperience for Undergraduates Program (Grant Number 1659248).

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Apr 26th, 12:00 AM

348— Geometric Analysis of Plasma Injection Events in Saturn’s Magnetic Field Environment

In the Cassini-Huygens mission, the Cassini spacecraft left Earth in 1997 and reached Saturn in 2004, where it orbited and collected data from the planet for 13 years. Cassini collected magnetic field data from a plasma spectrometer instrument known as CHarge Energy Mass Spectrometer (CHEMS). Gases are released from Saturn’s icy moon known as Enceladus. These gases become plasma when approaching Saturn’s magnetic field. Collaborators built a Python model to analyze 816 plasma events to evaluate their geometry. This study analyzed these events to determine if our model accurately aligns with the plasma injections discovered by CHEMS. We filtered the events to find a subset that occurred within a fixed distance to the satellite (0.25 Saturn radii). By comparing the model’s predictions with CHEMS spectrogram data, we found that a majority (181 injections) were determined to be “channel-like”, or radially extended, because they aligned with an observed dispersed ion signature, while 62 did not match a channel-like morphology. Most of the events required slight adjustments to the model’s drift speeds which improved our fit to the modeled particles on the spectrogram. A best-fit co-rotation rate was on average 8.9% faster than our nominal setting.

 

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