Single‐ and Multi‐Pass Magnetometric Subsurface Ocean Detection and Characterization in Icy Worlds Using Principal Component Analysis (PCA): Application to Triton

Abstract

Abstract Many moons in the solar system are thought to potentially harbor hidden oceans based on the features observed at their surfaces. However, the magnetic induction signatures measured in the vicinity of these moons provide the most compelling evidence for the presence of a subsurface ocean, specifically for the Jovian moons Europa and Callisto. Interpretation of these magnetic signatures can be challenging due to the various systematic and random sources of noise that are present in the magnetic field measurement. In this work, a novel magnetometric ocean detection methodology based on Principal Component Analysis is presented and shown to provide enhanced discrimination and geophysical characterization of ocean properties in the presence of noise and error sources. The proposed methodology is robust for a single‐encounter mission or an orbiting mission with multiple flybys. Here, it is applied to the Neptunian moon Triton as a prime example of an active, potential ocean world residing in the requisite time‐varying magnetic field environment that enables magnetic induction investigation of its interior. In addition to the usual noise sources, other confounding factors are addressed, including the presence of an intense conductive ionosphere, the small amplitude of Neptune's driving magnetic field, and the uncertainty of Neptune's magnetic phase at the time‐of‐arrival which can potentially hinder accurate ocean detection and characterization. The proposed methodology is applicable to any moon in the solar system residing in a time‐varying magnetic field environment.

Keywords

• Triton
• magnetic induction
• Principal Component Analysis
• ocean worlds
• subsurface ocean detection
• subsurface ocean characterization