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Statistical methods for partitioning ribbon and globally-distributed flux using data from the Interstellar Boundary Explorer

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arxiv 2302.03089 v2 pith:5QQJKBAF submitted 2023-02-06 stat.AP astro-ph.GA

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keywords fluxdatainterstellarmapsribbonboundaryglobally-distributedmethods
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NASA's Interstellar Boundary Explorer (IBEX) satellite collects data on energetic neutral atoms (ENAs) that can provide insight into the heliosphere boundary between our solar system and interstellar space. Using these data, scientists can construct maps of the ENA intensities (often, expressed in terms of flux) observed in all directions. The ENA flux observed in these maps is believed to come from at least two distinct sources: one source which manifests as a ribbon of concentrated ENA flux and one source (or possibly several) that results in a smoothly-varying globally-distributed flux. Each ENA source type and its corresponding ENA intensity map is of separate scientific interest. In this paper, we develop statistical algorithms for separating the total ENA intensity maps into two source-specific maps (ribbon and globally-distributed flux) and estimating corresponding uncertainty. Key advantages of the proposed method include enhanced model flexibility and improved propagation of estimation uncertainty. We evaluate the proposed methods on simulated data designed to mimic realistic data settings. We also propose new methods for estimating the center of the near-elliptical ribbon in the sky, which can be used in the future to study the location and variation of the local interstellar magnetic field.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Global Heliospheric Termination Shock Strength in the Solar-Interstellar Interaction

    astro-ph.SR 2025-01 conditional novelty 7.0 of 10

    First all-sky maps of the heliospheric termination shock compression ratio, inferred from IBEX energetic neutral atom data, show values around 2.5 to 3.0 with strong spatial and solar-cycle variations.

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