SynthIA: A Synthetic Inversion Approximation for the Stokes Vector Fusing SDO and Hinode into a Virtual Observatory

Abstract

Both NASA's Solar Dynamics Observatory (SDO) and the JAXA/NASA Hinode mission include spectropolarimetric instruments designed to measure the photospheric magnetic field. SDO's Helioseismic and Magnetic Imager (HMI) emphasizes full-disk high-cadence and good spatial resolution data acquisition while Hinode's Solar Optical Telescope Spectro-Polarimeter (SOT-SP) focuses on high spatial resolution and spectral sampling at the cost of a limited field of view and slower temporal cadence. This work introduces a deep-learning system named SynthIA (Synthetic Inversion Approximation), that can enhance both missions by capturing the best of each instrument's characteristics. We use SynthIA to produce a new magnetogram data product, SynodeP (Synthetic Hinode Pipeline), that mimics magnetograms from the higher spectral resolution Hinode/SOT-SP pipeline, but is derived from full-disk, high-cadence, and lower spectral-resolution SDO/HMI Stokes observations. Results on held-out data show that SynodeP has good agreement with the Hinode/SOT-SP pipeline inversions, including magnetic fill fraction, which is not provided by the current SDO/HMI pipeline. SynodeP further shows a reduction in the magnitude of the 24-hour oscillations present in the SDO/HMI data. To demonstrate SynthIA's generality, we show the use of SDO/AIA data and subsets of the HMI data as inputs, which enables trade-offs between fidelity to the Hinode/SOT-SP inversions, number of observations used, and temporal artifacts. We discuss possible generalizations of SynthIA and its implications for space weather modeling. This work is part of the NASA Heliophysics DRIVE Science Center (SOLSTICE) at the University of Michigan under grant NASA 80NSSC20K0600E, and will be open-sourced.

References in corpus (11)

• The Solar Optical Telescope for the Hinode Mission: An Overview
• The Helioseismic and Magnetic Imager (HMI) Vector Magnetic Field Pipeline: Overview and Performance
• Spectral Line Selection for HMI: A Comparison of Fe I 6173 and Ni I 6768
• The Helioseismic and Magnetic Imager (HMI) Vector Magnetic Field Pipeline: Optimization of the Spectral Line Inversion Code
• A Machine Learning Dataset Prepared From the NASA Solar Dynamics Observatory Mission
• Stokes Inversion based on Convolutional Neural Networks
• Comparison of inversion codes for polarized line formation in MHD simulations. I. Milne-Eddington codes
• Solar Coronal Magnetic Field Extrapolation from Synchronic Data with AI-generated Farside
• Inferring Vector Magnetic Fields from Stokes Profiles of GST/NIRIS Using a Convolutional Neural Network
• A Statistical Comparison between Photospheric Vector Magnetograms Obtained by SDO/HMI and Hinode/SP
• On a limitation of Zeeman polarimetry and imperfect instrumentation in representing solar magnetic fields with weaker polarization signal

Cited by in corpus (3)

• On Identifying and Mitigating Bias in Inferred Measurements for Solar Vector Magnetic Field Data
• Spectropolarimetric Inversion in Four Dimensions with Deep Learning (SPIn4D): I. Overview, Magnetohydrodynamic Modeling, and Stokes Profile Synthesis
• Large-Scale Spatial Cross-Calibration of Hinode/SOT-SP and SDO/HMI