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Both NASA's Solar Dynamics Observatory (SDO) and the JAXA/NASA Hinode missioninclude spectropolarimetric instruments designed to measure the photosphericmagnetic field. SDO's Helioseismic and Magnetic Imager (HMI) emphasizesfull-disk high-cadence and good spatial resolution data acquisition whileHinode's Solar Optical Telescope Spectro-Polarimeter (SOT-SP) focuses on highspatial resolution and spectral sampling at the cost of a limited field of viewand slower temporal cadence. This work introduces a deep-learning system namedSynthIA (Synthetic Inversion Approximation), that can enhance both missions bycapturing the best of each instrument's characteristics. We use SynthIA toproduce a new magnetogram data product, SynodeP (Synthetic Hinode Pipeline),that mimics magnetograms from the higher spectral resolution Hinode/SOT-SPpipeline, but is derived from full-disk, high-cadence, and lowerspectral-resolution SDO/HMI Stokes observations. Results on held-out data showthat SynodeP has good agreement with the Hinode/SOT-SP pipeline inversions,including magnetic fill fraction, which is not provided by the current SDO/HMIpipeline. SynodeP further shows a reduction in the magnitude of the 24-houroscillations 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, whichenables trade-offs between fidelity to the Hinode/SOT-SP inversions, number ofobservations used, and temporal artifacts. We discuss possible generalizationsof SynthIA and its implications for space weather modeling. This work is partof the NASA Heliophysics DRIVE Science Center (SOLSTICE) at the University ofMichigan under grant NASA 80NSSC20K0600E, and will be open-sourced.

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