Holography far-side images with HMI Irene Gonzalez Hernandez Charlie Lindsey Richard Bogart Phil Scherrer Sebastian Couvidat, and the calibration team !

Quick solution (I) High resolution Dopplergrams Low resolution Dopplergrams Binning Algorithm Stanford Low resolution Dopplergrams Tucson Farside maps NetDRMS GONG farside pipeline Tucson Web Publication Stanford Web Publication

First attempts to calculate far-side maps Apr May May

First attempts to calculate far-side maps HMI cuts of the central region of the “far-side map”

First attempts to calculate far-side maps GONG cuts of the central region of the “far-side map”

The input data HMI (binned) postel projected Doppler images

The input data HMI (binned) postel projected Doppler images Temporal series of a single pixel

The input data HMI averaged postel-projected Dopplergram

The input data Acoustic power map

The input data Doppler Parameters

The input data Sensitivity of the Doppler signature to the radial velocity of the Spacecraft

The input data Sensitivity of the Doppler signature to the radial velocity of the Spacecraft

Quick solution (II) FS Preprocessor Fourier transformed data cube Tucson Farside maps NetDRMS Modified GONG farside pipeline Tucson Web Publication Stanford Web Publication High resolution Dopplergrams Fourier transformed data cube Stanford H. Farside maps T-D. Farside maps + Time-distance pipeline

The FS Preprocessor Postel Projection of Dopplergrams Quality control: Frame rejection (based on NaN values) Glitch/cosmic-ray recognition and removal (deviation from temporal trends) Conformation to appropriate rotational profile Spatial filtering/condensation (what is this?) Spectral filtering: extraction of the mHz band ** Possibility of binning down to 90sec. Cadence (Nyquist frequency of 5.6mHz)

The FS Preprocessor Possibility of binning down to 90sec. Cadence (Nyquist frequency of 5.6mHz)