Cryogenic Near-Infrared Spectro-Polarimeter (Cryo-NIRSP) Processing Information

Validate SP Observe Task

Confirm that data form a consistent set that is valid for SP Science Calibration

Linearity Calibration

Generate linearity corrected frame data

Apply camera-specific pre-processing corrections. Check for scrambled data by verifying the location of two signals intentionally inserted into the data. Identify and fit the linear portion of the ramp for each pixel.

As well as calculating the polynomial fits for each exposure, the linearity calibration may also be performed by using pre-computed lookup tables.

Dark Correction

Remove dark current signal using dark calibration parameters

Test that input data form a consistent set that is suitable for dark calibration and that dark calibration meets quality criteria. Apply the dark correction to the SP data frames.

Modulated Gain Correction (Polarimetric Observations)

Divide each modulator state in input data by a gain image associated with the same modulator state.

Gain image is derived from the Gain4 calibration described in detail below.

Instrument Polarization Correction (Polarimetric Observations)

Apply a demodulation matrix (Instrument Polarization Calibration) to input data

Take an SP demodulation matrix computed by the PA&C Modules and apply it to the science data for each beam.

Telescope Polarization Correction (Polarimetric Observations)

Generate a DKIST Telescope Mueller Matrix that captures the effects of M1 – M6 and apply this matrix to demodulated data

Set up a PA&C Modules Telescope Model with the observed telescope configuration. Generate an inverse telescope Mueller matrix. Matrix-multiply the inverse matrix with the input data.

Combine Polarimetric Beams (Polarimetric Observations)

Create combined polarimetric beams

Following the Align3 calibration described below, take a full-frame SP image, split the beams, transform beam 2 into the same coordinates as beam 1, and combine the two beams together.

Unmodulated Gain Correction (Non-Polarimetric Observations)

Divide each input frame by a gain image.

The input gain is assumed to have no modulator data and all data frames are divided by the same gain image. Gain image is derived from the Gain4 calibration described in detail below. Modulator or Stokes information is NOT preserved.

Combine Intensity Beams
(Non-Polarimetric Observations)

Create combined intensity beams

Apply the Align3 calibration described below. Take a full-frame SP image (non-polarimetric data), split the beams, transform beam 2 into the same coordinates as beam 1, and combine the two beams together.

Geometric Correction

Remove dispersion angle and spectral curvature from data.

This function works on already combined polarimetric beams and thus only the corrections for beam 1 are applied.

Generate SP Science Calibration

Collect data and metadata into a single Science Calibration object

This calibration will result in version 4.0 FITS files grouped into datasets with similar observing characteristics such as primary wavelength. All the metadata in the calibrated frames will be SPEC-0214-compliant in step with calibrated data from other instruments.

Gain4 Calibration

Generate gain map for each modulator state and spectral shifts for each beam

Validate that input data form a consistent set that is suitable for Gain4 Calibration and apply linearity and dark corrections. Divide each modulator state in input data by a gain image associated with the same modulator state. Split a full-frame Cryo SP frame (to which the Align3 Calibration has been applied) along the beam border and rotate each beam by its dispersion angle. The beam split is simply along a pixel column. Computer and remove the spectral curvature so that all spectra are on the same wavelength grid. Generate a characteristic, average spectrum from an aligned and de-shifted 2D spectral image and apply the measured spectral curvature to it at all spatial locations. Take the two rotated beams and place them back in their original locations in the full Cryo SP frame. Remove the averaged solar spectrum from Gain4 data, normalize Gain4 data to mean of 1 and combine data and metadata into a single object.

Align3 Calibration

Measure the angle between the dispersion and detector axes, separately for each polarimetric beam. Clean both beams for NaNs and pepper outliers and then compute an Affine mapping from beam 2 to beam 1 using an initial guess. Currently only a scale and translation are expected, but shear and rotation are technically allowed as well. Iterate, using goodness of fit to determine the amount to change each of the Affine transform parameters. Chop an array along the rough beam border assuming that the split is essentially oriented along the detector axes and finally generate a binary image from a data array. Check the quality of the generate align3 calibration and combine dispersion angle, Affine transform information, and metadata into a single object.

Validate CI Observe Task

Confirm that data form a consistent set that is valid for CI Science Calibration

Linearity Calibration

Generate linearity corrected frame data

See “Linearity Calibration” above for more details

Dark Correction

Remove dark current signal using dark calibration parameters

Test that input data form a consistent set that is suitable for dark calibration and that dark calibration meets quality criteria. Apply the dark correction to the CI data frames.

Modulated Gain Correction (Polarimetric Observations)

Divide each modulator state in input data by a gain image associated with the same modulator state.

Gain image is derived from the Gain1 calibration described in detail above.

Instrument Polarization Correction (Polarimetric Observations)

Apply a demodulation matrix (Instrument Polarization Calibration) to input data

Take CI demodulation matrices computed by the PA&C Modules and apply it to the science data for each beam.

Telescope Polarization Correction (Polarimetric Observations)

Generate a DKIST Telescope Mueller Matrix that captures the effects of M1 – M6 and apply this matrix to demodulated data

Set up a PA&C Modules Telescope Model with the observed telescope configuration. Generate an inverse telescope Mueller matrix. Matrix-multiply the inverse matrix with the input data.

Generate CI Science Calibration

Collect data and metadata into a single Science Calibration object

This calibration will result in version 4.0 FITS files grouped into datasets with similar observing characteristics such as primary wavelength. All the metadata in the calibrated frames will be SPEC-0214-compliant in step with calibrated data from other instruments.