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Data analysis and testing has identified multiple sources of stray light in ViSP. One set of tests done with showed that a significant part of the stray light enters from the sides and top at the end of the camera arms that were open to the environment. Reduction of stray light to about the same level as during a dark current observation with the GOS dark shutter in the beam was only possible when both the camera arms and camera lenses where baffled. Various baffling attempts were made completely covered. Installation of various baffles was done between May and June and these . These were successful in reducing the stray light from external sources. Data taken through at least OCP 1.4 will be contain stray light from this source.
A second source of background light is identified to come from within the beam itself , and is only seen when the beam is allowed to pass through the slit. This second source cannot be mitigated with external baffles or enclosures, and must be mitigated using other means. It has a different signature (spatial and spectral) at different wavelengths and/or ViSP arms. It appears Analysis of this signal shows it to be additive and mostly unpolarized, much like a dark or background signal and is most easily seen . This signal is a much more significant contribution in frames with overall low flux (e.g. 396 nm and 854 nm channels, and the dimmer of the two dual beams). In order to mitigate this, the Data Center is currently using an ad hoc algorithm that uses the PolCal frames taken at a single slit position. We use the assumption that the modulation should be spectrally constant over the ~1nm bandpass covered within a ViSP camera arm. By normalizing each of the raw PolCal intensity spectra to the mean over all spectral pixels, we get
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Notice that in many spectral regions the spectra overlap very well, which is expected. In some regions, however, there is still a large difference. The algorithm find a single a spectrum compensated for the intensity modulation. Variation in these normalized intensities with wavelength is measure of the stray light impact. Spectral invariance of modulation has been confirmed in each camera arm, and also by comparing the intensity modulation curves of both orthogonally polarized beams recorded strictly simultaneously in the dual beams of each camera. The worst behavior has been observed in the 854nm channel, in one of the two beams as seen below:
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The algorithm finds a single background unpolarized spectrum, that when subtracted from all the individual modulated spectra, minimizes the differences in those regions. spectral variation of the mean-normalized intensities. These background intensities correlate well with a known stray light optical pathway. An example of the stray light background in the 854nm channel from June is below. We note that this background is recorded after, and is not impacted by installation of the external baffles discussed above.
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If we then subtract that the background signal from all of the individual spectra, prior to normalization, then we get the following modulation-normalized spectral shape:
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There’s still some residual difference between the normalized spectra, but overall, the normalized spectra look much more spectrally constant. The resulting modulation curves similarly agree much better in overall contrast and uniformity. Ultimately the best way to deal with this issue is to fix it opticallyremove the stray light with appropriate optical aperture stops and masking. Work on this topic is ongoing. The algorithm presented above isn’t is not a perfect solution. It is only intended to get data “good enough” at this point, and further tuning of the algorithm settings is necessary. You may notice that there are some line artifacts visible. If you do have any questions or if you see and any issues with line signals, you are encouraged to ask (DKIST Help Desk.)
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Lamp gains were being used directly. The lamp was designed to be bright, (1% to 15% of the full solar on-disk DKIST beam) but this came at the cost of spatial uniformity. Many of the lamp gains have their own strong optical response and thus this response was affecting all downstream data (both PolCal and science).
The Solar Gain calculation attempted to preserve detector variations through some complicated interpolation steps. Not only was this fundamentally incorrect but the repeated interpolation of narrow solar spectral lines (especially present in 630nm data) left very large spectral residuals. These residuals also affected.
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To identify and characterize the solar spectrum in the Solar Gain images we need to account for variations in the spectral shape along the slit that occur as a result of physical non-uniformities in the actual slit construction. In other words we can’t simply take the median spectrum along the slit because the true solar spectrum actually does vary varies along the slit. To compute the “characteristic spectra” we run a moving 1D Gaussian average along the slit. The width of this Gaussian window is an important tunable parameter.
The core gain algorithms are pretty simple: use a filtered Lamp Gain to remove detector variations, and use a Solar Gain (with solar spectrum removed) to remove several other optical variations. There are some important parameters to tune and further work is necessary to determine the best values for each wavelength region. In some/many cases we may be unable to perfectly remove all optical variations.
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Further improvements have been made to the geometric calculations: The algorithm for rotation between beams during the dual-beam merge was improved to fix some failures with some datasets. The algorithm to compute XY shifts between individual modulation states was updated.
854nm
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(Arm 3) & 397nm (Arm 2)
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Beam 2
An efficiency issue with beam 2 / arm3 (currently 854nm) have been noted.
854nm Beam2 (Arm3) has anomalously low modulation efficiency efficiency (35% vs 50%). It 397nm Beam2 (Arm2) also has reduced efficiency. It is suspected that this is due to low polarization beam splitter contrast. Optical mitigation likely will be required. 854nm Lamp gain has a “step” seen in Beam2. Raw PolCal frames also show this issue. It is unclear as to the origin of this step but it is quite possibly, an internal reflection issue., and modeling is ongoing. We note that subtraction of the intrinsic stray light (above) improved the modulation efficiency, but it remains at / below 38%.
Demodulation Sampling
Spatial scale for demodulation sampling is yet to-be-finalized. The initial “checkerboard” interpolation pattern, seen in earlier releases of ViSP data has now been fixed. However, several other issues create background signals. Further assessment is necessary to find the appropriate trade-off between errors and smoothness.
Multi-slit Position PolCals
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The QUV continuum levels are at variable levels around 1%. We are currently investigating different observing techniques to also improve the polarization zero point performance.
Cross-talk Possibilities
Please check the quality report for your data set to note any failures in PolCal fitting outputs. We have seen data sets where certain variables (transmission of polarization calibration optics) are far away from metrology expectations. For example, in some cases the variable representing the polarizer transmission is fitted to be near 100% transmission when the optic is known to be 91.5% transmission +/-0.3%. This fitting error can create cross-talk of all types through the correlation between fitted variables. The settings for polarization calibration are currently being investigated, and we expect improvements in the demodulation matrix accuracy as the algorithms are tuned.
VBI Data Set Caveats
The following issues have been found / are being worked on with VBI datasets.
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