Page History

• isrTask.py
  
  • Calls "biasCorrection", implemented in isrFunctions.py: subtracts a given biasMaskedImage from the image to correct.

• image_utils.py: there's the function in there called "bias_image()" which calls the function "bias_func()". The latter computes the bias by fitting a polynomial (def=linear) to the mean of each row of the selected overscan region.

Bias offset is removed by computing a row by row correction using the data in the overscan columns.

For each row in the segment, the mean value of the pixels in the serial overscan is computed. A cubic fit is then created for the function: overscan mean vs. row number. For each row of pixels in the image, a bias offset correction is calculated using the fit parameters. That value is then subtracted from that row in the segment (LCA-10301)

Dark current (95th percentile) shall not exceed 0.2 electrons per pixel per second. Measurement to be made at a detector temperature of -95±1° C with dark current integration time of no less than 500 seconds. (LCA-128)

• isrTask.py
  • darkCorrection

• darkCurrentTask.py (compute 95th percentile dark current in units of e-/sec/pixel)

Dark current is measured by calculating the amount of charge collected in each pixel during a dark current integration of a given duration. In order to eliminate the effects of charge generated by cosmic ray impacts, the 5 images in each of the data set are medianed together to create clean dark current images. These images are then bias-offset corrected. Multiplication by the system gain constant (e-/DN), and division by the integration time (seconds) provides a measure of the dark current per pixel in electrons per second. These pixel values are then sorted and the 95th percentile value is calculated (LCA-10103)

Dark integrations are images acquired after the CCD has been cleared of charge and then dark current signal has been allowed to integrate as signal for a specified time in the absence of any photon flux.

CCD-012: Active imaging area and Cosmetic Quality: the active imaging area shall contain no fewer than 16,129,000 pixels. The active imaging area excludes the 9 pixels closest to any edge of the device. The active imaging area definition also excludes any pixel within 5 rows of any midline anti- bloom stop.

Within this active imaging area a maximum of 0.5% of the pixels can be designated as defective. Defective pixels are defined as the following:

(a) any pixel with more than 5e-/s of dark current;
(b) any pixel with 500nm photoresponse less than 80% of the mean;
(c) any pixel in any column in which more than 20 contiguous pixels have more than 5e-/s of dark current;
(d) any pixel in any column in which more than 100 contiguous pixels have a 500nm photoresponse less than 80% of the mean;
(e) any pixel in any column in which a pixel traps more than 200 electrons;

Any defective columns (according to defective pixel definitions d-e above) shall be separated by at least 10 columns. (LCA-128)

• MaskedCCD.py:

Class to handle masks for a full sensor. You can add mask planes, they will be combined with an "||" ("OR"), and you can get bits to be used with an afwMath.makeStatistics object.

Note: The current "main" currently uses the following files:

mask_files = ('bright_pix_mask.fits', 'CCD250_DEFECTS_mask.fits')

• BrightPixels.py

Bright pixel defects and bright column defects are detected using dark integration images.

Find bright pixels and bright columns above a threshold specified in units of e- per second per pixel.

The mask that is generated will be identified as mask_plane.

• DarkPixels.py
  
  Find dark pixels and dark columns above a threshold specified in units of e- per second per pixel.

The mask that is generated will be identified as mask_plane.

• trapTask.py
  Task to find traps from pocket-pumped exposure
  Calls "Traps.py": uses a pocket-pumpet image, lists traps (x,y,size) per amplifier. Has method to write results to a FITS binary table. "Traps.py", in turn, uses the class defined in "TrapFinder.py", uses method in Kotov+14

Includes: bright pixels in dark frames, dark pixels in flat frames, death pixels...

Ask Jim:column defects (9.95 of LCA-10301): are they found by BrightPixels.py and DarkPixels.py? (that's probably the case)

CCD-008: Blooming Full well. Pixel charge capacity shall be no greater than 175,000 electrons. Note: Defined as the point at which the detector response (volts out divided by mean per pixel integrated photo-generated charge) saturates when illuminated by a flat field (LCA-128)

• ptc_full_well.py

Compute full well. Fit linear and quadratic functions to data, with constraint at inferred variance at 1000 e-. Full well obtains where the maximum fractional deviation between the linear and quadratic curves is greater than some maximum value, which is 10% as specified in LCA-128.

DetectorResponse.py also has a full well calculation in "full_well()" function.

-Ask Jim about the difference.

CCD-009:

Detector response (volts out divided by median per pixel integrated photo- generated charge) to flat field illumination shall be linear to within ±2% over the range of 1000 to 90,000 electrons.

The response of the CCD is the mean detected signal vs. incident flux. (LCA-128)

• linearityTask.py, uses DetectorResponse.py (general class to compute detector response charcateristics such as full well and linearity from pairs of flats).

Compute detector response vs incident flux for pairs of flats.

• Fe55GainFitter.py (fit Fe55 signal distribution to obtain the system gain. Two Gaussian model of Mn K-alpha and K-beta lines for Fe55 tests. The ratio of peak locations is fixed at the line energy ratio, and the line widths are assumed to be the same/

• cteTask.py: calls EPERTask() in eperTask.py

CTI is calculated by EPER in overscan using 500 nm superflat (see LCA-10103 9.5.3 for formula).

• cteTask.py: calls EPERTask() in eperTask.py

CTI is calculated by EPER in overscan using 500 nm superflat (see LCA-10103 9.4.3 for formula).

Quantum efficiency in the various LSST filter pass-bands is defined in 6 separate specifications. They are as follows. See LCA-128 for precise definitions of pass-bands and measurement wavelengths:

• CCD-021: u Band QE. u Band QE shall exceed 41%. u band defined as 321nm to 391nm FWHM
• CCD-022: g Band QE. g Band QE shall exceed 78%. g band defined as 402nm to 552nm FWHM
• CCD-023: r Band QE. r Band QE shall exceed 83%. r band defined as 552nm to 691nm FWHM
• CCD-024: i Band QE. i Band QE shall exceed 82%. i band defined as 691nm to 818nm FWHM
• CCD-025: z Band QE. z Band QE shall exceed 75%. z band defined as 818nm to 922nm FWHM
• CCD-026: y Band QE. y Band QE shall exceed 14.4%. y band defined as 930nm to 1070nm FWHM

• qeTask.py: Compute QE curves from the wavelength scan dataset. Uses method "calculate_QE" in class "QE_data", defined in QE.py.

Output-to-output crosstalk shall not exceed 0.19% with a goal of 0.02% (CCD-013, LCA-128)

• crosstalkTask.py (matrix calculation from a set of spot image files), calls crosstalk.py, which contains "system_crosstalk" (aggressor amp has single illuminated column) and "detector_crosstalk" (detector crosstalk from a spot image in aggressor) functions.

"to be measured with a point or line source exposing the sensor to a peak signal of greater than 80,000 electrons of integrated photo-generated charge per exposed pixel in one segment (aggressor), other segments (victims) dark. Measurement to be made at a detector temperature of -95±1° C" LCA-10103. Need to measure system crosstalk (with no CCD, pulse generator creates a column as aggressor) and total crosstalk to get detector crosstalk = total crosstalk - system crosstalk.

CCD-027: PRNU. The measured variation in photoresponse at wavelengths of 350 nm, 450 nm, 500 nm, 620 nm, 750 nm, 870 nm, and 1000 nm shall be less than 5% rms across the CCD. (LCA-128)

• prnuTask.py , uses class defined in prnu.py

• persistenceTask.py: Compute the deferred charge as a function of time in darks taken after a saturated flat has been taken.

Q: Are persistence and tearing the same thing?

e2V, Claire talked about T&RE during ISPA2018. Tearing/rabbit ears can be fixed by clocking things in a particular way. For DECam devices, persistence is fixed via the ERASE mechanism which operates the CCD in inversion for less than a second. Known as "skyline" in LBNL CCDS (according to Juan Estrada).

CCD-028: Point Spread Function. The PSF due to charge diffusion shall not exceed 5 μm rms. Note: The PSF measurement is via analysis of Fe55 x-ray generated charge packets. Algorithm for analysis shall be provided by LSST

The PSF due to charge diffusion is measured using the Fe55 data set

• fe55_psf.py: Fit 2D gaussian to Fe55 footprints to determine the Gaussian width of the charge dispersed signals. For each footprint, also compute the probability of the chi-square fit.
  Distribution of dispersion parameters is fit with model in Kotov+12.