CHAR-TARGET-001: Color Gradient Calibration Fields

Parent requirement

R-CAL-B-VS-6100
R-CAL-B-VS-6200
R-CAL-B-VS-6300
R-CAL-B-VS-6400
R-CAL-B-NP-4100
R-CAL-B-NP-4200
R-CAL-B-NP-4300
R-CAL-B-NP-4400

Objective

This is mostly NISP supporting VIS. For NISP itself, these observations are secondary.

VIS: Color gradients (spatially variable SEDs) within galaxies bias the shear measurement. The bias is larger for broad filters and if the PSF is a strong function of wavelength, both of which apply for the broad VIS filter and the diffraction limited Euclid PSF.

The impact of this bias was studied in Semboloni et al. (2013) and Er et al. (2018), showing that the bias can be calibrated using HST observations for which F606W and F814W data are available. Euclid observations of these HST fields are used to validate the analysis of the HST data, and to improve the (photometric) redshift estimates of the galaxies. The latter is important, because the bias depends on redshift, and needs to be determined for each tomographic redshift bin.

Compared to a pure instrumental calibration, this is a sample characterization task with high scientific value due to extensive ancillary ground- and space-based data.

NISP: Color gradients in galaxies could lead to a measurable effect in PSF photometry; it is possible that this effect is negligible, and could be corrected for in a later data release. The effect could be simulated by having different galaxy components with different SEDs. Currently, only a single SED is used.

Cadence

Observations

Targets and pointing constraints

Table 14: Color gradient calibration fields. N_ROS refers to the number of times the ROS needs to be repeated for each pointing to reach the desired S/N, compensating for extinction and background. N_ROS is determined by EC-SURV and not imposed by calibration. CSV file

# ID

R.A.

Dec

Geometry

N_ROS

Time

CANDLES/AEGIS

214.827

+52.82

2x1

18

42.3 h

CANDELS/GOODS-NORTH

189.250

+62.25

1x1

18

21.5 h

CANDELS/COSMOS*

150.120

+02.35

1x1

46

0.0 h (54.9 h)

CANDELS/UDS*

34.407

-05.22

1x1

37

0.0 h (44.2 h)

CANDELS/GOODS-CDFS*

53.125

-27.80

1x1

22

0.0 h (26.3 h)

* Note that the COSMOS, UDS and CDFS fields are already fully covered by CALBLOCK-F-005: Photo-z Calibration Fields observations.

Instrument configuration

Inter-operability constraints

Dependencies

Fulfilling

Fulfilled by

CALBLOCK-F-004: Color Gradient Calibration Fields

Time-critical

The AEGIS field should be completed in the first year as it has the largest HST coverage. At least one field must be observed every following year.

Validation

This is a substantial off-line task that must be worked out manually, see Er et al. (2018). The number and depth of fields provide sufficient control to validate the efficacy of the bias correction.

Recovery

The expected bias is small, and the PSF accuracy needed for this specific correction is not too restrictive. Hence this bias correction is weakly sensitive to the typical PSF variations experienced by VIS as a function of SAA and AA variation.

Decontamination would be a major event with the potential to significantly alter the PSF. The hope is that the underlying wavefront basis set and pupil amplitude model will remain unchanged. The particular PSF realisation may change, as long as that realisation is still drawn from the same basis set obtained from potential phase diversity observations.

If a remeasurement of in-focus PSF calibration fields after a decontamination event indicates that the PSF basis set is no longer valid, then in principal all calibrations that depend on the PSF should be repeated. In practice, that may not be required for those corrections which are weakly sensitive to PSF accuracy. The color gradient bias correction is likely one of them, but this cannot be predicted ahead of time.

In-orbit duration

Processing time

Processing input

Ground Processing Input Data: Full data set as for nominal wide/deep survey observations.

Data Description: Repeated wide-survey sequences of the same area.

Data volume

267948 MB (54 executions of the ROS)

Processing tools

L1 science pipeline for pixel processing. Manual tools to infer color gradient bias correction.

Processing element

DataModel: https://gitlab.euclid-sgs.uk/

Quality control parameters

DataModel: https://gitlab.euclid-sgs.uk/

Required accuracy, constraints

Processing method

Processing output

Same data products as for wide and deep survey fields.

Contact person

Calibration Lead

Status

2026/09/18 - In progress.

FLAG

Priority

Observation record

Comments