Predictive model of the temporal noise correlations in HgCdTe array

Kubik, B.; Barbier, R.; Castera, A.; Chabanat, E.; Ferriol, S.; Smadja, G.

doi:10.1016/j.nima.2015.01.011

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…The correlated readout noise is assumed to be Gaussian distributed with a (1/ f ) α -like spectrum in Fourier domain as in Kubik et al (2015b). In the time domain this is equivalent to a Gaussian distributed noise described by a correlation function 3 of the form: C [|δ t |], where δ t is the time interval between two given frames.…”

Section: Correlated Noise Covariance Matrixmentioning

confidence: 99%

“…The main properties of the readout noise assuming white noise are characterized during ground calibration and used in-flight. However, it has been found that individual H2RGs may present some level of correlated noise in the form of (1/ f ) α -like noise (Smadja et al 2010;Kubik et al 2015b). Such noise correlation might bias Euclid in-flight flux estimates.…”

Section: Introductionmentioning

confidence: 99%

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Euclid: Estimation of the Impact of Correlated Readout Noise for Flux Measurements with the Euclid NISP Instrument*

Munoz

Macías-Pérez

Secroun

et al. 2021

PASP

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The Euclid satellite, to be launched by ESA in 2022, will be a major instrument for cosmology for the next decades. Euclid is composed of two instruments: the Visible (VIS) instrument and the Near Infrared Spectromete and Photometer (NISP). In this work we estimate the implications of correlated readout noise in the NISP detectors for the final in-flight flux measurements. Considering the multiple accumulated (MACC) readout mode, for which the UTR (Up The Ramp) exposure frames are averaged in groups, we derive an analytical expression for the noise covariance matrix between groups in the presence of correlated noise. We also characterize the correlated readout noise properties in the NISP engineering grade detectors using long dark integrations. For this purpose, we assume a (1/ f ) α -like noise model and fit the model parameters to the data, obtaining typical values of σ = 19.7 +1.1 −0.8 e − Hz −0.5 , f knee = 5.2 +1.8 −1.3 × 10 −3 Hz and α = 1.24 +0.26 −0.21 . Furthermore, via realistic simulations and using a maximum likelihood flux estimator we derive the bias between the input flux and the recovered one. We find that using our analytical expression for the covariance matrix of the correlated readout noise we diminish this bias by up to a factor of four with respect to the white noise approximation for the covariance matrix. Finally, we conclude that the final bias on the in-flight NISP flux measurements should still be negligible even in the white noise approximation, which is taken as a baseline for the Euclid on-board processing.

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Section: Correlated Noise Covariance Matrixmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Euclid: Estimation of the Impact of Correlated Readout Noise for Flux Measurements with the Euclid NISP Instrument*

Munoz

Macías-Pérez

Secroun

et al. 2021

PASP

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“…The readout noise s R is assumed here to be uncorrelated from frame to frame, i.e., we neglect the f 1 noise component which correlates all the groups in the exposure. An estimate of the contribution of the f 1 noise to the signal variance was derived in Smadja et al (2010) and Kubik et al (2015b). It was shown that the f 1 noise component depends on the exact timing scheme adopted for the acquisition and can be significant for long spectroscopic exposures.…”

Section: Importance Of Working In the Differential Signal Modementioning

confidence: 99%

A New Signal Estimator from the NIR Detectors of the Euclid Mission

Kubik

Barbier

Chabanat

et al. 2016

PASP

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We describe how the Euclid detectors in the Near Infrared Spectrometer and Photometer (NISP) channel will be read out on board and present an analytic expression for the estimated fluence in each pixel with the associated quality factor of the fit per pixel. The method accounts for the Poisson like distribution of the data and includes the effects of noise correlations that arise after the coadding procedure of frames read non-destructively up the ramp during one exposure. The bias of the flux estimator presented in this paper is kept lower than 0.3% over a wide rang of scientifically interesting fluxes of Euclid. The associated error is by 6% lower than the commonly used formula derived in Rauscher et al. in the context of an equally weighted least squares fit. Moreover, the quality factor follows the very well known c x n ; th 2 ( ) distribution and thus provides a well behaved statistical tool to check the goodness of the ramp fit. The method is proposed in the context of a large amount of data per exposure, produced by the NISP detectors, that cannot be transferred to the ground for the subsequent processing. The method, which is validated using real and simulated test data, can be safely used by most near-infrared instruments which require very accurate measurements to be performed on board.

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