Planck-LFI radiometers' spectral response

Zonca, A.; Franceschet, C.; Battaglia, P.; Villa, F.; Mennella, A.; D'Arcangelo, O.; Silvestri, R.; Bersanelli, M.; Artal, E.; Butler, R. C.; Cuttaia, F.; Davis, R. J.; Galeotta, S.; Hughes, N.; Jukkala, P.; Kilpiä, V. H.; Laaninen, M.; Mandolesi, N.; Maris, M.; Mendes, L.; Sandri, M.; Terenzi, L.; Tuovinen, J.; Varis, J.; Wilkinson, A.

doi:10.1088/1748-0221/4/12/t12010

Cited by 25 publications

(39 citation statements)

References 15 publications

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“…In principle, the a-factors can be estimated from the bandpass profiles measured in the ground calibration campaign (Zonca et al 2009), but as anticipated by Leahy et al (2010), more accurate values can be found from the flight data; a detailed description of our approach to this will be discussed in a future paper. We estimate that our a-factors are currently accurate to about 0.05%, based on the scatter in values derived from multiple calibrators.…”

Section: Polarizationmentioning

confidence: 99%

Planck2013 results. II. Low Frequency Instrument data processing

Aghanim

Armitage-Caplan

Arnaud

et al. 2014

A&A

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We describe the data processing pipeline of the Planck Low Frequency Instrument (LFI) data processing centre (DPC) to create and characterize full-sky maps based on the first 15.5 months of operations at 30, 44, and 70 GHz. In particular, we discuss the various steps involved in reducing the data, from telemetry packets through to the production of cleaned, calibrated timelines and calibrated frequency maps. Data are continuously calibrated using the modulation induced on the mean temperature of the cosmic microwave background radiation by the proper motion of the spacecraft. Sky signals other than the dipole are removed by an iterative procedure based on simultaneous fitting of calibration parameters and sky maps. Noise properties are estimated from time-ordered data after the sky signal has been removed, using a generalized least squares map-making algorithm. A destriping code (Madam) is employed to combine radiometric data and pointing information into sky maps, minimizing the variance of correlated noise. Noise covariance matrices, required to compute statistical uncertainties on LFI and Planck products, are also produced. Main beams are estimated down to the ≈−20 dB level using Jupiter transits, which are also used for the geometrical calibration of the focal plane.

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Section: Polarizationmentioning

confidence: 99%

Planck2013 results. II. Low Frequency Instrument data processing

Aghanim

Armitage-Caplan

Arnaud

et al. 2014

A&A

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“…In practice, all the colour corrections listed in Table 1 are derived from averages across two or more bandpasses: values for individual radiometric chain assemblies (RCA) require averaging the main and side radiometers in each RCA, and the response of each radiometer is the average of the two independent detectors (Zonca et al 2009). For consistency, the weighting for these averages must duplicate the procedure used to average the data, as described in Planck Collaboration II (2014).…”

Section: Colour Correctionsmentioning

confidence: 99%

“…The difference is minor, since η ∆T varies by only a very small amount within any of the LFI bands, but it accounts for a small (<0.1%) difference between the C(α) values listed here and those derivable from the RIMO bandpasses. Our best estimate of the uncertainty in the values of C(α), dominated by bandpass uncertainty (Zonca et al 2009), comes from an indirect method, as follows. The two radiometers in each RCA, known as the main-and side-arms, are sensitive to orthogonal polarizations.…”

Section: Colour Correctionsmentioning

confidence: 99%

Planck2013 results. V. LFI calibration

Aghanim¹,

Armitage-Caplan²,

Arnaud³

et al. 2014

A&A

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We discuss the methods employed to photometrically calibrate the data acquired by the Low Frequency Instrument on Planck. Our calibration is based on a combination of the orbital dipole plus the solar dipole, caused respectively by the motion of the Planck spacecraft with respect to the Sun and by motion of the solar system with respect to the cosmic microwave background (CMB) rest frame. The latter provides a signal of a few mK with the same spectrum as the CMB anisotropies and is visible throughout the mission. In this data release we rely on the characterization of the solar dipole as measured by WMAP. We also present preliminary results (at 44 GHz only) on the study of the Orbital Dipole, which agree with the WMAP value of the solar system speed within our uncertainties. We compute the calibration constant for each radiometer roughly once per hour, in order to keep track of changes in the detectors' gain. Since non-idealities in the optical response of the beams proved to be important, we implemented a fast convolution algorithm which considers the full beam response in estimating the signal generated by the dipole. Moreover, in order to further reduce the impact of residual systematics due to sidelobes, we estimated time variations in the calibration constant of the 30 GHz radiometers (the ones with the largest sidelobes) using the signal of an internal reference load at 4 K instead of the CMB dipole. We have estimated the accuracy of the LFI calibration following two strategies: (1) we have run a set of simulations to assess the impact of statistical errors and systematic effects in the instrument and in the calibration procedure; and (2) we have performed a number of internal consistency checks on the data and on the brightness temperature of Jupiter. Errors in the calibration of this Planck/LFI data release are expected to be about 0.6% at 44 and 70 GHz, and 0.8% at 30 GHz. Both these preliminary results at low and high are consistent with WMAP results within uncertainties and comparison of power spectra indicates good consistency in the absolute calibration with HFI (0.3%) and a 1.4σ discrepancy with WMAP (0.9%).

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“…The external straylight contamination is evaluated with simulations in which the sky model includes the diffuse Galactic emission and the dipole, the two most important sources of external straylight contamination. At 30 GHz, the straylight assessment includes the beam frequency dependence and the receiver in-band response (see Zonca et al 2009;Planck Collaboration IX 2014) by dividing the bandpass response into discrete frequency intervals. For each frequency interval a weight factor is calculated as the integral of the bandpass response over the interval itself.…”

Section: Hz Spikesmentioning

confidence: 99%

“…Although accurate knowledge of the bandpass response allows us, in principle, to correct for this effect during data analysis, the ground bandpass measurements were not accurate enough to maintain this residual below 1% (Zonca et al 2009). For this reason the spurious polarisation from bandpass mismatch was estimated and removed using flight data, as described in Planck Collaboration II (2014).…”

Section: Introductionmentioning

confidence: 99%

Planck2013 results. III. LFI systematic uncertainties

Aghanim

Armitage-Caplan

Arnaud

et al. 2014

A&A

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We present the current estimate of instrumental and systematic effect uncertainties for the Planck-Low Frequency Instrument relevant to the first release of the Planck cosmological results. We give an overview of the main effects and of the tools and methods applied to assess residuals in maps and power spectra. We also present an overall budget of known systematic effect uncertainties, which are dominated by sidelobe straylight pick-up and imperfect calibration. However, even these two effects are at least two orders of magnitude weaker than the cosmic microwave background fluctuations as measured in terms of the angular temperature power spectrum. A residual signal above the noise level is present in the multipole range < 20, most notably at 30 GHz, and is probably caused by residual Galactic straylight contamination. Current analysis aims to further reduce the level of spurious signals in the data and to improve the systematic effects modelling, in particular with respect to straylight and calibration uncertainties.

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Planck-LFI radiometers' spectral response

Cited by 25 publications

References 15 publications

Planck2013 results. II. Low Frequency Instrument data processing

Planck2013 results. II. Low Frequency Instrument data processing

Planck2013 results. V. LFI calibration

Planck2013 results. III. LFI systematic uncertainties

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