LFI-Validation

Overview

Data validation is a step of paramount importance in the complex process of data analysis and the extraction of the final scientific goals of an experiment. The LFI approach to data validation is based upon null-tests approach and here we present the rationale behind envisaged/performed null-tests and the actual results for the present data release. Also we will provide results of the same kind of tests performed on previous release to show the overall improvements in the data quality.

Null-tests approach

In general null-tests are performed in order to highlight possible issues in the data related to instrumental systematic effect not properly accounted for within the processing pipeline and related to known events of the operational conditions (e.g. switch-over of the sorption coolers) or to intrinsic instrument properties coupled with sky signal like stray-light contamination.

Such null-tests are expected to be performed considering data on different time scales ranging from 1-minute to one year of observations, at different unit level (radiometer, horn, horn-pair, within frequency and cross-frequency both in total intensity and, when applicable, to polarisation.

This is quite demanding in terms of all possible combinations. In addition some tools are already available and can be properly used for this kind of analysis. However it may be possible that on some specific time-scale, detailed tools have to be developed in order to produce the desired null-test results. In this respect the actual half-ring jack-knives are suitable to track any effects on pointing period times scales. On time-scales between half-ring and survey there are lot of possibilities. It has to be verified if the actual code producing half-ring jack-knives ({\tt madam}) can handle data producing jack-knives of larger (e.g. 1 hour) times scales.

It is fundamental that such test have to be performed on DPC data product with clear and identified properties (e.g. single $R$, $DV/V$ single fit, etc.) in order to avoid any possible mis-understanding due to usage of non homogeneous data sets.

Many of the null-tests proposed are done at map level with sometime compression of their statistical information into an angular power spectrum. However together with full-sky maps it is interesting to have a closer look on some specific sources. I would be important to compare fluxes from both polarized and un-polarized point sources with different radiometers in order to asses possible calibration mis-match and/or polarization leakage issues. Such comparison will also possibly indicate problems related to channel central frequencies. The proposed set of sources would be: M42, Tau A, Cas A and Cyg A. However other H{\sc II} regions like Perseus are valuable. One can compare directly their fluxes from different sky surveys and/or the flux of the difference map and how this is consistent with instrumental noise.

Which kind of effect is probed with a null-test on a specific time scale? Here it is a simple list. At survey time scale it is possible to underlying any side-lobes effects, while on time scales of full-mission, it is possible to have an indication of calibration problems when observing the sky with the same S/C orientation. Differences at this time scale between horns at the same frequency may also reveal central frequency and beam issues.