1611.08467
The design strategy of scientific data quality control software for Euclid mission
Brescia et al
The most valuable asset of a space mission like Euclid are the data. Due to their huge volume, the automatic quality control becomes a crucial aspect over the entire lifetime of the experiment. Here, focus on the design strategy for the Science Ground Segment (SGS) Data Quality Common Tools (DQCT), which has the main role to provide SW solutions to gather, evaluate, and record quality information about the raw and derived data products from a primarily scientific perspective. The SGS DQCT will provide a quantitive basis for evaluating the application of reduction and calibration reference data, as well as diagnostic tools for quality parameters, flags, trend analysis diagrams and any other metadata parameter produced by the pipeline. In a large program like Euclid, it is prohibitively expensive to process large amount of data at the pixel level just for the purpose of quality evaluation. Thus, all measures of quality at the pixel level are implemented in the individual pipeline stages, and passed along as metadata in the production. In this sense most of the tasks related to science data quality are delegated to the pipeline stages, even though the responsibility for science data quality is managed at a higher level. The DQCT subsystem of the SGS is currently under development, but its path to full realization will likely be different than that of other subsystems. Primarily because, due to a high level of parallelism and to the wide pipeline processing redundancy, for instance the mechanism of double SDC for each processing function, the data quality tools have not only to be widely spread over all pipeline segments and data levels, but also to minimize the occurrences of potential diversity of solutions implemented for similar functions, ensuring the maximum of coherency and standardization for quality evaluation and reporting in the SGS.
1611.08606
Lensing is Low: cosmology, galaxy formation, or new physics?
Leauthaud, Saito, Hilbert, ... et al
Present high S/N GGL measurements of the BOSS CMASS sample using 250 square degrees of WL data from CFHTLenS and CS82. Compare this signal with predictions from mock catalogs trained to match observables including the stellar mass function and the projected and 2d clustering of CMASS. Show that the clustering of CMASS, together with standard models of the galaxy-halo connection, robustly predicts a lensing signal that is 20-40% larger than observed. Detailed tests show that the results are robust to a variety of systematic effects. Lowering the value of S8=sigma8 sqrt(Omega_m/0.3) compared to Planck 2015 reconciles the lensing with clustering. However, given the scale of the measurement (r<10 Mpc/h), other effects may also be at play and need to be taken into consideration. Explore the impact of baryon physics, assembly bias, massive neutrinos, and modifications to general relativity on DeltaSigma and show that several of these effects may be non-negligible given the precision of the measurement. Disentangling cosmo effects form the details of the galaxy-halo connection, the effects of baryons, and massive neutrinos, is the next challenge facing joint lensing and clustering analyses. This is especially true in the context of large galaxy sample from BAO surveys with precise measurements but complex selection functions.
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