A 3D model for carbon monoxide molecular line emission as a potential cosmic microwave background polarization contaminant

We present a model for simulating Carbon Monoxide (CO) rotational line emission in molecular clouds, taking account of their 3D spatial distribution in galaxies with different geometrical properties. The model implemented is based on recent results in the literature and has been designed for performing Monte-Carlo simulations of this emission. We compare the simulations produced with this model and calibrate them, both on the map level and on the power spectrum level, using the second release of data from the Planck satellite for the Galactic plane, where the signal-to-noise ratio is highest. We use the calibrated model to extrapolate the CO power spectrum at low Galactic latitudes where no high sensitivity observations are available yet. We then forecast the level of unresolved polarized emission from CO molecular clouds which could contaminate the power spectrum of Cosmic Microwave Background (CMB) polarization B-modes away from the Galactic plane. Assuming realistic levels of the polarization fraction, we show that the level of contamination is equivalent to a cosmological signal with r 720.02. The Monte-Carlo MOlecular Line Emission (MCMole3D) Python package, which implements this model, is being made publicly available

Smoke in the Pipe Nebula: dust emission and grain growth in the starless core FeSt 1-457

J. Forbrich, et al., “Smoke in the Pipe Nebula: dust emission and grain growth in the starless core FeSt 1-457”, Astronomy & Astrophysics, Vol 580, August 2015. This version of record is available online at: https://doi.org/10.1051/0004-6361/201425375 Reproduced with Permission from Astronomy and Astrophysics, © ESO 2016.(abridged) Methods: We derive maps of submillimeter dust optical depth and effective dust temperature from Herschel data that were calibrated against Planck. After calibration, we then fit a modified blackbody to the long-wavelength Herschel data, using the Planck-derived dust opacity spectral index beta, derived on scales of 30' (or ~1 pc). We use this model to make predictions of the submillimeter flux density at 850 micron, and we compare these in turn with APEX-Laboca observations. Results: A comparison of the submillimeter dust optical depth and near-infrared extinction data reveals evidence for an increased submillimeter dust opacity at high column densities, interpreted as an indication of grain growth in the inner parts of the core. Additionally, a comparison of the Herschel dust model and the Laboca data reveals that the frequency dependence of the submillimeter opacity, described by the spectral index beta, does not change. A single beta that is only slightly different from the Planck-derived value is sufficient to describe the data, beta=1.53+/-0.07. We apply a similar analysis to Barnard 68, a core with significantly lower column densities than FeSt 1-457, and we do not find evidence for grain growth but also a single beta. Conclusions: While we find evidence for grain growth from the dust opacity in FeSt 1-457, we find no evidence for significant variations in the dust opacity spectral index beta on scales 0.02x36x30'). The correction to the Planck-derived dust beta that we find in both cases is on the order of the measurement error, not including any systematic errors, and it would thus be reasonable to directly apply the dust beta from the Planck all-sky dust model. As a corollary, reliable effective temperature maps can be derived which would be otherwise affected by beta variations.Peer reviewe

Planck 2013 results X. Energetic particle effects: characterization, removal, and simulation

This paper presents the detection, interpretation and removal of the signal resulting from interactions of high energy particles with the Planck High Frequency Instrument (HFI). These interactions fall into two categories, heating the 0.1 K bolometer plate and glitches in each detector time stream. Glitch shapes are not simple single pole exponential decays and fall into a three families. The glitch shape for each family has been characterized empirically in flight data and removed from the detector time streams. The spectrum of the count rate/unit energy is computed for each family and a correspondence to where on the detector the particle hit is made. Most of the detected glitches are from galactic protons incident on the Si die frame supporting the micromachined bolometric detectors. At HFI, the particle flux is ~ 5 per square cm and per second and is dominated by protons incident on the spacecraft with an energy >39 MeV, leading to a rate of typically one event per second and per detector. Different categories of glitches have different signature in timestreams. Two of the glitch types have a low amplitude component that decays over nearly 1 second. This component produces an excess noise if not properly removed from the time ordered data. We have used a glitch detection and subtraction method based on the joint fit of population templates. The application of this novel glitch removal method removes excess noise from glitches. Using realistic simulations, we find this method does not introduce signal bias.Comment: 23 pages; v2: author list complete

Planck 2013 results. III. LFI systematic uncertainties

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 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 (CMB) fluctuations as measured in terms of the angular temperature power spectrum. A residual signal above the noise level is present in the multipole range $\ell<20$, most notably at 30 GHz, and is likely 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.Comment: Accepted for publication by A&

Planck 2013 results. VI. High Frequency Instrument data processing

We describe the processing of the 531 billion raw data samples from the High Frequency Instrument (hereafter HFI), which we performed to produce six temperature maps from the first 473 days of Planck-HFI survey data. These maps provide an accurate rendition of the sky emission at 100, 143, 217, 353, 545, and 857 GHz with an angular resolution ranging from 9.7 to 4.6 arcmin. The detector noise per (effective) beam solid angle is respectively, 10, 6, 12 and 39 microKelvin in HFI four lowest frequency channel (100--353 GHz) and 13 and 14 kJy/sr for the 545 and 857 GHz channels. Using the 143 GHz channel as a reference, these two high frequency channels are intercalibrated within 5% and the 353 GHz relative calibration is at the percent level. The 100 and 217 GHz channels, which together with the 143 GHz channel determine the high-multipole part of the CMB power spectrum (50 &lt; l &lt;2500), are intercalibrated at better than 0.2 %

Planck 2015 results. XXVII. The second Planck catalogue of Sunyaev-Zeldovich sources

We present the all-sky Planck catalogue of Sunyaev-Zeldovich (SZ) sources detected from the 29 month full-mission data. The catalogue (PSZ2) is the largest SZ-selected sample of galaxy clusters yet produced and the deepest systematic all-sky surveyof galaxy clusters. It contains 1653 detections, of which 1203 are confirmed clusters with identified counterparts in external data sets, and is the first SZ-selected cluster survey containing >103 confirmed clusters. We present a detailed analysis of the survey selection function in terms of its completeness and statistical reliability, placing a lower limit of 83% on the purity. Using simulations, we find that the estimates of the SZ strength parameter Y5R500are robust to pressure-profile variation and beam systematics, but accurate conversion to Y500 requires the use of prior information on the cluster extent. We describe the multi-wavelength search for counterparts in ancillary data, which makes use of radio, microwave, infra-red, optical, and X-ray data sets, and which places emphasis on the robustness of the counterpart match. We discuss the physical properties of the new sample and identify a population of low-redshift X-ray under-luminous clusters revealed by SZ selection. These objects appear in optical and SZ surveys with consistent properties for their mass, but are almost absent from ROSAT X-ray selected samples

Planck 2013 results. XX. Cosmology from Sunyaev-Zeldovich cluster counts

We present constraints on cosmological parameters using number counts as a function of redshift for a sub-sample of 189 galaxy clusters from the Planck SZ (PSZ) catalogue. The PSZ is selected through the signature of the Sunyaev--Zeldovich (SZ) effect, and the sub-sample used here has a signal-to-noise threshold of seven, with each object confirmed as a cluster and all but one with a redshift estimate. We discuss the completeness of the sample and our construction of a likelihood analysis. Using a relation between mass $M$ and SZ signal $Y$ calibrated to X-ray measurements, we derive constraints on the power spectrum amplitude $\sigma_8$ and matter density parameter $\Omega_{\mathrm{m}}$ in a flat $\Lambda$CDM model. We test the robustness of our estimates and find that possible biases in the $Y$--$M$ relation and the halo mass function are larger than the statistical uncertainties from the cluster sample. Assuming the X-ray determined mass to be biased low relative to the true mass by between zero and 30%, motivated by comparison of the observed mass scaling relations to those from a set of numerical simulations, we find that $\sigma_8=0.75\pm 0.03$, $\Omega_{\mathrm{m}}=0.29\pm 0.02$, and $\sigma_8(\Omega_{\mathrm{m}}/0.27)^{0.3} = 0.764 \pm 0.025$. The value of $\sigma_8$ is degenerate with the mass bias; if the latter is fixed to a value of 20% we find $\sigma_8(\Omega_{\mathrm{m}}/0.27)^{0.3}=0.78\pm 0.01$ and a tighter one-dimensional range $\sigma_8=0.77\pm 0.02$. We find that the larger values of $\sigma_8$ and $\Omega_{\mathrm{m}}$ preferred by Planck's measurements of the primary CMB anisotropies can be accommodated by a mass bias of about 40%. Alternatively, consistency with the primary CMB constraints can be achieved by inclusion of processes that suppress power on small scales relative to the $\Lambda$CDM model, such as a component of massive neutrinos (abridged).Comment: 20 pages, accepted for publication by A&

Planck 2015 results. V. LFI calibration

We present a description of the pipeline used to calibrate the Planck Low Frequency Instrument (LFI) timelines into thermodynamic temperatures for the Planck 2015 data release, covering four years of uninterrupted operations. As in the 2013 data release, our calibrator is provided by the spin-synchronous modulation of the cosmic microwave background dipole, but we now use the orbital component, rather than adopting the Wilkinson Microwave Anisotropy Probe (WMAP) solar dipole. This allows our 2015 LFI analysis to provide an independent Solar dipole estimate, which is in excellent agreement with that of HFI and within 1σ (0.3% in amplitude) of the WMAP value. This 0.3% shift in the peak-to-peak dipole temperature from WMAP and a general overhaul of the iterative calibration code increases the overall level of the LFI maps by 0.45% (30 GHz), 0.64% (44 GHz), and 0.82% (70 GHz) in temperature with respect to the 2013 Planck data release, thus reducing the discrepancy with the power spectrum measured by WMAP. We estimate that the LFI calibration uncertainty is now at the level of 0.20% for the 70 GHz map, 0.26% for the 44 GHz map, and 0.35% for the 30 GHz map. We provide a detailed description of the impact of all the changes implemented in the calibration since the previous data release

Planck 2015 results. VI. LFI mapmaking

This paper describes the mapmaking procedure applied to Planck Low Frequency Instrument (LFI) data. The mapmaking step takes as input the calibrated timelines and pointing information. The main products are sky maps of I, Q, and U Stokes components. For the first time, we present polarization maps at LFI frequencies. The mapmaking algorithm is based on a destriping technique, which is enhanced with a noise prior. The Galactic region is masked to reduce errors arising from bandpass mismatch and high signal gradients. We apply horn-uniform radiometer weights to reduce the effects of beam-shape mismatch. The algorithm is the same as used for the 2013 release, apart from small changes in parameter settings. We validate the procedure through simulations. Special emphasis is put on the control of systematics, which is particularly important for accurate polarization analysis. We also produce low-resolution versions of the maps and corresponding noise covariance matrices. These serve as input in later analysis steps and parameter estimation. The noise covariance matrices are validated through noise Monte Carlo simulations. The residual noise in the map products is characterized through analysis of half-ring maps, noise covariance matrices, and simulations

Planck 2013 results. IX. HFI spectral response

The Planck High Frequency Instrument (HFI) spectral response was determined through a series of ground based tests conducted with the HFI focal plane in a cryogenic environment prior to launch. The main goal of the spectral transmission tests was to measure the relative spectral response (including out-of-band signal rejection) of all HFI detectors. This was determined by measuring the output of a continuously scanned Fourier transform spectrometer coupled with all HFI detectors. As there is no on-board spectrometer within HFI, the ground-based spectral response experiments provide the definitive data set for the relative spectral calibration of the HFI. The spectral response of the HFI is used in Planck data analysis and component separation, this includes extraction of CO emission observed within Planck bands, dust emission, Sunyaev-Zeldovich sources, and intensity to polarization leakage. The HFI spectral response data have also been used to provide unit conversion and colour correction analysis tools. Verifications of the HFI spectral response data are provided through comparisons with photometric HFI flight data. This validation includes use of HFI zodiacal emission observations to demonstrate out-of-band spectral signal rejection better than 10^8. The accuracy of the HFI relative spectral response data is verified through comparison with complementary flight-data based unit conversion coefficients and colour correction coefficients. These coefficients include those based upon HFI observations of CO, dust, and Sunyaev-Zeldovich emission. General agreement is observed between the ground-based spectral characterization of HFI and corresponding in-flight observations, within the quoted uncertainty of each; explanations are provided for any discrepancies.Comment: 27 pages, 28 figures, one of the papers associated with the 2013 Planck data releas