Browsing by Subject "methods: data analysis"

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  • Pihajoki, Pauli (2017)
    We propose a new mathematical model for n - k-dimensional non-linear correlations with intrinsic scatter in n-dimensional data. The model is based on Riemannian geometry and is naturally symmetric with respect to the measured variables and invariant under coordinate transformations. We combine the model with a Bayesian approach for estimating the parameters of the correlation relation and the intrinsic scatter. A side benefit of the approach is that censored and truncated data sets and independent, arbitrary measurement errors can be incorporated. We also derive analytic likelihoods for the typical astrophysical use case of linear relations in n-dimensional Euclidean space. We pay particular attention to the case of linear regression in two dimensions and compare our results to existing methods. Finally, we apply our methodology to the well-known MBH-s correlation between the mass of a supermassive black hole in the centre of a galactic bulge and the corresponding bulge velocity dispersion. The main result of our analysis is that the most likely slope of this correlation is similar to 6 for the data sets used, rather than the values in the range of similar to 4-5 typically quoted in the literature for these data.
  • Keihänen, E.; Kiiveri, K.; Kurki-Suonio, H.; Reinecke, M. (2017)
    We present two novel methods for the estimation of the angular power spectrum of cosmic microwave background (CMB) anisotropies. We assume an absolute CMB experiment with arbitrary asymmetric beams and arbitrary sky coverage. The methods differ from the earlier ones in that the power spectrum is estimated directly from the time-ordered data, without first compressing the data into a sky map, and they take into account the effect of asymmetric beams. In particular, they correct the beam-induced leakage from temperature to polarization. The methods are applicable to a case where part of the sky has been masked out to remove foreground contamination, leaving a pure CMB signal, but incomplete sky coverage. The first method (deconvolution quadratic maximum likelihood) is derived as the optimal quadratic estimator, which simultaneously yields an unbiased spectrum estimate and minimizes its variance. We successfully apply it to multipoles up to l = 200. The second method is derived as a weak-signal approximation from the first one. It yields an unbiased estimate for the full multipole range, but relaxes the requirement of minimal variance. We validate the methods with simulations for the 70 GHz channel of Planck surveyor, and demonstrate that we are able to correct the beam effects in the TT, EE, BB and TE spectra up to multipole l = 1500. Together, the two methods cover the complete multipole range with no gap in between.
  • Penttilä, Antti; Hietala, Hilppa; Muinonen, Karri (2021)
    Aims. We explore the performance of neural networks in automatically classifying asteroids into their taxonomic spectral classes. We particularly focus on what the methodology could offer the ESA Gaia mission.Methods. We constructed an asteroid dataset that can be limited to simulating Gaia samples. The samples were fed into a custom-designed neural network that learns how to predict the samples' spectral classes and produces the success rate of the predictions. The performance of the neural network is also evaluated using three real preliminary Gaia asteroid spectra.Results. The overall results show that the neural network can identify taxonomic classes of asteroids in a robust manner. The success in classification is evaluated for spectra from the nominal 0.45-2.45 mu m wavelength range used in the Bus-DeMeo taxonomy, and from a limited range of 0.45-1.05 mu m following the joint wavelength range of Gaia observations and the Bus-DeMeo taxonomic system.Conclusions. The obtained results indicate that using neural networks to execute automated classification is an appealing solution for maintaining asteroid taxonomies, especially as the size of the available datasets grows larger with missions like Gaia.
  • Tauber, J. A.; Nielsen, P. H.; Martin-Polegre, A.; Crill, B.; Cuttaia, F.; Ganga, K.; Gudmundsson, J.; Jones, W.; Lawrence, C.; Meinhold, P.; Norgaard-Nielsen, H. U.; Oxborrow, C. A.; Partridge, B.; Roudier, G.; Sandri, M.; Scott, D.; Terenzi, L.; Villa, F.; Bernard, J. P.; Burigana, C.; Franceschi, E.; Kurki-Suonio, H.; Mandolesi, N.; Puget, J. L.; Toffolatti, L. (2019)
    The European Space Agency's Planck satellite was launched on 14 May 2009, and surveyed the sky stably and continuously between August 2009 and October 2013. The scientific analysis of the Planck data requires understanding the optical response of its detectors, which originates partly from a physical model of the optical system. In this paper, we use in-flight measurements of planets within similar to 1 degrees of boresight to estimate the geometrical properties of the telescope and focal plane. First, we use observed grating lobes to measure the amplitude of mechanical dimpling of the reflectors, which is caused by the hexagonal honeycomb structure of the carbon fibre reflectors. We find that the dimpling amplitude on the two reflectors is larger than expected from the ground, by 20% on the secondary and at least a factor of 2 on the primary. Second, we use the main beam shapes of 26 detectors to investigate the alignment of the various elements of the optical system, as well as the large-scale deformations of the reflectors. We develop a metric to guide an iterative fitting scheme, and are able to determine a new geometric model that fits the in-flight measurements better than the pre-flight prediction according to this metric. The new alignment model is within the mechanical tolerances expected from the ground, with some specific but minor exceptions. We find that the reflectors contain large-scale sinusoidal deformations most probably related to the mechanical supports. In spite of the better overall fit, the new model still does not fit the beam measurements at a level compatible with the needs of cosmological analysis. Nonetheless, future analysis of the Planck data would benefit from taking into account some of the features of the new model. The analysis described here exemplifies some of the limitations of in-flight retrieval of the geometry of an optical system similar to that of Planck, and provides useful information for similar efforts in future experiments.
  • Martinelli, M.; Martins, C. J. A. P.; Nesseris, S.; Sapone, D.; Tutusaus, I.; Avgoustidis, A.; Camera, S.; Carbone, C.; Casas, S.; Ilic, S.; Sakr, Z.; Yankelevich, V.; Auricchio, N.; Balestra, A.; Bodendorf, C.; Bonino, D.; Branchini, E.; Brescia, M.; Brinchmann, J.; Capobianco, V.; Carretero, J.; Castellano, M.; Cavuoti, S.; Cledassou, R.; Congedo, G.; Conversi, L.; Corcione, L.; Dubath, F.; Ealet, A.; Frailis, M.; Franceschi, E.; Fumana, M.; Garilli, B.; Gillis, B.; Giocoli, C.; Grupp, F.; Haugan, S. V. H.; Holmes, W.; Hormuth, F.; Jahnke, K.; Kermiche, S.; Kilbinger, M.; Kitching, T. D.; Kubik, B.; Kunz, M.; Kurki-Suonio, H.; Ligori, S.; Lilje, P. B.; Lloro, I.; Marggraf, O.; Markovic, K.; Massey, R.; Mei, S.; Meneghetti, M.; Meylan, G.; Moscardini, L.; Niemi, S.; Padilla, C.; Paltani, S.; Pasian, F.; Pettorino, V.; Pires, S.; Polenta, G.; Poncet, M.; Popa, L.; Pozzetti, L.; Raison, F.; Rhodes, J.; Roncarelli, M.; Saglia, R.; Schneider, P.; Secroun, A.; Serrano, S.; Sirignano, C.; Sirri, G.; Sureau, F.; Taylor, A. N.; Tereno, I.; Toledo-Moreo, R.; Valenziano, L.; Vassallo, T.; Wang, Y.; Welikala, N.; Weller, J.; Zacchei, A. (2020)
    Context. In metric theories of gravity with photon number conservation, the luminosity and angular diameter distances are related via the Etherington relation, also known as the distance duality relation (DDR). A violation of this relation would rule out the standard cosmological paradigm and point to the presence of new physics.Aims. We quantify the ability of Euclid, in combination with contemporary surveys, to improve the current constraints on deviations from the DDR in the redshift range 0<z<1.6.Methods. We start with an analysis of the latest available data, improving previously reported constraints by a factor of 2.5. We then present a detailed analysis of simulated Euclid and external data products, using both standard parametric methods (relying on phenomenological descriptions of possible DDR violations) and a machine learning reconstruction using genetic algorithms.Results. We find that for parametric methods Euclid can (in combination with external probes) improve current constraints by approximately a factor of six, while for non-parametric methods Euclid can improve current constraints by a factor of three.Conclusions. Our results highlight the importance of surveys like Euclid in accurately testing the pillars of the current cosmological paradigm and constraining physics beyond the standard cosmological model.
  • Pöntinen, M.; Granvik, M.; Nucita, A. A.; Conversi, L.; Altieri, B.; Auricchio, N.; Bodendorf, C.; Bonino, D.; Brescia, M.; Capobianco, V.; Carretero, J.; Carry, B.; Castellano, M.; Cledassou, R.; Congedo, G.; Corcione, L.; Cropper, M.; Dusini, S.; Frailis, M.; Franceschi, E.; Fumana, M.; Garilli, B.; Grupp, F.; Hormuth, F.; Israel, H.; Jahnke, K.; Kermiche, S.; Kitching, T.; Kohley, R.; Kubik, B.; Kunz, M.; Laureijs, R.; Lilje, P. B.; Lloro, I.; Maiorano, E.; Marggraf, O.; Massey, R.; Meneghetti, M.; Meylan, G.; Moscardini, L.; Padilla, C.; Paltani, S.; Pasian, F.; Pires, S.; Polenta, G.; Raison, F.; Roncarelli, M.; Rossetti, E.; Saglia, R.; Schneider, P.; Secroun, A.; Serrano, S.; Sirri, G.; Tereno, I.; Toledo-Moreo, R.; Valenziano, L.; Wetzstein, M.; Zoubian, J. (2020)
    Context. The ESA Euclid space telescope could observe up to 150 000 asteroids as a side product of its primary cosmological mission. Asteroids appear as trailed sources, that is streaks, in the images. Owing to the survey area of 15 000 square degrees and the number of sources, automated methods have to be used to find them. Euclid is equipped with a visible camera, VIS (VISual imager), and a near-infrared camera, NISP (Near-Infrared Spectrometer and Photometer), with three filters.Aims. We aim to develop a pipeline to detect fast-moving objects in Euclid images, with both high completeness and high purity.Methods. We tested the StreakDet software to find asteroids from simulated Euclid images. We optimized the parameters of StreakDet to maximize completeness, and developed a post-processing algorithm to improve the purity of the sample of detected sources by removing false-positive detections.Results.StreakDet finds 96.9% of the synthetic asteroid streaks with apparent magnitudes brighter than 23rd magnitude and streak lengths longer than 15 pixels (10 arcsec h(-1)), but this comes at the cost of finding a high number of false positives. The number of false positives can be radically reduced with multi-streak analysis, which utilizes all four dithers obtained by Euclid.Conclusions.StreakDet is a good tool for identifying asteroids in Euclid images, but there is still room for improvement, in particular, for finding short (less than 13 pixels, corresponding to 8 arcsec h(-1)) and/or faint streaks (fainter than the apparent magnitude of 23).
  • Price, Daniel; Pomoell, Jens; Kilpua, Emilia (2020)
    Aims. We present a detailed examination of the magnetic evolution of AR 12473 using time-dependent, data-driven magnetofrictional modelling.Methods. We used maps of the photospheric electric field inverted from vector magnetogram observations, obtained by the Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory (SDO), to drive our fully time-dependent, data-driven magnetofrictional model. Our modelled field was directly compared to extreme ultraviolet observations from the Atmospheric Imaging Assembly, also onboard SDO. Metrics were also computed to provide a quantitative analysis of the evolution of the magnetic field.Results. The flux rope associated with the eruption on 28 December 2015 from AR 12473 was reproduced by the simulation and found to have erupted due to a torus instability.
  • Gaia Collaboration; Spoto, F.; Muinonen, K.; Granvik, M.; Fedorets, G.; Siltala, L. (2018)
    Context. The Gaia spacecraft of the European Space Agency (ESA) has been securing observations of solar system objects (SSOs) since the beginning of its operations. Data Release 2 (DR2) contains the observations of a selected sample of 14,099 SSOs. These asteroids have been already identified and have been numbered by the Minor Planet Center repository. Positions are provided for each Gaia observation at CCD level. As additional information, complementary to astrometry, the apparent brightness of SSOs in the unfiltered G band is also provided for selected observations. Aims. We explain the processing of SSO data, and describe the criteria we used to select the sample published in Gaia DR2. We then explore the data set to assess its quality. Methods. To exploit the main data product for the solar system in Gaia DR2, which is the epoch astrometry of asteroids, it is necessary to take into account the unusual properties of the uncertainty, as the position information is nearly one-dimensional. When this aspect is handled appropriately, an orbit fit can be obtained with post-fit residuals that are overall consistent with the a-priori error model that was used to define individual values of the astrometric uncertainty. The role of both random and systematic errors is described. The distribution of residuals allowed us to identify possible contaminants in the data set (such as stars). Photometry in the G band was compared to computed values from reference asteroid shapes and to the flux registered at the corresponding epochs by the red and blue photometers (RP and BP). Results. The overall astrometric performance is close to the expectations, with an optimal range of brightness G similar to 12 - 17. In this range, the typical transit-level accuracy is well below 1 mas. For fainter asteroids, the growing photon noise deteriorates the performance. Asteroids brighter than G similar to 12 are affected by a lower performance of the processing of their signals. The dramatic improvement brought by Gaia DR2 astrometry of SSOs is demonstrated by comparisons to the archive data and by preliminary tests on the detection of subtle non-gravitational effects.
  • Gaia Collaboration; Eyer, L.; Muinonen, K.; Fedorets, G.; Granvik, M.; Siltala, L. (2019)
    Context. The ESA Gaia mission provides a unique time-domain survey for more than 1.6 billion sources with G less than or similar to 21 mag. Aims. We showcase stellar variability in the Galactic colour-absolute magnitude diagram (CaMD). We focus on pulsating, eruptive, and cataclysmic variables, as well as on stars that exhibit variability that is due to rotation and eclipses. Methods. We describe the locations of variable star classes, variable object fractions, and typical variability amplitudes throughout the CaMD and show how variability-related changes in colour and brightness induce "motions". To do this, we use 22 months of calibrated photometric, spectro-photometric, and astrometric Gaia data of stars with a significant parallax. To ensure that a large variety of variable star classes populate the CaMD, we crossmatched Gaia sources with known variable stars. We also used the statistics and variability detection modules of the Gaia variability pipeline. Corrections for interstellar extinction are not implemented in this article. Results. Gaia enables the first investigation of Galactic variable star populations in the CaMD on a similar, if not larger, scale as was previously done in the Magellanic Clouds. Although the observed colours are not corrected for reddening, distinct regions are visible in which variable stars occur. We determine variable star fractions to within the current detection thresholds of Gaia. Finally, we report the most complete description of variability-induced motion within the CaMD to date. Conclusions. Gaia enables novel insights into variability phenomena for an unprecedented number of stars, which will benefit the understanding of stellar astrophysics. The CaMD of Galactic variable stars provides crucial information on physical origins of variability in a way that has previously only been accessible for Galactic star clusters or external galaxies. Future Gaia data releases will enable significant improvements over this preview by providing longer time series, more accurate astrometry, and additional data types (time series BP and RP spectra, RVS spectra, and radial velocities), all for much larger samples of stars.
  • Patton, David R.; Wilson, Kieran D.; Metrow, Colin J.; Ellison, Sara L.; Torrey, Paul; Brown, Westley; Hani, Maan H.; McAlpine, Stuart; Moreno, Jorge; Woo, Joanna (2020)
    We use the IllustrisTNG cosmological hydrodynamical simulations to investigate how the specific star formation rates (sSFRs) of massive galaxies (M-* > 10(10) M-circle dot) depend on the distance to their closest companions. We estimate sSFR enhancements by comparing with control samples that are matched in redshift, stellar mass, local density, and isolation, and we restrict our analysis to pairs with stellar mass ratios of 0.1 to 10. At small separations (similar to 15 kpc), the mean sSFR is enhanced by a factor of 2.0 +/- 0.1 in the flagship (110.7Mpc)(3) simulation (TNG100-1). Statistically significant enhancements extend out to 3D separations of 280 kpc in the (302.6Mpc)(3) simulation (TNG300-1). We find similar trends in the EAGLE and Illustris simulations, although their sSFR enhancements are lower than those in TNG100-1 by about a factor of two. Enhancements in IllustrisTNG galaxies are seen throughout the redshift range explored (0
  • Cellino, A.; Hestroffer, D.; Lu, X-P; Muinonen, K.; Tanga, P. (2019)
    Context. Sparse photometric data can be used to determine the spin properties and infer information about the shapes of asteroids. The algorithm adopted for the inversion of Gaia photometric data assumes, for the sake of simplicity and to minimize CPU execution time, that the objects have triaxial ellipsoid shapes. In the past, this algorithm was tested against large sets of simulated data and small numbers of sparse photometric measurements obtained by HIPPARCOS. Aims. After the second Gaia data release, it is now possible to test the inversion algorithm against small samples of actual Gaia data for the first time. At the same time, we can attempt a new inversion of older HIPPARCOS measurements, using an updated version of the photometric inversion algorithm. Methods. The new version of our inversion algorithm includes the treatment of a Lommel-Seeliger scattering relation especially developed for the case of triaxial ellipsoid shapes. In addition, we also performed inversion attempts using a more refined shape model, based on the so-called cellinoid shapes. Results. With respect to the old inversion of HIPPARCOS data carried out in the past, we obtain only marginal improvements. In the case of Gaia data, however, we obtain very encouraging results. A successful determination of the rotation period is possible in most cases, in spite of the limited time span covered by data published in the second Gaia data release (GDR2), which makes the determination of the spin axis direction still uncertain. Even a small number of measurements, less than 30 in many cases, are sufficient to obtain a satisfactory inversion solution. Using the more realistic cellinoid shape model, we find further improvement in the determination of the spin period. Conclusions. This is a relevant validation of GDR2 photometry of asteroids, and proof of the satisfactory performances of the adopted inversion algorithm.
  • Keihänen, Elina; Keskitalo, Reijo; Kurki-Suonio, Hannu; Poutanen, Torsti; Sirviö, Anna-Stiina (2010)
  • Simola, U.; Dumusque, X.; Cisewski-Kehe, J. (2019)
    Context. Stellar activity is one of the primary limitations to the detection of low-mass exoplanets using the radial-velocity (RV) technique. Stellar activity can be probed by measuring time-dependent variations in the shape of the cross-correlation function (CCF). It is therefore critical to measure with high-precision these shape variations to decorrelate the signal of an exoplanet from spurious RV signals caused by stellar activity. Aims. We propose to estimate the variations in shape of the CCF by fitting a Skew Normal (SN) density which, unlike the commonly employed Normal density, includes a Skewness parameter to capture the asymmetry of the CCF induced by stellar activity and the convective blueshift. Methods. We compared the performances of the proposed method to the commonly employed Normal density using both simulations and real observations with different levels of activity and signal-to-noise ratios. Results. When considering real observations, the correlation between the RV and the asymmetry of the CCF and between the RV and the width of the CCF are stronger when using the parameters estimated with the SN density rather than those obtained with the commonly employed Normal density. In particular, the strongest correlations have been obtained when using the mean of the SN as an estimate for the RV. This suggests that the CCF parameters estimated using a SN density are more sensitive to stellar activity, which can be helpful when estimating stellar rotational periods and when characterizing stellar activity signals. Using the proposed SN approach, the uncertainties estimated on the RV defined as the median of the SN are on average 10% smaller than the uncertainties calculated on the mean of the Normal. The uncertainties estimated on the asymmetry parameter of the SN are on average 15% smaller than the uncertainties measured on the Bisector Inverse Slope Span (BIS SPAN), which is the commonly used parameter to evaluate the asymmetry of the CCF. We also propose a new model to account for stellar activity when fitting a planetary signal to RV data. Based on simple simulations, we were able to demonstrate that this new model improves the planetary detection limits by 12% compared to the model commonly used to account for stellar activity. Conclusions. The SN density is a better model than the Normal density for characterizing the CCF since the correlations used to probe stellar activity are stronger and the uncertainties of the RV estimate and the asymmetry of the CCF are both smaller.
  • Moreno-Ibanez, Manuel; Gritsevich, Maria; Trigo-Rodriguez, Josep M.; Silber, Elizabeth A. (2020)
    Meteoroids impacting the Earth atmosphere are commonly classified using the PE criterion. This criterion was introduced to support the identification of the fireball type by empirically linking its orbital origin and composition characteristics. Additionally, it is used as an indicator of the meteoroid tensile strength and its ability to penetrate the atmosphere. However, the level of classification accuracy of the PE criterion depends on the ability to constrain the value of the input data, retrieved from the fireball observation, required to derive the PE value. To overcome these uncertainties and achieve a greater classification detail, we propose a new formulation using scaling laws and dimensionless variables that groups all the input variables into two parameters that are directly obtained from the fireball observations. These two parameters, alpha and beta, represent the drag and the mass-loss rates along the luminous part of the trajectory, respectively, and are linked to the shape, strength, ablation efficiency, mineralogical nature of the projectile, and duration of the fireball. Thus, the new formulation relies on a physical basis. This work shows the mathematical equivalence between the PE criterion and the logarithm of 2 alpha beta under the same PE criterion assumptions. We demonstrate that log(2 alpha beta) offers a more general formulation that does not require any preliminary constraint on the meteor flight scenario and discuss the suitability of the new formulation for expanding the classification beyond fully disintegrating fireballs to larger impactors including meteorite-dropping fireballs. The reliability of the new formulation is validated using the Prairie Network meteor observations.
  • Aghanim, N.; Chen, X.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kiiveri, K.; Kurki-Suonio, H.; Lähteenmäki, Anne; Lindholm, Valtteri; Poutanen, T.; Suur-Uski, A. -S.; Tuovinen, Jari; Väliviita, Jussi; Planck Collaboration (2014)
  • Aghanim, N.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kiiveri, Kimmo; Kurki-Suonio, H.; Lähteenmäki, Anne; Lindholm, V.; Poutanen, T.; Suur-Uski, Anna-Stiina; Tuovinen, J.; Väliviita, Jussi; Planck Collaboration (2014)
  • Aghanim, N.; Juvela, M.; Kangaslahti, P.; Keihanen, E.; Keskitalo, R.; Kiiveri, K.; Kurki-Suonio, H.; Lähteenmäki, Anne; Lindholm, V.; Poutanen, T.; Suur-Uski, A. -S.; Tuovinen, J.; Väliviita, Jussi; Varis, J.; Planck Collaboration (2014)
  • Aghanim, N.; Juvela, M.; Keihanen, E.; Keskitalo, R.; Kurki-Suonio, H.; Lähteenmäki, Anne; Suur-Uski, A. -S.; Väliviita, Jussi; Planck Collaboration (2014)
  • Ade, P. A. R.; Juvela, M.; Keihanen, E.; Keskitalo, R.; Kurki-Suonio, H.; Poutanen, T.; Suur-Uski, A. -S.; Valiviita, J.; Planck Collaboration (2014)
  • Ade, P. A. R.; Aghanim, N.; Armitage-Caplan, C.; Arnaud, M.; Ashdown, M.; Atrio-Barandela, F.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Battaner, E.; Benabed, K.; Benoit, A.; Benoit-Levy, A.; Bernard, J. -P.; Bersanelli, M.; Bertincourt, B.; Bielewicz, P.; Bobin, J.; Bock, J. J.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bridges, M.; Bucher, M.; Burigana, C.; Cardoso, J. -F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R. -R.; Chen, X.; Chiang, H. C.; Chiang, L. -Y; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Delouis, J. -M.; Desert, F. -X.; Dickinson, C.; Diego, J. M.; Dole, H.; Donzelli, S.; Dore, O.; Douspis, M.; Dupac, X.; Efstathiou, G.; Ensslin, T. A.; Eriksen, H. K.; Filliard, C.; Finelli, F.; Forni, O.; Frailis, M.; Franceschi, E.; Galeotta, S.; Ganga, K.; Giard, M.; Giardino, G.; Giraud-Heraud, Y.; Gonzalez-Nuevo, J.; Gorski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Hansen, F. K.; Hanson, D.; Harrison, D.; Helou, G.; Henrot-Versille, S.; Hernandez-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihanen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J. -M.; Lasenby, A.; Laureijs, R. J.; Lawrence, C. R.; Le Jeune, M.; Lellouch, E.; Leonardi, R.; Leroy, C.; Lesgourgues, J.; Liguori, M.; Lilje, P. B.; Linden-Vornle, M.; Lopez-Caniego, M.; Lubin, P. M.; Macias-Perez, J. F.; Maffei, B.; Mandolesi, N.; Maris, M.; Marshall, D. J.; Martin, P. G.; Martinez-Gonzalez, E.; Masi, S.; Massardi, M.; Matarrese, S.; Matthai, F.; Maurin, L.; Mazzotta, P.; McGehee, P.; Meinhold, P. R.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschenes, M. -A.; Moneti, A.; Montier, L.; Moreno, R.; Morgante, G.; Mortlock, D.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Norgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Osborne, S.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paladini, R.; Paoletti, D.; Partridge, B.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Perrotta, F.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Popa, L.; Poutanen, T.; Pratt, G. W.; Prezeau, G.; Prunet, S.; Puget, J. -L.; Rachen, J. P.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Roudier, G.; Rusholme, B.; Santos, D.; Savini, G.; Scott, D.; Shellard, E. P. S.; Spencer, L. D.; Starck, J. -L.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sunyaev, R.; Sureau, F.; Sutton, D.; Suur-Uski, A. -S.; Sygnet, J. -F.; Tauber, J. A.; Tavagnacco, D.; Techene, S.; Terenzi, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Vittorio, N.; Wade, L. A.; Wandelt, B. D.; Yvon, D.; Zacchei, A.; Zonca, A. (2014)