Browsing by Subject "cosmology: observations"

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  • Comparat, J.; Merloni, A.; Salvato, M.; Nandra, K.; Boller, T.; Georgakakis, A.; Finoguenov, A.; Dwelly, T.; Buchner, J.; Del Moro, A.; Clerc, N.; Wang, Y.; Zhao, G.; Prada, F.; Yepes, G.; Brusa, M.; Krumpe, M.; Liu, T. (2019)
    In the context of the upcoming SRG/eROSITA survey, we present an N-body simulation-based mock catalogue for X-ray-selected active galactic nucleus (AGN) samples. The model reproduces the observed hard X-ray AGN luminosity function (XLF) and the soft X-ray logN-logS from redshift 0 to 6. The XLF is reproduced to within +/- 5 per cent and the logN-logS to within +/- 20 per cent. We develop a joint X-ray - optical extinction and classification model. We adopt a set of empirical spectral energy distributions to predict observed magnitudes in the UV, optical, and NIR. With the latest eROSITA all sky survey sensitivity model, we create a high-fidelity full-sky mock catalogue of X-ray AGN. It predicts their distributions in right ascension, declination, redshift, and fluxes. Using empirical medium resolution optical spectral templates and an exposure time calculator, we find that 1.1 x 10(6) (4 x 10(5)) fibre-hours are needed to follow-up spectroscopically from the ground the detected X-ray AGN with an optical magnitude 21 <r <22.8 (22.8 <r <25) with a 4-m (8-m) class multiobject spectroscopic facility. We find that future clustering studies will measure the AGN bias to the per cent level at redshift z <1.2 and should discriminate possible scenarios of galaxy-AGN co-evolution. We predict the accuracy to which the baryon acoustic oscillation standard ruler will be measured using X-ray AGN: better than 3 per cent for AGN between redshift 0.5 to 3 and better than 1 per cent using the Ly alpha forest of X-ray QSOs discovered between redshift 2 and 3. eROSITA will provide an outstanding set of targets for future galaxy evolution and cosmological studies.
  • Mirkazemi, M.; Finoguenov, A.; Pereira, M. J.; Tanaka, M.; Lerchster, M.; Brimioulle, F.; Egami, E.; Kettula, K.; Erfanianfar, G.; McCracken, H. J.; Mellier, Y.; Kneib, J. P.; Rykoff, E.; Seitz, S.; Erben, T.; Taylor, J. E. (2015)
  • Lindholm, V.; Finoguenov, A.; Comparat, J.; Kirkpatrick, C. C.; Rykoff, E.; Clerc, N.; Collins, C.; Damsted, S.; Chitham, J. Ider; Padilla, N. (2021)
    Context. The clustering of galaxy clusters links the spatial nonuniformity of dark matter halos to the growth of the primordial spectrum of perturbations. The amplitude of the clustering signal is widely used to estimate the halo mass of astrophysical objects. The advent of cluster mass calibrations enables using clustering in cosmological studies.Aims. We analyze the autocorrelation function of a large contiguous sample of galaxy clusters, the Constrain Dark Energy with X-ray (CODEX) sample, in which we take particular care of cluster definition. These clusters were X-ray selected using the ROentgen SATellite All-Sky Survey and then identified as galaxy clusters using the code redMaPPer run on the photometry of the Sloan Digital Sky Survey. We develop methods for precisely accounting for the sample selection effects on the clustering and demonstrate their robustness using numerical simulations.Methods. Using the clean CODEX sample, which was obtained by applying a redshift-dependent richness selection, we computed the two-point autocorrelation function of galaxy clusters in the 0.1 Omega m0 = 0.22-0.03+0.04 Omega m 0 = 0 . 22 - 0.03 + 0.04 and S8 = sigma 8(Omega m0/0.3)0.5 = 0.85-0.08+0.10 S 8 = sigma 8 ( Omega m 0 / 0.3 ) 0.5 = 0 . 85 - 0.08 + 0.10 with estimated additional systematic errors of sigma Omega m0=0.02 and sigma S8=0.20. We illustrate the complementarity of clustering constraints by combining them with CODEX cosmological constraints based on the X-ray luminosity function, deriving Omega m0=0.25 +/- 0.01 and sigma (8) = 0.81(-0.02)(+0.01) sigma 8 = 0 . 81 - 0.02 + 0.01 with an estimated additional systematic error of sigma Omega m0=0.07 and sigma sigma 8=0.04. The mass calibration and statistical quality of the mass tracers are the dominant source of uncertainty.
  • 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.
  • Inserra, C.; Nichol, R. C.; Scovacricchi, D.; Amiaux, J.; Brescia, M.; Burigana, C.; Cappellaro, E.; Carvalho, C. S.; Cavuoti, S.; Conforti, V.; Cuillandre, J. -C.; da Silva, A.; De Rosa, A.; Della Valle, M.; Dinis, J.; Franceschi, E.; Hook, I.; Hudelot, P.; Jahnke, K.; Kitching, T.; Kurki-Suonio, H.; Lloro, I.; Longo, G.; Maiorano, E.; Maris, M.; Rhodes, J. D.; Scaramella, R.; Smartt, S. J.; Sullivan, M.; Tao, C.; Toledo-Moreo, R.; Tereno, I.; Trifoglio, M.; Valenziano, L. (2018)
    Context. In the last decade, astronomers have found a new type of supernova called superluminous supernovae (SLSNe) due to their high peak luminosity and long light-curves. These hydrogen-free explosions (SLSNe-I) can be seen to z similar to 4 and therefore, offer the possibility of probing the distant Universe. Aims. We aim to investigate the possibility of detecting SLSNe-I using ESA's Euclid satellite, scheduled for launch in 2020. In particular, we study the Euclid Deep Survey (EDS) which will provide a unique combination of area, depth and cadence over the mission. Methods. We estimated the redshift distribution of Euclid SLSNe-I using the latest information on their rates and spectral energy distribution, as well as known Euclid instrument and survey parameters, including the cadence and depth of the EDS. To estimate the uncertainties, we calculated their distribution with two different set-ups, namely optimistic and pessimistic, adopting different star formation densities and rates. We also applied a standardization method to the peak magnitudes to create a simulated Hubble diagram to explore possible cosmological constraints. Results. We show that Euclid should detect approximately 140 high-quality SLSNe-I to z similar to 3.5 over the first five years of the mission (with an additional 70 if we lower our photometric classification criteria). This sample could revolutionize the study of SLSNe-I at z > 1 and open up their use as probes of star-formation rates, galaxy populations, the interstellar and intergalactic medium. In addition, a sample of such SLSNe-I could improve constraints on a time-dependent dark energy equation-of-state, namely w (a), when combined with local SLSNe-I and the expected SN Ia sample from the Dark Energy Survey. Conclusions. We show that Euclid will observe hundreds of SLSNe-I for free. These luminous transients will be in the Euclid data-stream and we should prepare now to identify them as they offer a new probe of the high-redshift Universe for both astrophysics and cosmology.
  • Euclid Collaboration; Blanchard, A.; Keihanen, E.; Kurki-Suonio, H.; Kirkpatrick IV, C.C. (2020)
    Aims. The Euclid space telescope will measure the shapes and redshifts of galaxies to reconstruct the expansion history of the Universe and the growth of cosmic structures. The estimation of the expected performance of the experiment, in terms of predicted constraints on cosmological parameters, has so far relied on various individual methodologies and numerical implementations, which were developed for different observational probes and for the combination thereof. In this paper we present validated forecasts, which combine both theoretical and observational ingredients for different cosmological probes. This work is presented to provide the community with reliable numerical codes and methods for Euclid cosmological forecasts.Methods. We describe in detail the methods adopted for Fisher matrix forecasts, which were applied to galaxy clustering, weak lensing, and the combination thereof. We estimated the required accuracy for Euclid forecasts and outline a methodology for their development. We then compare and improve different numerical implementations, reaching uncertainties on the errors of cosmological parameters that are less than the required precision in all cases. Furthermore, we provide details on the validated implementations, some of which are made publicly available, in different programming languages, together with a reference training-set of input and output matrices for a set of specific models. These can be used by the reader to validate their own implementations if required.Results. We present new cosmological forecasts for Euclid. We find that results depend on the specific cosmological model and remaining freedom in each setting, for example flat or non-flat spatial cosmologies, or different cuts at non-linear scales. The numerical implementations are now reliable for these settings. We present the results for an optimistic and a pessimistic choice for these types of settings. We demonstrate that the impact of cross-correlations is particularly relevant for models beyond a cosmological constant and may allow us to increase the dark energy figure of merit by at least a factor of three.
  • Euclid Collaboration; Adam, R.; Kurki-Suonio, H. (2019)
    Galaxy cluster counts in bins of mass and redshift have been shown to be a competitive probe to test cosmological models. This method requires an efficient blind detection of clusters from surveys with a well-known selection function and robust mass estimates, which is particularly challenging at high redshift. The Euclid wide survey will cover 15 000 deg(2) of the sky, avoiding contamination by light from our Galaxy and our solar system in the optical and near-infrared bands, down to magnitude 24 in the H-band. The resulting data will make it possible to detect a large number of galaxy clusters spanning a wide-range of masses up to redshift similar to 2 and possibly higher. This paper presents the final results of the Euclid Cluster Finder Challenge (CFC), fourth in a series of similar challenges. The objective of these challenges was to select the cluster detection algorithms that best meet the requirements of the Euclid mission. The final CFC included six independent detection algorithms, based on different techniques, such as photometric redshift tomography, optimal filtering, hierarchical approach, wavelet and friend-of-friends algorithms. These algorithms were blindly applied to a mock galaxy catalog with representative Euclid-like properties. The relative performance of the algorithms was assessed by matching the resulting detections to known clusters in the simulations down to masses of M-200 similar to 10(13.25) M-circle dot. Several matching procedures were tested, thus making it possible to estimate the associated systematic effects on completeness to 80% completeness for a mean purity of 80% down to masses of 10(14) M-circle dot and up to redshift z = 2. Based on these results, two algorithms were selected to be implemented in the Euclid pipeline, the Adaptive Matched Identifier of Clustered Objects (AMICO) code, based on matched filtering, and the PZWav code, based on an adaptive wavelet approach.
  • Euclid Collaboration; Guglielmo, Christopher G.; Gozaliasl, G.; Keihanen, E.; Kurki-Suonio, H.; Kirkpatrick IV, C.C. (2020)
    The Complete Calibration of the Colour-Redshift Relation survey (C3R2) is a spectroscopic e ffort involving ESO and Keck facilities designed specifically to empirically calibrate the galaxy colour-redshift relation - P(z jC) to the Euclid depth (iAB = 24 :5) and is intimately linked to the success of upcoming Stage IV dark energy missions based on weak lensing cosmology. The aim is to build a spectroscopic calibration sample that is as representative as possible of the galaxies of the Euclid weak lensing sample. In order to minimise the number of spectroscopic observations necessary to fill the gaps in current knowledge of the P(z jC), self-organising map (SOM) representations of the galaxy colour space have been constructed. Here we present the first results of an ESO@VLT Large Programme approved in the context of C3R2, which makes use of the two VLT optical and near-infrared multi-object spectrographs, FORS2 and KMOS. This data release paper focuses on high-quality spectroscopic redshifts of high-redshift galaxies observed with the KMOS spectrograph in the near-infrared H- and K-bands. A total of 424 highly-reliable redshifts are measured in the 1:3 2 galaxies.
  • Mattila, K.; Väisänen, P.; Lehtinen, K.; von Appen-Schnur, G.; Leinert, Ch. (2017)
    In a project aimed at measuring the optical extragalactic background light (EBL), we are using the shadow of a dark cloud. We have performed, with the ESO VLT/FORS, spectrophotometry of the surface brightness towards the high-galactic-latitude dark cloud Lynds 1642. A spectrum representing the difference between the opaque core of the cloud and several unobscured positions around the cloud was presented in Paper I. The topic of this paper is the separation of the scattered starlight from the dark cloud itself which is the only remaining foreground component in this difference. While the scattered starlight spectrum has the characteristic Fraunhofer lines and the discontinuity at 400 nm, typical of integrated light of galaxies, the EBL spectrum is a smooth one without these features. As template for the scattered starlight, we make use of the spectra at two semitransparent positions. The resulting EBL intensity at 400 nm is I-EBL = 2.9 +/- 1.1 10(-9) erg cm(-2) s(-1) sr(-1) angstrom(-1) or 11.6 +/- 4.4 nW m(-2) sr(-1), which represents a 2.6 sigma detection; the scaling uncertainty is +20 per cent/-16 per cent. At 520 nm, we have set a 2 sigma upper limit of I-EBL
  • Mattila, K.; Lehtinen, K.; Väisänen, P.; von Appen-Schnur, G.; Leinert, Ch. (2017)
    We present the method and observations for the measurement of the Extragalactic Background Light (EBL) utilizing the shadowing effect of a dark cloud. We measure the surface brightness difference between the opaque cloud core and its unobscured surroundings. In the difference the large atmospheric and Zodiacal light components are eliminated and the only remaining foreground component is the scattered starlight from the cloud itself. Although much smaller, its separation is the key problem in the method. For its separation we use spectroscopy. While the scattered starlight has the characteristic Fraunhofer lines and 400 nm discontinuity, the EBL spectrum is smooth and without these features. Medium resolution spectrophotometry at lambda = 380-580 nm was performed with VLT/FORS at ESO of the surface brightness in and around the high-galactic-latitude dark cloud Lynds 1642. Besides the spectrum for the core with AV greater than or similar to 15 mag, further spectra were obtained for intermediate-opacity cloud positions. They are used as proxy for the spectrum of the impinging starlight spectrum and to facilitate the separation of the scattered starlight (cf. Paper II; Mattila et al.). Our spectra reach a precision of less than or similar to 0.5 x 10(-9) erg cm(-2) s(-1) sr(-1) angstrom(-1) as required to measure an EBL intensity in range of similar to 1 to a few times 10(-9) erg cm(-2) s(-1) sr(-1) angstrom(-1). Because all surface brightness components are measured using the same equipment, the method does not require unusually high absolute calibration accuracy, a condition that has been a problem for some previous EBL projects.
  • Mulroy, Sarah L.; Farahi, Arya; Evrard, August E.; Smith, Graham P.; Finoguenov, Alexis; O'Donnell, Christine; Marrone, Daniel P.; Abdulla, Zubair; Bourdin, Herve; Carlstrom, John E.; Democles, Jessica; Haines, Chris P.; Martino, Rossella; Mazzotta, Pasquale; McGee, Sean L.; Okabe, Nobuhiro (2019)
    We present a simultaneous analysis of galaxy cluster scaling relations between weak-lensing mass and multiple cluster observables, across a wide range of wavelengths, that probe both gas and stellar content. Our new hierarchical Bayesian model simultaneously considers the selection variable alongside all other observables in order to explicitly model intrinsic property covariance and account for selection effects. We apply this method to a sample of 41 clusters at 0.15 <z <0.30, with a well-defined selection criteria based on RASS X-ray luminosity, and observations from Chandra/XMM, SZA, Planck, UKIRT, SUSS, and Subaru. These clusters have well-constrained weak-lensing mass measurements based on Subaru/SuprimeCam observations, which serve as the reference masses in our model. We present 30 scaling relation parameters for 10 properties. All relations probing the intracluster gas are slightly shallower than self-similar predictions, in moderate tension with prior measurements, and the stellar fraction decreases with mass. K-band luminosity has the lowest intrinsic scatter with a 95th percentile of 0.16, while the lowest scatter gas probe is gas mass with a fractional intrinsic scatter of 0.16 +/- 0.03. We find no distinction between the core-excised X-ray or high-resolution Sunyaev-Zel'dovich relations of clusters of different central entropy, but find with modest significance that higher entropy clusters have higher stellar fractions than their lower entropy counterparts. We also report posterior mass estimates from our likelihood model.
  • Vacca, V.; Murgia, M.; Govoni, F.; Loi, F.; Vazza, F.; Finoguenov, A.; Carretti, E.; Feretti, L.; Giovannini, G.; Concu, R.; Melis, A.; Gheller, C.; Paladino, R.; Poppi, S.; Valente, G.; Bernardi, G.; Boschin, W.; Brienza, M.; Clarke, T. E.; Colafrancesco, S.; Ensslin, T. A.; Ferrari, C.; de Gasperin, F.; Gastaldello, F.; Girardi, M.; Gregorini, L.; Johnston-Hollitt, M.; Junklewitz, H.; Orru, E.; Parma, P.; Perley, R.; Taylor, G. B. (2018)
    We report the detection of diffuse radio emission which might be connected to a large-scale filament of the cosmic web covering a 8 degrees x 8 degrees area in the sky, likely associated with a z approximate to 0.1 overdensity traced by nine massive galaxy clusters. In this work, we present radio observations of this region taken with the Sardinia Radio Telescope. Two of the clusters in the field host a powerful radio halo sustained by violent ongoing mergers and provide direct proof of intracluster magnetic fields. In order to investigate the presence of large-scale diffuse radio synchrotron emission in and beyond the galaxy clusters in this complex system, we combined the data taken at 1.4 GHz with the Sardinia. Radio Telescope with higher resolution data taken with the NRAO VIA Sky Survey. We found 28 candidate new sources with a size larger and X-ray emission fainter than known diffuse large-scale synchrotron cluster sources for a given radio power. This new population is potentially the tip of the iceberg of a class of diffuse large-scale synchrotron sources associated with the filaments of the cosmic web. In addition, we found in the field a candidate new giant radio galaxy.
  • Ade, P. A. R.; Juvela, M.; Keihanen, E.; Keskitalo, R.; Kiiveri, K.; Kurki-Suonio, H.; Lähteenmäki, Anne; Lindholm, Valtteri; Poutanen, T.; Savelainen, M.; Suur-Uski, A-S.; Tuovinen, J.; Valiviita, J.; Planck Collaboration (2014)
  • 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)
  • 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.; 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.; Comis, B.; 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.; Falgarone, E.; Finelli, F.; Forni, O.; Frailis, M.; Franceschi, E.; Galeotta, S.; Ganga, K.; Ciard, M.; Giraud-Heraud, Y.; Gonzadlez-Nuevo, J.; Gorski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Hansen, F. K.; Hanson, D.; Harrison, D.; 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.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihanen, E.; Keskitalo, R.; Kisner, T. S.; Kneiss, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J. -M.; Lasenby, A.; Laureijs, R. J.; Lawrence, C. R.; Leahy, J. P.; 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.; Mazzotta, P.; McGehee, P.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschenes, M. -A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Norgaard-Nielsen, H. U.; North, C.; Noviello, F.; Novikov, D.; Novikov, I.; Osborne, S.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Pasian, F.; Patanchon, G.; 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.; Sureau, F.; Sutton, D.; Suur-Uski, A. -S.; Sygnet, J. -F.; Tauber, J. A.; Tavagnacco, D.; 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)
  • 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, E.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Battaner, E.; Benabed, K.; Benoit, A.; Benoit-Levy, A.; Bernard, J. -P.; Bersanelli, M.; Bielewicz, P.; Bobin, J.; Bock, J. J.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Bowyer, J. W.; Bridges, M.; Bucher, M.; Burigana, C.; Cardoso, J. -E; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R. -R.; Chiang, H. C.; Chiang, L. -Y; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, E.; Danese, L.; Davies, R. D.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Delouis, J. -M.; Desert, F. -X.; Diego, J. M.; Dole, H.; Donzelli, S.; Dore, O.; Douspis, M.; Dunkley, J.; Dupac, X.; Efstathiou, G.; Ensslin, T. A.; Eriksen, H. K.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Galeotta, S.; Ganga, K.; Giard, M.; Giraud-Heraud, Y.; Gonzalez-Nuevo, J.; Gorski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Haissinski, J.; Hansen, F. K.; Hanson, D.; Harrison, D.; Henrot-Versille, S.; Hernandez-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hou, Z.; Hovest, W.; Huffenberger, K. M.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihanen, E.; Keskitalo, R.; Kisner, T. S.; Kneiss, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J. -M.; Lasenby, A.; Laureijs, R. J.; Lawrence, C. R.; Leonardi, R.; Leroy, C.; Lesgourgues, J.; Liguori, M.; Lilje, P. B.; Linden-Vornle, M.; Lopez-Caniego, M.; Lubin, P. M.; Macias-Perez, J. F.; MacTavish, C. J.; Maffei, B.; Mandolesi, N.; Maris, M.; Marshall, D. J.; Martin, P. G.; Martinez-Gonzalez, E.; Masi, S.; Massardi, M.; Matarrese, S.; Matsumura, T.; Matthai, E.; Mazzotta, P.; McGehee, P.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschenes, M. -A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, E.; 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.; Paoletti, D.; Pasian, F.; Patanchon, G.; Perdereau, O.; Perotto, L.; Perrotta, F.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polegre, A. M.; 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.; Rowan-Robinson, M.; Rusholme, B.; Sandri, M.; Santos, D.; Sauve, A.; Savini, G.; Scott, D.; Shellard, E. P. S.; Spencer, L. D.; Starck, J. -L.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sureau, E.; Sutton, D.; Suur-Uski, A-S.; Sygnet, J. -F.; Tauber, J. A.; Tavagnacco, D.; 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)
  • 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)
  • 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.; Bielewicz, P.; Bobin, J.; Bock, J. J.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Bridges, M.; Bucher, M.; Burigana, C.; Cardoso, J. -F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chiang, H. C.; Chiang, L. -Y.; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Couchot, F.; Coulais, A.; Crill, P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Juvela, M.; Keihanen, E.; Keskitalo, R.; Kurki-Suonio, H.; Poutanen, T.; Suur-Uski, A. -S.; Valiviita, J. (2014)