Planck 2015 results. I. Overview of products and scientific results

Adam, R.; Ade, P.A.R.; Aghanim, N.; Akrami, Y.; Alves, M.I.R.; Arg�eso, F.; Arnaud, M.; Arroja, F.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Ballardini, M.; Banday, A.J.; Barreiro, R.B.; Bartlett, J.G.; Bartolo, N.; Basak, S.; Battaglia, P.; Battaner, E.; Battye, R.; Benabed, K.; Beno�t, A.; Benoit-L�vy, A.; Bernard, J.-P.; Bersanelli, M.; Bertincourt, B.; Bielewicz, P.; Bikmaev, I.; Bock, J.J.; B�hringer, H.; Bonaldi, A.; Bonavera, L.; Bond, J.R.; Borrill, J.; Bouchet, F.R.; Boulanger, F.; Bucher, M.; Burenin, R.; Burigana, C.; Butler, R.C.; Calabrese, E.; Cardoso, J.-F.; Carvalho, P.; Casaponsa, B.; Castex, G.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.-R.; Chiang, H.C.; Chluba, J.; Chon, G.; Christensen, P.R.; Church, S.; Clemens, M.; Clements, D.L.; Colombi, S.; Colombo, L.P.L.; Combet, C.; Comis, B.; Contreras, D.; Couchot, F.; Coulais, A.; Crill, B.P.; Cruz, M.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R.D.; Davis, R.J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Delouis, J.-M.; D�sert, F.-X.; Di Valentino, E.; Dickinson, C.; Diego, J.M.; Dolag, K.; Dole, H.; Donzelli, S.; Dor�, O.; Douspis, M.; Ducout, A.; Dunkley, J.; Dupac, X.; Efstathiou, G.; Eisenhardt, P.R.M.; Elsner, F.; En�lin, T.A.; Eriksen, H.K.; Falgarone, E.; Fantaye, Y.; Farhang, M.; Feeney, S.; Fergusson, J.; Fernandez-Cobos, R.; Feroz, F.; Finelli, F.; Florido, E.; Forni, O.; Frailis, M.; Fraisse, A.A.; Franceschet, C.; Franceschi, E.; Frejsel, A.; Frolov, A.; Galeotta, S.; Galli, S.; Ganga, K.; Gauthier, C.; G�nova-Santos, R.T.; Gerbino, M.; Ghosh, T.; Giard, M.; Giraud-H�raud, Y.; Giusarma, E.; Gjerl�w, E.; Gonz�lez-Nuevo, J.; G�rski, K.M.; Grainge, K.J.B.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J.E.; Hamann, J.; Handley, W.; Hansen, F.K.; Hanson, D.; Harrison, D.L.; Heavens, A.; Helou, G.; Henrot-Versill�, S.; Hern�ndez-Monteagudo, C.; Herranz, D.; Hildebrandt, S.R.; Hivon, E.; Hobson, M.; Holmes, W.A.; Hornstrup, A.; Hovest, W.; Huang, Z.; Huffenberger, K.M.; Hurier, G.; Ili?, S.; Jaffe, A.H.; Jaffe, T.R.; Jin, T.; Jones, W.C.; Juvela, M.; Karakci, A.; Keih�nen, E.; Keskitalo, R.; Khamitov, I.; Kiiveri, K.; Kim, J.; Kisner, T.S.; Kneissl, R.; Knoche, J.; Knox, L.; Krachmalnicoff, N.; Kunz, M.; Kurki-Suonio, H.; Lacasa, F.; Lagache, G.; L�hteenm�ki, A.; Lamarre, J.-M.; Langer, M.; Lasenby, A.; Lattanzi, M.; Lawrence, C.R.; Le Jeune, M.; Leahy, J.P.; Lellouch, E.; Leonardi, R.; Le�n-Tavares, J.; Lesgourgues, J.; Levrier, F.; Lewis, A.; Liguori, M.; Lilje, P.B.; Lilley, M.; Linden-V�rnle, M.; Lindholm, V.; Liu, H.; L�pez-Caniego, M.; Lubin, P.M.; Ma, Y.-Z.; Mac�as-P�rez, J.F.; Maggio, G.; Maino, D.; Mak, D.S.Y.; Mandolesi, N.; Mangilli, A.; Marchini, A.; Marcos-Caballero, A.; Marinucci, D.; Maris, M.; Marshall, D.J.; Martin, P.G.; Martinelli, M.; Mart�nez-Gonz�lez, E.; Masi, S.; Matarrese, S.; Mazzotta, P.; McEwen, J.D.; McGehee, P.; Mei, S.; Meinhold, P.R.; Melchiorri, A.; Melin, J.-B.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mikkelsen, K.; Millea, M.; Mitra, S.; Miville-Desch�nes, M.-A.; Molinari, D.; Moneti, A.; Montier, L.; Moreno, R.; Morgante, G.; Mortlock, D.; Moss, Adam; Mottet, S.; M�nchmeyer, M.; Munshi, D.; Murphy, J.A.; Narimani, A.; Naselsky, P.; Nastasi, A.; Nati, F.; Natoli, P.; Negrello, M.; Netterfield, C.B.; N�rgaard-Nielsen, H.U.; Noviello, F.; Novikov, D.; Novikov, I.; Olamaie, M.; Oppermann, N.; Orlando, E.; Oxborrow, C.A.; Paci, F.; Pagano, L.; Pajot, F.; Paladini, R.; Pandolfi, S.; Paoletti, D.; Partridge, B.; Pasian, F.; Patanchon, G.; Pearson, T.J.; Peel, M.; Peiris, H.V.; Pelkonen, V.-M.; Perdereau, O.; Perotto, L.; Perrott, Y.C.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pogosyan, D.; Pointecouteau, E.; Polenta, G.; Popa, L.; Pratt, G.W.; Pr�zeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J.P.; Racine, B.; Reach, W.T.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Roman, M.; Romelli, E.; Rosset, C.; Rossetti, M.; Rotti, A.; Roudier, G.; Rouill� d�Orfeuil, B.; Rowan-Robinson, M.; Rubi�o-Mart�n, J.A.; Ruiz-Granados, B.; Rumsey, C.; Rusholme, B.; Said, N.; Salvatelli, V.; Salvati, L.; Sandri, M.; Sanghera, H.S.; Santos, D.; Saunders, R.D.E.; Sauv�, A.; Savelainen, M.; Savini, G.; Schaefer, B.M.; Schammel, M.P.; Scott, D.; Seiffert, M.D.; Serra, P.; Shellard, E.P.S.; Shimwell, T.W.; Shiraishi, M.; Smith, K.; Souradeep, T.; Spencer, L.D.; Spinelli, M.; Stanford, S.A.; Stern, D.; Stolyarov, V.; Stompor, R.; Strong, A.W.; Sudiwala, R.; Sunyaev, R.; Sutter, P.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J.A.; Tavagnacco, D.; Terenzi, L.; Texier, D.; Toffolatti, L.; Tomasi, M.; Tornikoski, M.; Tramonte, D.; Tristram, M.; Troja, A.; Trombetti, T.; Tucci, M.; Tuovinen, J.; T�rler, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, F.; Vassallo, T.; Vibert, L.; Vidal, M.; Viel, M.; Vielva, P.; Villa, F.; Wade, L.A.; Walter, B.; Wandelt, B.D.; Watson, R.; Wehus, I.K.; Welikala, N.; Weller, J.; White, M.; White, S.D.M.; Wilkinson, A.; Yvon, D.; Zacchei, A.; Zibin, J.P.; Zonca, A.

doi:10.1051/0004-6361/201527101

Using machine learning to optimise chameleon fifth force experiments (2024)
Journal Article
Briddon, C., Burrage, C., Moss, A., & Tamosiunas, A. (2024). Using machine learning to optimise chameleon fifth force experiments. Journal of Cosmology and Astroparticle Physics, 2024(2), Article 11. https://doi.org/10.1088/1475-7516/2024/02/011

The chameleon is a theorised scalar field that couples to matter and possess a screening mechanism, which weakens observational constraints from experiments performed in regions of higher matter density. One consequence of this screening mechanism is... Read More about Using machine learning to optimise chameleon fifth force experiments.

Chameleon screening in cosmic voids (2022)
Journal Article
Tamosiunas, A., Briddon, C., Burrage, C., Cutforth, A., Moss, A., & Vincent, T. (2022). Chameleon screening in cosmic voids. Journal of Cosmology and Astroparticle Physics, 2022(11), Article 056. https://doi.org/10.1088/1475-7516/2022/11/056

A key goal in cosmology in the upcoming decade will be to form a better understanding of the accelerated expansion of the Universe. Upcoming surveys, such as the Vera C. Rubin Observatory's 10-year Legacy Survey of Space and Time (LSST), Euclid and t... Read More about Chameleon screening in cosmic voids.

CMB constraints on monodromy inflation at strong coupling (2022)
Journal Article
Copeland, E. J., Cunillera, F., Moss, A., & Padilla, A. (2022). CMB constraints on monodromy inflation at strong coupling. Journal of Cosmology and Astroparticle Physics, 2022(09), Article 080. https://doi.org/10.1088/1475-7516/2022/09/080

We carry out a thorough numerical examination of field theory monodromy inflation at strong coupling. We perform an MCMC analysis using a Gaussian likelihood, fitting multiparameter models using CMB constraints on the spectral index and the tensor to... Read More about CMB constraints on monodromy inflation at strong coupling.

SELCIE: a tool for investigating the chameleon field of arbitrary sources (2021)
Journal Article
Briddon, C., Burrage, C., Moss, A., & Tamosiunas, A. (2021). SELCIE: a tool for investigating the chameleon field of arbitrary sources. Journal of Cosmology and Astroparticle Physics, 2021(12), 1-24. https://doi.org/10.1088/1475-7516/2021/12/043

The chameleon model is a modified gravity theory that introduces an additional scalar field that couples to matter through a conformal coupling. This `chameleon field' possesses a screening mechanism through a nonlinear self-interaction term which al... Read More about SELCIE: a tool for investigating the chameleon field of arbitrary sources.

A High-Resolution Investigation of the Multi-Phase ISM in a Galaxy during the First Two Billion Years (2021)
Journal Article
Dye, S., Eales, S. A., Gomez, H. L., Jones, G. C., Smith, M. W. L., Borsato, E., …Vlahakis, C. (2022). A High-Resolution Investigation of the Multi-Phase ISM in a Galaxy during the First Two Billion Years. Monthly Notices of the Royal Astronomical Society, 510(3), 3734–3757. https://doi.org/10.1093/mnras/stab3569

We have carried out the first spatially-resolved investigation of the multi-phase interstellar medium (ISM) at high redshift, using the z = 4.24 strongly-lensed sub-millimetre galaxy H-ATLASJ142413.9+022303 (ID141). We present high-resolution (down t... Read More about A High-Resolution Investigation of the Multi-Phase ISM in a Galaxy during the First Two Billion Years.

Constraints on primordial gravitational waves from the cosmic microwave background (2020)
Journal Article
Clarke, T. J., Copeland, E. J., & Moss, A. (2020). Constraints on primordial gravitational waves from the cosmic microwave background. Journal of Cosmology and Astroparticle Physics, 2020(10), Article 002. https://doi.org/10.1088/1475-7516/2020/10/002

Searches for primordial gravitational waves have resulted in constraints in a large frequency range from a variety of sources. The standard Cosmic Microwave Background (CMB) technique is to parameterise the tensor power spectrum in terms of the tenso... Read More about Constraints on primordial gravitational waves from the cosmic microwave background.

Planck 2018 results: VI. Cosmological parameters (2020)
Journal Article
Aghanim, N., Akrami, Y., Ashdown, M., Aumont, J., Baccigalupi, C., Ballardini, M., …Zonca, A. (2020). Planck 2018 results: VI. Cosmological parameters. Astronomy and Astrophysics, 641, Article A6. https://doi.org/10.1051/0004-6361/201833910

We present cosmological parameter results from the final full-mission Planck measurements of the cosmic microwave background (CMB) anisotropies, combining information from the temperature and polarization maps and the lensing reconstruction. Compared... Read More about Planck 2018 results: VI. Cosmological parameters.

Accelerated Bayesian inference using deep learning (2020)
Journal Article
Moss, A. (2020). Accelerated Bayesian inference using deep learning. Monthly Notices of the Royal Astronomical Society, 496(1), 328-338. https://doi.org/10.1093/mnras/staa1469

We present a novel Bayesian inference tool that uses a neural network (NN) to parametrize efficient Markov Chain Monte Carlo (MCMC) proposals. The target distribution is first transformed into a diagonal, unit variance Gaussian by a series of non-lin... Read More about Accelerated Bayesian inference using deep learning.

The shape dependence of chameleon screening (2018)
Journal Article
Burrage, C., Copeland, E. J., Moss, A., & Stevenson, J. A. (2018). The shape dependence of chameleon screening. Journal of Cosmology and Astroparticle Physics, 2018(1), https://doi.org/10.1088/1475-7516/2018/01/056

Chameleon scalar fields can screen their associated fifth forces from detection by changing their mass with the local density. These models are an archetypal example of a screening mechanism, and have become an important target for both cosmological... Read More about The shape dependence of chameleon screening.

Deep recurrent neural networks for supernovae classification (2017)
Journal Article
Charnock, T., & Moss, A. (2017). Deep recurrent neural networks for supernovae classification. Astrophysical Journal, 837(2), https://doi.org/10.3847/2041-8213/aa603d

We apply deep recurrent neural networks, which are capable of learning complex sequential information, to classify supernovae (code available at https://github.com/adammoss/supernovae). The observational time and filter fluxes are used as inputs to t... Read More about Deep recurrent neural networks for supernovae classification.

Planck intermediate results. L. Evidence of spatial variation of the polarized thermal dust spectral energy distribution and implications for CMB B-mode analysis (2017)
Journal Article
Planck Collaboration, Aghanim, N., Ashdown, M., Aumont, J., Baccigalupi, C., Ballardini, M., …Zonca, A. (2017). Planck intermediate results. L. Evidence of spatial variation of the polarized thermal dust spectral energy distribution and implications for CMB B-mode analysis. Astronomy and Astrophysics, 599, Article A51. https://doi.org/10.1051/0004-6361/201629164

The characterization of the Galactic foregrounds has been shown to be the main obstacle in thechallenging quest to detect primordial B-modes in the polarized microwave sky. We make use of the Planck-HFI 2015 data release at high frequencies to place... Read More about Planck intermediate results. L. Evidence of spatial variation of the polarized thermal dust spectral energy distribution and implications for CMB B-mode analysis.

Planck intermediate results. XLVII. Planck constraints on reionization history (2016)
Journal Article
Planck Collaboration, Adam, R., Aghanim, N., Ashdown, M., Aumont, J., Baccigalupi, C., …Zonca, A. (2016). Planck intermediate results. XLVII. Planck constraints on reionization history. Astronomy and Astrophysics, 596, Article A108. https://doi.org/10.1051/0004-6361/201628897

We investigate constraints on cosmic reionization extracted from the Planck cosmic microwave background (CMB) data. We combine the Planck CMB anisotropy data in temperature with the low-multipole polarization data to fit ΛCDM models with various para... Read More about Planck intermediate results. XLVII. Planck constraints on reionization history.

Planck intermediate results. XLIV. Structure of the Galactic magnetic field from dust polarization maps of the southern Galactic cap (2016)
Journal Article
Planck Collaboration, Aghanim, N., Alves, M. I. R., Arzoumanian, D., Aumont, J., Baccigalupi, C., …Zonca, A. (2016). Planck intermediate results. XLIV. Structure of the Galactic magnetic field from dust polarization maps of the southern Galactic cap. Astronomy and Astrophysics, 596, Article A105. https://doi.org/10.1051/0004-6361/201628636

Using data from the Planck satellite, we study the statistical properties of interstellar dust polarization at high Galactic latitudes around the south pole (b < −60°). Our aim is to advance the understanding of the magnetized interstellar medium (IS... Read More about Planck intermediate results. XLIV. Structure of the Galactic magnetic field from dust polarization maps of the southern Galactic cap.

Planck intermediate results. XLVI. Reduction of large-scale systematic effects in HFI polarization maps and estimation of the reionization optical depth (2016)
Journal Article
Planck Collaboration, Aghanim, N., Ashdown, M., Aumont, J., Baccigalupi, C., Ballardini, M., …Zonca, A. (2016). Planck intermediate results. XLVI. Reduction of large-scale systematic effects in HFI polarization maps and estimation of the reionization optical depth. Astronomy and Astrophysics, 596, Article A107. https://doi.org/10.1051/0004-6361/201628890

This paper describes the identification, modelling, and removal of previously unexplained systematic effects in the polarization data of the Planck High Frequency Instrument (HFI) on large angular scales, including new mapmaking and calibration proce... Read More about Planck intermediate results. XLVI. Reduction of large-scale systematic effects in HFI polarization maps and estimation of the reionization optical depth.

Planck intermediate results. XLVIII. Disentangling Galactic dust emission and cosmic infrared background anisotropies (2016)
Journal Article
Planck Collaboration, Aghanim, N., Ashdown, M., Aumont, J., Baccigalupi, C., Ballardini, M., …Zonca, A. (2016). Planck intermediate results. XLVIII. Disentangling Galactic dust emission and cosmic infrared background anisotropies. Astronomy and Astrophysics, 596, Article A109. https://doi.org/10.1051/0004-6361/201629022

Using the Planck 2015 data release (PR2) temperature maps, we separate Galactic thermal dust emission from cosmic infrared background (CIB) anisotropies. For this purpose, we implement a specifically tailored component-separation method, the so-calle... Read More about Planck intermediate results. XLVIII. Disentangling Galactic dust emission and cosmic infrared background anisotropies.

Planck intermediate results. XLIX. Parity-violation constraints from polarization data (2016)
Journal Article
Aghanim, N., Ashdown, M., Aumont, J., Baccigalupi, C., Ballardini, M., Banday, A., …Zonca, A. (in press). Planck intermediate results. XLIX. Parity-violation constraints from polarization data. Astronomy and Astrophysics, 596, Article A110. https://doi.org/10.1051/0004-6361/201629018

Parity-violating extensions of the standard electromagnetic theory cause in vacuo rotation of the plane of polarization of propagating photons. This effect, also known as cosmic birefringence, has an impact on the cosmic microwave background (CMB) an... Read More about Planck intermediate results. XLIX. Parity-violation constraints from polarization data.

Planck 2015 results. XV. Gravitational lensing (2016)
Journal Article
Ade, P., Aghanim, N., Arnaud, M., Ashdown, M., Aumont, J., Baccigalupi, C., …Zonca, A. (2016). Planck 2015 results. XV. Gravitational lensing. Astronomy and Astrophysics, 594, 1-28. https://doi.org/10.1051/0004-6361/201525941

We present the most significant measurement of the cosmic microwave background (CMB) lensing potential to date (at a level of 40σ), using temperature and polarization data from the Planck 2015 full-mission release. Using a polarization-only estimator... Read More about Planck 2015 results. XV. Gravitational lensing.

Planck 2015 results: VI. LFI mapmaking (2016)
Journal Article
Kisner, T. S., Kiiveri, K., Keskitalo, R., Kurki-Suonio, H., Kunz, M., Knoche, J., …Zonca, A. (2016). Planck 2015 results: VI. LFI mapmaking. Astronomy and Astrophysics, 594, A6. https://doi.org/10.1051/0004-6361/201525813

© ESO, 2016. 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... Read More about Planck 2015 results: VI. LFI mapmaking.

Planck 2015 results. IV. Low Frequency Instrument beams and window functions (2016)
Journal Article
Ade, P., Aghanim, N., Ashdown, M., Aumont, J., Baccigalupi, C., Banday, A., …Zonca, A. (2016). Planck 2015 results. IV. Low Frequency Instrument beams and window functions. Astronomy and Astrophysics, 594, Article A4. https://doi.org/10.1051/0004-6361/201525809

This paper presents the characterization of the in-flight beams, the beam window functions, and the associated uncertainties for the Planck Low Frequency Instrument (LFI). The structure of the paper is similar to that presented in the 2013 Planck rel... Read More about Planck 2015 results. IV. Low Frequency Instrument beams and window functions.

Planck 2015 results. I. Overview of products and scientific results (2016)
Journal Article
Adam, R., Ade, P., Aghanim, N., Akrami, Y., Alves, M., Argüeso, F., …Zonca, A. (2016). Planck 2015 results. I. Overview of products and scientific results. Astronomy and Astrophysics, 594, Article A1. https://doi.org/10.1051/0004-6361/201527101

The European Space Agency’s Planck satellite, which is dedicated to studying the early Universe and its subsequent evolution, was launched on 14 May 2009. It scanned the microwave and submillimetre sky continuously between 12 August 2009 and 23 Octob... Read More about Planck 2015 results. I. Overview of products and scientific results.

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