Planck 2015 results. VI. LFI mapmakingTools Ade, P.A.R., Aghanim, N., Ashdown, M., Aumont, J., Baccigalupi, C., Banday, A.J., Barreiro, R.B., Bartolo, N., Battaner, E., Benabed, K., Benoît, A., Benoit-Lévy, A., Bernard, J.-P., Bersanelli, M., Bielewicz, P., Bonaldi, A., Bonavera, L., Bond, J.R., Borrill, J., Bouchet, F.R., Bucher, M., Burigana, C., Butler, R.C., Calabrese, E., Cardoso, J.-F., Catalano, A., Chamballu, A., Chary, R.-R., Christensen, P.R., Colombi, S., Colombo, L.P.L., Crill, B.P., Curto, A., Cuttaia, F., Danese, L., Davies, R.D., Davis, R.J., de Bernardis, P., de Rosa, A., de Zotti, G., Delabrouille, J., Dickinson, C., Diego, J.M., Dole, H., Donzelli, S., Doré, O., Douspis, M., Ducout, A., Dupac, X., Efstathiou, G., Elsner, F., Enßlin, T.A., Eriksen, H.K., Fergusson, J., Finelli, F., Forni, O., Frailis, M., Franceschi, E., Frejsel, A., Galeotta, S., Galli, S., Ganga, K., Giard, M., Giraud-Héraud, Y., Gjerløw, E., González-Nuevo, J., Górski, K.M., Gratton, S., Gregorio, A., Gruppuso, A., Hansen, F.K., Hanson, D., Harrison, D.L., Henrot-Versillé, S., 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., Juvela, M., Keihänen, E., Keskitalo, R., Kiiveri, K., Kisner, T.S., Knoche, J., Kunz, M., Kurki-Suonio, H., Lähteenmäki, A., Lamarre, J.-M., Lasenby, A., Lattanzi, M., Lawrence, C.R., Leahy, J.P., Leonardi, R., Lesgourgues, J., Levrier, F., Liguori, M., Lilje, P.B., Linden-Vørnle, M., Lindholm, V., López-Caniego, M., Lubin, P.M., Macías-Pérez, J.F., Maggio, G., Maino, D., Mandolesi, N., Mangilli, A., Martin, P.G., Martínez-González, E., Masi, S., Matarrese, S., Mazzotta, P., McGehee, P., Meinhold, P.R., Melchiorri, A., Mendes, L., Mennella, A., Migliaccio, M., Mitra, S., Montier, L., Morgante, G., Mortlock, D., Moss, Adam, Munshi, D., Murphy, J.A., Naselsky, P., Nati, F., Natoli, P., Netterfield, C.B., Nørgaard-Nielsen, H.U., Novikov, D., Novikov, I., Paci, F., Pagano, L., Paoletti, D., Partridge, B., Pasian, F., Patanchon, G., Pearson, T.J., Perdereau, O., Perotto, L., Perrotta, F., Pettorino, V., Pierpaoli, E., Pietrobon, D., Pointecouteau, E., Polenta, G., Pratt, G.W., Prézeau, G., Prunet, S., Puget, J.-L., Rachen, J.P., Rebolo, R., Reinecke, M., Remazeilles, M., Renzi, A., Rocha, G., Rosset, C., Rossetti, M., Roudier, G., Rubiño-Martín, J.A., Rusholme, B., Sandri, M., Santos, D., Savelainen, M., Scott, D., Seiffert, M.D., Shellard, E.P.S., Spencer, L.D., Stolyarov, V., Stompor, R., Sutton, D., Suur-Uski, A.-S., Sygnet, J.-F., Tauber, J.A., Terenzi, L., Toffolatti, L., Tomasi, M., Tristram, M., Tucci, M., Tuovinen, J., Valenziano, L., Valiviita, J., Van Tent, B., Vassallo, T., Vielva, P., Villa, F., Wade, L.A., Wandelt, B.D., Watson, R., Wehus, I.K., Yvon, D., Zacchei, A. and Zonca, A. (2016) Planck 2015 results. VI. LFI mapmaking. Astronomy & Astrophysics, 594 . A6/1-A6/23. ISSN 1432-0746 Full text not available from this repository.AbstractThis 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.
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