Now showing items 1-3 of 3

  • Friedrich, Oliver; Andrade-Oliveira, F.; Camacho, Hugo; Alves, O.; Rosenfeld, R.; Sanchez, J.; Fang, Xiao; Eifler, Tim F.; Krause, E.; Chang, C.; Omori, Y.; Amon, A.; Baxter, E.; Elvin-Poole, J.; Huterer, Dragan; Porredon, Anna; Prat, Judit; Terra, V.; Troja, A.; Alarcon, A.; Bechtol, Keith; Bernstein, Gary M.; Buchs, R.; Campos, A.; Cornero Rosell, Aurelio; Carrasco Kind, Matias; Cawthon, R.; Choi, A.; Cordero, J.; Crocce, Martin; Davis, C.; DeRose, J.; Diehl, Herman T.; Dodelson, Scott; Doux, Cyrille; Drlica-Wagner, Alex; Elsner, F.; Everett, S.; Fosalba, Pablo; Gatti, M.; Giannini, G.; Gruen, Daniel; Gruendl, Robert A.; Harrison, Ian; Hartley, William G.; Jain, Bhuvnesh; Jarvis, M.; MacCrann, Niall; McCullough, J.; Muir, J.; Myles, Justin; Pandey, S.; Raveri, Marco; Roodman, A.; Rodriguez-Monroy, Martin; Rykoff, Eli S.; Samuroff, Simon; Sánchez, C.; Secco, Lucas Frozza; Sevilla-Noarbe, Ignacio; Sheldon, E.; Troxel, Michael A.; Weaverdyck, Noah; Yanny, Brian; Aguena, Michel; Avila, S.; Bacon, D.; Bertin, E.; Bhargava, S.; Brooks, D.; Burke, David L.; Carretero, J.; Costanzi, Matteo; da Costa, L. N.; Pereira, Maria Elidaiana da Silva; De Vicente, Juan; Desai, S.; Evrard, August E.; Ferrero, Ismael; Frieman, J.; García-Bellido, Juan; Gaztañaga, Enrique; Gerdes, David W.; Giannantonio, Tommaso; Gschwend, J.; Gutierrez, G.; Hinton, Samuel R.; Hollowood, Devon L.; Honscheid, Klaus; James, D. J.; Kuehn, Kyler; Lahav, Ofer; Lima, M.; Maia, Marcio A. G.; Menanteau, Felipe; Miquel, R.; Morgan, R.; Palmese, Antonella; Paz-Chinchón, Francisco; Plazas, Andrés A.; Sanchez, E.; Scarpine, V.; Serrano, S.; Soares-Santos, Marcelle; Smith, M.; Suchyta, E.; Tarlé, Gregory; Thomas, D.; To, Chun-Hao; Varga, Tamas Norbert; Weller, Jochen; Wilkinson, R. D. (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2021)
    We describe and test the fiducial covariance matrix model for the combined two-point function analysis of the Dark Energy Survey Year 3 (DES-Y3) data set. Using a variety of new ansatzes for covariance modelling and testing, ...
  • Andrade-Oliveira, Felipe; Camacho, Hugo; Faga, L.; Gomes, R.; Rosenfeld, R.; Troja, A.; Alves, O.; Doux, Cyrille; Elvin-Poole, J.; Fang, Xiao; Friedrich, Oliver; Kokron, N.; Lima, M.; Miranda, V.; Pandey, S.; Porredon, Anna; Sanchez, J.; Aguena, Michel; Allam, Sahar; Annis, James; Avila, Santiago; Bertin, Emmanuel; Brooks, D.; Burke, David L.; Carrasco Kind, Matias; Carretero, Jorge; Cawthon, Ross; Chang, Chihway L.; Choi, A.; Costanzi, Matteo; Crocce, Martin; da Costa, Luiz N.; Pereira, Maria Elidaiana da Silva; Desai, S.; Diehl, Herman T.; Doel, Peter; Drlica-Wagner, Alex; Everett, Spencer; Evrard, August E.; Ferrero, Ismael; Frieman, Josh; García-Bellido, Juan; Gaztañaga, Enrique; Gerdes, David W.; Gruen, Daniel; Gruendl, Robert A.; Hinton, Samuel R.; Hollowood, Devon L.; Jain, Bhuvnesh; James, David J.; Kuropatkin, Nikolay; Lahav, Ofer; MacCrann, Niall; Maia, Marcio A. G.; March, Marisa; Melchior, Peter; Menanteau, Felipe; Miquel, Ramon; Morgan, R.; Myles, Justin; Ogando, Ricardo L. C.; Palmese, Antonella; Paz-Chinchón, Francisco; Plazas Malagón, Andrés A.; Rodriguez-Monroy, Martin; Sanchez, E.; Scarpine, Vic; Serrano, Santiago; Sevilla-Noarbe, Ignacio; Smith, Mathew; Soares-Santos, Marcelle; Suchyta, Eric; Tarlé, Gregory; To, Chun-Hao (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2021)
    ABSTRACT We perform an analysis in harmonic space of the Dark Energy Survey Year 1 Data (DES-Y1) galaxy clustering photometric data using products obtained for the real-space analysis. We test our pipeline with ...
  • Riquelme, Walter; Avila, Santiago; García-Bellido, Juan; Porredon, Anna; Ferrero, Ismael; Chan, Kwan Chuen; Rosenfeld, Rogerio; Camacho, Hugo; Adame, Adrian G.; Carnero Rosell, Aurelio; Crocce, Martin; De Vicente, Juan; Eifler, Tim; Elvin-Pool, Jack; Fang, Xiao; Krause, Elisabeth; Rodriguez Monroy, Martin; Ross, Ashley J.; Sanchez, Eusebio; Sevilla, Ignacio (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2023)
    Local primordial non-Gaussianity (PNG) is a promising observable of the underlying physics of inflation, characterized by flocNL⁠. We present the methodology to measure flocNL from the Dark Energy Survey (DES) data using ...