Browsing by Author "Banerji, M."

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    AGNFITTER-RX: Modeling the radio-to-X-ray spectral energy distributions of AGNs
    (2024) Martinez-Ramirez, L. N.; Rivera, G. Calistro; Lusso, E.; Bauer, F. E.; Nardini, E.; Buchner, J.; Brown, M. J. I.; Pineda, J. C. B.; Temple, M. J.; Banerji, M.; Stalevski, M.; Hennawi, J. F.
    We present new advancements in the modeling of the spectral energy distributions (SEDs) of active galaxies by introducing the radio-to-X-ray fitting capabilities of the publicly available Bayesian code AGNFITTER. The new code release, called AGNFITTER-RX, models the broad-band photometry covering the radio, infrared (IR), optical, ultraviolet (UV), and X-ray bands consistently using a combination of theoretical and semi-empirical models of the active galactic nucleus (AGN) and host-galaxy emission. This framework enables the detailed characterization of four physical components of the active nuclei, namely the accretion disk, the hot dusty torus, the relativistic jets and core radio emission, and the hot corona, and can be used to model three components within the host galaxy: stellar populations, cold dust, and the radio emission from the star-forming regions. Applying AGNFITTER-RX to a diverse sample of 36 AGN SEDs at z less than or similar to 0.7 from the AGN SED ATLAS, we investigated and compared the performance of state-of-the-art torus and accretion disk emission models in terms of fit quality and inferred physical parameters. We find that clumpy torus models that include polar winds and semi-empirical accretion disk templates including emission-line features significantly increase the fit quality in 67% of the sources by reducing by 2 sigma fit residuals in the 1.5-5 mu m and 0.7 mu m regimes. We demonstrate that, by applying AGNFITTER-RX to photometric data, we are able to estimate the inclination and opening angles of the torus, consistent with spectroscopic classifications within the AGN unified model, as well as black hole masses congruent with virial estimates based on H alpha. We investigate wavelength-dependent AGN fractions across the spectrum for Type 1 and Type 2 AGNs, finding dominant AGN fractions in radio, mid-infrared, and X-ray bands, which are in agreement with the findings from empirical methods for AGN selection. The wavelength coverage and the flexibility for the inclusion of state-of-the-art theoretical models make AGNFITTER-RX a unique tool for the further development of SED modeling for AGNs in present and future radio-to-X-ray galaxy surveys.
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    First cosmology results using Type Ia supernova from the Dark Energy Survey: simulations to correct supernova distance biases
    (2019) Kessler, R.; Brout, D.; D'Andrea, C. B.; Davis, T. M.; Hinton, S. R.; Kim, A. G.; Lasker, J.; Lidman, C.; Macaulay, E.; Moeller, A.; Sako, M.; Scolnic, D.; Smith, M.; Sullivan, M.; Zhang, B.; Andersen, P.; Asorey, J.; Avelino, A.; Calcino, J.; Carollo, D.; Challis, P.; Childress, M.; Clocchiatti, A.; Crawford, S.; Filippenko, A. V.; Foley, R. J.; Glazebrook, K.; Hoormann, J. K.; Kasai, E.; Kirshner, R. P.; Lewis, G. F.; Mandel, K. S.; March, M.; Morganson, E.; Muthukrishna, D.; Nugent, P.; Pan, Y. -C.; Sommer, N. E.; Swann, E.; Thomas, R. C.; Tucker, B. E.; Uddin, S. A.; Abbott, T. M. C.; Allam, S.; Annis, J.; Avila, S.; Banerji, M.; Bechtol, K.; Bertin, E.; Brooks, D.; Buckley-Geer, E.; Burke, D. L.; Carnero Rosell, A.; Kind, M. Carrasco; Carretero, J.; Castander, F. J.; Crocce, M.; da Costa, L. N.; Davis, C.; De Vicente, J.; Desai, S.; Diehl, H. T.; Doel, P.; Eifler, T. F.; Flaugher, B.; Fosalba, P.; Frieman, J.; Garcia-Bellido, J.; Gaztanaga, E.; Gerdes, D. W.; Gruen, D.; Gruendl, R. A.; Gutierrez, G.; Hartley, W. G.; Hollowood, D. L.; Honscheid, K.; James, D. J.; Johnson, M. W. G.; Johnson, M. D.; Krause, E.; Kuehn, K.; Kuropatkin, N.; Lahav, O.; Li, T. S.; Lima, M.; Marshall, J. L.; Martini, P.; Menanteau, F.; Miller, C. J.; Miquel, R.; Nord, B.; Plazas, A. A.; Roodman, A.; Sanchez, E.; Scarpine, V.; Schindler, R.; Schubnell, M.; Serrano, S.; Sevilla-Noarbe, I.; Soares-Santos, M.; Sobreira, F.; Suchyta, E.; Tarle, G.; Thomas, D.; Walker, A. R.; Zhang, Y.
    We describe catalogue-level simulations of Type Ia supernova (SN Ia) light curves in the Dark Energy Survey Supernova Program (DES-SN) and in low-redshift samples from the Center for Astrophysics (CfA) and the Carnegie Supernova Project (CSP). These simulations are used to model biases from selection effects and light-curve analysis and to determine bias corrections for SN Ia distance moduli that are used to measure cosmological parameters. To generate realistic light curves, the simulation uses a detailed SN Ia model, incorporates information from observations (point spread function, sky noise, zero-point), and uses summary information (e.g. detection efficiency versus signal-to-noise ratio) based on 10 000 fake SN light curves whose fluxes were overlaid on images and processed with our analysis pipelines. The quality of the simulation is illustrated by predicting distributions observed in the data. Averaging within redshift bins, we find distance modulus biases up to 0.05 mag over the redshift ranges of the low-z and DES-SN samples. For individual events, particularly those with extreme red or blue colour, distance biases can reach 0.4 mag. Therefore, accurately determining bias corrections is critical for precision measurements of cosmological parameters. Files used to make these corrections are available at https://des.ncsa.illinois.edu/releases/sn.
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    MOONS: The New Multi-Object Spectrograph for the VLT
    (2020) Cirasuolo, M.; Fairley, A.; Rees, P.; González, O. A.; Taylor, W.; Maiolino, R.; Afonso, J.; Evans, C.; Flores, H.; Lilly, S.; Oliva, E.; Paltani, S.; Vanzi, L.; Abreu, M.; Accardo, M.; Adams, N.; Álvarez Méndez, D.; Amans, J. -P.; Amarantidis, S.; Atek, H.; Atkinson, D.; Banerji, M.; Barrett, J.; Barrientos, F.; Bauer, F.; Beard, S.; Béchet, C.; Belfiore, A.; Bellazzini, M.; Benoist, C.; Best, P.; Biazzo, K.; Black, M.; Boettger, D.; Bonifacio, P.; Bowler, R.; Bragaglia, A.; Brierley, S.; Brinchmann, J.; Brinkmann, M.; Buat, V.; Buitrago, F.; Burgarella, D.; Burningham, B.; Buscher, D.; Cabral, A.; Caffau, E.; Cardoso, L.; Carnall, A.; Carollo, M.; Castillo, R.; Castignani, G.; Catelan, Márcio; Cicone, C.; Cimatti, A.; Cioni, M. -R. L.; Clementini, G.; Cochrane, W.; Coelho, J.; Colling, M.; Contini, T.; Contreras, R.; Conzelmann, R.; Cresci, G.; Cropper, M.; Cucciati, O.; Cullen, F.; Cumani, C.; Curti, M.; Da Silva, A.; Daddi, E.; Dalessandro, E.; Dalessio, F.; Dauvin, L.; Davidson, G.; de Laverny, P.; Delplancke-Ströbele, F.; De Lucia, G.; Del Vecchio, C.; Dessauges-Zavadsky, M.; Di Matteo, P.; Dole, H.; Drass, H.; Dunlop, J.; Dünner, R.; Eales, S.; Ellis, R.; Enriques, B.; Fasola, G.; Ferguson, A.; Ferruzzi, D.; Fisher, M.; Flores, M.; Fontana, A.; Forchi, V.; Francois, P.; Franzetti, P.; Gargiulo, A.; Garilli, B.; Gaudemard, J.; Gieles, M.; Gilmore, G.; Ginolfi, M.; Gomes, J. M.; Guinouard, I.; Gutierrez, P.; Haigron, R.; Hammer, F.; Hammersley, P.; Haniff, C.; Harrison, C.; Haywood, M.; Hill, V.; Hubin, N.; Humphrey, A.; Ibata, R.; Infante, L.; Ives, D.; Ivison, R.; Iwert, O.; Jablonka, P.; Jakob, G.; Jarvis, M.; King, D.; Kneib, J. -P.; Laporte, P.; Lawrence, A.; Lee, D.; Li Causi, G.; Lorenzoni, S.; Lucatello, S.; Luco, Y.; Macleod, A.; Magliocchetti, M.; Magrini, L.; Mainieri, V.; Maire, C.; Mannucci, F.; Martin, N.; Matute, I.; Maurogordato, S.; McGee, S.; Mcleod, D.; McLure, R.; McMahon, R.; Melse, B. -T.; Messias, H.; Mucciarelli, A.; Nisini, B.; Nix, J.; Norberg, P.; Oesch, P.; Oliveira, A.; Origlia, L.; Padilla, N.; Palsa, R.; Pancino, E.; Papaderos, P.; Pappalardo, C.; Parry, I.; Pasquini, L.; Peacock, J.; Pedichini, F.; Pello, R.; Peng, Y.; Pentericci, L.; Pfuhl, O.; Piazzesi, R.; Popovic, D.; Pozzetti, L.; Puech, M.; Puzia, T.; Raichoor, A.; Randich, S.; Recio-Blanco, A.; Reis, S.; Reix, F.; Renzini, A.; Rodrigues, M.; Rojas, F.; Rojas-Arriagada, Á.; Rota, S.; Royer, F.; Sacco, G.; Sanchez-Janssen, R.; Sanna, N.; Santos, P.; Sarzi, M.; Schaerer, D.; Schiavon, R.; Schnell, R.; Schultheis, M.; Scodeggio, M.; Serjeant, S.; Shen, T. -C.; Simmonds, C.; Smoker, J.; Sobral, D.; Sordet, M.; Spérone, D.; Strachan, J.; Sun, X.; Swinbank, M.; Tait, G.; Tereno, I.; Tojeiro, R.; Torres, M.; Tosi, M.; Tozzi, A.; Tresiter, E.; Valenti, E.; Valenzuela Navarro, Á.; Vanzella, E.; Vergani, S.; Verhamme, A.; Vernet, J.; Vignali, C.; Vinther, J.; Von Dran, L.; Waring, C.; Watson, S.; Wild, V.; Willesme, B.; Woodward, B.; Wuyts, S.; Yang, Y.; Zamorani, G.; Zoccali, M.; Bluck, A.; Trussler, J.
    MOONS is the new Multi-Object Optical and Near-infrared Spectrograph currently under construction for the Very Large Telescope (VLT) at ESO. This remarkable instrument combines, for the first time, the collecting power of an 8-m telescope, 1000 fibres with individual robotic positioners, and both low- and high-resolution simultaneous spectral coverage across the 0.64-1.8 μm wavelength range. This facility will provide the astronomical community with a powerful, world-leading instrument able to serve a wide range of Galactic, extragalactic and cosmological studies. Construction is now proceeding full steam ahead and this overview article presents some of the science goals and the technical description of the MOONS instrument. More detailed information on the MOONS surveys is provided in the other dedicated articles in this Messenger issue....