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17 results on '"Morice-Atkinson, Xan"'

1. A field-level emulator for modified gravity

Author

Saadeh, Daniela, Koyama, Kazuya, and Morice-Atkinson, Xan

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology
Abstract

Stage IV dark energy surveys such as the Vera C. Rubin Observatory and Euclid present a unique opportunity to shed light on the nature of dark energy. However, the full constraining power of the new data cannot be unlocked unless accurate predictions are available at all observable scales. Currently, only the linear regime is well understood in models beyond $\Lambda$CDM: on the nonlinear scales, expensive numerical simulations become necessary, making their direct use impractical in the analyses of large datasets. Recently, machine learning techniques have shown potential to break this impasse: by training emulators, we can reproduce complex data fields in a fraction of the time it takes to produce them. In this work, we present a field-level emulator capable of turning a $\Lambda$CDM N-body simulation into one evolved under $f(R)$ gravity. To achieve this, we build on the map2map neural network, using the strength of modified gravity $|f_{R_0}|$ as style parameter. We find that our emulator correctly estimates the changes it needs to apply to the positions and velocities of the input N-body particles to produce the target simulation. We test the performance of our network against several summary statistics, finding $1\%$ agreement in the power spectrum up to $k \sim 1$ $h/$Mpc, and $1.5\%$ agreement against the independent boost emulator eMantis. Although the algorithm is trained on fixed cosmological parameters, we find it can extrapolate to models it was not trained on. Coupled with available field-level emulators and simulations suites for $\Lambda$CDM, our algorithm can be used to constrain modified gravity in the large-scale structure using full information available at the field-level., Comment: 13 pages, 9 figures; to be submitted to MNRAS

Published
2024

2. Low-latency gravitational wave alert products and their performance at the time of the fourth LIGO-Virgo-KAGRA observing run

Author

Chaudhary, Sushant Sharma, Toivonen, Andrew, Waratkar, Gaurav, Mo, Geoffrey, Chatterjee, Deep, Antier, Sarah, Brockill, Patrick, Coughlin, Michael W., Essick, Reed, Ghosh, Shaon, Morisaki, Soichiro, Baral, Pratyusava, Baylor, Amanda, Adhikari, Naresh, Brady, Patrick, Davies, Gareth Cabourn, Canton, Tito Dal, Cavaglià, Marco, Creighton, Jolien, Choudhary, Sunil, Chu, Yu-Kuang, Clearwater, Patrick, Davis, Luke, Dent, Thomas, Drago, Marco, Ewing, Becca, Godwin, Patrick, Guo, Weichangfeng, Hanna, Chad, Huxford, Rachel, Harry, Ian, Katsavounidis, Erik, Kovalam, Manoj, Li, Alvin K. Y., Magee, Ryan, Marx, Ethan, Meacher, Duncan, Messick, Cody, Morice-Atkinson, Xan, Pace, Alexander, De Pietri, Roberto, Piotrzkowski, Brandon, Roy, Soumen, Sachdev, Surabhi, Singer, Leo P., Singh, Divya, Szczepanczyk, Marek, Tang, Daniel, Trevor, Max, Tsukada, Leo, Villa-Ortega, Verónica, Wen, Linqing, and Wysocki, Daniel

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Multi-messenger searches for BNS and NSBH mergers are currently one of the most exciting areas of astronomy. The search for joint electromagnetic and neutrino counterparts to GWs has resumed with O4. To support this effort, public semi-automated data products are sent in near real-time and include localization and source properties to guide complementary observations. In preparation for O4, we have conducted a study using a simulated population of compact binaries and a MDC in the form of a real-time replay to optimize and profile the software infrastructure and scientific deliverables. End-to-end performance was tested, including data ingestion, running online search pipelines, performing annotations, and issuing alerts to the astrophysics community. We present an overview of the low-latency infrastructure and the performance of the data products that are now being released during O4 based on the MDC. We report the expected median latency for the preliminary alert of full bandwidth searches (29.5s) and show consistency and accuracy of released data products using the MDC. For the first time, we report the expected median latency for triggers from early warning searches (-3.1s), which are new in O4 and target neutron star mergers during inspiral phase. This paper provides a performance overview for LVK low-latency alert infrastructure and data products using the MDC and serves as a useful reference for the interpretation of O4 detections.

Published
2023
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3. Candidate Massive Galaxies at $z \sim 4$ in the Dark Energy Survey

Author

Guarnieri, Pierandrea, Maraston, Claudia, Thomas, Daniel, Pforr, Janine, Gonzalez-Perez, Violeta, Etherington, James, Carlsen, Joakim, Morice-Atkinson, Xan, Conselice, Christopher J., Gschwend, Julia, Kind, Matias Carrasco, Abbott, Tim, Allam, Sahar, Brooks, David, Burke, David, Rosell, Aurelio Carnero, Carretero, Jorge, Cunha, Carlos, ďAndrea, Chris, da Costa, Luiz, De Vincente, Juan, DePoy, Darren, Diehl, H. Thomas, Doel, Peter, Frieman, Josh, Garcia-Bellido, Juan, Gruen, Daniel, Gutierrez, Gaston, Hanley, Dominic, Hollowood, Devon, Honscheid, Klaus, James, David, Jeltema, Tesla, Kuehn, Kyler, Lima, Marcos, Maia, Marcio A. G., Marshall, Jennifer, Martini, Paul, Melchior, Peter, Menanteau, Felipe, Miquel, Ramon, Malagon, Andres Plazas, Richardson, Samuel, Romer, Kathy, Sanchez, Eusebio, Scarpine, Vic, Schindler, Rafe, Sevilla, Ignacio, Smith, Mathew, Soares-Santos, Marcelle, Sobreira, Flavia, Suchyta, Eric, Tarle, Gregory, Walker, Alistair, and Wester, William

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Using stellar population models, we predicted that the Dark Energy Survey (DES) - due to its special combination of area (5000 deg. sq.) and depth ($i = 24.3$) - would be in the position to detect massive ($\gtrsim 10^{11}$ M$_{\odot}$) galaxies at $z \sim 4$. We confront those theoretical calculations with the first $\sim 150$ deg. sq. of DES data reaching nominal depth. From a catalogue containing $\sim 5$ million sources, $\sim26000$ were found to have observed-frame $g-r$ vs $r-i$ colours within the locus predicted for $z \sim 4$ massive galaxies. We further removed contamination by stars and artefacts, obtaining 606 galaxies lining up by the model selection box. We obtained their photometric redshifts and physical properties by fitting model templates spanning a wide range of star formation histories, reddening and redshift. Key to constrain the models is the addition, to the optical DES bands $g$, $r$, $i$, $z$, and $Y$, of near-IR $J$, $H$, $K_{s}$ data from the Vista Hemisphere Survey. We further applied several quality cuts to the fitting results, including goodness of fit and a unimodal redshift probability distribution. We finally select 233 candidates whose photometric redshift probability distribution function peaks around $z\sim4$, have high stellar masses ($\log($M$^{*}$/M$_{\odot})\sim 11.7$ for a Salpeter IMF) and ages around 0.1 Gyr, i.e. formation redshift around 5. These properties match those of the progenitors of the most massive galaxies in the local universe. This is an ideal sample for spectroscopic follow-up to select the fraction of galaxies which is truly at high redshift. These initial results and those at the survey completion, which we shall push to higher redshifts, will set unprecedented constraints on galaxy formation, evolution, and the re-ionisation epoch., Comment: 24 pages (41 with appendix), 16 figures, MNRAS in press

Published
2018
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4. Machine learning approaches for astrophysics and cosmology

Author

Morice-Atkinson, Xan, Bacon, David James, and Koyama, Kazuya

Subjects
523.01
Abstract

This thesis focuses on applying machine learning methods to both astronomical and cosmological problems. Regarding the application to astronomy, I use data analysis techniques new to astronomy to detect strong correlations in observed data to perform feature pre-selection, machine learning techniques (four tree-based methods including Random Forests) to classify astronomical objects, and novel software packages to interpret a machine learning model in an attempt to understand how it is correctly classifying objects. I showcase these techniques by applying them to the problem of star-galaxy separation using data from the Sloan Digital Sky Survey (hereafter SDSS) and the results show that the rate of misclassifications can be reduced by up to ≈ 33% over the standard SDSS frames approach. In reference to the application to cosmology, I seek to answer the question: 'can we distinguish between cosmological/gravitational models using machine learning, and if so, what features are useful discriminants?'. To approach this, I use an image classi cation machine learning method called Convolutional Neural Networks (CNNs) to classify dark matter particle simulations created with different theories of gravity. The results show that these simulations can be classified to a high degree of accuracy. I then investigate the model, using generated datasets with known parameters to probe the decision boundaries of the CNN and determine where the model breaks down. I also manipulate the CNN into creating representations of dark matter particle simulations to understand which features of the simulations it has been able to learn about - showing that CNNs do not have to simply focus on matter density variance and can learn about higher order statistics such as isodensity curvature. All of these methods are new to the analysis of different theories of gravity in cosmology.

Published
2019

5. Learning from the machine: interpreting machine learning algorithms for point- and extended- source classification

Author

Morice-Atkinson, Xan, Hoyle, Ben, and Bacon, David

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Physics - Data Analysis, Statistics and Probability
Abstract

We investigate star-galaxy classification for astronomical surveys in the context of four methods enabling the interpretation of black-box machine learning systems. The first is outputting and exploring the decision boundaries as given by decision tree based methods, which enables the visualization of the classification categories. Secondly, we investigate how the Mutual Information based Transductive Feature Selection (MINT) algorithm can be used to perform feature pre-selection. If one would like to provide only a small number of input features to a machine learning classification algorithm, feature pre-selection provides a method to determine which of the many possible input properties should be selected. Third is the use of the tree-interpreter package to enable popular decision tree based ensemble methods to be opened, visualized, and understood. This is done by additional analysis of the tree based model, determining not only which features are important to the model, but how important a feature is for a particular classification given its value. Lastly, we use decision boundaries from the model to revise an already existing method of classification, essentially asking the tree based method where decision boundaries are best placed and defining a new classification method. We showcase these techniques by applying them to the problem of star-galaxy separation using data from the Sloan Digital Sky Survey (hereafter SDSS). We use the output of MINT and the ensemble methods to demonstrate how more complex decision boundaries improve star-galaxy classification accuracy over the standard SDSS frames approach (reducing misclassifications by up to $\approx33\%$). We then show how tree-interpreter can be used to explore how relevant each photometric feature is when making a classification on an object by object basis., Comment: 12 pages, 8 figures, 8 tables

Published
2017
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6. Core or cusps: The central dark matter profile of a redshift one strong lensing cluster with a bright central image

Author

Collett, Thomas E., Buckley-Geer, Elizabeth, Lin, Huan, Bacon, David, Nichol, Robert C., Nord, Brian, Morice-Atkinson, Xan, Amara, Adam, Birrer, Simon, Kuropatkin, Nikolay, More, Anupreeta, Papovich, Casey, Romer, Kathy K., Tessore, Nicolas, Abbott, Tim M. C., Allam, Sahar, Annis, James, Benoit-Lévy, Aurélien, Brooks, David, Burke, David L., Kind, Matias Carrasco, Castander, Francisco Javier J., D'Andrea, Chris B., da Costa, Luiz N., Desai, Shantanu, Diehl, H. Thomas, Doel, Peter, Eifler, Tim F., Flaugher, Brenna, Frieman, Josh, Gerdes, David W., Goldstein, Daniel A., Gruen, Daniel, Gschwend, Julia, Gutierrez, Gaston, James, David J., Kuehn, Kyler, Kuhlmann, Steve, Lahav, Ofer, Li, Ting S., Lima, Marcos, Maia, Marcio A. G., March, Marisa, Marshall, Jennifer L., Martini, Paul, Melchior, Peter, Miquel, Ramon, Plazas, Andrés A., Rykoff, Eli S., Sanchez, Eusebio, Scarpine, Vic, Schindler, Rafe, Schubnell, Michael, Sevilla-Noarbe, Ignacio, Smith, Mathew, Sobreira, Flavia, Suchyta, Eric, Swanson, Molly E. C., Tarle, Gregory, Tucker, Douglas L., and Walker, Alistair R.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract

We report on SPT-CLJ2011-5228, a giant system of arcs created by a cluster at $z=1.06$. The arc system is notable for the presence of a bright central image. The source is a Lyman Break galaxy at $z_s=2.39$ and the mass enclosed within the 14 arc second radius Einstein ring is $10^{14.2}$ solar masses. We perform a full light profile reconstruction of the lensed images to precisely infer the parameters of the mass distribution. The brightness of the central image demands that the central total density profile of the lens be shallow. By fitting the dark matter as a generalized Navarro-Frenk-White profile---with a free parameter for the inner density slope---we find that the break radius is $270^{+48}_{-76}$ kpc, and that the inner density falls with radius to the power $-0.38\pm0.04$ at 68 percent confidence. Such a shallow profile is in strong tension with our understanding of relaxed cold dark matter halos; dark matter only simulations predict the inner density should fall as $r^{-1}$. The tension can be alleviated if this cluster is in fact a merger; a two halo model can also reconstruct the data, with both clumps (density going as $r^{-0.8}$ and $r^{-1.0}$) much more consistent with predictions from dark matter only simulations. At the resolution of our Dark Energy Survey imaging, we are unable to choose between these two models, but we make predictions for forthcoming Hubble Space Telescope imaging that will decisively distinguish between them., Comment: 13 Pages. Accepted for publication in ApJ

Published
2017
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7. Low-latency gravitational wave alert products and their performance at the time of the fourth LIGO-Virgo-KAGRA observing run

Author

Chaudhary, Sushant Sharma, primary, Toivonen, Andrew, additional, Waratkar, Gaurav, additional, Mo, Geoffrey, additional, Chatterjee, Deep, additional, Antier, Sarah, additional, Brockill, Patrick, additional, Coughlin, Michael W., additional, Essick, Reed, additional, Ghosh, Shaon, additional, Morisaki, Soichiro, additional, Baral, Pratyusava, additional, Baylor, Amanda, additional, Adhikari, Naresh, additional, Brady, Patrick, additional, Cabourn Davies, Gareth, additional, Dal Canton, Tito, additional, Cavaglia, Marco, additional, Creighton, Jolien, additional, Choudhary, Sunil, additional, Chu, Yu-Kuang, additional, Clearwater, Patrick, additional, Davis, Luke, additional, Dent, Thomas, additional, Drago, Marco, additional, Ewing, Becca, additional, Godwin, Patrick, additional, Guo, Weichangfeng, additional, Hanna, Chad, additional, Huxford, Rachael, additional, Harry, Ian, additional, Katsavounidis, Erik, additional, Kovalam, Manoj, additional, Li, Alvin K.Y., additional, Magee, Ryan, additional, Marx, Ethan, additional, Meacher, Duncan, additional, Messick, Cody, additional, Morice-Atkinson, Xan, additional, Pace, Alexander, additional, De Pietri, Roberto, additional, Piotrzkowski, Brandon, additional, Roy, Soumen, additional, Sachdev, Surabhi, additional, Singer, Leo P., additional, Singh, Divya, additional, Szczepanczyk, Marek, additional, Tang, Daniel, additional, Trevor, Max, additional, Tsukada, Leo, additional, Villa-Ortega, Verónica, additional, Wen, Linqing, additional, and Wysocki, Daniel, additional

Published
2024
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8. Core or Cusps: The Central Dark Matter Profile of a Strong Lensing Cluster with a Bright Central Image at Redshift 1

Author

Collett, Thomas E, Buckley-Geer, Elizabeth, Lin, Huan, Bacon, David, Nichol, Robert C, Nord, Brian, Morice-Atkinson, Xan, Amara, Adam, Birrer, Simon, Kuropatkin, Nikolay, More, Anupreeta, Papovich, Casey, Romer, Kathy K, Tessore, Nicolas, Abbott, Tim MC, Allam, Sahar, Annis, James, Benoit-Lévy, Aurlien, Brooks, David, Burke, David L, Kind, Matias Carrasco, Castander, Francisco Javier J, D’Andrea, Chris B, da Costa, Luiz N, Desai, Shantanu, Diehl, H Thomas, Doel, Peter, Eifler, Tim F, Flaugher, Brenna, Frieman, Josh, Gerdes, David W, Goldstein, Daniel A, Gruen, Daniel, Gschwend, Julia, Gutierrez, Gaston, James, David J, Kuehn, Kyler, Kuhlmann, Steve, Lahav, Ofer, Li, Ting S, Lima, Marcos, Maia, Marcio AG, March, Marisa, Marshall, Jennifer L, Martini, Paul, Melchior, Peter, Miquel, Ramon, Plazas, Andrs A, Rykoff, Eli S, Sanchez, Eusebio, Scarpine, Vic, Schindler, Rafe, Schubnell, Michael, Sevilla-Noarbe, Ignacio, Smith, Mathew, Sobreira, Flavia, Suchyta, Eric, Swanson, Molly EC, Tarle, Gregory, Tucker, Douglas L, and Walker, Alistair R

Subjects
Nuclear and Plasma Physics, Physical Sciences, dark matter, galaxies: clusters: individual, galaxies: halos, gravitational lensing: strong, Astronomical and Space Sciences, Atomic, Molecular, Nuclear, Particle and Plasma Physics, Physical Chemistry (incl. Structural), Astronomy & Astrophysics, Astronomical sciences, Particle and high energy physics, Space sciences
Abstract

We report on SPT-CLJ2011-5228, a giant system of arcs created by a cluster at z = 1.06. The arc system is notable for the presence of a bright central image. The source is a Lyman break galaxy at z s = 2.39 and the mass enclosed within the Einstein ring of radius 14 arcsec is . We perform a full reconstruction of the light profile of the lensed images to precisely infer the parameters of the mass distribution. The brightness of the central image demands that the central total density profile of the lens be shallow. By fitting the dark matter as a generalized Navarro-Frenk-White profile - with a free parameter for the inner density slope - we find that the break radius is kpc, and that the inner density falls with radius to the power -0.38 ±0.04 at 68% confidence. Such a shallow profile is in strong tension with our understanding of relaxed cold dark matter halos; dark matter-only simulations predict that the inner density should fall as . The tension can be alleviated if this cluster is in fact a merger; a two-halo model can also reconstruct the data, with both clumps (density varying as and ) much more consistent with predictions from dark matter-only simulations. At the resolution of our Dark Energy Survey imaging, we are unable to choose between these two models, but we make predictions for forthcoming Hubble Space Telescope imaging that will decisively distinguish between them.

Published
2017

9. The Eleventh and Twelfth Data Releases of the Sloan Digital Sky Survey: Final Data from SDSS-III

Author

Alam, Shadab, Albareti, Franco D., Prieto, Carlos Allende, Anders, F., Anderson, Scott F., Andrews, Brett H., Armengaud, Eric, Aubourg, Éric, Bailey, Stephen, Bautista, Julian E., Beaton, Rachael L., Beers, Timothy C., Bender, Chad F., Berlind, Andreas A., Beutler, Florian, Bhardwaj, Vaishali, Bird, Jonathan C., Bizyaev, Dmitry, Blake, Cullen H., Blanton, Michael R., Blomqvist, Michael, Bochanski, John J., Bolton, Adam S., Bovy, Jo, Bradley, A. Shelden, Brandt, W. N., Brauer, D. E., Brinkmann, J., Brown, Peter J., Brownstein, Joel R., Burden, Angela, Burtin, Etienne, Busca, Nicolás G., Cai, Zheng, Capozzi, Diego, Rosell, Aurelio Carnero, Carrera, Ricardo, Chen, Yen-Chi, Chiappini, Cristina, Chojnowski, S. Drew, Chuang, Chia-Hsun, Clerc, Nicolas, Comparat, Johan, Covey, Kevin, Croft, Rupert A. C., Cuesta, Antonio J., Cunha, Katia, da Costa, Luiz N., Da Rio, Nicola, Davenport, James R. A., Dawson, Kyle S., De Lee, Nathan, Delubac, Timothée, Deshpande, Rohit, Dutra-Ferreira, Letícia, Dwelly, Tom, Ealet, Anne, Ebelke, Garrett L., Edmondson, Edward M., Eisenstein, Daniel J., Escoffier, Stephanie, Esposito, Massimiliano, Fan, Xiaohui, Fernández-Alvar, Emma, Feuillet, Diane, Ak, Nurten Filiz, Finley, Hayley, Finoguenov, Alexis, Flaherty, Kevin, Fleming, Scott W., Font-Ribera, Andreu, Foster, Jonathan, Frinchaboy, Peter M., Galbraith-Frew, J. G., García-Hernández, D. A., Pérez, Ana E. García, Gaulme, Patrick, Ge, Jian, Génova-Santos, R., Ghezzi, Luan, Gillespie, Bruce A., Girardi, Léo, Goddard, Daniel, Gontcho, Satya Gontcho A, Hernández, Jonay I. González, Grebel, Eva K., Grieb, Jan Niklas, Grieves, Nolan, Gunn, James E., Guo, Hong, Harding, Paul, Hasselquist, Sten, Hawley, Suzanne L., Hayden, Michael, Hearty, Fred R., Ho, Shirley, Hogg, David W., Holley-Bockelmann, Kelly, Holtzman, Jon A., Honscheid, Klaus, Huehnerhoff, Joseph, Jiang, Linhua, Johnson, Jennifer A., Kinemuchi, Karen, Kirkby, David, Kitaura, Francisco, Klaene, Mark A., Kneib, Jean-Paul, Koenig, Xavier P., Lam, Charles R., Lan, Ting-Wen, Lang, Dustin, Laurent, Pierre, Goff, Jean-Marc Le, Leauthaud, Alexie, Lee, Khee-Gan, Lee, Young Sun, Licquia, Timothy C., Liu, Jian, Long, Daniel C., López-Corredoira, Martín, Lorenzo-Oliveira, Diego, Lucatello, Sara, Lundgren, Britt, Lupton, Robert H., Mack III, Claude E., Mahadevan, Suvrath, Maia, Marcio A. G., Majewski, Steven R., Malanushenko, Elena, Malanushenko, Viktor, Manchado, A., Manera, Marc, Mao, Qingqing, Maraston, Claudia, Marchwinski, Robert C., Margala, Daniel, Martell, Sarah L., Martig, Marie, Masters, Karen L., McBride, Cameron K., McGehee, Peregrine M., McGreer, Ian D., McMahon, Richard G., Ménard, Brice, Menzel, Marie-Luise, Merloni, Andrea, Mészáros, Szabolcs, Miller, Adam A., Miralda-Escudé, Jordi, Miyatake, Hironao, Montero-Dorta, Antonio D., More, Surhud, Morice-Atkinson, Xan, Morrison, Heather L., Muna, Demitri, Myers, Adam D., Newman, Jeffrey A., Neyrinck, Mark, Nguyen, Duy Cuong, Nichol, Robert C., Nidever, David L., Noterdaeme, Pasquier, Nuza, Sebastián E., O'Connell, Julia E., O'Connell, Robert W., O'Connell, Ross, Ogando, Ricardo L. C., Olmstead, Matthew D., Oravetz, Audrey E., Oravetz, Daniel J., Osumi, Keisuke, Owen, Russell, Padgett, Deborah L., Padmanabhan, Nikhil, Paegert, Martin, Palanque-Delabrouille, Nathalie, Pan, Kaike, Parejko, John K., Park, Changbom, Pâris, Isabelle, Pattarakijwanich, Petchara, Pellejero-Ibanez, M., Pepper, Joshua, Percival, Will J., Pérez-Fournon, Ismael, Pérez-Ràfols, Ignasi, Petitjean, Patrick, Pieri, Matthew M., Pinsonneault, Marc H., de Mello, Gustavo F. Porto, Prada, Francisco, Prakash, Abhishek, Price-Whelan, Adrian M., Raddick, M. Jordan, Rahman, Mubdi, Reid, Beth A., Rich, James, Rix, Hans-Walter, Robin, Annie C., Rockosi, Constance M., Rodrigues, Thaíse S., Rodríguez-Rottes, Sergio, Roe, Natalie A., Ross, Ashley J., Ross, Nicholas P., Rossi, Graziano, Ruan, John J., Rubiño-Martín, J. A., Rykoff, Eli S., Salazar-Albornoz, Salvador, Salvato, Mara, Samushia, Lado, Sánchez, Ariel G., Santiago, Basílio, Sayres, Conor, Schiavon, Ricardo P., Schlegel, David J., Schmidt, Sarah J., Schneider, Donald P., Schultheis, Mathias, Schwope, Axel D., Scóccola, C. G., Sellgren, Kris, Seo, Hee-Jong, Shane, Neville, Shen, Yue, Shetrone, Matthew, Shu, Yiping, Sivarani, Thirupathi, Skrutskie, M. F., Slosar, Anže, Smith, Verne V., Sobreira, Flávia, Stassun, Keivan G., Steinmetz, Matthias, Strauss, Michael A., Streblyanska, Alina, Swanson, Molly E. C., Tan, Jonathan C., Tayar, Jamie, Terrien, Ryan C., Thakar, Aniruddha R., Thomas, Daniel, Thompson, Benjamin A., Tinker, Jeremy L., Tojeiro, Rita, Troup, Nicholas W., Vargas-Magaña, Mariana, Vazquez, Jose A., Verde, Licia, Viel, Matteo, Vogt, Nicole P., Wake, David A., Wang, Ji, Weaver, Benjamin A., Weinberg, David H., Weiner, Benjamin J., White, Martin, Wilson, John C., Wisniewski, John P., Wood-Vasey, W. M., Yèche, Christophe, York, Donald G., Zakamska, Nadia L., Zamora, O., Zasowski, Gail, Zehavi, Idit, Zhao, Gong-Bo, Zheng, Zheng, Zhou, Xu, Zhou, Zhimin, Zhu, Guangtun, and Zou, Hu

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Solar and Stellar Astrophysics
Abstract

The third generation of the Sloan Digital Sky Survey (SDSS-III) took data from 2008 to 2014 using the original SDSS wide-field imager, the original and an upgraded multi-object fiber-fed optical spectrograph, a new near-infrared high-resolution spectrograph, and a novel optical interferometer. All the data from SDSS-III are now made public. In particular, this paper describes Data Release 11 (DR11) including all data acquired through 2013 July, and Data Release 12 (DR12) adding data acquired through 2014 July (including all data included in previous data releases), marking the end of SDSS-III observing. Relative to our previous public release (DR10), DR12 adds one million new spectra of galaxies and quasars from the Baryon Oscillation Spectroscopic Survey (BOSS) over an additional 3000 sq. deg of sky, more than triples the number of H-band spectra of stars as part of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE), and includes repeated accurate radial velocity measurements of 5500 stars from the Multi-Object APO Radial Velocity Exoplanet Large-area Survey (MARVELS). The APOGEE outputs now include measured abundances of 15 different elements for each star. In total, SDSS-III added 2350 sq. deg of ugriz imaging; 155,520 spectra of 138,099 stars as part of the Sloan Exploration of Galactic Understanding and Evolution 2 (SEGUE-2) survey; 2,497,484 BOSS spectra of 1,372,737 galaxies, 294,512 quasars, and 247,216 stars over 9376 sq. deg; 618,080 APOGEE spectra of 156,593 stars; and 197,040 MARVELS spectra of 5,513 stars. Since its first light in 1998, SDSS has imaged over 1/3 of the Celestial sphere in five bands and obtained over five million astronomical spectra., Comment: DR12 data are available at http://www.sdss3.org/dr12. 30 pages. 11 figures. Accepted to ApJS

Published
2015
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10. Low-latency gravitational wave alert products and their performance in anticipation of the fourth LIGO-Virgo-KAGRA observing run

Author

Chaudhary, Sushant Sharma, Toivonen, Andrew, Waratkar, Gaurav, Mo, Geoffrey, Chatterjee, Deep, Antier, Sarah, Brockill, Patrick, Coughlin, Michael W., Essick, Reed, Ghosh, Shaon, Morisaki, Soichiro, Baral, Pratyusava, Baylor, Amanda, Adhikari, Naresh, Brady, Patrick, Davies, Gareth Cabourn, Canton, Tito Dal, Cavaglià, Marco, Creighton, Jolien, Choudhary, Sunil, Chu, Yu-Kuang, Clearwater, Patrick, Davis, Luke, Dent, Thomas, Drago, Marco, Ewing, Becca, Godwin, Patrick, Guo, Weichangfeng, Hanna, Chad, Huxford, Rachel, Harry, Ian, Katsavounidis, Erik, Kovalam, Manoj, Li, Alvin K. Y., Magee, Ryan, Marx, Ethan, Meacher, Duncan, Messick, Cody, Morice-Atkinson, Xan, Pace, Alexander, De Pietri, Roberto, Piotrzkowski, Brandon, Roy, Soumen, Sachdev, Surabhi, Singer, Leo P., Singh, Divya, Szczepanczyk, Marek, Tang, Daniel, Trevor, Max, Tsukada, Leo, Villa-Ortega, Verónica, Wen, Linqing, Wysocki, Daniel, Chaudhary, Sushant Sharma, Toivonen, Andrew, Waratkar, Gaurav, Mo, Geoffrey, Chatterjee, Deep, Antier, Sarah, Brockill, Patrick, Coughlin, Michael W., Essick, Reed, Ghosh, Shaon, Morisaki, Soichiro, Baral, Pratyusava, Baylor, Amanda, Adhikari, Naresh, Brady, Patrick, Davies, Gareth Cabourn, Canton, Tito Dal, Cavaglià, Marco, Creighton, Jolien, Choudhary, Sunil, Chu, Yu-Kuang, Clearwater, Patrick, Davis, Luke, Dent, Thomas, Drago, Marco, Ewing, Becca, Godwin, Patrick, Guo, Weichangfeng, Hanna, Chad, Huxford, Rachel, Harry, Ian, Katsavounidis, Erik, Kovalam, Manoj, Li, Alvin K. Y., Magee, Ryan, Marx, Ethan, Meacher, Duncan, Messick, Cody, Morice-Atkinson, Xan, Pace, Alexander, De Pietri, Roberto, Piotrzkowski, Brandon, Roy, Soumen, Sachdev, Surabhi, Singer, Leo P., Singh, Divya, Szczepanczyk, Marek, Tang, Daniel, Trevor, Max, Tsukada, Leo, Villa-Ortega, Verónica, Wen, Linqing, and Wysocki, Daniel

Abstract

Multi-messenger searches for binary neutron star (BNS) and neutron star-black hole (NSBH) mergers are currently one of the most exciting areas of astronomy. The search for joint electromagnetic and neutrino counterparts to gravitational wave (GW)s has resumed with Advanced LIGO (aLIGO)'s, Advanced Virgo (AdVirgo)'s and KAGRA's fourth observing run (O4). To support this effort, public semi-automated data products are sent in near real-time and include localization and source properties to guide complementary observations. Subsequent refinements, as and when available, are also relayed as updates. In preparation for O4, we have conducted a study using a simulated population of compact binaries and a Mock Data Challenge (MDC) in the form of a real-time replay to optimize and profile the software infrastructure and scientific deliverables. End-to-end performance was tested, including data ingestion, running online search pipelines, performing annotations, and issuing alerts to the astrophysics community. In this paper, we present an overview of the low-latency infrastructure as well as an overview of the performance of the data products to be released during O4 based on a MDC. We report on expected median latencies for the preliminary alert of full bandwidth searches (29.5 s) and for the creation of early warning triggers (-3.1 s), and show consistency and accuracy of released data products using the MDC. This paper provides a performance overview for LVK low-latency alert structure and data products using the MDC in anticipation of O4.

Published
2023

11. Candidate Massive Galaxies at z~4 in the Dark Energy Survey

Author

Guarnieri, Pierandrea, Maraston, Claudia, Thomas, Daniel, Pforr, Janine, Gonzalez-Perez, Violeta, Etherington, James, Carlsen, Joakim, Morice-Atkinson, Xan, Conselice, Christopher J., Gschwend, Julia, Kind, Matias Carrasco, Abbott, Tim, Allam, Sahar, Brooks, David, Burke, David, Rosell, Aurelio Carnero, Carretero, Jorge, Cunha, Carlos, ďAndrea, Chris, Costa, Luiz da, Vincente, Juan De, DePoy, Darren, Diehl, H. Thomas, Doel, Peter, Frieman, Josh, Garcia-Bellido, Juan, Gruen, Daniel, Gutierrez, Gaston, Hanley, Dominic, Hollowood, Devon, Honscheid, Klaus, James, David, Jeltema, Tesla, Kuehn, Kyler, Lima, Marcos, Maia, Marcio A. G., Marshall, Jennifer, Martini, Paul, Melchior, Peter, Menanteau, Felipe, Miquel, Ramon, Malagon, Andres Plazas, Richardson, Samuel, Romer, Kathy, Sanchez, Eusebio, Scarpine, Vic, Schindler, Rafe, Sevilla, Ignacio, Smith, Mathew, Soares-Santos, Marcelle, Sobreira, Flavia, Suchyta, Eric, Tarle, Gregory, Walker, Alistair, Wester, William, Guarnieri, Pierandrea, Maraston, Claudia, Thomas, Daniel, Pforr, Janine, Gonzalez-Perez, Violeta, Etherington, James, Carlsen, Joakim, Morice-Atkinson, Xan, Conselice, Christopher J., Gschwend, Julia, Kind, Matias Carrasco, Abbott, Tim, Allam, Sahar, Brooks, David, Burke, David, Rosell, Aurelio Carnero, Carretero, Jorge, Cunha, Carlos, ďAndrea, Chris, Costa, Luiz da, Vincente, Juan De, DePoy, Darren, Diehl, H. Thomas, Doel, Peter, Frieman, Josh, Garcia-Bellido, Juan, Gruen, Daniel, Gutierrez, Gaston, Hanley, Dominic, Hollowood, Devon, Honscheid, Klaus, James, David, Jeltema, Tesla, Kuehn, Kyler, Lima, Marcos, Maia, Marcio A. G., Marshall, Jennifer, Martini, Paul, Melchior, Peter, Menanteau, Felipe, Miquel, Ramon, Malagon, Andres Plazas, Richardson, Samuel, Romer, Kathy, Sanchez, Eusebio, Scarpine, Vic, Schindler, Rafe, Sevilla, Ignacio, Smith, Mathew, Soares-Santos, Marcelle, Sobreira, Flavia, Suchyta, Eric, Tarle, Gregory, Walker, Alistair, and Wester, William

Abstract

Using stellar population models, we predicted that the Dark Energy Survey (DES) - due to its special combination of area (5000 deg. sq.) and depth ($i = 24.3$) - would be in the position to detect massive ($\gtrsim 10^{11}$ M$_{\odot}$) galaxies at $z \sim 4$. We confront those theoretical calculations with the first $\sim 150$ deg. sq. of DES data reaching nominal depth. From a catalogue containing $\sim 5$ million sources, $\sim26000$ were found to have observed-frame $g-r$ vs $r-i$ colours within the locus predicted for $z \sim 4$ massive galaxies. We further removed contamination by stars and artefacts, obtaining 606 galaxies lining up by the model selection box. We obtained their photometric redshifts and physical properties by fitting model templates spanning a wide range of star formation histories, reddening and redshift. Key to constrain the models is the addition, to the optical DES bands $g$, $r$, $i$, $z$, and $Y$, of near-IR $J$, $H$, $K_{s}$ data from the Vista Hemisphere Survey. We further applied several quality cuts to the fitting results, including goodness of fit and a unimodal redshift probability distribution. We finally select 233 candidates whose photometric redshift probability distribution function peaks around $z\sim4$, have high stellar masses ($\log($M$^{*}$/M$_{\odot})\sim 11.7$ for a Salpeter IMF) and ages around 0.1 Gyr, i.e. formation redshift around 5. These properties match those of the progenitors of the most massive galaxies in the local universe. This is an ideal sample for spectroscopic follow-up to select the fraction of galaxies which is truly at high redshift. These initial results and those at the survey completion, which we shall push to higher redshifts, will set unprecedented constraints on galaxy formation, evolution, and the re-ionisation epoch.

Published
2019

12. Candidate massive galaxies atz ∼ 4 in the Dark Energy Survey

Author

Guarnieri, Pierandrea, primary, Maraston, Claudia, additional, Thomas, Daniel, additional, Pforr, Janine, additional, Gonzalez-Perez, Violeta, additional, Etherington, James, additional, Carlsen, Joakim, additional, Morice-Atkinson, Xan, additional, Conselice, Christopher J, additional, Gschwend, Julia, additional, Carrasco Kind, Matias, additional, Abbott, Tim, additional, Allam, Sahar, additional, Brooks, David, additional, Burke, David, additional, Carnero Rosell, Aurelio, additional, Carretero, Jorge, additional, Cunha, Carlos, additional, D’Andrea, Chris, additional, da Costa, Luiz, additional, De Vincente, Juan, additional, DePoy, Darren, additional, Thomas Diehl, H, additional, Doel, Peter, additional, Frieman, Josh, additional, Garcia-Bellido, Juan, additional, Gruen, Daniel, additional, Gutierrez, Gaston, additional, Hanley, Dominic, additional, Hollowood, Devon, additional, Honscheid, Klaus, additional, James, David, additional, Jeltema, Tesla, additional, Kuehn, Kyler, additional, Lima, Marcos, additional, Maia, Marcio A G, additional, Marshall, Jennifer, additional, Martini, Paul, additional, Melchior, Peter, additional, Menanteau, Felipe, additional, Miquel, Ramon, additional, Plazas Malagon, Andres, additional, Richardson, Samuel, additional, Romer, Kathy, additional, Sanchez, Eusebio, additional, Scarpine, Vic, additional, Schindler, Rafe, additional, Sevilla, Ignacio, additional, Smith, Mathew, additional, Soares-Santos, Marcelle, additional, Sobreira, Flavia, additional, Suchyta, Eric, additional, Tarle, Gregory, additional, Walker, Alistair, additional, and Wester, William, additional

Published
2018
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13. Core or cusps:the central dark matter profile of a redshift one strong lensing cluster with a bright central image at Redshift 1

Author

Collett, Thomas E., Buckley-Geer, Elizabeth J., Lin, Huan, Bacon, David, Nichol, Robert C., Nord, Brian, Morice-Atkinson, Xan, Amara, Adam, Birrer, Simon, Kuropatkin, Nikolay, More, Anupreeta, Papovich, Casey, Romer, A. Kathy, Tessore, Nicolas, Abbott, Tim M. C., Allam, Sahar S., Annis, James, Benoit-Lévy, Aurélien, Brooks, David, Burke, David L., Kind, Matias Carrasco, Castander, Francisco Javier, D'Andrea, Chris B., Costa, Luiz A. N. da, Desai, Shantanu, Diehl, H. Thomas, Doel, Peter, Eifler, Tim F., Flaugher, Brenna, Frieman, Josh, Gerdes, David W., Goldstein, Daniel A., Gruen, Daniel, Gschwend, Julia, Gutierrez, Gaston R., James, David J., Kuehn, Kyler, Kuhlmann, Steve, Lahav, Ofer, Li, Ting S., Lima, Marcos, Maia, Marcio Antonio Geimba, March, Marisa C., Marshall, Jennifer L., Martini, Paul, Melchior, Peter, Miquel, Ramon, Plazas, Andrés A., Rykoff, Eli S., Sanchez, Eusebio, Scarpine, Vic, Schindler, Rafe, Schubnell, Michael, Sevilla-Noarbe, Ignacio, Smith, Mathew, Sobreira, Flavia, Suchyta, Eric, Swanson, Molly E. C., Tarle, Gregory, Tucker, Douglas L., and Walker, Alistair R.

Subjects
Cosmology and Gravitation, astro-ph.GA, astro-ph.CO, RCUK, Astrophysics::Cosmology and Extragalactic Astrophysics, Astrophysics::Galaxy Astrophysics, STFC
Abstract

We report on SPT-CLJ2011-5228, a giant system of arcs created by a cluster at z = 1.06. The arc system is notable for the presence of a bright central image. The source is a Lyman break galaxy at z s = 2.39 and the mass enclosed within the Einstein ring of radius 14 arcsec is ∼ 1014.2 MΘ. We perform a full reconstruction of the light profile of the lensed images to precisely infer the parameters of the mass distribution. The brightness of the central image demands that the central total density profile of the lens be shallow. By fitting the dark matter as a generalized Navarro–Frenk–White profile—with a free parameter for the inner density slope—we find that the break radius is 270∨{-76}^{+48} kpc, and that the inner density falls with radius to the power −0.38 ± 0.04 at 68% confidence. Such a shallow profile is in strong tension with our understanding of relaxed cold dark matter halos; dark matter-only simulations predict that the inner density should fall as r-1. The tension can be alleviated if this cluster is in fact a merger; a two-halo model can also reconstruct the data, with both clumps (density varying as r-0.8 and r-1.0) much more consistent with predictions from dark matter-only simulations. At the resolution of our Dark Energy Survey imaging, we are unable to choose between these two models, but we make predictions for forthcoming Hubble Space Telescope imaging that will decisively distinguish between them.

Published
2017

15. Candidate massive galaxies at z  ∼ 4 in the Dark Energy Survey.

Author

Guarnieri, Pierandrea, Maraston, Claudia, Thomas, Daniel, Pforr, Janine, Gonzalez-Perez, Violeta, Etherington, James, Carlsen, Joakim, Morice-Atkinson, Xan, Conselice, Christopher J, Gschwend, Julia, Carrasco Kind, Matias, Abbott, Tim, Allam, Sahar, Brooks, David, Burke, David, Carnero Rosell, Aurelio, Carretero, Jorge, Cunha, Carlos, D'Andrea, Chris, and da Costa, Luiz

Subjects
DARK energy, STELLAR populations, GALAXIES, REDSHIFT, ASTRONOMICAL photometry
Abstract

Using stellar population models, we predicted that the Dark Energy Survey (DES) – due to its special combination of area (5000 deg2) and depth (i  = 24.3) – would be in the position to detect massive (≳1011 M⊙) galaxies at |$z$|  ∼ 4. We confront those theoretical calculations with the first ∼150 deg2 of DES data reaching nominal depth. From a catalogue containing ∼5 million sources, ∼26 000 were found to have observed-frame g − r versus  r − i colours within the locus predicted for |$z$|  ∼ 4 massive galaxies. We further removed contamination by stars and artefacts, obtaining 606 galaxies lining up by the model selection box. We obtained their photometric redshifts and physical properties by fitting model templates spanning a wide range of star formation histories, reddening and redshift. Key to constrain the models is the addition, to the optical DES bands g, r, i, |$z$|⁠, and Y, of near-IR J, H, Ks data from the Vista Hemisphere Survey. We further applied several quality cuts to the fitting results, including goodness of fit and a unimodal redshift probability distribution. We finally select 233 candidates whose photometric redshift probability distribution function peaks around |$z$|  ∼ 4, have high stellar masses [log (M */M⊙) ∼ 11.7 for a Salpeter IMF] and ages around 0.1 Gyr, i.e. formation redshift around 5. These properties match those of the progenitors of the most massive galaxies in the local Universe. This is an ideal sample for spectroscopic follow-up to select the fraction of galaxies which are truly at high redshift. These initial results and those at the survey completion, which we shall push to higher redshifts, will set unprecedented constraints on galaxy formation, evolution, and the re-ionization epoch. [ABSTRACT FROM AUTHOR]

Published
2019
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16. THE ELEVENTH AND TWELFTH DATA RELEASES OF THE SLOAN DIGITAL SKY SURVEY: FINAL DATA FROM SDSS-III

Author

Alam, Shadab, primary, Albareti, Franco D., additional, Prieto, Carlos Allende, additional, Anders, F., additional, Anderson, Scott F., additional, Anderton, Timothy, additional, Andrews, Brett H., additional, Armengaud, Eric, additional, Aubourg, Éric, additional, Bailey, Stephen, additional, Basu, Sarbani, additional, Bautista, Julian E., additional, Beaton, Rachael L., additional, Beers, Timothy C., additional, Bender, Chad F., additional, Berlind, Andreas A., additional, Beutler, Florian, additional, Bhardwaj, Vaishali, additional, Bird, Jonathan C., additional, Bizyaev, Dmitry, additional, Blake, Cullen H., additional, Blanton, Michael R., additional, Blomqvist, Michael, additional, Bochanski, John J., additional, Bolton, Adam S., additional, Bovy, Jo, additional, Bradley, A. Shelden, additional, Brandt, W. N., additional, Brauer, D. E., additional, Brinkmann, J., additional, Brown, Peter J., additional, Brownstein, Joel R., additional, Burden, Angela, additional, Burtin, Etienne, additional, Busca, Nicolás G., additional, Cai, Zheng, additional, Capozzi, Diego, additional, Rosell, Aurelio Carnero, additional, Carr, Michael A., additional, Carrera, Ricardo, additional, Chambers, K. C., additional, Chaplin, William James, additional, Chen, Yen-Chi, additional, Chiappini, Cristina, additional, Chojnowski, S. Drew, additional, Chuang, Chia-Hsun, additional, Clerc, Nicolas, additional, Comparat, Johan, additional, Covey, Kevin, additional, Croft, Rupert A. C., additional, Cuesta, Antonio J., additional, Cunha, Katia, additional, Costa, Luiz N. da, additional, Rio, Nicola Da, additional, Davenport, James R. A., additional, Dawson, Kyle S., additional, Lee, Nathan De, additional, Delubac, Timothée, additional, Deshpande, Rohit, additional, Dhital, Saurav, additional, Dutra-Ferreira, Letícia, additional, Dwelly, Tom, additional, Ealet, Anne, additional, Ebelke, Garrett L., additional, Edmondson, Edward M., additional, Eisenstein, Daniel J., additional, Ellsworth, Tristan, additional, Elsworth, Yvonne, additional, Epstein, Courtney R., additional, Eracleous, Michael, additional, Escoffier, Stephanie, additional, Esposito, Massimiliano, additional, Evans, Michael L., additional, Fan, Xiaohui, additional, Fernández-Alvar, Emma, additional, Feuillet, Diane, additional, Ak, Nurten Filiz, additional, Finley, Hayley, additional, Finoguenov, Alexis, additional, Flaherty, Kevin, additional, Fleming, Scott W., additional, Font-Ribera, Andreu, additional, Foster, Jonathan, additional, Frinchaboy, Peter M., additional, Galbraith-Frew, J. G., additional, García, Rafael A., additional, García-Hernández, D. A., additional, Pérez, Ana E. García, additional, Gaulme, Patrick, additional, Ge, Jian, additional, Génova-Santos, R., additional, Georgakakis, A., additional, Ghezzi, Luan, additional, Gillespie, Bruce A., additional, Girardi, Léo, additional, Goddard, Daniel, additional, Gontcho, Satya Gontcho A, additional, Hernández, Jonay I. González, additional, Grebel, Eva K., additional, Green, Paul J., additional, Grieb, Jan Niklas, additional, Grieves, Nolan, additional, Gunn, James E., additional, Guo, Hong, additional, Harding, Paul, additional, Hasselquist, Sten, additional, Hawley, Suzanne L., additional, Hayden, Michael, additional, Hearty, Fred R., additional, Hekker, Saskia, additional, Ho, Shirley, additional, Hogg, David W., additional, Holley-Bockelmann, Kelly, additional, Holtzman, Jon A., additional, Honscheid, Klaus, additional, Huber, Daniel, additional, Huehnerhoff, Joseph, additional, Ivans, Inese I., additional, Jiang, Linhua, additional, Johnson, Jennifer A., additional, Kinemuchi, Karen, additional, Kirkby, David, additional, Kitaura, Francisco, additional, Klaene, Mark A., additional, Knapp, Gillian R., additional, Kneib, Jean-Paul, additional, Koenig, Xavier P., additional, Lam, Charles R., additional, Lan, Ting-Wen, additional, Lang, Dustin, additional, Laurent, Pierre, additional, Goff, Jean-Marc Le, additional, Leauthaud, Alexie, additional, Lee, Khee-Gan, additional, Lee, Young Sun, additional, Licquia, Timothy C., additional, Liu, Jian, additional, Long, Daniel C., additional, López-Corredoira, Martín, additional, Lorenzo-Oliveira, Diego, additional, Lucatello, Sara, additional, Lundgren, Britt, additional, Lupton, Robert H., additional, III, Claude E. Mack, additional, Mahadevan, Suvrath, additional, Maia, Marcio A. G., additional, Majewski, Steven R., additional, Malanushenko, Elena, additional, Malanushenko, Viktor, additional, Manchado, A., additional, Manera, Marc, additional, Mao, Qingqing, additional, Maraston, Claudia, additional, Marchwinski, Robert C., additional, Margala, Daniel, additional, Martell, Sarah L., additional, Martig, Marie, additional, Masters, Karen L., additional, Mathur, Savita, additional, McBride, Cameron K., additional, McGehee, Peregrine M., additional, McGreer, Ian D., additional, McMahon, Richard G., additional, Ménard, Brice, additional, Menzel, Marie-Luise, additional, Merloni, Andrea, additional, Mészáros, Szabolcs, additional, Miller, Adam A., additional, Miralda-Escudé, Jordi, additional, Miyatake, Hironao, additional, Montero-Dorta, Antonio D., additional, More, Surhud, additional, Morganson, Eric, additional, Morice-Atkinson, Xan, additional, Morrison, Heather L., additional, Mosser, Benôit, additional, Muna, Demitri, additional, Myers, Adam D., additional, Nandra, Kirpal, additional, Newman, Jeffrey A., additional, Neyrinck, Mark, additional, Nguyen, Duy Cuong, additional, Nichol, Robert C., additional, Nidever, David L., additional, Noterdaeme, Pasquier, additional, Nuza, Sebastián E., additional, O’Connell, Julia E., additional, O’Connell, Robert W., additional, O’Connell, Ross, additional, Ogando, Ricardo L. C., additional, Olmstead, Matthew D., additional, Oravetz, Audrey E., additional, Oravetz, Daniel J., additional, Osumi, Keisuke, additional, Owen, Russell, additional, Padgett, Deborah L., additional, Padmanabhan, Nikhil, additional, Paegert, Martin, additional, Palanque-Delabrouille, Nathalie, additional, Pan, Kaike, additional, Parejko, John K., additional, Pâris, Isabelle, additional, Park, Changbom, additional, Pattarakijwanich, Petchara, additional, Pellejero-Ibanez, M., additional, Pepper, Joshua, additional, Percival, Will J., additional, Pérez-Fournon, Ismael, additional, Pe´rez-Ra`fols, Ignasi, additional, Petitjean, Patrick, additional, Pieri, Matthew M., additional, Pinsonneault, Marc H., additional, Mello, Gustavo F. Porto de, additional, Prada, Francisco, additional, Prakash, Abhishek, additional, Price-Whelan, Adrian M., additional, Protopapas, Pavlos, additional, Raddick, M. Jordan, additional, Rahman, Mubdi, additional, Reid, Beth A., additional, Rich, James, additional, Rix, Hans-Walter, additional, Robin, Annie C., additional, Rockosi, Constance M., additional, Rodrigues, Thaíse S., additional, Rodríguez-Torres, Sergio, additional, Roe, Natalie A., additional, Ross, Ashley J., additional, Ross, Nicholas P., additional, Rossi, Graziano, additional, Ruan, John J., additional, Rubiño-Martín, J. A., additional, Rykoff, Eli S., additional, Salazar-Albornoz, Salvador, additional, Salvato, Mara, additional, Samushia, Lado, additional, Sánchez, Ariel G., additional, Santiago, Basílio, additional, Sayres, Conor, additional, Schiavon, Ricardo P., additional, Schlegel, David J., additional, Schmidt, Sarah J., additional, Schneider, Donald P., additional, Schultheis, Mathias, additional, Schwope, Axel D., additional, Scóccola, C. G., additional, Scott, Caroline, additional, Sellgren, Kris, additional, Seo, Hee-Jong, additional, Serenelli, Aldo, additional, Shane, Neville, additional, Shen, Yue, additional, Shetrone, Matthew, additional, Shu, Yiping, additional, Aguirre, V. Silva, additional, Sivarani, Thirupathi, additional, Skrutskie, M. F., additional, Slosar, Anže, additional, Smith, Verne V., additional, Sobreira, Flávia, additional, Souto, Diogo, additional, Stassun, Keivan G., additional, Steinmetz, Matthias, additional, Stello, Dennis, additional, Strauss, Michael A., additional, Streblyanska, Alina, additional, Suzuki, Nao, additional, Swanson, Molly E. C., additional, Tan, Jonathan C., additional, Tayar, Jamie, additional, Terrien, Ryan C., additional, Thakar, Aniruddha R., additional, Thomas, Daniel, additional, Thomas, Neil, additional, Thompson, Benjamin A., additional, Tinker, Jeremy L., additional, Tojeiro, Rita, additional, Troup, Nicholas W., additional, Vargas-Magaña, Mariana, additional, Vazquez, Jose A., additional, Verde, Licia, additional, Viel, Matteo, additional, Vogt, Nicole P., additional, Wake, David A., additional, Wang, Ji, additional, Weaver, Benjamin A., additional, Weinberg, David H., additional, Weiner, Benjamin J., additional, White, Martin, additional, Wilson, John C., additional, Wisniewski, John P., additional, Wood-Vasey, W. M., additional, Ye`che, Christophe, additional, York, Donald G., additional, Zakamska, Nadia L., additional, Zamora, O., additional, Zasowski, Gail, additional, Zehavi, Idit, additional, Zhao, Gong-Bo, additional, Zheng, Zheng, additional, Zhou (周旭), Xu, additional, Zhou (周志民), Zhimin, additional, Zou (邹虎), Hu, additional, and Zhu, Guangtun, additional

Published
2015
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17. Core or cusps: The central dark matter profile of a redshift one strong lensing cluster with a bright central image

Author

Collett, Thomas E., Buckley-Geer, Elizabeth, Lin, Huan, Bacon, David, Nichol, Robert C., Nord, Brian, Morice-Atkinson, Xan, Amara, Adam, Birrer, Simon, Kuropatkin, Nikolay, More, Anupreeta, Papovich, Casey, Romer, Kathy K., Tessore, Nicolas, Abbott, Tim M. C., Allam, Sahar, Annis, James, Benoit-Lévy, Aurélien, Brooks, David, Burke, David L., Matias Carrasco Kind, Castander, Francisco Javier J., D Andrea, Chris B., Da Costa, Luiz N., Desai, Shantanu, Diehl, H. Thomas, Doel, Peter, Eifler, Tim F., Flaugher, Brenna, Frieman, Josh, Gerdes, David W., Goldstein, Daniel A., Gruen, Daniel, Gschwend, Julia, Gutierrez, Gaston, James, David J., Kuehn, Kyler, Kuhlmann, Steve, Lahav, Ofer, Li, Ting S., Lima, Marcos, Maia, Marcio A. G., March, Marisa, Marshall, Jennifer L., Martini, Paul, Melchior, Peter, Miquel, Ramon, Plazas, Andrés A., Rykoff, Eli S., Sanchez, Eusebio, Scarpine, Vic, Schindler, Rafe, Schubnell, Michael, Sevilla-Noarbe, Ignacio, Smith, Mathew, Sobreira, Flavia, Suchyta, Eric, Swanson, Molly E. C., Tarle, Gregory, Tucker, Douglas L., and Walker, Alistair R.

Subjects
Cosmology and Nongalactic Astrophysics (astro-ph.CO), Astrophysics of Galaxies (astro-ph.GA), FOS: Physical sciences, Astrophysics::Cosmology and Extragalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics::Galaxy Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

We report on SPT-CLJ2011-5228, a giant system of arcs created by a cluster at $z=1.06$. The arc system is notable for the presence of a bright central image. The source is a Lyman Break galaxy at $z_s=2.39$ and the mass enclosed within the 14 arc second radius Einstein ring is $10^{14.2}$ solar masses. We perform a full light profile reconstruction of the lensed images to precisely infer the parameters of the mass distribution. The brightness of the central image demands that the central total density profile of the lens be shallow. By fitting the dark matter as a generalized Navarro-Frenk-White profile---with a free parameter for the inner density slope---we find that the break radius is $270^{+48}_{-76}$ kpc, and that the inner density falls with radius to the power $-0.38\pm0.04$ at 68 percent confidence. Such a shallow profile is in strong tension with our understanding of relaxed cold dark matter halos; dark matter only simulations predict the inner density should fall as $r^{-1}$. The tension can be alleviated if this cluster is in fact a merger; a two halo model can also reconstruct the data, with both clumps (density going as $r^{-0.8}$ and $r^{-1.0}$) much more consistent with predictions from dark matter only simulations. At the resolution of our Dark Energy Survey imaging, we are unable to choose between these two models, but we make predictions for forthcoming Hubble Space Telescope imaging that will decisively distinguish between them., 13 Pages. Accepted for publication in ApJ

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