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31 results on '"Biswas, Rahul"'

1. Causal Functional Connectivity in Alzheimer's Disease Computed from Time Series fMRI data

Author

Biswas, Rahul and Sripada, SuryaNarayana

Subjects
FOS: Computer and information sciences, FOS: Biological sciences, Quantitative Biology - Neurons and Cognition, Neurons and Cognition (q-bio.NC), Applications (stat.AP), Quantitative Biology - Quantitative Methods, Statistics - Applications, Quantitative Methods (q-bio.QM)
Abstract

Functional Connectivity between brain regions is known to be altered in Alzheimer's disease, and promises to be a biomarker for early diagnosis of the disease. While several approaches for functional connectivity obtain an un-directed network representing stochastic associations (correlations) between brain regions, association does not necessarily imply causation. In contrast, Causal Functional Connectivity is more informative, providing a directed network representing causal relationships between brain regions. In this paper, we obtained the causal functional connectome for the whole brain from recordings of resting-state functional magnetic resonance imaging (rs-fMRI) for subjects from three clinical groups: cognitively normal, mild cognitive impairment, and Alzheimer's disease. We applied the recently developed Time-aware PC (TPC) algorithm to infer the causal functional connectome for the whole brain. TPC supports model-free estimation of whole brain causal functional connectivity based on directed graphical modeling in a time series setting. We then identified the causal brain connections between brain regions which have significantly different strengths between pairs of subject groups, and over the three subject groups. We used the significant causal brain connections thus obtained to compile a comprehensive list of brain regions impacted by Alzheimer's disease according to the current data set. The obtained brain regions are in agreement with existing literature published by researchers from clinical/medical institutions thus validating the approach. We then discuss the soundness and completeness of the results and the potential for using causal functional connectivity obtained using this methodology as a basis for the prognosis and diagnosis of Alzheimer's disease.

Published
2023

2. Tensor Recovery in High-Dimensional Ising Models

Author

Liu, Tianyu, Mukherjee, Somabha, and Biswas, Rahul

Subjects
Methodology (stat.ME), FOS: Computer and information sciences, FOS: Mathematics, Mathematics - Statistics Theory, Statistics Theory (math.ST), Statistics - Methodology
Abstract

The $k$-tensor Ising model is an exponential family on a $p$-dimensional binary hypercube for modeling dependent binary data, where the sufficient statistic consists of all $k$-fold products of the observations, and the parameter is an unknown $k$-fold tensor, designed to capture higher-order interactions between the binary variables. In this paper, we describe an approach based on a penalization technique that helps us recover the signed support of the tensor parameter with high probability, assuming that no entry of the true tensor is too close to zero. The method is based on an $\ell_1$-regularized node-wise logistic regression, that recovers the signed neighborhood of each node with high probability. Our analysis is carried out in the high-dimensional regime, that allows the dimension $p$ of the Ising model, as well as the interaction factor $k$ to potentially grow to $\infty$ with the sample size $n$. We show that if the minimum interaction strength is not too small, then consistent recovery of the entire signed support is possible if one takes $n = \Omega((k!)^8 d^3 \log \binom{p-1}{k-1})$ samples, where $d$ denotes the maximum degree of the hypernetwork in question. Our results are validated in two simulation settings, and applied on a real neurobiological dataset consisting of multi-array electro-physiological recordings from the mouse visual cortex, to model higher-order interactions between the brain regions., Comment: 28 pages, 7 figures

Published
2023
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3. Consistent Causal Inference from Time Series with PC Algorithm and its Time-Aware Extension

Author

Biswas, Rahul and Mukherjee, Somabha

Subjects
Methodology (stat.ME), FOS: Computer and information sciences, Applications (stat.AP), Statistics - Applications, Statistics - Methodology
Abstract

The estimator of a causal directed acyclic graph (DAG) with the PC algorithm is known to be consistent based on independent and identically distributed samples. In this paper, we consider the scenario when the multivariate samples are identically distributed but not independent. A common example is a stationary multivariate time series. We show that under a standard set of assumptions on the underlying time series involving $\rho$-mixing, the PC algorithm is consistent in this dependent sample scenario. Further, we show that for the popular time series models such as vector auto-regressive moving average and linear processes, consistency of the PC algorithm holds. We also prove the consistency for the Time-Aware PC algorithm, a recent adaptation of the PC algorithm for the time series scenario. Our findings are supported by simulations and benchmark real data analyses provided towards the end of the paper.

Published
2022

5. DESC DC2 Data Release Note

Author

LSST Dark Energy Science Collaboration, Abolfathi, Bela, Armstrong, Robert, Awan, Humna, Babuji, Yadu N., Bauer, Franz Erik, Beckett, George, Biswas, Rahul, Bogart, Joanne R., Boutigny, Dominique, Chard, Kyle, Chiang, James, Cohen-Tanugi, Johann, Connolly, Andrew J., Daniel, Scott F., Digel, Seth W., Drlica-Wagner, Alex, Dubois, Richard, Gawiser, Eric, Glanzman, Thomas, Habib, Salman, Hearin, Andrew P., Heitmann, Katrin, Hernandez, Fabio, Hložek, Renée, Hollowed, Joseph, Jarvis, Mike, Jha, Saurabh W., Kalmbach, J. Bryce, Kelly, Heather M., Kovacs, Eve, Korytov, Danila, Krughoff, K. Simon, Lage, Craig S., Lanusse, François, Larsen, Patricia, Li, Nan, Longley, Emily Phillips, Lupton, Robert H., Mandelbaum, Rachel, Mao, Yao-Yuan, Marshall, Phil, Meyers, Joshua E., Park, Ji Won, Peloton, Julien, Perrefort, Daniel, Perry, James, Plaszczynski, Stéphane, Pope, Adrian, Rykoff, Eli S., Sánchez, F. Javier, Schmidt, Samuel J., Uram, Thomas D., Villarreal, Antonia, Walter, Christopher W., Wiesner, Matthew P., Wood-Vasey, W. Michael, Laboratoire d'Annecy de Physique des Particules (LAPP), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Laboratoire Univers et Particules de Montpellier (LUPM), Université Montpellier 2 - Sciences et Techniques (UM2)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique de Clermont (LPC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Centre de Calcul de l'IN2P3 (CC-IN2P3), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Astrophysique Interprétation Modélisation (AIM (UMR_7158 / UMR_E_9005 / UM_112)), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7), Laboratoire de Physique des 2 Infinis Irène Joliot-Curie (IJCLab), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), LSST Dark Energy Science, Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Astrophysique Interprétation Modélisation (AIM (UMR7158 / UMR_E_9005 / UM_112)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), and HEP, INSPIRE

Subjects
Cosmology and Nongalactic Astrophysics (astro-ph.CO), [PHYS.PHYS.PHYS-INS-DET] Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], FOS: Physical sciences, [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], Astrophysics - Instrumentation and Methods for Astrophysics, [PHYS.ASTR] Physics [physics]/Astrophysics [astro-ph], [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], Instrumentation and Methods for Astrophysics (astro-ph.IM), Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

In preparation for cosmological analyses of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), the LSST Dark Energy Science Collaboration (LSST DESC) has created a 300 deg$^2$ simulated survey as part of an effort called Data Challenge 2 (DC2). The DC2 simulated sky survey, in six optical bands with observations following a reference LSST observing cadence, was processed with the LSST Science Pipelines (19.0.0). In this Note, we describe the public data release of the resulting object catalogs for the coadded images of five years of simulated observations along with associated truth catalogs. We include a brief description of the major features of the available data sets. To enable convenient access to the data products, we have developed a web portal connected to Globus data services. We describe how to access the data and provide example Jupyter Notebooks in Python to aid first interactions with the data. We welcome feedback and questions about the data release via a GitHub repository., Comment: 25 pages, 3 figures; 9 tables. A detailed changelog can be found in Appendix A. To obtain data, visit the DESC Data Portal at https://data.lsstdesc.org/

Published
2021

6. The Zwicky Transient Facility Bright Transient Survey. II. A Public Statistical Sample for Exploring Supernova Demographics* * An interactive catalog with all data used in this paper is available at https://sites.astro.caltech.edu/ztf/bts and is updated in real time

Author

Perley, Daniel A, Fremling, Christoffer, Sollerman, Jesper, Miller, Adam A, Dahiwale, Aishwarya S, Sharma, Yashvi, Bellm, Eric C, Biswas, Rahul, Brink, Thomas G, Bruch, Rachel J, De, Kishalay, Dekany, Richard, Drake, Andrew J, Duev, Dmitry A, Filippenko, Alexei V, Gal-Yam, Avishay, Goobar, Ariel, Graham, Matthew J, Graham, Melissa L, Ho, Anna YQ, Irani, Ido, Kasliwal, Mansi M, Kim, Young-Lo, Kulkarni, SR, Mahabal, Ashish, Masci, Frank J, Modak, Shaunak, Neill, James D, Nordin, Jakob, Riddle, Reed L, Soumagnac, Maayane T, Strotjohann, Nora L, Schulze, Steve, Taggart, Kirsty, Tzanidakis, Anastasios, Walters, Richard S, and Yan, Lin

Subjects
astro-ph.HE, Supernovae, Particle and Plasma Physics, Time domain astronomy, Molecular, Nuclear, Catalogs, Surveys, Astronomy & Astrophysics, Atomic, Transient sources, Astronomical and Space Sciences, Physical Chemistry (incl. Structural)
Abstract

We present a public catalog of transients from the Zwicky Transient Facility (ZTF) Bright Transient Survey, a magnitude-limited (m < 19 mag in either the g or r filter) survey for extragalactic transients in the ZTF public stream. We introduce cuts on survey coverage, sky visibility around peak light, and other properties unconnected to the nature of the transient, and show that the resulting statistical sample is spectroscopically 97% complete at -16 mag), 10% in red-sequence galaxies, and 1% in massive ellipticals. We find no significant difference in the luminosity or color distributions between the host galaxies of SNe Type II and SNe Type Ib/c, suggesting that line-driven wind stripping does not play a major role in the loss of the hydrogen envelope from their progenitors. Future large-scale classification efforts with ZTF and other wide-area surveys will provide highquality measurements of the rates, properties, and environments of all known types of optical transients and limits on the existence of theoretically predicted but as yet unobserved explosions.

Published
2020

7. Neuro-PC: Causal Functional Connectivity from Neural Dynamics

Author

Biswas, Rahul and Shlizerman, Eli

Subjects
Quantitative Biology - Neurons and Cognition, FOS: Biological sciences, Neurons and Cognition (q-bio.NC)
Abstract

Functional connectome extends the anatomical connectome by capturing the relations between neurons according to their activity and interactions. When these relations are causal, the functional connectome maps how neural activity flows within neural circuits and provides the possibility for inference of functional neural pathways, such as sensory-motor-behavioral pathways. While there exist various information approaches for non-causal estimations of the functional connectome, approaches that characterize the causal functional connectivity - the causal relationships between neuronal time series, are scarce. In this work, we develop the Neuro-PC algorithm which is a novel methodology for inferring the causal functional connectivity between neurons from multi-dimensional time series, such as neuronal recordings. The core of our methodology relies on a novel adaptation of the PC algorithm, a state-of-the-art method for statistical causal inference, to the multi-dimensional time-series of neural dynamics. We validate the performance of the method on network motifs with various interactions between their neurons simulated using continuous-time artificial network of neurons. We then consider the application of the method to obtain the causal functional connectome for recent multi-array electrophysiological recordings from the mouse visual cortex in the presence of different stimuli. We show how features of the mapping can be used for quantification of the similarities between neural responses subject to different stimuli.

Published
2020
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8. The zwicky transient facility: Science objectives

Author

Graham, Matthew J, Kulkarni, SR, Bellm, Eric C, Adams, Scott M, Barbarino, Cristina, Blagorodnova, Nadejda, Bodewits, Dennis, Bolin, Bryce, Brady, Patrick R, Cenko, S Bradley, Chang, Chan-Kao, Coughlin, Michael W, De, Kishalay, Eadie, Gwendolyn, Farnham, Tony L, Feindt, Ulrich, Franckowiak, Anna, Fremling, Christoffer, Gezari, Suvi, Ghosh, Shaon, Goldstein, Daniel A, Golkhou, V Zach, Goobar, Ariel, Ho, Anna YQ, Huppenkothen, Daniela, Ivezić, Željko, Jones, R Lynne, Juric, Mario, Kaplan, David L, Kasliwal, Mansi M, Kelley, Michael SP, Kupfer, Thomas, Lee, Chien-De, Lin, Hsing Wen, Lunnan, Ragnhild, Mahabal, Ashish A, Miller, Adam A, Ngeow, Chow-Choong, Nugent, Peter, Ofek, Eran O, Prince, Thomas A, Rauch, Ludwig, van Roestel, Jan, Schulze, Steve, Singer, Leo P, Sollerman, Jesper, Taddia, Francesco, Yan, Lin, Ye, Quan-Zhi, Yu, Po-Chieh, Barlow, Tom, Bauer, James, Beck, Ron, Belicki, Justin, Biswas, Rahul, Brinnel, Valery, Brooke, Tim, Bue, Brian, Bulla, Mattia, Burruss, Rick, Connolly, Andrew, Cromer, John, Cunningham, Virginia, Dekany, Richard, Delacroix, Alex, Desai, Vandana, Duev, Dmitry A, Feeney, Michael, Flynn, David, Frederick, Sara, Gal-Yam, Avishay, Giomi, Matteo, Groom, Steven, Hacopians, Eugean, Hale, David, Helou, George, Henning, John, Hover, David, Hillenbrand, Lynne A, Howell, Justin, Hung, Tiara, Imel, David, Ip, Wing-Huen, Jackson, Edward, Kaspi, Shai, Kaye, Stephen, Kowalski, Marek, Kramer, Emily, Kuhn, Michael, Landry, Walter, Laher, Russ R, Mao, Peter, Masci, Frank J, Monkewitz, Serge, Murphy, Patrick, Nordin, Jakob, Patterson, Maria T, Penprase, Bryan, Porter, Michael, and Rebbapragada, Umaa

Subjects
) quasars: general [(galaxies], astro-ph.HE, surveys, ) supernovae: general [(stars], Astronomy & Astrophysics, Astronomical and Space Sciences, astro-ph.IM
Abstract

The Zwicky Transient Facility (ZTF), a public–private enterprise, is a new time-domain survey employing a dedicated camera on the Palomar 48-inch Schmidt telescope with a 47 deg2 field of view and an 8 second readout time. It is well positioned in the development of time-domain astronomy, offering operations at 10% of the scale and style of the Large Synoptic Survey Telescope (LSST) with a single 1-m class survey telescope. The public surveys will cover the observable northern sky every three nights in g and r filters and the visible Galactic plane every night in g and r. Alerts generated by these surveys are sent in real time to brokers. A consortium of universities that provided funding (“partnership”) are undertaking several boutique surveys. The combination of these surveys producing one million alerts per night allows for exploration of transient and variable astrophysical phenomena brighter than r∼20.5 on timescales of minutes to years. We describe the primary science objectives driving ZTF, including the physics of supernovae and relativistic explosions, multi-messenger astrophysics, supernova cosmology, active galactic nuclei, and tidal disruption events, stellar variability, and solar system objects.

Published
2019

9. Dark Matter Science in the Era of LSST

Author

Bechtol, Keith, Drlica-Wagner, Alex, Abazajian, Kevork N., Abidi, Muntazir, Adhikari, Susmita, Ali-Haïmoud, Yacine, Annis, James, Ansarinejad, Behzad, Armstrong, Robert, Asorey, Jacobo, Baccigalupi, Carlo, Banerjee, Arka, Banik, Nilanjan, Bennett, Charles, Beutler, Florian, Bird, Simeon, Birrer, Simon, Biswas, Rahul, Biviano, Andrea, Blazek, Jonathan, Boddy, Kimberly K., Bonaca, Ana, Borrill, Julian, Bose, Sownak, Bovy, Jo, Frye, Brenda, Brooks, Alyson M., Buckley, Matthew R., Buckley-Geer, Elizabeth, Bulbul, Esra, Burchat, Patricia R., Burgess, Cliff, Calore, Francesca, Caputo, Regina, Castorina, Emanuele, Chang, Chihway, Chapline, George, Charles, Eric, Chen, Xingang, Clowe, Douglas, Cohen-Tanugi, Johann, Comparat, Johan, Croft, Rupert Ac, Cuoco, Alessandro, Cyr-Racine, Francis-Yan, D Amico, Guido, Davis, Tamara M., Dawson, William A., Macorra, Axel La, Valentino, Eleonora Di, Rivero, Ana Díaz, Digel, Seth, Dodelson, Scott, Doré, Olivier, Dvorkin, Cora, Eckner, Christopher, Ellison, John, Erkal, Denis, Farahi, Arya, Fassnacht, Christopher D., Ferreira, Pedro G., Flaugher, Brenna, Foreman, Simon, Friedrich, Oliver, Frieman, Joshua, García-Bellido, Juan, Gawiser, Eric, Gerbino, Martina, Maurizio Giannotti, Gill, Mandeep Ss, Gluscevic, Vera, Golovich, Nathan, Gontcho, Satya Gontcho A., González-Morales, Alma X., Grin, Daniel, Gruen, Daniel, Hearin, Andrew P., Hendel, David, Hezaveh, Yashar D., Hirata, Christopher M., Hložek, Renee, Horiuchi, Shunsaku, Jain, Bhuvnesh, Jee, M. James, Jeltema, Tesla E., Kamionkowski, Marc, Kaplinghat, Manoj, Keeley, Ryan E., Keeton, Charles R., Khatri, Rishi, Koposov, Sergey E., Koushiappas, Savvas M., Kovetz, Ely D., Lahav, Ofer, Lam, Casey, Lee, Chien-Hsiu, Li, Ting S., Liguori, Michele, Lin, Tongyan, Lisanti, Mariangela, Loverde, Marilena, Lu, Jessica R., Mandelbaum, Rachel, Mao, Yao-Yuan, Mcdermott, Samuel D., Mcnanna, Mitch, Medford, Michael, Meerburg, P. Daniel, Meyer, Manuel, Mirbabayi, Mehrdad, Mishra-Sharma, Siddharth, Marc, Moniez, More, Surhud, Moustakas, John, Muñoz, Julian B., Murgia, Simona, Myers, Adam D., Nadler, Ethan O., Necib, Lina, Newburgh, Laura, Newman, Jeffrey A., Nord, Brian, Nourbakhsh, Erfan, Nuss, Eric, O Connor, Paul, Pace, Andrew B., Padmanabhan, Hamsa, Palmese, Antonella, Peiris, Hiranya V., Peter, Annika Hg, Piacentni, Francesco, Piacentini, Francesco, Plazas, Andrés, Polin, Daniel A., Prakash, Abhishek, Prescod-Weinstein, Chanda, Read, Justin I., Ritz, Steven, Robertson, Brant E., Rose, Benjamin, Rosenfeld, Rogerio, Rossi, Graziano, Samushia, Lado, Sánchez, Javier, Sánchez-Conde, Miguel A., Schaan, Emmanuel, Sehgal, Neelima, Senatore, Leonardo, Seo, Hee-Jong, Shafieloo, Arman, Shan, Huanyuan, Shipp, Nora, Simon, Joshua D., Simon, Sara, Slatyer, Tracy R., Slosar, Anže, Sridhar, Srivatsan, Stebbins, Albert, Straniero, Oscar, Strigari, Louis E., Tait, Tim Mp, Tollerud, Erik, Troxel, Ma, Tyson, J. Anthony, Uhlemann, Cora, Urenña-López, L. Arturo, Verma, Aprajita, Vilalta, Ricardo, Walter, Christopher W., Wang, Mei-Yu, Watson, Scott, Wechsler, Risa H., Wittman, David, Xu, Weishuang, Yanny, Brian, Young, Sam, Yu, Hai-Bo, Zaharijas, Gabrijela, Zentner, Andrew R., Zuntz, Joe, Laboratoire d'Annecy-le-Vieux de Physique Théorique (LAPTH), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Laboratoire Univers et Particules de Montpellier (LUPM), Université Montpellier 2 - Sciences et Techniques (UM2)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de l'Accélérateur Linéaire (LAL), Université Paris-Sud - Paris 11 (UP11)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Sud - Paris 11 (UP11), Université de Montpellier (UM)-Université Montpellier 2 - Sciences et Techniques (UM2)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), and HEP, INSPIRE

Subjects
Astrophysics and Astronomy, Cosmology and Nongalactic Astrophysics (astro-ph.CO), [PHYS.HEXP] Physics [physics]/High Energy Physics - Experiment [hep-ex], Dark matter, FOS: Physical sciences, Astrophysics::Cosmology and Extragalactic Astrophysics, Compact star, 01 natural sciences, Standard Model, High Energy Physics - Experiment, High Energy Physics - Experiment (hep-ex), Particle mass, 0103 physical sciences, [PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex], 010303 astronomy & astrophysics, High Energy Astrophysical Phenomena (astro-ph.HE), astro-ph.HE, Physics, hep-ex, 010308 nuclear & particles physics, Astrophysics::Instrumentation and Methods for Astrophysics, Astronomy, 13. Climate action, Fundamental physics, astro-ph.CO, [PHYS.ASTR] Physics [physics]/Astrophysics [astro-ph], [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], Astrophysics - High Energy Astrophysical Phenomena, Particle Physics - Experiment, dark matter: parameter space, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Astrophysical observations currently provide the only robust, empirical measurements of dark matter. In the coming decade, astrophysical observations will guide other experimental efforts, while simultaneously probing unique regions of dark matter parameter space. This white paper summarizes astrophysical observations that can constrain the fundamental physics of dark matter in the era of LSST. We describe how astrophysical observations will inform our understanding of the fundamental properties of dark matter, such as particle mass, self-interaction strength, non-gravitational interactions with the Standard Model, and compact object abundances. Additionally, we highlight theoretical work and experimental/observational facilities that will complement LSST to strengthen our understanding of the fundamental characteristics of dark matter., 11 pages, 2 figures, Science Whitepaper for Astro 2020, more information at https://lsstdarkmatter.github.io

Published
2019

10. LSST: From Science Drivers to Reference Design and Anticipated Data Products

Author

Ivezić, Željko, Kahn, Steven M, Tyson, J Anthony, Abel, Bob, Acosta, Emily, Allsman, Robyn, Alonso, David, AlSayyad, Yusra, Anderson, Scott F, Andrew, John, Angel, James Roger P, Angeli, George Z, Ansari, Reza, Antilogus, Pierre, Araujo, Constanza, Armstrong, Robert, Arndt, Kirk T, Astier, Pierre, Aubourg, Éric, Auza, Nicole, Axelrod, Tim S, Bard, Deborah J, Barr, Jeff D, Barrau, Aurelian, Bartlett, James G, Bauer, Amanda E, Bauman, Brian J, Baumont, Sylvain, Bechtol, Ellen, Bechtol, Keith, Becker, Andrew C, Becla, Jacek, Beldica, Cristina, Bellavia, Steve, Bianco, Federica B, Biswas, Rahul, Blanc, Guillaume, Blazek, Jonathan, Blandford, Roger D, Bloom, Josh S, Bogart, Joanne, Bond, Tim W, Booth, Michael T, Borgland, Anders W, Borne, Kirk, Bosch, James F, Boutigny, Dominique, Brackett, Craig A, Bradshaw, Andrew, Brandt, William Nielsen, Brown, Michael E, Bullock, James S, Burchat, Patricia, Burke, David L, Cagnoli, Gianpietro, Calabrese, Daniel, Callahan, Shawn, Callen, Alice L, Carlin, Jeffrey L, Carlson, Erin L, Chandrasekharan, Srinivasan, Charles-Emerson, Glenaver, Chesley, Steve, Cheu, Elliott C, Chiang, Hsin-Fang, Chiang, James, Chirino, Carol, Chow, Derek, Ciardi, David R, Claver, Charles F, Cohen-Tanugi, Johann, Cockrum, Joseph J, Coles, Rebecca, Connolly, Andrew J, Cook, Kem H, Cooray, Asantha, Covey, Kevin R, Cribbs, Chris, Cui, Wei, Cutri, Roc, Daly, Philip N, Daniel, Scott F, Daruich, Felipe, Daubard, Guillaume, Daues, Greg, Dawson, William, Delgado, Francisco, Dellapenna, Alfred, de Peyster, Robert, de Val-Borro, Miguel, Digel, Seth W, Doherty, Peter, Dubois, Richard, Dubois-Felsmann, Gregory P, Durech, Josef, Economou, Frossie, Eifler, Tim, Eracleous, Michael, Emmons, Benjamin L, and Neto, Angelo Fausti

Subjects
general [stars], Organic Chemistry, observational [methods], Molecular, Astronomy & Astrophysics, Physical Chemistry, Atomic, observations [cosmology], Particle and Plasma Physics, surveys, astro-ph, astrometry, Nuclear, general [Galaxy], Astronomical and Space Sciences, Physical Chemistry (incl. Structural)
Abstract

We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the solar system, exploring the transient optical sky, and mapping the Milky Way. LSST will be a large, wide-field ground-based system designed to obtain repeated images covering the sky visible from Cerro Pachón in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg 2 field of view, a 3.2-gigapixel camera, and six filters (ugrizy) covering the wavelength range 320-1050 nm. The project is in the construction phase and will begin regular survey operations by 2022. About 90% of the observing time will be devoted to a deep-wide-fast survey mode that will uniformly observe a 18,000 deg 2 region about 800 times (summed over all six bands) during the anticipated 10 yr of operations and will yield a co-added map to r ∼27.5. These data will result in databases including about 32 trillion observations of 20 billion galaxies and a similar number of stars, and they will serve the majority of the primary science programs. The remaining 10% of the observing time will be allocated to special projects such as Very Deep and Very Fast time domain surveys, whose details are currently under discussion. We illustrate how the LSST science drivers led to these choices of system parameters, and we describe the expected data products and their characteristics.

Published
2019

11. Probing the Fundamental Nature of Dark Matter with the Large Synoptic Survey Telescope

Author

Drlica-Wagner, Alex, Mao, Yao-Yuan, Adhikari, Susmita, Armstrong, Robert, Banerjee, Arka, Banik, Nilanjan, Bechtol, Keith, Bird, Simeon, Boddy, Kimberly K, Bonaca, Ana, Bovy, Jo, Buckley, Matthew R, Bulbul, Esra, Chang, Chihway, Chapline, George, Cohen-Tanugi, Johann, Cuoco, Alessandro, Cyr-Racine, Francis-Yan, Dawson, William A, Rivero, Ana Díaz, Dvorkin, Cora, Erkal, Denis, Fassnacht, Christopher D, García-Bellido, Juan, Giannotti, Maurizio, Gluscevic, Vera, Golovich, Nathan, Hendel, David, Hezaveh, Yashar D, Horiuchi, Shunsaku, Jee, M James, Kaplinghat, Manoj, Keeton, Charles R, Koposov, Sergey E, Li, Ting S, Mandelbaum, Rachel, McDermott, Samuel D, McNanna, Mitch, Medford, Michael, Meyer, Manuel, Marc, Moniez, Murgia, Simona, Nadler, Ethan O, Necib, Lina, Nuss, Eric, Pace, Andrew B, Peter, Annika HG, Polin, Daniel A, Prescod-Weinstein, Chanda, Read, Justin I, Rosenfeld, Rogerio, Shipp, Nora, Simon, Joshua D, Slatyer, Tracy R, Straniero, Oscar, Strigari, Louis E, Tollerud, Erik, Tyson, J Anthony, Wang, Mei-Yu, Wechsler, Risa H, Wittman, David, Yu, Hai-Bo, Zaharijas, Gabrijela, Ali-Haïmoud, Yacine, Annis, James, Birrer, Simon, Biswas, Rahul, Blazek, Jonathan, Brooks, Alyson M, Buckley-Geer, Elizabeth, Caputo, Regina, Charles, Eric, Digel, Seth, Dodelson, Scott, Flaugher, Brenna, Frieman, Joshua, Gawiser, Eric, Hearin, Andrew P, Hložek, Renee, Jain, Bhuvnesh, Jeltema, Tesla E, Koushiappas, Savvas M, Lisanti, Mariangela, LoVerde, Marilena, Mishra-Sharma, Siddharth, Newman, Jeffrey A, Nord, Brian, Nourbakhsh, Erfan, Ritz, Steven, Robertson, Brant E, Sánchez-Conde, Miguel A, Slosar, Anže, Tait, Tim MP, Verma, Aprajita, Vilalta, Ricardo, Walter, Christopher W, Yanny, Brian, and Zentner, Andrew R

Subjects
astro-ph.HE, hep-ex, astro-ph.GA, Astrophysics::Instrumentation and Methods for Astrophysics, astro-ph.CO, hep-ph, Astrophysics::Cosmology and Extragalactic Astrophysics
Abstract

Astrophysical and cosmological observations currently provide the only robust, empirical measurements of dark matter. Future observations with Large Synoptic Survey Telescope (LSST) will provide necessary guidance for the experimental dark matter program. This white paper represents a community effort to summarize the science case for studying the fundamental physics of dark matter with LSST. We discuss how LSST will inform our understanding of the fundamental properties of dark matter, such as particle mass, self-interaction strength, non-gravitational couplings to the Standard Model, and compact object abundances. Additionally, we discuss the ways that LSST will complement other experiments to strengthen our understanding of the fundamental characteristics of dark matter. More information on the LSST dark matter effort can be found at https://lsstdarkmatter.github.io/ .

Published
2019

12. Effects of Massive Neutrinos and Dynamical Dark Energy on the Cluster Mass Function

Author

Biswas, Rahul, Heitmann, Katrin, Habib, Salman, Upadhye, Amol, Pope, Adrian, and Frontiere, Nicholas

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

The presence of massive neutrinos affects the growth of large-scale structure in the universe, leaving a potentially observable imprint on the abundance and properties of massive dark matter-dominated halos. Cosmological surveys detect large numbers of these halos in the form of rich groups and clusters, using the information as an input to constraining the properties of dark energy. We use a suite of N-body simulations that include the effects of massive neutrinos as well as of dynamical dark energy to study the properties of the mass function. As in our previous work, we follow an approach valid at low neutrino mass, where the neutrino overdensities are assumed to be too small to act as a significant nonlinear source term for gravity. We study how well a universal form for the halo mass function describes our numerical results, finding that the use of an appropriate linear power spectrum within the formalism yields a good match to the simulation results, correctly accounting for the (neutrino mass-dependent) suppression of the mass function., 11 pages, 5 figures, to be submitted to PRD

Published
2019

13. The Zwicky Transient Facility: System Overview, Performance, and First Results

Author

Bellm, Eric C, Kulkarni, Shrinivas R, Graham, Matthew J, Dekany, Richard, Smith, Roger M, Riddle, Reed, Masci, Frank J, Helou, George, Prince, Thomas A, Adams, Scott M, Barbarino, C, Barlow, Tom, Bauer, James, Beck, Ron, Belicki, Justin, Biswas, Rahul, Blagorodnova, Nadejda, Bodewits, Dennis, Bolin, Bryce, Brinnel, Valery, Brooke, Tim, Bue, Brian, Bulla, Mattia, Burruss, Rick, Cenko, S Bradley, Chang, Chan-Kao, Connolly, Andrew, Coughlin, Michael, Cromer, John, Cunningham, Virginia, De, Kishalay, Delacroix, Alex, Desai, Vandana, Duev, Dmitry A, Eadie, Gwendolyn, Farnham, Tony L, Feeney, Michael, Feindt, Ulrich, Flynn, David, Franckowiak, Anna, Frederick, S, Fremling, C, Gal-Yam, Avishay, Gezari, Suvi, Giomi, Matteo, Goldstein, Daniel A, Golkhou, V Zach, Goobar, Ariel, Groom, Steven, Hacopians, Eugean, Hale, David, Henning, John, Ho, Anna YQ, Hover, David, Howell, Justin, Hung, Tiara, Huppenkothen, Daniela, Imel, David, Ip, Wing-Huen, Ivezić, Željko, Jackson, Edward, Jones, Lynne, Juric, Mario, Kasliwal, Mansi M, Kaspi, S, Kaye, Stephen, Kelley, Michael SP, Kowalski, Marek, Kramer, Emily, Kupfer, Thomas, Landry, Walter, Laher, Russ R, Lee, Chien-De, Lin, Hsing Wen, Lin, Zhong-Yi, Lunnan, Ragnhild, Mahabal, Ashish, Mao, Peter, Miller, Adam A, Monkewitz, Serge, Murphy, Patrick, Ngeow, Chow-Choong, Nordin, Jakob, Nugent, Peter, Ofek, Eran, Patterson, Maria T, Penprase, Bryan, Porter, Michael, Rauch, Ludwig, Rebbapragada, Umaa, Reiley, Dan, Rigault, Mickael, Rodriguez, Hector, van Roestel, Jan, Rusholme, Ben, van Santen, Jakob, Schulze, S, Shupe, David L, and Singer, Leo P

Subjects
photometers [instrumentation], telescopes, Astronomy & Astrophysics, Astronomical and Space Sciences, astro-ph.IM
Abstract

The Zwicky Transient Facility (ZTF) is a new optical time-domain survey that uses the Palomar 48 inch Schmidt telescope. A custom-built wide-field camera provides a 47 deg 2 field of view and 8 s readout time, yielding more than an order of magnitude improvement in survey speed relative to its predecessor survey, the Palomar Transient Factory. We describe the design and implementation of the camera and observing system. The ZTF data system at the Infrared Processing and Analysis Center provides near-real-time reduction to identify moving and varying objects. We outline the analysis pipelines, data products, and associated archive. Finally, we present on-sky performance analysis and first scientific results from commissioning and the early survey. ZTF’s public alert stream will serve as a useful precursor for that of the Large Synoptic Survey Telescope.

Published
2019

14. Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Wide-Fast-Deep Survey

Author

Lochner, Michelle, Scolnic, Daniel M., Awan, Humna, Regnault, Nicolas, Gris, Philippe, Mandelbaum, Rachel, Gawiser, Eric, Almoubayyed, Husni, Setzer, Christian N., Huber, Simon, Graham, Melissa L., Hložek, Renée, Biswas, Rahul, Eifler, Tim, Rothchild, Daniel, Allam, Tarek, Blazek, Jonathan, Chang, Chihway, Collett, Thomas, Goobar, Ariel, Hook, Isobel M., Jarvis, Mike, Jha, Saurabh W., Kim, Alex G., Marshall, Phil, Mcewen, Jason D., Moniez, Marc, Newman, Jeffrey A., Hiranya Peiris, Petrushevska, Tanja, Rhodes, Jason, Sevilla-Noarbe, Ignacio, Slosar, Anže, Suyu, Sherry H., Tyson, J. Anthony, Yoachim, Peter, Laboratoire de Physique Nucléaire et de Hautes Énergies (LPNHE (UMR_7585)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris Diderot - Paris 7 (UPD7)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique de Clermont (LPC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Clermont Auvergne (UCA)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de l'Accélérateur Linéaire (LAL), Université Paris-Sud - Paris 11 (UP11)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), LSST Dark Energy Science, Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), and Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Sud - Paris 11 (UP11)

Subjects
FOS: Physical sciences, Astrophysics::Cosmology and Extragalactic Astrophysics, [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], Astrophysics - Instrumentation and Methods for Astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM), astro-ph.IM
Abstract

Cosmology is one of the four science pillars of LSST, which promises to be transformative for our understanding of dark energy and dark matter. The LSST Dark Energy Science Collaboration (DESC) has been tasked with deriving constraints on cosmological parameters from LSST data. Each of the cosmological probes for LSST is heavily impacted by the choice of observing strategy. This white paper is written by the LSST DESC Observing Strategy Task Force (OSTF), which represents the entire collaboration, and aims to make recommendations on observing strategy that will benefit all cosmological analyses with LSST. It is accompanied by the DESC DDF (Deep Drilling Fields) white paper (Scolnic et al.). We use a variety of metrics to understand the effects of the observing strategy on measurements of weak lensing, large-scale structure, clusters, photometric redshifts, supernovae, strong lensing and kilonovae. In order to reduce systematic uncertainties, we conclude that the current baseline observing strategy needs to be significantly modified to result in the best possible cosmological constraints. We provide some key recommendations: moving the WFD (Wide-Fast-Deep) footprint to avoid regions of high extinction, taking visit pairs in different filters, changing the 2x15s snaps to a single exposure to improve efficiency, focusing on strategies that reduce long gaps (>15 days) between observations, and prioritizing spatial uniformity at several intervals during the 10-year survey., The LSST DESC response (WFD) to the Call for White Papers on LSST Cadence Optimization. Comments welcome

Published
2018

15. Optimizing the LSST Observing Strategy for Dark Energy Science: DESC Recommendations for the Deep Drilling Fields and other Special Programs

Author

Scolnic, Daniel M., Lochner, Michelle, Gris, Phillipe, Regnault, Nicolas, Hlo��ek, Ren��e, Aldering, Greg, Allam, Tarek, Awan, Humna, Biswas, Rahul, Blazek, Jonathan, Chang, Chihway, Gawiser, Eric, Goobar, Ariel, Hook, Isobel M., Jha, Saurabh W., McEwen, Jason D., Mandelbaum, Rachel, Marshall, Phil, Neilsen, Eric, Rhodes, Jason, Rothchild, Daniel, Noarbe, Ignacio Sevilla, Slosar, An��e, Yoachim, Peter, Laboratoire de Physique de Clermont (LPC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Clermont Auvergne (UCA)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique Nucléaire et de Hautes Énergies (LPNHE (UMR_7585)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris Diderot - Paris 7 (UPD7)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), LSST Dark Energy Science, Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), and Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS)

Subjects
FOS: Physical sciences, [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], Astrophysics - Instrumentation and Methods for Astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM)
Abstract

We review the measurements of dark energy enabled by observations of the Deep Drilling Fields and the optimization of survey design for cosmological measurements. This white paper is the result of efforts by the LSST DESC Observing Strategy Task Force (OSTF), which represents the entire collaboration, and aims to make recommendations on observing strategy for the DDFs that will benefit all cosmological analyses with LSST. It is accompanied by the DESC-WFD white paper (Lochner et al.). We argue for altering the nominal deep drilling plan to have $>6$ month seasons, interweaving $gri$ and $zy$ observations every 3 days with 2, 4, 8, 25, 4 visits in $grizy$, respectively. These recommendations are guided by metrics optimizing constraints on dark energy and mitigation of systematic uncertainties, including specific requirements on total number of visits after Y1 and Y10 for photometric redshifts (photo-$z$) and weak lensing systematics. We specify the precise locations for the previously-chosen LSST deep fields (ELAIS-S1, XMM-LSS, CDF-S, and COSMOS) and recommend Akari Deep Field South as the planned fifth deep field in order to synergize with Euclid and WFIRST. Our recommended DDF strategy uses $6.2\%$ of the LSST survey time. We briefly discuss synergy with white papers from other collaborations, as well as additional mini-surveys and Target-of-Opportunity programs that lead to better measurements of dark energy., The LSST DESC response (DDF) to the Call for White Papers on LSST Cadence Optimization. Comments welcome

Published
2018

16. The Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC): Data set

Author

The PLAsTiCC Team, Allam, Tarek, Bahmanyar, Anita, Biswas, Rahul, Dai, Mi, Galbany, Llu��s, Hlo��ek, Ren��e, Ishida, Emille E. O., Jha, Saurabh W., Jones, David O., Kessler, Richard, Lochner, Michelle, Mahabal, Ashish A., Malz, Alex I., Mandel, Kaisey S., Mart��nez-Galarza, Juan Rafael, McEwen, Jason D., Muthukrishna, Daniel, Narayan, Gautham, Peiris, Hiranya, Peters, Christina M., Ponder, Kara, Setzer, Christian N., Collaboration, The LSST Dark Energy Science, Transients, The LSST, and Collaboration, Variable Stars Science

Subjects
Astrophysics - Solar and Stellar Astrophysics, FOS: Physical sciences, Astrophysics - Instrumentation and Methods for Astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM), Solar and Stellar Astrophysics (astro-ph.SR)
Abstract

The Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC) is an open data challenge to classify simulated astronomical time-series data in preparation for observations from the Large Synoptic Survey Telescope (LSST), which will achieve first light in 2019 and commence its 10-year main survey in 2022. LSST will revolutionize our understanding of the changing sky, discovering and measuring millions of time-varying objects. In this challenge, we pose the question: how well can we classify objects in the sky that vary in brightness from simulated LSST time-series data, with all its challenges of non-representativity? In this note we explain the need for a data challenge to help classify such astronomical sources and describe the PLAsTiCC data set and Kaggle data challenge, noting that while the references are provided for context, they are not needed to participate in the challenge., Research note to accompany the https://www.kaggle.com/c/PLAsTiCC-2018 challenge

Published
2018

17. The LSST Dark Energy Science Collaboration (DESC) Science Requirements Document

Author

The LSST Dark Energy Science Collaboration, Mandelbaum, Rachel, Eifler, Tim, Hlo��ek, Ren��e, Collett, Thomas, Gawiser, Eric, Scolnic, Daniel, Alonso, David, Awan, Humna, Biswas, Rahul, Blazek, Jonathan, Burchat, Patricia, Chisari, Nora Elisa, Dell'Antonio, Ian, Digel, Seth, Frieman, Josh, Goldstein, Daniel A., Hook, Isobel, Ivezi��, ��eljko, Kahn, Steven M., Kamath, Sowmya, Kirkby, David, Kitching, Thomas, Krause, Elisabeth, Leget, Pierre-Fran��ois, Marshall, Philip J., Meyers, Joshua, Miyatake, Hironao, Newman, Jeffrey A., Nichol, Robert, Rykoff, Eli, Sanchez, F. Javier, Slosar, An��e, Sullivan, Mark, and Troxel, M. A.

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

The Large Synoptic Survey Telescope (LSST) Dark Energy Science Collaboration (DESC) will use five cosmological probes: galaxy clusters, large scale structure, supernovae, strong lensing, and weak lensing. This Science Requirements Document (SRD) quantifies the expected dark energy constraining power of these probes individually and together, with conservative assumptions about analysis methodology and follow-up observational resources based on our current understanding and the expected evolution within the field in the coming years. We then define requirements on analysis pipelines that will enable us to achieve our goal of carrying out a dark energy analysis consistent with the Dark Energy Task Force definition of a Stage IV dark energy experiment. This is achieved through a forecasting process that incorporates the flowdown to detailed requirements on multiple sources of systematic uncertainty. Future versions of this document will include evolution in our software capabilities and analysis plans along with updates to the LSST survey strategy., 32 pages + 60 pages of appendices. This is v1.0.2 of the DESC SRD, an internal collaboration document that is being made public and is not planned for submission to a journal. Data products for reproducing key plots are available on Zenodo, https://doi.org/10.5281/zenodo.1409815 ; see "Executive Summary and User Guide" for how to use and cite those products

Published
2018

18. On high-dimensional modifications of some graph-based two-sample tests

Author

Sarkar, Soham, Biswas, Rahul, and Ghosh, Anil K.

Subjects
Methodology (stat.ME), FOS: Computer and information sciences, Statistics - Methodology
Abstract

Testing for the equality of two high-dimensional distributions is a challenging problem, and this becomes even more challenging when the sample size is small. Over the last few decades, several graph-based two-sample tests have been proposed in the literature, which can be used for data of arbitrary dimensions. Most of these test statistics are computed using pairwise Euclidean distances among the observations. But, due to concentration of pairwise Euclidean distances, these tests have poor performance in many high-dimensional problems. Some of them can have powers even below the nominal level when the scale-difference between two distributions dominates the location-difference. To overcome these limitations, we introduce a new class of dissimilarity indices and use it to modify some popular graph-based tests. These modified tests use the distance concentration phenomenon to their advantage, and as a result, they outperform the corresponding tests based on the Euclidean distance in a wide variety of examples. We establish the high-dimensional consistency of these modified tests under fairly general conditions. Analyzing several simulated as well as real data sets, we demonstrate their usefulness in high dimension, low sample size situations.

Published
2018
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21. The LSST Data Management System

Author

Jurić, Mario, Kantor, Jeffrey, Lim, K-T, Lupton, Robert H., Dubois-Felsmann, Gregory, Jenness, Tim, Axelrod, Tim S., Aleksić, Jovan, Allsman, Roberta A., AlSayyad, Yusra, Alt, Jason, Armstrong, Robert, Basney, Jim, Becker, Andrew C., Becla, Jacek, Bickerton, Steven J., Biswas, Rahul, Bosch, James, Boutigny, Dominique, Kind, Matias Carrasco, Ciardi, David R., Connolly, Andrew J., Daniel, Scott F., Daues, Gregory E., Economou, Frossie, Chiang, Hsin-Fang, Fausti, Angelo, Fisher-Levine, Merlin, Freemon, D. Michael, Gee, Perry, Gris, Philippe, Hernandez, Fabio, Hoblitt, Joshua, Ivezić, Željko, Jammes, Fabrice, Jevremović, Darko, Jones, R. Lynne, Kalmbach, J. Bryce, Kasliwal, Vishal P., Krughoff, K. Simon, Lang, Dustin, Lurie, John, Lust, Nate B., Mullally, Fergal, MacArthur, Lauren A., Melchior, Peter, Moeyens, Joachim, Nidever, David L., Owen, Russell, Parejko, John K, Peterson, J. Matt, Petravick, Donald, Pietrowicz, Stephen R., Price, Paul A., Reiss, David J., Shaw, Richard A., Sick, Jonathan, Slater, Colin T., Strauss, Michael A., Sullivan, Ian S., Swinbank, John D., Van Dyk, Schuyler, Vujčić, Veljko, Withers, Alexander, and Yoachim, Peter

Subjects
FOS: Physical sciences, Astrophysics - Instrumentation and Methods for Astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM)
Abstract

The Large Synoptic Survey Telescope (LSST) is a large-aperture, wide-field, ground-based survey system that will image the sky in six optical bands from 320 to 1050 nm, uniformly covering approximately $18,000$deg$^2$ of the sky over 800 times. The LSST is currently under construction on Cerro Pach\'on in Chile, and expected to enter operations in 2022. Once operational, the LSST will explore a wide range of astrophysical questions, from discovering "killer" asteroids to examining the nature of Dark Energy. The LSST will generate on average 15 TB of data per night, and will require a comprehensive Data Management system to reduce the raw data to scientifically useful catalogs and images with minimum human intervention. These reductions will result in a real-time alert stream, and eleven data releases over the 10-year duration of LSST operations. To enable this processing, the LSST project is developing a new, general-purpose, high-performance, scalable, well documented, open source data processing software stack for O/IR surveys. Prototypes of this stack are already capable of processing data from existing cameras (e.g., SDSS, DECam, MegaCam), and form the basis of the Hyper-Suprime Cam (HSC) Survey data reduction pipeline., Comment: 10 pages, 3 figures, to appear in the Proceedings of ADASS XXV

Published
2015
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22. HYDRAULIC MODELLING FOR RELIABLE LIFT STATION DESIGN AND OPERATION

Author

R. Biswas Rahul

Subjects
Lift (force), 030507 speech-language pathology & audiology, 03 medical and health sciences, 0202 electrical engineering, electronic engineering, information engineering, Environmental science, 020201 artificial intelligence & image processing, 02 engineering and technology, 0305 other medical science, Marine engineering
Published
2017

23. Learning Hierarchical Object Maps Of Non-Stationary Environments with mobile robots

Author

Anguelov, Dragomir, Biswas, Rahul, Koller, Daphne, Limketkai, Benson, and Thrun, Sebastian

Subjects
FOS: Computer and information sciences, Computer Science - Learning, Computer Science - Robotics, Statistics - Machine Learning, Machine Learning (stat.ML), Robotics (cs.RO), Machine Learning (cs.LG)
Abstract

Building models, or maps, of robot environments is a highly active research area; however, most existing techniques construct unstructured maps and assume static environments. In this paper, we present an algorithm for learning object models of non-stationary objects found in office-type environments. Our algorithm exploits the fact that many objects found in office environments look alike (e.g., chairs, recycling bins). It does so through a two-level hierarchical representation, which links individual objects with generic shape templates of object classes. We derive an approximate EM algorithm for learning shape parameters at both levels of the hierarchy, using local occupancy grid maps for representing shape. Additionally, we develop a Bayesian model selection algorithm that enables the robot to estimate the total number of objects and object templates in the environment. Experimental results using a real robot equipped with a laser range finder indicate that our approach performs well at learning object-based maps of simple office environments. The approach outperforms a previously developed non-hierarchical algorithm that models objects but lacks class templates., Appears in Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence (UAI2002)

Published
2012

24. The reliability of the AIC method in Cosmological Model Selection

Author

Tan, Ming Yang Jeremy and Biswas, Rahul

Subjects
Statistics::Machine Learning, Statistics::Theory, Cosmology and Nongalactic Astrophysics (astro-ph.CO), Statistics::Applications, Physics - Data Analysis, Statistics and Probability, Statistics::Methodology, FOS: Physical sciences, Astrophysics - Instrumentation and Methods for Astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM), Data Analysis, Statistics and Probability (physics.data-an), Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

The Akaike information criterion (AIC) has been used as a statistical criterion to compare the appropriateness of different dark energy candidate models underlying a particular data set. Under suitable conditions, the AIC is an indirect estimate of the Kullback-Leibler divergence D(T//A) of a candidate model A with respect to the truth T. Thus, a dark energy model with a smaller AIC is ranked as a better model, since it has a smaller Kullback-Leibler discrepancy with T. In this paper, we explore the impact of statistical errors in estimating the AIC during model comparison. Using a parametric bootstrap technique, we study the distribution of AIC differences between a set of candidate models due to different realizations of noise in the data and show that the shape and spread of this distribution can be quite varied. We also study the rate of success of the AIC procedure for different values of a threshold parameter popularly used in the literature. For plausible choices of true dark energy models, our studies suggest that investigating such distributions of AIC differences in addition to the threshold is useful in correctly interpreting comparisons of dark energy models using the AIC technique., Comment: Figures and further discussions of the results were added, and the version matches the version published in MNRAS

Published
2011
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25. Parameters and pitfalls in dark energy models with time varying equation of state

Author

Biswas, Rahul and Wandelt, Benjamin D.

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

Are geometrical summaries of the CMB and LSS sufficient for estimating cosmological parameters? And how does our choice of a dark energy model impact the current constraints on standard cosmological parameters? We address these questions in the context of the widely used CPL parametrization of a time varying equation of state w in a cosmology allowing spatial curvature. We study examples of different behavior allowed in a CPL parametrization in a phase diagram, and relate these to effects on the observables. We examine parameter constraints in such a cosmology by combining WMAP5, SDSS, SNe, HST data sets by comparing the power spectra. We carefully quantify the differences of these constraints to those obtained by using geometrical summaries for the same data sets. We find that (a) using summary parameters instead of the full data sets give parameter constraints that are similar, but with discernible differences, (b) due to degeneracies, the constraints on the standard parameters broaden significantly for the same data sets. In particular, we find that in the context of CPL dark energy, (i) a Harrison-Zeldovich spectrum cannot be ruled out at $2\sigma$ levels with our current data sets. and (ii) the SNe IA, HST, and WMAP 5 data are not sufficient to constrain spatial curvature; we additionally require the SDSS DR4 data to achieve this., Comment: 20 pages, 11 figures, Submitted to Astrophysical Journal

Published
2009

26. The LSST Data Management System

Author

Jurić, Mario, Kantor, Jeffrey, Lim, K-T, Lupton, Robert H., Dubois-Felsmann, Gregory, Jenness, Tim, Axelrod, Tim S., Aleksić, Jovan, Allsman, Roberta A., Alsayyad, Yusra, Alt, Jason, Armstrong, Robert, Basney, Jim, Becker, Andrew C., Becla, Jacek, Bickerton, Steven J., Biswas, Rahul, Bosch, James, Boutigny, Dominique, Matias Carrasco Kind, Ciardi, David R., Connolly, Andrew J., Daniel, Scott F., Daues, Gregory E., Economou, Frossie, Chiang, Hsin-Fang, Fausti, Angelo, Fisher-Levine, Merlin, Freemon, D. Michael, Gee, Perry, Gris, Philippe, Hernandez, Fabio, Hoblitt, Joshua, Ivezić, Željko, Jammes, Fabrice, Jevremović, Darko, Jones, R. Lynne, Bryce Kalmbach, J., Kasliwal, Vishal P., Krughoff, K. Simon, Lang, Dustin, Lurie, John, Lust, Nate B., Mullally, Fergal, Macarthur, Lauren A., Melchior, Peter, Moeyens, Joachim, Nidever, David L., Owen, Russell, Parejko, John K., Peterson, J. Matt, Petravick, Donald, Pietrowicz, Stephen R., Price, Paul A., Reiss, David J., Shaw, Richard A., Sick, Jonathan, Slater, Colin T., Strauss, Michael A., Sullivan, Ian S., Swinbank, John D., Dyk, Schuyler, Vujčić, Veljko, Withers, Alexander, Yoachim, Peter, and Lsst Project, For The

27. Probing the Fundamental Nature of Dark Matter with the Large Synoptic Survey Telescope

Author

Drlica-Wagner, Alex, Mao, Yao-Yuan, Adhikari, Susmita, Armstrong, Robert, Banerjee, Arka, Banik, Nilanjan, Bechtol, Keith, Bird, Simeon, Boddy, Kimberly K., Bonaca, Ana, Bovy, Jo, Buckley, Matthew R., Bulbul, Esra, Chang, Chihway, Chapline, George, Cohen-Tanugi, Johann, Cuoco, Alessandro, Cyr-Racine, Francis-Yan, Dawson, William A., Rivero, Ana Díaz, Dvorkin, Cora, Erkal, Denis, Fassnacht, Christopher D., García-Bellido, Juan, Giannotti, Maurizio, Gluscevic, Vera, Golovich, Nathan, Hendel, David, Hezaveh, Yashar D., Horiuchi, Shunsaku, James Jee, M., Kaplinghat, Manoj, Keeton, Charles R., Koposov, Sergey E., Lam, Casey Y., Li, Ting S., Lu, Jessica R., Mandelbaum, Rachel, Mcdermott, Samuel D., Mcnanna, Mitch, Medford, Michael, Meyer, Manuel, Marc, Moniez, Murgia, Simona, Nadler, Ethan O., Necib, Lina, Nuss, Eric, Pace, Andrew B., Peter, Annika H. G., Polin, Daniel A., Prescod-Weinstein, Chanda, Read, Justin I., Rosenfeld, Rogerio, Shipp, Nora, Simon, Joshua D., Slatyer, Tracy R., Straniero, Oscar, Strigari, Louis E., Tollerud, Erik, Anthony Tyson, J., Wang, Mei-Yu, Wechsler, Risa H., Wittman, David, Yu, Hai-Bo, Zaharijas, Gabrijela, Ali-Haimoud, Yacine, Annis, James, Birrer, Simon, Biswas, Rahul, Blazek, Jonathan, Brooks, Alyson M., Buckley-Geer, Elizabeth, Caputo, Regina, Charles, Eric, Digel, Seth, Dodelson, Scott, Flaugher, Brenna, Frieman, Joshua, Gawiser, Eric, Hearin, Andrew P., Hložek, Renee, Jain, Bhuvnesh, Jeltema, Tesla E., Koushiappas, Savvas M., Lisanti, Mariangela, Loverde, Marilena, Siddharth Mishra-Sharma, Newman, Jeffrey A., Nord, Brian, Nourbakhsh, Erfan, Ritz, Steven, Robertson, Brant E., Sánchez-Conde, Miguel A., Slosar, Anže, Tait, Tim M. P., Verma, Aprajita, Vilalta, Ricardo, Walter, Christopher W., Yanny, Brian, and Zentner, Andrew R.

Subjects
astro-ph.HE, High Energy Astrophysical Phenomena (astro-ph.HE), Cosmology and Nongalactic Astrophysics (astro-ph.CO), hep-ex, astro-ph.GA, Astrophysics::Instrumentation and Methods for Astrophysics, FOS: Physical sciences, hep-ph, Astrophysics::Cosmology and Extragalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, High Energy Physics - Experiment, High Energy Physics - Phenomenology, High Energy Physics - Experiment (hep-ex), High Energy Physics - Phenomenology (hep-ph), Astrophysics of Galaxies (astro-ph.GA), astro-ph.CO, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Astrophysical and cosmological observations currently provide the only robust, empirical measurements of dark matter. Future observations with Large Synoptic Survey Telescope (LSST) will provide necessary guidance for the experimental dark matter program. This white paper represents a community effort to summarize the science case for studying the fundamental physics of dark matter with LSST. We discuss how LSST will inform our understanding of the fundamental properties of dark matter, such as particle mass, self-interaction strength, non-gravitational couplings to the Standard Model, and compact object abundances. Additionally, we discuss the ways that LSST will complement other experiments to strengthen our understanding of the fundamental characteristics of dark matter. More information on the LSST dark matter effort can be found at https://lsstdarkmatter.github.io/ ., Comment: 96 pages, 22 figures, 1 table

28. Large Synoptic Survey Telescope: Dark Energy Science Collaboration

Author

Abate, Alexandra, Aldering, Greg, Allen, Steven W., Ansari, Reza, Antilogus, Pierre, Applegate, Douglas, Astier, Pierre, Aubourg, Eric, Bahcall, Neta A., Bard, Deborah, Barkhouse, Wayne A., Bartlett, James G., Bean, Rachel, Becker, Andrew, Beckmann, Volcker, Bernstein, Gary, Biswas, Rahul, Blanc, Guillaume, Bongard, Sebastien, Bosch, James, Boutigny, Dominique, Bradac, Marusa, Bradshaw, Andrew, Brunner, Robert J., Burchat, Patricia R., Burke, David L., Cahn, Robert, Campagne, Jean-Eric, Carrasco Kind, Matias, Chihway Chang, Cheu, Elliott C., Chiang, James, Cinabro, David, Claver, Chuck, Clowe, Douglas, Cohn, Joanne D., Connolly, Andrew, Cooray, Asantha, Croft, Rupert A. C., Cui, Wei, Cunha, Carlos, Antonio, Ian P., Digel, Seth W., Di Matteo, Tiziana, Dodelson, Scott, Dore, Olivier, Dubois, Richard, Dubois-Felsmann, Gregory P., Ealet, Anne, Escoffier, Stephanie, Fassnacht, Chris, Finley, David A., Fouchez, Dominique, Frieman, Joshua A., Ganga, Ken, Gangler, Emmanuel, Garzoglio, Gabriele, Gawiser, Eric, Gilman, Fred, Gilmore, Kirk, Gladney, Larry, Glanzman, Thomas, Gottschalk, Erik E., Gnedin, Nickolay Y., Gris, Philippe, Guy, Julien, Habib, Salman, Heitmann, Katrin, Hilbert, Stefan, Ho, Shirley, Hogan, Craig, Honscheid, Klaus, Huard, Zachary, Huff, Eric M., Ivezic, Zeljko, Jain, Bhuvnesh, Jarvis, Mike, Jee, M. James, Jeltema, Tesla, Jha, Saurabh W., Johns, Kenneth A., Johnson, Anthony S., Johnson, Robert P., Kahn, Steven M., Kent, Stephen, Kessler, Richard, Kiessling, Alina, Kim, Alex G., Kirkby, David, Kirshner, Robert P., Kovacs, Eve V., Knox, Lloyd, Kratochvil, Jan M., Kuhlmann, Steve, Levi, Michael, Li, Guoliang, Lin, Huan, Linder, Eric, Lupton, Robert, Ma, Zhaoming, Macintosh, Bruce, Mandelbaum, Rachel, Mantz, Adam, Marshall, Philip J., Marshall, Stuart, May, Morgan, Mcdonald, Patrick, Meadows, Brian, Melchior, Peter M., Menard, Brice, Moniez, Marc, Morandi, Andrea, Morris, R. Glenn, Newman, Jeffrey A., Neyrinck, Mark C., Nugent, Peter, O Connor, Paul, Olivier, Scot S., Padmanabhan, Nikhil, Pain, Reynald, Peng, En-Hsin, Perdereau, Olivier, Perlmutter, Saul, Peterson, John R., Petrosian, Vahé, Plaszczynski, Stephane, Pope, Adrian C., Raccanelli, Alvise, Rasmussen, Andrew, Reil, Kevin, Rhodes, Jason, Ricker, Paul M., Ricol, Jean-Stephane, Roe, Natalie, Roodman, Aaron, Rosenberg, Leslie, Roucelle, Cecile, Russo, Stefano, Sako, Masao, Schindler, Rafe H., Schmidt, Samuel J., Schneider, Michael D., Sehgal, Neelima, Seljak, Uros, Sembroski, Glenn, Seo, Hee-Jong, Shipsey, Ian, Singal, Jack, Spergel, David, Soares-Santos, Marcelle, Spinka, Harold, Stebbins, Albert, Strauss, Michael A., Stubbs, Christopher W., Tao, Charling, Thaler, Jon J., Thomas, Rollin C., Thorman, Paul A., Tilquin, Andre, Trac, Hy, Treu, Tommaso, Tristram, Matthieu, Tyson, J. Anthony, Wandelt, Benjamin D., Wang, Yun, Wechsler, Risa H., Wenaus, Torre, White, Martin, Wittman, David, Wood-Vasey, W. Michael, Xin, Bo, Yoachim, Peter, Zentner, Andrew R., and Zhan, Hu

29. Science-Driven Optimization of the LSST Observing Strategy

Author

Lsst, Science Collaboration, Marshall, Phil, Anguita, Timo, Bianco, Federica B., Bellm, Eric C., Brandt, Niel, Clarkson, Will, Connolly, Andy, Gawiser, Eric, Ivezic, Zeljko, Jones, Lynne, Lochner, Michelle, Lund, Michael B., Mahabal, Ashish, Nidever, David, Olsen, Knut, Ridgway, Stephen, Rhodes, Jason, Shemmer, Ohad, Trilling, David, Vivas, Kathy, Walkowicz, Lucianne, Willman, Beth, Yoachim, Peter, Anderson, Scott, Antilogus, Pierre, Angus, Ruth, Arcavi, Iair, Awan, Humna, Biswas, Rahul, Bell, Keaton J., Bennett, David, Britt, Chris, Buzasi, Derek, Casetti-Dinescu, Dana I., Chomiuk, Laura, Claver, Chuck, Cook, Kem, Davenport, James, Debattista, Victor, Digel, Seth, Doctor, Zoheyr, Firth, R. E., Foley, Ryan, Fong, Wen-Fai, Lluís Galbany, Giampapa, Mark, Gizis, John E., Graham, Melissa L., Grillmair, Carl, Gris, Phillipe, Haiman, Zoltan, Hartigan, Patrick, Hawley, Suzanne, Hlozek, Renee, Jha, Saurabh W., Johns-Krull, C., Kanbur, Shashi, Kalogera, Vassiliki, Kashyap, Vinay, Kasliwal, Vishal, Kessler, Richard, Kim, Alex, Kurczynski, Peter, Lahav, Ofer, Liu, Michael C., Malz, Alex, Margutti, Raffaella, Matheson, Tom, Mcewen, Jason D., Mcgehee, Peregrine, Meibom, Soren, Meyers, Josh, Monet, Dave, Neilsen, Eric, Newman, Jeffrey, O Dowd, Matt, Peiris, Hiranya V., Penny, Matthew T., Peters, Christina, Poleski, Radoslaw, Ponder, Kara, Richards, Gordon, Rho, Jeonghee, Rubin, David, Schmidt, Samuel, Schuhmann, Robert L., Shporer, Avi, Slater, Colin, Smith, Nathan, Soares-Santos, Marcelles, Stassun, Keivan, Strader, Jay, Strauss, Michael, Street, Rachel, Stubbs, Christopher, Sullivan, Mark, Szkody, Paula, Trimble, Virginia, Tyson, Tony, Val-Borro, Miguel, Valenti, Stefano, Wagoner, Robert, Wood-Vasey, W. Michael, Zauderer, Bevin Ashley, Laboratoire de Physique Nucléaire et de Hautes Énergies (LPNHE (UMR_7585)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris Diderot - Paris 7 (UPD7)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique de Clermont (LPC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Clermont Auvergne (UCA)-Centre National de la Recherche Scientifique (CNRS), LSST, Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), and Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA)

Subjects
Earth and Planetary Astrophysics (astro-ph.EP), Cosmology and Nongalactic Astrophysics (astro-ph.CO), Astrophysics - Solar and Stellar Astrophysics, Astrophysics of Galaxies (astro-ph.GA), FOS: Physical sciences, [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], Astrophysics - Instrumentation and Methods for Astrophysics, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], Instrumentation and Methods for Astrophysics (astro-ph.IM), Astrophysics - Astrophysics of Galaxies, Solar and Stellar Astrophysics (astro-ph.SR), Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Earth and Planetary Astrophysics
Abstract

The Large Synoptic Survey Telescope is designed to provide an unprecedented optical imaging dataset that will support investigations of our Solar System, Galaxy and Universe, across half the sky and over ten years of repeated observation. However, exactly how the LSST observations will be taken (the observing strategy or "cadence") is not yet finalized. In this dynamically-evolving community white paper, we explore how the detailed performance of the anticipated science investigations is expected to depend on small changes to the LSST observing strategy. Using realistic simulations of the LSST schedule and observation properties, we design and compute diagnostic metrics and Figures of Merit that provide quantitative evaluations of different observing strategies, analyzing their impact on a wide range of proposed science projects. This is work in progress: we are using this white paper to communicate to each other the relative merits of the observing strategy choices that could be made, in an effort to maximize the scientific value of the survey. The investigation of some science cases leads to suggestions for new strategies that could be simulated and potentially adopted. Notably, we find motivation for exploring departures from a spatially uniform annual tiling of the sky: focusing instead on different parts of the survey area in different years in a "rolling cadence" is likely to have significant benefits for a number of time domain and moving object astronomy projects. The communal assembly of a suite of quantified and homogeneously coded metrics is the vital first step towards an automated, systematic, science-based assessment of any given cadence simulation, that will enable the scheduling of the LSST to be as well-informed as possible., 312 pages, 90 figures. Browse the current version at https://github.com/LSSTScienceCollaborations/ObservingStrategy, new contributions welcome!

30. The Zwicky Transient Facility: Science Objectives

Author

Graham, Matthew J., Kulkarni, S. R., Bellm, Eric C., Adams, Scott M., Barbarino, Cristina, Blagorodnova, Nadejda, Bodewits, Dennis, Bolin, Bryce, Brady, Patrick R., Cenko, S. Bradley, Chang, Chan-Kao, Coughlin, Michael W., De, Kishalay, Eadie, Gwendolyn, Farnham, Tony L., Feindt, Ulrich, Franckowiak, Anna, Fremling, Christoffer, Gezari, Suvi, Ghosh, Shaon, Goldstein, Daniel A., Golkhou, V. Zach, Goobar, Ariel, Ho, Anna Y. Q., Huppenkothen, Daniela, Ivezić, Željko, Jones, R. Lynne, Juric, Mario, Kaplan, David L., Kasliwal, Mansi M., Kelley, Michael S. P., Kupfer, Thomas, Lee, Chien-De, Lin, Hsing Wen, Lunnan, Ragnhild, Mahabal, Ashish A., Miller, Adam A., Ngeow, Chow-Choong, Nugent, Peter, Ofek, Eran O., Prince, Thomas A., Rauch, Ludwig, Roestel, Jan Van, Schulze, Steve, Singer, Leo P., Sollerman, Jesper, Taddia, Francesco, Yan, Lin, Ye, Quan-Zhi, Yu, Po-Chieh, Barlow, Tom, Bauer, James, Beck, Ron, Belicki, Justin, Biswas, Rahul, Brinnel, Valery, Brooke, Tim, Bue, Brian, Bulla, Mattia, Burruss, Rick, Connolly, Andrew, Cromer, John, Cunningham, Virginia, Dekany, Richard, Delacroix, Alex, Desai, Vandana, Duev, Dmitry A., Feeney, Michael, Flynn, David, Frederick, Sara, Gal-Yam, Avishay, Giomi, Matteo, Groom, Steven, Hacopians, Eugean, Hale, David, Helou, George, Henning, John, Hover, David, Hillenbrand, Lynne A., Howell, Justin, Hung, Tiara, Imel, David, Ip, Wing-Huen, Jackson, Edward, Kaspi, Shai, Kaye, Stephen, Kowalski, Marek, Kramer, Emily, Kuhn, Michael, Landry, Walter, Laher, Russ R., Mao, Peter, Masci, Frank J., Monkewitz, Serge, Murphy, Patrick, Nordin, Jakob, Patterson, Maria T., Penprase, Bryan, Porter, Michael, Rebbapragada, Umaa, Reiley, Dan, Riddle, Reed, Rigault, Mickael, Rodriguez, Hector, Rusholme, Ben, Santen, Jakob Van, Shupe, David L., Smith, Roger M., Soumagnac, Maayane T., Stein, Robert, Surace, Jason, Szkody, Paula, Terek, Scott, Sistine, Angela Van, Velzen, Sjoert Van, Vestrand, W. Thomas, Walters, Richard, Ward, Charlotte, Zhang, Chaoran, and Zolkower, Jeffry

Subjects
14. Life underwater, 7. Clean energy
Abstract

Publications of the Astronomical Society of the Pacific 131(1001), 078001 (2019). doi:10.1088/1538-3873/ab006c, The Zwicky Transient Facility (ZTF), a public–private enterprise, is a new time-domain survey employing a dedicated camera on the Palomar 48-inch Schmidt telescope with a 47 deg2 field of view and an 8 second readout time. It is well positioned in the development of time-domain astronomy, offering operations at 10% of the scale and style of the Large Synoptic Survey Telescope (LSST) with a single 1-m class survey telescope. The public surveys will cover the observable northern sky every three nights in g and r filters and the visible Galactic plane every night in g and r. Alerts generated by these surveys are sent in real time to brokers. A consortium of universities that provided funding ("partnership") are undertaking several boutique surveys. The combination of these surveys producing one million alerts per night allows for exploration of transient and variable astrophysical phenomena brighter than r ~ 20.5 on timescales of minutes to years. We describe the primary science objectives driving ZTF, including the physics of supernovae and relativistic explosions, multi-messenger astrophysics, supernova cosmology, active galactic nuclei, and tidal disruption events, stellar variability, and solar system objects., Published by Univ. of Chicago Press, Journals Division10692, Chicago, Ill.

31. LSST Science Book, Version 2.0

Author

Lsst, Science Collaboration, Abell, Paul A., Allison, Julius, Anderson, Scott F., Andrew, John R., Angel, J. Roger P., Armus, Lee, Arnett, David, Asztalos, S. J., Axelrod, Tim S., Bailey, Stephen, Ballantyne, D. R., Bankert, Justin R., Barkhouse, Wayne A., Barr, Jeffrey D., Barrientos, L. Felipe, Barth, Aaron J., Bartlett, James G., Becker, Andrew C., Becla, Jacek, Beers, Timothy C., Bernstein, Joseph P., Biswas, Rahul, Blanton, Michael R., Bloom, Joshua S., Bochanski, John J., Boeshaar, Pat, Borne, Kirk D., Bradac, Marusa, Brandt, W. N., Bridge, Carrie R., Brown, Michael E., Brunner, Robert J., Bullock, James S., Burgasser, Adam J., Burge, James H., Burke, David L., Cargile, Phillip A., Chandrasekharan, Srinivasan, Chartas, George, Chesley, Steven R., Chu, You-Hua, Cinabro, David, Claire, Mark W., Claver, Charles F., Clowe, Douglas, Connolly, A. J., Cook, Kem H., Cooke, Jeff, Cooray, Asantha, Covey, Kevin R., Culliton, Christopher S., Jong, Roelof, Vries, Willem H., Debattista, Victor P., Delgado, Francisco, Antonio, Ian P., Dhital, Saurav, Di Stefano, Rosanne, Dickinson, Mark, Dilday, Benjamin, Djorgovski, S. G., Dobler, Gregory, Donalek, Ciro, Dubois-Felsmann, Gregory, Durech, Josef, Eliasdottir, Ardis, Eracleous, Michael, Eyer, Laurent, Falco, Emilio E., Fan, Xiaohui, Fassnacht, Christopher D., Ferguson, Harry C., Fernandez, Yanga R., Fields, Brian D., Finkbeiner, Douglas, Figueroa, Eduardo E., Fox, Derek B., Francke, Harold, Frank, James S., Frieman, Josh, Fromenteau, Sebastien, Furqan, Muhammad, Galaz, Gaspar, Gal-Yam, A., Garnavich, Peter, Gawiser, Eric, Geary, John, Gee, Perry, Gibson, Robert R., Gilmore, Kirk, Grace, Emily A., Green, Richard F., Gressler, William J., Grillmair, Carl J., Habib, Salman, Haggerty, J. S., Hamuy, Mario, Harris, Alan W., Hawley, Suzanne L., Heavens, Alan F., Hebb, Leslie, Henry, Todd J., Hileman, Edward, Hilton, Eric J., Hoadley, Keri, Holberg, J. B., Holman, Matt J., Howell, Steve B., Infante, Leopoldo, Ivezic, Zeljko, Jacoby, Suzanne H., Jain, Bhuvnesh, R, Jedicke, Jee, M. James, Garrett Jernigan, J., Jha, Saurabh W., Johnston, Kathryn V., Jones, R. Lynne, Juric, Mario, Kaasalainen, Mikko, Styliani, Kafka, Kahn, Steven M., Kaib, Nathan A., Kalirai, Jason, Kantor, Jeff, Kasliwal, Mansi M., Keeton, Charles R., Kessler, Richard, Knezevic, Zoran, Kowalski, Adam, Krabbendam, Victor L., Krughoff, K. Simon, Kulkarni, Shrinivas, Kuhlman, Stephen, Lacy, Mark, Lepine, Sebastien, Liang, Ming, Lien, Amy, Lira, Paulina, Long, Knox S., Lorenz, Suzanne, Lotz, Jennifer M., Lupton, R. H., Lutz, Julie, Macri, Lucas M., Mahabal, Ashish A., Mandelbaum, Rachel, Marshall, Phil, May, Morgan, Mcgehee, Peregrine M., Meadows, Brian T., Meert, Alan, Milani, Andrea, Miller, Christopher J., Miller, Michelle, Mills, David, Minniti, Dante, Monet, David, Mukadam, Anjum S., Nakar, Ehud, Neill, Douglas R., Newman, Jeffrey A., Nikolaev, Sergei, Nordby, Martin, O Connor, Paul, Oguri, Masamune, Oliver, John, Olivier, Scot S., Olsen, Julia K., Olsen, Knut, Olszewski, Edward W., Oluseyi, Hakeem, Padilla, Nelson D., Parker, Alex, Pepper, Joshua, Peterson, John R., Petry, Catherine, Pinto, Philip A., Pizagno, James L., Popescu, Bogdan, Prsa, Andrej, Radcka, Veljko, Raddick, M. Jordan, Rasmussen, Andrew, Rau, Arne, Rho, Jeonghee, Rhoads, James E., Richards, Gordon T., Ridgway, Stephen T., Robertson, Brant E., Roskar, Rok, Saha, Abhijit, Sarajedini, Ata, Scannapieco, Evan, Schalk, Terry, Schindler, Rafe, Schmidt, Samuel, Schmidt, Sarah, Schneider, Donald P., Schumacher, German, Scranton, Ryan, Sebag, Jacques, Seppala, Lynn G., Ohad Shemmer, Simon, Joshua D., Sivertz, M., Smith, Howard A., Allyn Smith, J., Smith, Nathan, Spitz, Anna H., Stanford, Adam, Stassun, Keivan G., Strader, Jay, Strauss, Michael A., Stubbs, Christopher W., Sweeney, Donald W., Szalay, Alex, Szkody, Paula, Takada, Masahiro, Thorman, Paul, Trilling, David E., Trimble, Virginia, Tyson, Anthony, Berg, Richard, Vanden Berk, Daniel, Vanderplas, Jake, Verde, Licia, Vrsnak, Bojan, Walkowicz, Lucianne M., Wandelt, Benjamin D., Wang, Sheng, Wang, Yun, Warner, Michael, Wechsler, Risa H., West, Andrew A., Wiecha, Oliver, Williams, Benjamin F., Willman, Beth, Wittman, David, Wolff, Sidney C., Wood-Vasey, W. Michael, Wozniak, Przemek, Young, Patrick, Zentner, Andrew, Zhan, Hu, APC - Cosmologie, AstroParticule et Cosmologie (APC (UMR_7164)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), LSST, Bartlett, James, Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), Physique Corpusculaire et Cosmologie - Collège de France (PCC), Collège de France (CdF)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Collège de France (CdF)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-AstroParticule et Cosmologie (APC (UMR_7164)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Observatoire de Paris, and PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7)

Subjects
Active galactic nucleus, Cosmology and Nongalactic Astrophysics (astro-ph.CO), [SDU.ASTR.CO]Sciences of the Universe [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO], media_common.quotation_subject, Milky Way, FOS: Physical sciences, Large Synoptic Survey Telescope, Astrophysics::Cosmology and Extragalactic Astrophysics, Astrophysics, 01 natural sciences, [PHYS.ASTR.CO]Physics [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO], 0103 physical sciences, Solar and Stellar Astrophysics, 010303 astronomy & astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM), Weak gravitational lensing, Solar and Stellar Astrophysics (astro-ph.SR), Astrophysics::Galaxy Astrophysics, media_common, Physics, Earth and Planetary Astrophysics (astro-ph.EP), [SDU.ASTR.CO] Sciences of the Universe [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO], 010308 nuclear & particles physics, Astrophysics::Instrumentation and Methods for Astrophysics, Astronomy, Cosmology and Extragalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Redshift, Galaxy, Astrophysics - Solar and Stellar Astrophysics, Sky, [PHYS.ASTR.CO] Physics [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO], Astrophysics of Galaxies (astro-ph.GA), Dark energy, Instrumentation and Methods for Astrophysics, Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics, Galaxy Astrophysics, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Earth and Planetary Astrophysics
Abstract

A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade. The Large Synoptic Survey Telescope (LSST) will have an effective aperture of 6.7 meters and an imaging camera with field of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over 20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a total point-source depth of r~27.5. The LSST Science Book describes the basic parameters of the LSST hardware, software, and observing plans. The book discusses educational and outreach opportunities, then goes on to describe a broad range of science that LSST will revolutionize: mapping the inner and outer Solar System, stellar populations in the Milky Way and nearby galaxies, the structure of the Milky Way disk and halo and other objects in the Local Volume, transient and variable objects both at low and high redshift, and the properties of normal and active galaxies at low and high redshift. It then turns to far-field cosmological topics, exploring properties of supernovae to z~1, strong and weak lensing, the large-scale distribution of galaxies and baryon oscillations, and how these different probes may be combined to constrain cosmological models and the physics of dark energy., 596 pages. Also available at full resolution at http://www.lsst.org/lsst/scibook

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