LSST Science Book, Version 2.0

Abell, P. A.; Allison, Julius; Anderson, Scott F.; Andrew, John; Angel, J. R. P.; Armus, L.; Arnett, David; Asztalos, S. J.; Axelrod, T. S.; Bailey, S.; Ballantyne, D. R.; Bankert, J.; Barkhouse, W. A.; Barr, Jeffrey D.; Barrientos, L. Felipe; Barth, Aaron J.; Bartlett, J. G.; Becker, A. C.; Becla, Jacek; Beers, Timothy C.; Bernstein, Joseph P.; Biswas, Rahul; Blanton, Michael R.; Bloom, J.; Bochanski, John J.; Boeshaar, Pat; Borne, K. D.; Bradač, Maruša; Brandt, W. N.; Bridge, Carrie; Brown, Michael E.; Brunner, Róbert; Bullock, James S.; Burgasser, Adam J.; Burge, James H.; Burke, D. L.; Cargile, Phillip A.; Chandrasekharan, Srinivasan; Chartas, G.; Chesley, Steven R.; Chu, You‐Hua; Cinabro, D.; Claire, Mark; Claver, Charles F.; Clowe, Douglas; Connolly, Andrew J.; Cook, K. H.; Cooke, Jeff; Cooray, Asantha; Covey, Kevin R.; Culliton, Christopher S.; Jong, Roelof de; Vries, W. H. de; Debattista, Victor P.; Delgado, Francisco; Dell’Antonio, Ian; Dhital, Saurav; Stefano, Rosanne Di; Dickinson, Mark; Dilday, Benjamin; Djorgovski, S. G.; Dobler, Gregory; Donalek, C.; Dubois-Felsmann, G. P.; Ďurech, Josef; Elíasdóttir, Árdís; Eracleous, Michael; Eyer, L.; Falco, E.; Fan, Xiaohui; Fassnacht, Christopher D.; Ferguson, Harry; Fernández, Yanga; Fields, Brian D.; Finkbeiner, Douglas P.; Figueroa, Eduardo E.; Fox, D. B.; Francke, Harold; Frank, James S.; Frieman, J.; Fromenteau, S.; Furqan, Muhammad; Galaz, Gaspar; Gal‐Yam, A.; Garnavich, P.; Gawiser, Eric; Geary, John C.; Gee, Perry M.; Gibson, R. R.; Gilmore, K.; Grace, E.; Green, Richard F.; Gressler, William J.; Grillmair, Carl J.; Habib, Salman; Haggerty, J. S.; Hamuy, M.; Harris, Alan W.; Hawley, Suzanne L.; Heavens, Alan; Hebb, Leslie; Henry, Todd J.; Hileman, Edward A.; Hilton, Eric J.; Hoadley, Keri; Holberg, J. B.; Holman, M.; Howell, Steve B.; Infante, L.; Ivezić, Željko; Jacoby, Suzanne; Jain, Bhuvnesh; Jedicke,; Jee, M. James; Jernigan, J. G.; Jha, Saurabh W.; Johnston, Kathryn V.; Jones, R. Lynne; Jurić, Mario; Kaasalainen, M.; Styliani,; Kafka,; Kahn, S. M.; Kaib, Nathan A.; Kalirai, Jason; Kantor, J.; Kasliwal, M. M.; Keeton, Charles R.; Keßler, R.; Knežević, Ž.; Kowalski, Adam F.; Krabbendam, Victor L.; Krughoff, K. Simon; Kulkarni, S. R.; Kuhlman, S.; Lacy, Mark; Lépine, Sébastien; Liang, Ming; Lien, A. Y.; Lira, P.; Long, Knox S.; Lorenz, Suzanne; Lotz, Jennifer M.; Lupton, Robert H.; Lutz, J. H.; Macri, L. M.; Mahabal, A.; Mandelbaum, Rachel; Marshall, Phil; May, M.; McGehee, P.; Meadows, B.; Meert, A.; Milani, Andrea; Miller, Christopher J.; Miller, M. C.; Mills, David; Minniti, D.; Monet, D. G.; Mukadam, Anjum S.; Nakar, Ehud; Neill, Douglas R.; Newman, Jeffrey A.; Nikolaev, Sergei; Nordby, M.; O’Connor, P.; Oguri, Masamune; Oliver, J.; Olivier, Scot S.; Olsen, Julia K.; Olsen, Knut; Olszewski, Edward W.; Oluseyi, Hakeem M.; Padilla, Nelson; Parker, A. H.; Pepper, Joshua; Peterson, J. R.; Petry, C. E.; Pinto, Philip A.; Pizagno, James; Popescu, Bogdan; Prša, Andrej; Radcka, Veljko; Raddick, M. Jordan; Rasmussen, Andrew; Rau, A.; Rho, Jeonghee; Rhoads, James E.; Richards, Gordon T.; Ridgway, Stephen T.; Robertson, Brant; Roškar, Rok; Saha, Abhijit; Sarajedini, Ata; Scannapieco, Evan; Schalk, T.; Schindler, R. H.; Schmidt, Samuel J.; Schmidt, Sarah J.; Schneider, Donald P.; Schumacher, Germán; Scranton, Ryan; Sebag, Jacques; Seppala, Lynn G.; Shemmer, Ohad; Simon, Joshua D.; Sivertz, M.; Smith, H. A.; Smith, Jennifer; Smith, Nathan; Spitz, Anna H.; Stanford, Adam; Stassun, Keivan G.; Strader, Jay; Strauss, Michael A.; Stubbs, C. W.; Sweeney, Donald W.; Szalay, A. S.; Szkody, Paula; Takada, Masahiro; Thorman, Paul; Trilling, David E.; Trimble, Virginia; Tyson, A.; Berg, R. Van; Berk, Daniel Vanden; Vanderplas, Jake; Verde, Licia; Vršnak, Bojan; Walkowicz, Lucianne M.; Wandelt, B. 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. M.; Woźniak, P. R.; Young, Patrick; Zentner, Andrew R.; Zhan, Hu

doi:10.48550/arxiv.0912.0201

Cited by 568 publications

(757 citation statements)

References 8 publications

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“…Weak Lensing: The sample of billions of galaxies produced by LSST will be by far the largest ever compiled [1]. Measuring the cosmological weak gravitational lensing signal of this galaxy sample will yield unprecedented constraints on cosmology, as this is one of the most powerful and direct probes of cosmology.…”

Section: Static Sciencementioning

confidence: 99%

“…Large-Scale Structure and Galaxy Clusters: The same enormous dataset of galaxies will allow the use of cutting-edge analysis techniques, such as galaxy-galaxy correlations, cross-correlation with weak lensing, counts of galaxy clusters, and cross correlation with the CMB [1]. Large-scale structure studies will place constraints on primordial fluctuations that are competitive with those from the CMB and will allow stringent tests of non-Gaussianity.…”

Section: Static Sciencementioning

confidence: 99%

“…Supernovae: LSST will produce a catalog of hundreds of thousands of type Ia supernovae (SNIa), the exact number being highly dependent on the observing strategy, allowing unprecedented tests of cosmology with supernovae alone [1]. The sheer number of objects will also enable the study of the evolution of supernova intrinsic properties with redshift, as well as the impact of galaxy type and environment on cosmological constraints.…”

Section: Transient Sciencementioning

confidence: 99%

“…• We note that a rolling cadence 3 may be required to achieve this frequency of inter-night visits but more study is needed to determine this. 1 We use the following quality cuts: SNR> 5 in at least 3 bands, 5 visits before peak and 10 after peak in any band and the error on the color parameter σ c < 0.04.…”

Section: High-level Descriptionmentioning

confidence: 99%

See 3 more Smart Citations

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

Lochner¹,

Scolnic²,

Awan³

et al. 2018

Preprint

Self Cite

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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 2×15s 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.

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Section: Static Sciencementioning

confidence: 99%

Section: Static Sciencementioning

confidence: 99%

Section: Transient Sciencementioning

confidence: 99%

Section: High-level Descriptionmentioning

confidence: 99%

See 2 more Smart Citations

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

Lochner¹,

Scolnic²,

Awan³

et al. 2018

Preprint

Self Cite

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“…Accessing the sub-mm sky is essential for two reasons: (i) probing rest-frame frequencies close to the peak of the thermal dust emission to obtain accurate estimates of the total L IR and dust temperature; and (ii) targeting the key diagnostic FIR lines [25] across all redshifts, from the peak epoch of galaxy formation at z ≈ 1-2 to earlier times (e.g., [C II] is observed at 474 µm at z = 2). We envision a simple, but highly versatile large-area blind imaging and spectroscopic survey with strong legacy value in and of itself and with a high degree of complementarity to existing and future projects such as Large Synoptic Survey Telescope (LSST, [26]), Euclid, [27], WFIRST [28], SPHEREx [29], Athena [30] and Square Kilometer Array (SKA) surveys. To lay out the broad science themes, feasibility and basic requirements of such a survey, let us focus on a new facility called the Atacama Large-Aperture Sub-mm/mm Telescope (AtLAST) 1 .…”

Section: A Sub-millimeter Spectroscopic Surveymentioning

confidence: 99%

The case for a 'sub-millimeter SDSS': a 3D map of galaxy evolution to z~10

Geach,

Banerji,

Bertoldi

et al. 2019

Preprint

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The Sloan Digital Sky Survey (SDSS) was revolutionary because of the extraordinary breadth and ambition of its optical imaging and spectroscopy. We argue that a 'sub-millimeter SDSS' -a sensitive large-area imaging+spectroscopic survey in the sub-mm window -will revolutionize our understanding of galaxy evolution in the early Universe. By detecting the thermal dust continuum emission and atomic and molecular line emission of galaxies out to z ≈ 10 it will be possible to measure the redshifts, star formation rates, dust and gas content of hundreds of thousands of high-z galaxies down to ∼L . Many of these galaxies will have counterparts visible in the deep optical imaging of the Large Synoptic Survey Telescope. This 3D map of galaxy evolution will span the peak epoch of galaxy formation all the way back to cosmic dawn, measuring the co-evolution of the star formation rate density and molecular gas content of galaxies, tracking the production of metals and charting the growth of large-scale structure.

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Standard Model mass spectrum in inflationary universe

Chen

Wang

Xianyu

2017

J. High Energ. Phys.

111

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We work out the Standard Model (SM) mass spectrum during inflation with quantum corrections, and explore its observable consequences in the squeezed limit of nonGaussianity. Both non-Higgs and Higgs inflation models are studied in detail. We also illustrate how some inflationary loop diagrams can be computed neatly by Wick-rotating the inflation background to Euclidean signature and by dimensional regularization.

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LSST Science Book, Version 2.0

Cited by 568 publications

References 8 publications

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

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

The case for a 'sub-millimeter SDSS': a 3D map of galaxy evolution to z~10

Standard Model mass spectrum in inflationary universe

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