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Astrophysics with Terabytes
Astrophysics with Terabytes Alex Szalay The Johns Hopkins University Jim Gray Microsoft Research Living in an Exponential World • Astronomers have a few hundred TB now – 1 pixel (byte) / sq arc second ~ 4TB – Multi-spectral, temporal, … _ 1PB • They mine it looking for 1000 new (kinds of) objects or more of interesting ones (quasars), 100 density variations in 400-D space 10 correlations in 400-D space 1 • Data doubles every year 0.1 2000 1995 1990 1985 1980 1975 1970 CCDs Glass The Challenges Exponential data growth: Distributed collections Soon Petabytes Data Collection Discovery Publishing and Analysis New analysis paradigm: New publishing paradigm: Data federations, Scientists are publishers Move analysis to data and Curators Why Is Astronomy Special? • Especially attractive for the wide public • Community is not very large • It has no commercial value – No privacy concerns, freely share results with others – Great for experimenting with algorithms • It is real and well documented – High-dimensional (with confidence intervals) – Spatial, temporal • Diverse and distributed – Many different instruments from many different places and many different times • The questions are interesting • There is a lot of it (soon petabytes) The Virtual Observatory • Premise: most data is (or could be online) • The Internet is the world’s best telescope: – It has data on every part of the sky – In every measured spectral band: optical, x-ray, radio.. – As deep as the best instruments (2 years ago). – It is up when you are up – The “seeing” is always great – It’s a smart telescope: links objects and data to literature on them • Software became the capital expense – Share, standardize, reuse. -
Things You Need to Know About Big Data
Critical Missions Are Built On NetApp NetApp’s Big Data solutions deliver high performance computing, full motion video (FMV) and intelligence, surveillance and reconnaissance (ISR) capabilities to support national safety, defense and intelligence missions and scientific research. UNDERWRITTEN BY To learn more about how NetApp and VetDS can solve your big data challenges, call us at 919.238.4715 or visit us online at VetDS.com. ©2011 NetApp. All rights reserved. Specifications are subject to change without notice. NetApp, the NetApp logo, and Go further, faster are trademarks or registered trademarks of NetApp, Inc. in the United States and/or other countries. All other brands or products are trademarks or registered trademarks of their respective holders and should be treated as such. Critical Missions Are Things You NeedBuilt On NetApp to Know About Big Data NetApp’s Big Data solutions deliver high Big data has been making big news in fields rangingperformance from astronomy computing, full motionto online video advertising. (FMV) and intelligence, surveillance and By Joseph Marks The term big data can be difficult to pin down because it reconnaissanceshows up in (ISR) so capabilities many toplaces. support Facebook national safety, defense and intelligence crunches through big data on your user profile and friend networkmissions and to scientific deliver research. micro-targeted ads. Google does the same thing with Gmail messages, Search requests and YouTube browsing. Companies including IBM are sifting through big data from satellites, the Global Positioning System and computer networks to cut down on traffic jams and reduce carbon emissions in cities. And researchers are parsing big data produced by the Hubble Space Telescope, the Large Hadron Collider and numerous other sources to learn more about the nature and origins of the universe. -
The Wigglez Dark Energy Survey: Probing the Epoch of Radiation Domination Using Large-Scale Structure
MNRAS 429, 1902–1912 (2013) doi:10.1093/mnras/sts431 The WiggleZ Dark Energy Survey: probing the epoch of radiation domination using large-scale structure Gregory B. Poole,1,2‹ Chris Blake,1 David Parkinson,3 Sarah Brough,4 Matthew Colless,4 Carlos Contreras,1 Warrick Couch,1 Darren J. Croton,1 Scott Croom,5 Tamara Davis,3 Michael J. Drinkwater,3 Karl Forster,6 David Gilbank,7 Mike Gladders,8 Karl Glazebrook,1 Ben Jelliffe,5 Russell J. Jurek,9 I-hui Li,10 Barry Madore,11 D. Christopher Martin,6 Kevin Pimbblet,12 Michael Pracy,1,13 4,13 1,14 15 Rob Sharp, Emily Wisnioski, David Woods, Downloaded from Ted K. Wyder6 and H. K. C. Yee10 1Centre for Astrophysics & Supercomputing, Swinburne University of Technology, PO Box 218, Hawthorn, VIC 3122, Australia 2School of Physics, University of Melbourne, Parksville, VIC 3010, Australia 3School of Mathematics and Physics, University of Queensland, Brisbane, QLD 4072, Australia 4Australian Astronomical Observatory, PO Box 915, North Ryde, NSW 1670, Australia http://mnras.oxfordjournals.org/ 5Sydney Institute for Astronomy, School of Physics, University of Sydney, NSW 2006, Australia 6California Institute of Technology, MC 278-17, 1200 East California Boulevard, Pasadena, CA 91125, USA 7South African Astronomical Observatory, PO Box 9, 7935 Observatory, Cape Town, South Africa 8Department of Astronomy and Astrophysics, University of Chicago, 5640 South Ellis Avenue, Chicago, IL 60637, USA 9Australia Telescope National Facility, CSIRO, Epping, NSW 1710, Australia 10Department of Astronomy and Astrophysics, -
Gerard Lemson Alex Szalay, Mike Rippin DIBBS/Sciserver Collaborative Data-Driven Science
Collaborative data-driven science Gerard Lemson Alex Szalay, Mike Rippin DIBBS/SciServer Collaborative data-driven science } Started with the SDSS SkyServer } Built in a few months in 2001 } Goal: instant access to rich content } Idea: bring the analysis to the data } Interac@ve access at the core } Much of the scien@fic process is about data ◦ Data collec@on, data cleaning, data archiving, data organizaon, data publishing, mirroring, data distribu@on, data analy@cs, data curaon… 2 Collaborative data-driven science Form Based Queries 3 Collaborative data-driven science Image Access Collaborative data-driven science Custom SQL Collaborative data-driven science Batch Queries, MyDB Collaborative data-driven science Cosmological Simulations Collaborative data-driven science Turbulence Database Collaborative data-driven science Web Service Access through Python Collaborative data-driven science } Interac@ve science on petascale data } Sustain and enhance our astronomy effort } Create scalable open numerical laboratories } Scale system to many petabytes } Deep integraon with the “Long Tail” } Large footprint across many disciplines ◦ Also: Genomics, Oceanography, Materials Science } Use commonly shared building blocks } Major naonal and internaonal impact 10 Collaborative data-driven science } Offer more compung resources server side } Augment and combine SQL queries with easy- to-use scrip@ng tools } Heavy use of virtual machines } Interac@ve portal via iPython/Matlab/R } Batch jobs } Enhanced visualizaon tools 11 Collaborative data-driven science -
The Wigglez Dark Energy Survey
The WiggleZ Dark Energy Survey Chris Blake (Swinburne University) Sarah Brough, Warrick Couch, Karl Glazebrook, Greg Poole (Swinburne University); Tamara Davis, Michael Drinkwater, Russell Jurek, Kevin Pimbblet (Uni. of Queensland); Matthew Colless, Rob Sharp (Anglo-Australian Observatory); Scott Croom (University of Sydney); Michael Pracy (Australian National University); David Woods (University of New South Wales); Barry Madore (OCIW); Chris Martin, Ted Wyder (Caltech) Abstract: The accelerating expansion rate of the Universe, attributed to “dark energy”, has no accepted theoretical explanation. The origin of this phenomenon unambiguously implicates new physics via a novel form of matter exerting neg- ative pressure or an alteration to Einstein’s General Relativity. These profound consequences have inspired a new generation of cosmological surveys which will measure the influence of dark energy using various techniques. One of the forerun- ners is the WiggleZ Survey at the Anglo-Australian Telescope, a new large-scale high-redshift galaxy survey which is now 50% complete and scheduled to finish in 2010. The WiggleZ project is aiming to map the cosmic expansion history using delicate features in the galaxy clustering pattern imprinted 13.7 billion years ago. In this article we outline the survey design and context, and predict the likely science highlights. Figure 1: Caption: The distribution of galaxies currently observed in the three WiggleZ Survey fields located near the Northern Galactic Pole. The observer is situated at the origin of the co-ordinate system. The radial distance of each galaxy from the origin indicates the observed redshift, and the polar angle indicates the galaxy right ascension. The faint patterns of galaxy clustering are visible in each field. -
Harnessing Grid Resources to Enable the Dynamic Analysis of Large Astronomy Datasets Year 1 Progress Report & Year 2 Proposal
January 27, 2007 NASA GSRP Proposal Page 1 of 5 Ioan Raicu Harnessing Grid Resources to Enable the Dynamic Analysis of Large Astronomy Datasets Year 1 Progress Report & Year 2 Proposal 1 Year 1 Proposal In order to setup the context for this progress report, this section covers a brief motivation for our work and summarizes the Year 1 Proposal we originally submitted under grant number NNA06CB89H. Large datasets are being produced at a very fast pace in the astronomy domain. In principle, these datasets are most valuable if and only if they are made available to the entire community, which may have tens to thousands of members. The astronomy community will generally want to perform various analyses on these datasets to be able to extract new science and knowledge that will both justify the investment in the original acquisition of the datasets as well as provide a building block for other scientists and communities to build upon to further the general quest for knowledge. Grid Computing has emerged as an important new field focusing on large-scale resource sharing and high- performance orientation. The Globus Toolkit, the “de facto standard” in Grid Computing, offers us much of the needed middleware infrastructure that is required to realize large scale distributed systems. We proposed to develop a collection of Web Services-based systems that use grid computing to federate large computing and storage resources for dynamic analysis of large datasets. We proposed to build a Globus Toolkit 4 based prototype named the “AstroPortal” that would support the “stacking” analysis on the Sloan Digital Sky Survey (SDSS). -
Universal Distance Scale E NCYCLOPEDIAOF a STRONOMYAND a STROPHYSICS
Universal Distance Scale E NCYCLOPEDIAOF A STRONOMYAND A STROPHYSICS Universal Distance Scale from key project Cepheid distances are surface brightness fluctuations in galaxies, the globular cluster luminosity The HUBBLE CONSTANT is the local expansion rate of the function, the planetary nebula luminosity function and the universe, local in space and local in time. The equation expanding photospheres method for type II supernovae. of uniform expansion is One-step methods v H r (1) = 0 Critics of both the above approaches point to the propagation of errors in a three-step ladder from where v is recession velocity and r is distance from the trigonometric parallaxes to Cepheids to secondary observer. To measure the proportionality constant, we distance indicators to H0. One-step methods to determine adopt a definition of the Hubble constant as the asymptotic H0 include GRAVITATIONAL LENSING of distant QUASARS value of the ratio of recession velocity to distance, in the by intervening mass concentrations, which results in limit that the effect of random velocities of galaxies is measurable phase delays between images of the time- negligible. In galactic structure the velocity of the local varying input signal from the source. Where these phase standard of rest has wider significance for the dynamics delays can be accurately determined, and when the model of the Milky Way than the velocity of the Sun. We have mass distribution can be uniquely inferred, they directly to abstract the Hubble constant from local motions in a lead to z/H0, where z is the REDSHIFT of the lens (Turner similar way. 1997). -
The H-Index in Australian Astronomy
Addenda: The h-index in Australian Astronomy Kevin A. PimbbletA,B A School of Physics, Monash University, Clayton, VIC 3800, Australia B Email: [email protected] Abstract: Pimbblet (2011) published an evaluation of the Hirsch h-index in the context of the Aus- tralian astronomical community. This addenda adds treatment of changes of surname to the compu- tation of the h-index and presents derivative data on the m-index. Keywords: Errata, Addenda 1 Change of Surname Table 1: Top 10 h-index for Australian Astron- Pimbblet (2011) published a variety of analyses on the omy, excluding overseas professionals with correc- h-index (e.g. Hirsch 2005) in the context of Australian tion applied for surname changes. Astronomy. Alongside that, a discussion of a number Rank Name h of caveats was also made. One further caveat merits =1 KenFREEMAN 77 explicit attention in the interpretation of the h-index: =1 JeremyMOULD 77 changes of surname. In the Pimbblet (2011) analysis, 3 Karl GLAZEBROOK 71 no attempt was made to track surname changes. This 4 Dick MANCHESTER 68 has the effect of depressing the h-index of individuals 5 MichaelDOPITA 64 who have changed their names over the years. Its effect can readily be seen in Table 1 where we re-compute the 6 Warrick COUCH 61 top ten h-index for Australian Astronomy and account 7 Joss BLAND-HAWTHORN 57 for changing surnames: Bland-Hawthorn’s previous h- 8 MatthewCOLLESS 56 index was suppressed by 4 points by not taking this in 9 Brian SCHMIDT 54 to account. We emphasize that the same dataset was 10 MikeBESSELL 53 used for this re-computation as the original paper. -
Warmth Elevating the Depths: Shallower Voids with Warm Dark Matter
MNRAS 451, 3606–3614 (2015) doi:10.1093/mnras/stv1087 Warmth elevating the depths: shallower voids with warm dark matter Lin F. Yang,1‹ Mark C. Neyrinck,1 Miguel A. Aragon-Calvo,´ 2 Bridget Falck3 and Joseph Silk1,4,5 1Department of Physics & Astronomy, The Johns Hopkins University, 3400 N Charles Street, Baltimore, MD 21218, USA 2Department of Physics and Astronomy, University of California, Riverside, CA 92521, USA 3Institute of Cosmology and Gravitation, University of Portsmouth, Dennis Sciama Building, Burnaby Rd, Portsmouth PO1 3FX, UK 4Institut d’Astrophysique de Paris – 98 bis boulevard Arago, F-75014 Paris, France 5Beecroft Institute of Particle Astrophysics and Cosmology, Department of Physics, University of Oxford, Denys Wilkinson Building, 1 Keble Road, Oxford OX1 3RH, UK Downloaded from https://academic.oup.com/mnras/article/451/4/3606/1101530 by guest on 28 September 2021 Accepted 2015 May 12. Received 2015 May 1; in original form 2014 December 11 ABSTRACT Warm dark matter (WDM) has been proposed as an alternative to cold dark matter (CDM), to resolve issues such as the apparent lack of satellites around the Milky Way. Even if WDM is not the answer to observational issues, it is essential to constrain the nature of the dark matter. The effect of WDM on haloes has been extensively studied, but the small-scale initial smoothing in WDM also affects the present-day cosmic web and voids. It suppresses the cosmic ‘sub- web’ inside voids, and the formation of both void haloes and subvoids. In N-body simulations run with different assumed WDM masses, we identify voids with the ZOBOV algorithm, and cosmic-web components with the ORIGAMI algorithm. -
The EMU View of the Large Magellanic Cloud: Troubles for Sub-Tev Wimps
Prepared for submission to JCAP The EMU view of the Large Magellanic Cloud: Troubles for sub-TeV WIMPs Marco Regis,a;b Javier Reynoso-Cordova,a;b Miroslav D. Filipovi´c,c Marcus Br¨uggen,d Ettore Carretti,e Jordan Collier,f;c Andrew M. Hopkins,g;c Emil Lenc,h Umberto Maio,i Joshua R. Marvil,l Ray P. Norris,c;h and Tessa Vernstromm aDipartimento di Fisica, Universit`adi Torino, via P. Giuria 1, I{10125 Torino, Italy bIstituto Nazionale di Fisica Nucleare, Sezione di Torino, via P. Giuria 1, I{10125 Torino, Italy cWestern Sydney University, Locked Bag 1797, Penrith South DC, NSW 2751, Aus- tralia dUniversity of Hamburg, Gojenbergsweg 112, 21029 Hamburg, Germany eINAF Istituto di Radioastronomia, via Gobetti 101, 40129 Bologna, Italy f University of Cape Town, The Inter-University Institute for Data Intensive Astron- omy (IDIA), Department of Astronomy, Private Bag X3, Rondebosch 7701, South Africa gAustralian Astronomical Optics, Macquarie University, 105 Delhi Rd, North Ryde, NSW 2113, Australia hCSIRO, Space and Astronomy, PO Box 76, Epping, NSW 1710, Australia iINAF - Italian National Institute for Astrophysics, Observatory of Trieste, via G. Tiepolo 11, 34143 Trieste, Italy lNational Radio Astronomy Observatory, P.O. Box O, Socorro, NM 87801, USA mCSIRO Astronomy and Space Science, Kensington Perth 6151, Australia Abstract. We present a radio search for WIMP dark matter in the Large Magellanic Cloud (LMC). We make use of a recent deep image of the LMC obtained from obser- arXiv:2106.08025v1 [astro-ph.HE] 15 Jun 2021 vations of the Australian Square Kilometre Array Pathfinder (ASKAP), and processed as part of the Evolutionary Map of the Universe (EMU) survey. -
Large Scale Structures of the Universe Proceedings of the 130Th Symposium of the International Astronomical Union, Dedicated to the Memory of Marc A
springer.com Physics : Astronomy, Observations and Techniques Audouze, J., Pelletan, M.-C., Szalay, A. (Eds.) Large Scale Structures of the Universe Proceedings of the 130th Symposium of the International Astronomical Union, Dedicated to the Memory of Marc A. Aaronson (1950–1987), Held in Balatonfured, Hungary, June 15–20, 1987 Ten years ago in August 1977 Malcom Longair and Jan Einasto organized IAU Symposium nO 79 on exactly the same exciting and most important topic i.e. the Large Scale Structure of the Universe. Many of us have the recollection of an outstanding meeting which fulfilled two goals (i) establish most of the foundation of a fast growing field (ii) set up a confrontation between the excellent observational and theoretical work performed in eastern and western countries. A decade after such a meeting Alex Szalay and I have felt the need to reassemble the Springer cosmologists working actively on problems dealing with the Uni• verse as a whole. Indeed a 1988, XXXIV, 622 p. lot of progress has been achieved in the building of large surveys in the discovery of voids, 1st sponges and filaments in the galaxy clus• ter distribution, in refined numerical simulations, in edition experimental and theoretical particle physics (outcome of new particles (cold particles) and unification (GUT, supersymmetry) schemes), in research of quantum gravity and inflation scenarios etc ... A new confrontation between all the specialists working all throughout the Printed book world on such questions appeared to us to be most timely. This is why the location of Hardcover Balatonfiired in Hungary to be accessible to anyone as Tallin in 1977 has been chosen. -
2016 – Aug – 09 CURRICULUM VITAE Mike Specian Contact
2016 – Aug – 09 CURRICULUM VITAE Mike Specian Contact Information: Home Address: 7023 Heathfield Rd.; Baltimore, MD 21212 Mobile: (443) 653-1690 Email: [email protected], [email protected] Webpage: www.mikespecian.com Twitter: @mspecian Education: 2009-2015 – Ph.D., Johns Hopkins University, astrophysics Dissertation: Improved Galaxy Counting Techniques and Noise Reduction Algorithms as Applied to the Sloan Digital Sky Survey, advisor: Prof. Alex Szalay 2004-2009 – M.A., Johns Hopkins University, astrophysics 1999-2003 – B.A. cum laude and with distinction, Boston University, joint concentration in physics and astronomy Professional History: 2016-present Visiting Scientist – Johns Hopkins University – same Work as When I Was an assistant research scientist, but With a different title 2016 Guest Instructor, Beth Tfiloh Dahan Community School – taught classes to prepare high school students for the AP Physics exam 2015 Assistant Research Scientist, Johns Hopkins University – research focused on making corrections to the Sloan Digital Sky Survey footprint, mapping galaxies Without redshifts, applying noise filters to galaxy overdensities 2012-2013 Scientific Consultant, US Global Change Research Program’s National Climate Assessment; Washington, DC – provide recommendations of physical climate change indicators to the technical team 2012-2013 Member, Media and Message Working Group for MD House of Delegates Campaign; Baltimore County, MD – conduct background research on House of Delegates members, write Op-Eds, contribute to campaign strategy