GW Observations with INTEGRAL and XMM-Newton – the Operational Perspective
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
ESA Missions AO Analysis
ESA Announcements of Opportunity Outcome Analysis Arvind Parmar Head, Science Support Office ESA Directorate of Science With thanks to Kate Isaak, Erik Kuulkers, Göran Pilbratt and Norbert Schartel (Project Scientists) ESA UNCLASSIFIED - For Official Use The ESA Fleet for Astrophysics ESA UNCLASSIFIED - For Official Use Dual-Anonymous Proposal Reviews | STScI | 25/09/2019 | Slide 2 ESA Announcement of Observing Opportunities Ø Observing time AOs are normally only used for ESA’s observatory missions – the targets/observing strategies for the other missions are generally the responsibility of the Science Teams. Ø ESA does not provide funding to successful proposers. Ø Results for ESA-led missions with recent AOs presented: • XMM-Newton • INTEGRAL • Herschel Ø Gender information was not requested in the AOs. It has been ”manually” derived by the project scientists and SOC staff. ESA UNCLASSIFIED - For Official Use Dual-Anonymous Proposal Reviews | STScI | 25/09/2019 | Slide 3 XMM-Newton – ESA’s Large X-ray Observatory ESA UNCLASSIFIED - For Official Use Dual-Anonymous Proposal Reviews | STScI | 25/09/2019 | Slide 4 XMM-Newton Ø ESA’s second X-ray observatory. Launched in 1999 with annual calls for observing proposals. Operational. Ø Typically 500 proposals per XMM-Newton Call with an over-subscription in observing time of 5-7. Total of 9233 proposals. Ø The TAC typically consists of 70 scientists divided into 13 panels with an overall TAC chair. Ø Output is >6000 refereed papers in total, >300 per year ESA UNCLASSIFIED - For Official Use -
Asteroseismology with Corot, Kepler, K2 and TESS: Impact on Galactic Archaeology Talk Miglio’S
Asteroseismology with CoRoT, Kepler, K2 and TESS: impact on Galactic Archaeology talk Miglio’s CRISTINA CHIAPPINI Leibniz-Institut fuer Astrophysik Potsdam PLATO PIC, Padova 09/2019 AsteroseismologyPlato as it is : a Legacy with CoRoT Mission, Kepler for Galactic, K2 and TESS: impactArchaeology on Galactic Archaeology talk Miglio’s CRISTINA CHIAPPINI Leibniz-Institut fuer Astrophysik Potsdam PLATO PIC, Padova 09/2019 Galactic Archaeology strives to reconstruct the past history of the Milky Way from the present day kinematical and chemical information. Why is it Challenging ? • Complex mix of populations with large overlaps in parameter space (such as Velocities, Metallicities, and Ages) & small volume sampled by current data • Stars move away from their birth places (migrate radially, or even vertically via mergers/interactions of the MW with other Galaxies). • Many are the sources of migration! • Most of information was confined to a small volume Miglio, Chiappini et al. 2017 Key: VOLUME COVERAGE & AGES Chiappini et al. 2018 IAU 334 Quantifying the impact of radial migration The Rbirth mix ! Stars that today (R_now) are in the green bins, came from different R0=birth Radial Migration Sources = bar/spirals + mergers + Inside-out formation (gas accretion) GalacJc Center Z Sun R Outer Disk R = distance from GC Minchev, Chiappini, MarJg 2013, 2014 - MCM I + II A&A A&A 558 id A09, A&A 572, id A92 Two ways to expand volume for GA • Gaia + complementary photometric information (but no ages for far away stars) – also useful for PIC! • Asteroseismology of RGs (with ages!) - also useful for core science PLATO (miglio’s talk) The properties at different places in the disk: AMR CoRoT, Gaia+, K2 + APOGEE Kepler, TESS, K2, Gaia CoRoT, Gaia+, K2 + APOGEE PLATO + 4MOST? Predicon: AMR Scatter increases towards outer regions Age scatter increasestowars outer regions ExtracGng the best froM GaiaDR2 - Anders et al. -
LISA, the Gravitational Wave Observatory
The ESA Science Programme Cosmic Vision 2015 – 25 Christian Erd Planetary Exploration Studies, Advanced Studies & Technology Preparations Division 04-10-2010 1 ESAESA spacespace sciencescience timelinetimeline JWSTJWST BepiColomboBepiColombo GaiaGaia LISALISA PathfinderPathfinder Proba-2Proba-2 PlanckPlanck HerschelHerschel CoRoTCoRoT HinodeHinode AkariAkari VenusVenus ExpressExpress SuzakuSuzaku RosettaRosetta DoubleDouble StarStar MarsMars ExpressExpress INTEGRALINTEGRAL ClusterCluster XMM-NewtonXMM-Newton CassiniCassini-H-Huygensuygens SOHOSOHO ImplementationImplementation HubbleHubble OperationalOperational 19901990 19941994 19981998 20022002 20062006 20102010 20142014 20182018 20222022 XMM-Newton • X-ray observatory, launched in Dec 1999 • Fully operational (lost 3 out of 44 X-ray CCD early in mission) • No significant loss of performances expected before 2018 • Ranked #1 at last extension review in 2008 (with HST & SOHO) • 320 refereed articles per year, with 38% in the top 10% most cited • Observing time over- subscribed by factor ~8 • 2,400 registered users • Largest X-ray catalogue (263,000 sources) • Best sensitivity in 0.2-12 keV range • Long uninterrupted obs. • Follow-up of SZ clusters 04-10-2010 3 INTEGRAL • γ-ray observatory, launched in Oct 2002 • Imager + Spectrograph (E/ΔE = 500) + X- ray monitor + Optical camera • Coded mask telescope → 12' resolution • 72 hours elliptical orbit → low background • P/L ~ nominal (lost 4 out 19 SPI detectors) • No serious degradation before 2016 • ~ 90 refereed articles per year • Obs -
Data Mining in the Spanish Virtual Observatory. Applications to Corot and Gaia
Highlights of Spanish Astrophysics VI, Proceedings of the IX Scientific Meeting of the Spanish Astronomical Society held on September 13 - 17, 2010, in Madrid, Spain. M. R. Zapatero Osorio et al. (eds.) Data mining in the Spanish Virtual Observatory. Applications to Corot and Gaia. Mauro L´opez del Fresno1, Enrique Solano M´arquez1, and Luis Manuel Sarro Baro2 1 Spanish VO. Dep. Astrof´ısica. CAB (INTA-CSIC). P.O. Box 78, 28691 Villanueva de la Ca´nada, Madrid (Spain) 2 Departamento de Inteligencia Artificial. ETSI Inform´atica.UNED. Spain Abstract Manual methods for handling data are impractical for modern space missions due to the huge amount of data they provide to the scientific community. Data mining, understood as a set of methods and algorithms that allows us to recover automatically non trivial knowledge from datasets, are required. Gaia and Corot are just a two examples of actual missions that benefits the use of data mining. In this article we present a brief summary of some data mining methods and the main results obtained for Corot, as well as a description of the future variable star classification system that it is being developed for the Gaia mission. 1 Introduction Data in Astronomy is growing almost exponentially. Whereas projects like VISTA are pro- viding more than 100 terabytes of data per year, future initiatives like LSST (to be operative in 2014) and SKY (foreseen for 2024) will reach the petabyte level. It is, thus, impossible a manual approach to process the data returned by these surveys. It is impossible a manual approach to process the data returned by these surveys. -
Two Fundamental Theorems About the Definite Integral
Two Fundamental Theorems about the Definite Integral These lecture notes develop the theorem Stewart calls The Fundamental Theorem of Calculus in section 5.3. The approach I use is slightly different than that used by Stewart, but is based on the same fundamental ideas. 1 The definite integral Recall that the expression b f(x) dx ∫a is called the definite integral of f(x) over the interval [a,b] and stands for the area underneath the curve y = f(x) over the interval [a,b] (with the understanding that areas above the x-axis are considered positive and the areas beneath the axis are considered negative). In today's lecture I am going to prove an important connection between the definite integral and the derivative and use that connection to compute the definite integral. The result that I am eventually going to prove sits at the end of a chain of earlier definitions and intermediate results. 2 Some important facts about continuous functions The first intermediate result we are going to have to prove along the way depends on some definitions and theorems concerning continuous functions. Here are those definitions and theorems. The definition of continuity A function f(x) is continuous at a point x = a if the following hold 1. f(a) exists 2. lim f(x) exists xœa 3. lim f(x) = f(a) xœa 1 A function f(x) is continuous in an interval [a,b] if it is continuous at every point in that interval. The extreme value theorem Let f(x) be a continuous function in an interval [a,b]. -
Herschel Space Observatory and the NASA Herschel Science Center at IPAC
Herschel Space Observatory and The NASA Herschel Science Center at IPAC u George Helou u Implementing “Portals to the Universe” Report April, 2012 Implementing “Portals to the Universe”, April 2012 Herschel/NHSC 1 [OIII] 88 µm Herschel: Cornerstone FIR/Submm Observatory z = 3.04 u Three instruments: imaging at {70, 100, 160}, {250, 350 and 500} µm; spectroscopy: grating [55-210]µm, FTS [194-672]µm, Heterodyne [157-625]µm; bolometers, Ge photoconductors, SIS mixers; 3.5m primary at ambient T u ESA mission with significant NASA contributions, May 2009 – February 2013 [+/-months] cold Implementing “Portals to the Universe”, April 2012 Herschel/NHSC 2 Herschel Mission Parameters u Userbase v International; most investigator teams are international u Program Model v Observatory with Guaranteed Time and competed Open Time v ESA “Corner Stone Mission” (>$1B) with significant NASA contributions v NASA Herschel Science Center (NHSC) supports US community u Proposals/cycle (2 Regular Open Time cycles) v Submissions run 500 to 600 total, with >200 with US-based PI (~x3.5 over- subscription) u Users/cycle v US-based co-Investigators >500/cycle on >100 proposals u Funding Model v NASA funds US data analysis based on ESA time allocation u Default Proprietary Data Period v 6 months now, 1 year at start of mission Implementing “Portals to the Universe”, April 2012 Herschel/NHSC 3 Best Practices: International Collaboration u Approach to projects led elsewhere needs to be designed carefully v NHSC Charter remains firstly to support US community v But ultimately success of THE mission helps everyone v Need to express “dual allegiance” well and early to lead/other centers u NHSC became integral part of the larger team, worked for Herschel success, though focused on US community participation v Working closely with US community reveals needs and gaps for all users v Anything developed by NHSC is available to all users of Herschel v Trust follows from good teaming: E.g. -
MATH 1512: Calculus – Spring 2020 (Dual Credit) Instructor: Ariel
MATH 1512: Calculus – Spring 2020 (Dual Credit) Instructor: Ariel Ramirez, Ph.D. Email: [email protected] Office: LRC 172 Phone: 505-925-8912 OFFICE HOURS: In the Math Center/LRC or by Appointment COURSE DESCRIPTION: Limits. Continuity. Derivative: definition, rules, geometric and rate-of- change interpretations, applications to graphing, linearization and optimization. Integral: definition, fundamental theorem of calculus, substitution, applications to areas, volumes, work, average. Meets New Mexico Lower Division General Education Common Core Curriculum Area II: Mathematics (NMCCN 1614). (4 Credit Hours). Prerequisites: ((123 or ACCUPLACER College-Level Math =100-120) and (150 or ACT Math =28- 31 or SAT Math Section =660-729)) or (153 or ACT Math =>32 or SAT Math Section =>730). COURSE OBJECTIVES: 1. State, motivate and interpret the definitions of continuity, the derivative, and the definite integral of a function, including an illustrative figure, and apply the definition to test for continuity and differentiability. In all cases, limits are computed using correct and clear notation. Student is able to interpret the derivative as an instantaneous rate of change, and the definite integral as an averaging process. 2. Use the derivative to graph functions, approximate functions, and solve optimization problems. In all cases, the work, including all necessary algebra, is shown clearly, concisely, in a well-organized fashion. Graphs are neat and well-annotated, clearly indicating limiting behavior. English sentences summarize the main results and appropriate units are used for all dimensional applications. 3. Graph, differentiate, optimize, approximate and integrate functions containing parameters, and functions defined piecewise. Differentiate and approximate functions defined implicitly. 4. Apply tools from pre-calculus and trigonometry correctly in multi-step problems, such as basic geometric formulas, graphs of basic functions, and algebra to solve equations and inequalities. -
The GAIA/CHEOPS Synergy
The GAIA/CHEOPS synergy Valerio Nascimbeni (INAF-OAPD) and the CHEOPS A1 working group CHEOPS Science workshop #3, Madrid 2015 Jun 17-19 Introduction GAIA is the most accurate (~10 μas) astrometric survey ever; it was launched in 2013 and is performing well (though some technical issues) Final catalog is expected in ≥2022, with a few intermediate releases starting from 2016 What planets (or planetary candidates) can GAIA provide to CHEOPS? This was investigated within the CHEOPS A1 WG, designed to 1) build an overview of available targets, 2) monitor present and future planet-search surveys, 3) establishing selection criteria for CHEOPS, 4) and proposing strategies to build the target list. CHEOPS Science workshop #3, Madrid 2015 Jun 17-19 The GAIA/CHEOPS synergy We started reviewing some recent works about the GAIA planet yield: ▶ Casertano+ 2008, A&A 482, 699. “Double-blind test program for astrometric planet detection with GAIA” ▶ Perryman+ 2014, Apj 797, 14. “Astrometric Exoplanet Detection with GAIA” ▶ Dzigan & Zucker 2012, ApJ 753, 1. “Detection of Transiting Jovian Exoplanets by GAIA Photometry” ▶ Sozzetti+ 2014, MNRAS 437, 497, “Astrometric detection of giant planets around nearby M dwarfs: the GAIA potential” ▶ Lucy 2014, A&A 571, 86. “Analysing weak orbital signals in GAIA data” ▶ Sahlmann+ 2015, MNRAS 447, 287. “GAIA's potential for the discovery of circumbinary planets” CHEOPS Science workshop #3, Madrid 2015 Jun 17-19 “Photometric” planets Challenges of GAIA planets discovered by photometry: ▶ GAIA's photometric detection of transiting planets will be limited by precision (1 mmag) and especially by the sparse sampling of the scanning law (Dzigan & Zucker 2012) ▶ Nearly all those planets will be VHJ (P < 3 d); only ~40 of them will be robustly detected and bright enough for CHEOPS (G < 12). -
ARIEL – 13Th Appleton Space Conference PLANETS ARE UBIQUITOUS
Background image credit NASA ARIEL – 13th Appleton Space Conference PLANETS ARE UBIQUITOUS OUR GALAXY IS MADE OF GAS, STARS & PLANETS There are at least as many planets as stars Cassan et al, 2012; Batalha et al., 2015; ARIEL – 13th Appleton Space Conference 2 EXOPLANETS TODAY: HUGE DIVERSITY 3700+ PLANETS, 2700 PLANETARY SYSTEMS KNOWN IN OUR GALAXY ARIEL – 13th Appleton Space Conference 3 HUGE DIVERSITY: WHY? FORMATION & EVOLUTION PROCESSES? MIGRATION? INTERACTION WITH STAR? Accretion Gaseous planets form here Interaction with star Planet migration Ices, dust, gas ARIEL – 13th Appleton Space Conference 4 STAR & PLANET FORMATION/EVOLUTION WHAT WE KNOW: CONSTRAINTS FROM OBSERVATIONS – HERSCHEL, ALMA, SOLAR SYSTEM Measured elements in Solar system ? Image credit ESA-Herschel, ALMA (ESO/NAOJ/NRAO), Marty et al, 2016; André, 2012; ARIEL – 13th Appleton Space Conference 5 THE SUN’S PLANETS ARE COLD SOME KEY O, C, N, S MOLECULES ARE NOT IN GAS FORM T ~ 150 K Image credit NASA Juno mission, NASA Galileo ARIEL – 13th Appleton Space Conference 6 WARM/HOT EXOPLANETS O, C, N, S (TI, VO, SI) MOLECULES ARE IN GAS FORM Atmospheric pressure 0.01Bar H2O gas CO2 gas CO gas CH4 gas HCN gas TiO gas T ~ 500-2500 K Condensates VO gas H2S gas 1 Bar Gases from interior ARIEL – 13th Appleton Space Conference 7 CHEMICAL MEASUREMENTS TODAY SPECTROSCOPIC OBSERVATIONS WITH CURRENT INSTRUMENTS (HUBBLE, SPITZER,SPHERE,GPI) • Precision of 20 ppm can be reached today by Hubble-WFC3 • Current data are sparse, instruments not absolutely calibrated • ~ 40 planets analysed -
The Evolution of the Milky Way's Radial Metallicity Gradient As Seen By
Astronomy in Focus - XXX Proceedings IAU Symposium No. XXX, 2018 c International Astronomical Union 2020 M. T. Lago, ed. doi:10.1017/S174392131900423X The evolution of the Milky Way’s radial metallicity gradient as seen by APOGEE, CoRoT, and Gaia Friedrich Anders, Ivan Minchev and Cristina Chiappini Leibniz-Institut f¨ur Astrophysik Potsdam (AIP), An der Sternwarte 16, 14482 Potsdam, Germany Abstract. The time evolution of the radial metallicity gradient is one of the most important constraints for Milky Way chemical and chemo-dynamical models. In this talk we reviewed the status of the observational debate and presented a new measurement of the age dependence of the radial abundance gradients, using combined asteroseismic and spectroscopic observations of red giant stars. We compared our results to state-of-the-art chemo-dynamical Milky Way models and recent literature results obtained with open clusters and planetary nebulae, and propose a new method to infer the past history of the Galactic radial abundance profile. Keywords. stars: asteroseismology, stars: late-type, stars: abundances, stars: distances, stars: ages, Galaxy: stellar content, Galaxy: evolution In Anders et al. (2017), we used combined asteroseismic CoRoT and spectroscopic APOGEE observations of 418 red giants located close to the Galactic disc plane (6 kpc <RGal < 13 kpc) to derive the age dependence of the Milky Way’s radial metallic- ity gradient. The radial iron gradient traced by the youngest red-giant population (−0.058 ± 0.008 ± 0.003 dex/kpc) reproduces the results obtained with young Cepheids and HII regions, while for the 1-4 Gyr population we obtain a slightly steeper gradient (−0.066 ± 0.007 ± 0.002 dex/kpc). -
Arxiv:2007.10189V2 [Astro-Ph.SR] 26 Jul 2020
Astronomy & Astrophysics manuscript no. worley_k2ges c ESO 2020 July 28, 2020 The Gaia-ESO Survey: Spectroscopic-asteroseismic analysis of K2 stars in Gaia-ESO The K2 Galactic Caps Project C. C. Worley1, P. Jofré2, B. Rendle3, A. Miglio3, L. Magrini4, D. Feuillet5;12, A. Gavel6, R. Smiljanic7, K. Lind5;6;21, A. Korn6, G. Gilmore1, S. Randich4, A. Hourihane1, A. Gonneau1, P. Francois8, J. Lewis1, G. Sacco4, A. Bragaglia11, U. Heiter6, S. Feltzing12, T. Bensby12, M. Irwin1, E. Gonzalez Solares1, D. Murphy1, A. Bayo19;22, L. Sbordone17, T. Zwitter18, A. C. Lanzafame10, N. Walton1, S. Zaggia9, E. J. Alfaro13, L. Morbidelli4, S. Sousa14, L. Monaco15, G. Carraro16, and C. Lardo20 (Affiliations can be found after the references) Received ; accepted ABSTRACT Context. The extensive stellar spectroscopic datasets that are available for studies in Galactic Archeaology thanks to, for example, the Gaia-ESO Survey, now benefit from having a significant number of targets that overlap with asteroseismology projects such as Kepler, K2, and CoRoT. Combining the measurements from spectroscopy and asteroseismology allows us to attain greater accuracy with regard to the stellar parameters needed to characterise the stellar populations of the Milky Way. Aims. The aim of this Gaia-ESO Survey special project is to produce a catalogue of self-consistent stellar parameters by combining measurements from high-resolution spectroscopy and precision asteroseismology. Methods. We carried out an iterative analysis of 90 K2@Gaia-ESO red giants. The spectroscopic values of Teff were used as input in the seismic analysis to obtain log g values. The seismic estimates of log g were then used to re-determine the spectroscopic values of Teff and [Fe/H]. -
Differentiating an Integral
Differentiating an Integral P. Haile, February 2020 b(t) Leibniz Rule. If (t) = a(t) f(z, t)dz, then R d b(t) @f(z, t) db da = dz + f (b(t), t) f (a(t), t) . dt @t dt dt Za(t) That’s the rule; now let’s see why this is so. We start by reviewing some things you already know. Let f be a smooth univariate function (i.e., a “nice” function of one variable). We know from the fundamental theorem of calculus that if the function is defined as x (x) = f(z) dz Zc (where c is a constant) then d (x) = f(x). (1) dx You can gain some really useful intuition for this by remembering that the x integral c f(z) dz is the area under the curve y = f(z), between z = a and z = x. Draw this picture to see that as x increases infinitessimally, the added contributionR to the area is f (x). Likewise, if c (x) = f(z) dz Zx then d (x) = f(x). (2) dx Here, an infinitessimal increase in x reduces the area under the curve by an amount equal to the height of the curve. Now suppose f is a function of two variables and define b (t) = f(z, t)dz (3) Za where a and b are constants. Then d (t) b @f(z, t) = dz (4) dt @t Za i.e., we can swap the order of the operations of integration and differentiation and “differentiate under the integral.” You’ve probably done this “swapping” 1 before.