Gaia: Mapping the Milky Way
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1 Gaia: Mapping the Milky Way (A very brief overview, and something about the Swedish participation) Lennart Lindegren Lund Observatory Department of Astronomy and Theoretical Physics Lund University 1
2 Gaia in a nutshell ESA mission Launch: March 2013 Main objective is astrometry: positions, proper motions and parallaxes (distances) for one billion stars (magnitude 6-20) Major H/W elements are being integrated (EADS Astrium) - see following pictures Preparing the data processing that will produce the Gaia Catalogue is a major ongoing science effort (DPAC = Data Processing and Analysis Consortium) - end ca See 2
3 One of the two primary mirrors 3
4 November 2010
5 Torus with some of the mirrors mounted (drawing) 5
6 Optical instrument (drawing) Primary mirror 1.45 x 0.5 m 2 Torus (optical bench) Bipods for spacecraft mounting Radial Velocity Spectrograph Focal Plane Assembly 6
7 Blazed transmission grating (flight model) Etched binary pattern 5 µm RVS = Radial Velocity Spectrometer (slitless spectrograph, nm) Credits: EADS Astrium, IOF Jena, Selex Galileo Wedge lenses 7
8 Science with Gaia Stellar astrophysics: accurate (< 1%) parallax distances to 10 7 stars luminosities, masses, ages, distance scale census of binaries and (large) planetary companions Galactic astronomy (near-field cosmology): stellar kinematics + astrophysical parameters for large samples history of star formation, mergers and dynamical perturbations dark matter distribution on small scales (~100 pc) Solar system and fundamental physics: extremely accurate orbits for asteroids: dynamical families, masses, occultation predictions, near-earth objects tests of General Relativity (PPN γ, β, quadrupole moment) 8
9 Predicted astrometric performance Sky-averaged standard errors for G0V stars V magnitude mag Parallax µas Proper motion µas/yr µas Note: 20 µas = rad (the size of a pin-head at 10,000 km) 20 µas parallax error = 10% distance error at 5 kpc (K2III is V = 14) 9
10 Gaia - schedule Proposal Concept & Technology Study Mission Selection now Definition Re-Assessment Study Phase B1 Selection of Prime Contractor (EADS Astrium) Implementation Operation Data Processing Studies Phase B2 Phase C/D Software Development Launch - March 2013 Scientific operation Nominal Extended Mission Data Processing Mission Products Intermediate Final 10
11 Gaia - organization 11
12 ESA and DPAC responsibilities Mission operations centre Data acquisition Telemetry data Data processing Final results positions proper motions parallaxes radial velocities magnitudes variability orbits, masses T eff, log g catalogue access 12
13 Gaia Data Processing and Analysis Consortium (DPAC) CU : Coordination Unit DPC : Data Processing Centre Steering Committee Gaia Project Team DPACE Gaia Project Scientist CU1 System Architecture Lund Uppsala Gaia Science Team CU2 Simulation CU3 Core Processing CU4 Object Processing CU5 Photometric Processing CU6 Spectroscopic Processing CU7 Variability Processing CU8 Astrophysical parameters CU9 Archive Access DPC ESAC DPC Barcelona DPC Torino DPC Cambridge DPC Geneva DPC CNES 13
14 Swedish participation in DPAC According to the multilateral agreement, Sweden will provide the definition, design, development, validation and maintenance of: 1. The main algorithms for the Astrometric Global Iterative Solution (AGIS) including the solution of attitude and astrometric calibration (for CU3) Lund team (Lennart Lindegren, David Hobbs, Berry Holl) 2. Synthetic stellar spectra, covering the known range of main physical parameters, required for the photometric and spectroscopic data processing (for CU8); ground-based observations for Gaia Uppsala team (Andreas Korn, Ulrike Heiter, Bengt Edvardsson, Kjell Eriksson, Bengt Gustafsson, Oleg Kochukhov, Paul Barklem) 14
15 Swedish participation (wider context) Science applications of the core astrometry algorithms (Lund): Daniel Michalik (PhD project: Nano-JASMINE astrometry - next slide) NN (PhD project: Fundamental physics with Gaia) Chris Skoog, Adriaan Ludl (MSc projects) Gaia Research for European Astronomy Training (GREAT): ESF-supported Research Networking Programme (RNP) Supports workshops, conferences, visiting researchers EU-FP7 Initial Training Network (ITN) - PhD position (Lund) European network in preparation for Gaia follow-up (ground-based obs): Co-PIs for Swedish participation: Sofia Feltzing (Lund) Andreas Korn (Uppsala) GAIA-ESO Survey - proposed spectroscopic survey Proposed multi-object spectrographs (4MOST, MOONS, WEAVE) 15
16 Nano-JASMINE Flight model (Oct 2010) Credit: JASMINE Team First Japanese space astrometry mission Technical demonstrator for JASMINE (IR pointed imaging) Size: 50 x 50 x 50 cm, 35 kg 5 cm telescope, 0.5 FoV (x 2) 1k x 1k CCD ( µm) ~ 1 mas (10 6 stars ) Launch August 2011 (Ukrainian rocket from Brazil) Collaboration with Gaia/CU3 teams at ESAC and Lund for the astrometric solution (Daniel Michalik) 16
17 Astrometric Global Iterative Solution (AGIS) Experimental [small-scale] setup (AGISLab) Stellar astrometric parameters (s) must be solved together with: the satellite attitude (a) the calibration parameters (c) any global parameters (g) such as PPN γ Direct solution impossible must use iterative solution algorithms Data Initial star catalogue g s AGIS c a Final star catalogue 17
18 Iterative astrometric solution for 100,000 stars (using CG): Error in parallax (solution - true) in successive iterations µas 18
19 Same run, comparing errors and updates Initial errors ~0.1 arcsec RMS error & update [µas] After 30 iterations the astrometric errors level out at ~10 µas due to photon noise Updates Errors After 85 iterations: RMS updates ~10-5 µas due to numerical noise Iteration number Credit: Hobbs & Holl (2010) 19
20 Conclusions Two years from launch: Preparations for the data processing going ahead at full speed Crucial contributions by teams in Uppsala and Lund Lots of progress Even more still to be done... Gaia has become a focus point for European collaboration in galactic and stellar astronomy and a catalyst for many other science activities spectroscopic surveys, ground-based follow-up observations, improved theoretical models, large-scale statistical analysis methods,... JASMINE collaboration: an unexpected but interesting addition Support from many sources gratefully acknowledged: SNSB, LU, UU, EU (FP6 & FP7), VR, ESF, ESA 20
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