1 / 24

PLATO INPUT CATALOG (PIC)

PLATO INPUT CATALOG (PIC). Giampaolo Piotto Dipartimento di Astronomia Universita’ di Padova. exoplanets around bright and nearby stars. PLATO target samples. > 20,000 bright ( ~ m V ≤11) cool dwarfs/subgiants (>F5V&IV): exoplanet transits AND

melia
Download Presentation

PLATO INPUT CATALOG (PIC)

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. PLATO INPUT CATALOG (PIC) Giampaolo Piotto Dipartimento di Astronomia Universita’ di Padova

  2. exoplanets around bright and nearby stars PLATO targetsamples > 20,000 bright (~ mV≤11) cool dwarfs/subgiants (>F5V&IV): exoplanet transits AND seismic analysis of their host stars AND ultra-high precision RV follow-up noise < 2.7 10-5 in 1hr for >2 years >3,000 very bright (mV≤8) cool dwarfs/subgiants for >2 months >1,000 very bright (mV≤8) cool dwarfs/subgiants for >2 years > 6,000 nearby M-dwarfs (mV≤15) noise < 8. 10-4 in 1hr for >2 years > 6,000 nearby M-dwarfs (mV≤15) noise < 8. 10-4 in 1hr for >2 months > 250,000 cool dwarfs/subgiants(~ mV≤13) exoplanet transits + RV follow-up noise < 8.10-5 in 1hrfor >2 years

  3. Sky coverage Observation strategy: 1. two long pointings : 3 years or 2 years 2. « step&stare » phase (1 or 2 years) : N fields 2-5 months each ≈ 2000 sqdeg Kepler PLATO CoRoT CoRoT PLATO 20,000 sqdeg  50% of the sky !

  4. How Kepler selected its targets The Kepler Field is narrower (~ 110 sq°) and deeper (V <~ 16) than the Plato Field. Batalha et al. (2010) builded the Kepler Input Catalog from aground-based photometric surveyin broad-band (Sloan griz) and intermediate band (e.g. DDO51) filters. Classification was performed by choosing the most probable parameters following a Bayesian approach and was found to be ~90% reliable (confirmed in flight). Synthetic photometry shows that well-chosen intermediate and UV bands are very effective in breaking the degeneracies between log g, Te, [M/H] (Zdanavicius 2005). • A similarphotometriccampaignisnotfeasiblefor the PlatoFields! Still, we must consider the photometric surveys: • For the optimal selection of long term PLATO fields (at least, the first one) • As a backup solution? In this case, additional observations are needed. Teig (2008)‏

  5. How shall we select PLATO targets? 1. GAIA, starting with GAIA early release catalog 2. Available ground-based and space catalogs Once the targets will be selected, we need, for each target, to include a list of parameters for target prioritization, final target selection, and for the target characterization. The target list and their parameters will constitute the PLATO Input Catalog (PIC)

  6. Allowed pointing regions celestial equator =0 galactic plane b=0 ecliptic latitude =60 Kepler Field (actual)‏ ~PLATO field The center of the two long duration (LD)pointing fields must be located within 30 deg from the ecliptic poles (|β|>60, R-SCI-040). Thus the allowed regions are two 2750 deg2 caps at |δ|>40. Each Plato FOV will cover ~2000 deg2 During the 5-yr mission (LD+S&S phases) up ~50% of the sky will be covered by Plato! We need an unprecedented all-sky stellar classification (V<13) to select the fields and the targets.

  7. How to separate dwarfs from giants TRILEGAL simulated CMD of 10 deg2 at b=20, V<11.Suitable Plato targets are within the blue box The Plato Stellar Samples P1,P2,P3,P5 must be late-type (SpT>F5) dwarfs and subgiants. Both observations and simulations show that, in a typical magnitude-limited field close to the galactic plane, most stars are giants and early-type MS stars. In principle, the best techniques to identify our targets are: spectroscopy parallaxes narrow-band photometry (e.g. KIC)‏ These data are available only on limited regions of the sky, for certain spectral types or only for very bright stars (i.e. V≤7.5 for Hipparcos). At the present time, an all-sky classification of faint stars (V<13, samples P1&P5) has to rely only on broad-band magnitudes and proper motions.

  8. Available and forthcoming catalogs 2MASS provides accurate (dm~0.01 mag) all-sky NIR photometry down to V~16 Tycho-2 provides accurate all-sky B,V photometry and astrometry down to V~11.5 UCAC3 provides accurate astrometry (PM) down to V~16. No accurate all-sky VIS photometry is currently available for V>11.5 UV all-sky photometry will be provided only by forthcoming surveys. What can we do with the available catalogs?

  9. Classification from broad-band photometry Deriving stellar parameters from broad-band photometry is challenging, as the effects of gravity on colors are small (few 0.01 magtipically) and strongly degenerated with reddening and metallicity on some regions of the parameter space. Many attempts have used Tycho-2 BTVT and 2MASS JHK magnitudes as input: Ammonset al. (2006): fitting of spline functions of BVJHK colors and proper motions, using the Hipparcos catalog as training set Ofek (2008): SED fitting of BVJHK magnitudes with the Pickles (1998) spectral library. Belikov & Roser (2008): fitting of synthetic extinction-free Q-values on BVJHK photometry, calibrated on a subset with spectroscopical info. Biliret al. (2006): linear fit of “V”+JHKmag-mag diagrams with a spectroscopical training set (V band from various and unspecified sources)‏

  10. As pointed out by Klement et al. (2010),the contamination of a sample of dwarfs classified by broad-band photometry is typically around 20%: a lower contamination can be achieved only decreasing the completeness to unacceptable levels. AT PRESENT TIME, PLATO ALLOWS TO COVER 50% MORE TARGETS THAN IN PRESENT SCIENCE REQUIREMENTS Completeness/Contamination issues We matched the Ofek and Ammons database with the RAVE dr2 spectroscopical survey – confirming Klement: ~14% (for Ammons) and ~22% (for Ofek) of late dwarfs classified by photometry show log(g) and Teff are probably giants or earlier dwarfs. A similar value is also found for the Belikov database (~20%).

  11. Target density maps The biggest issue when dealing with broad-band classifications is that (so far) they rely on Tycho-2 for BV magnitudes: the completeness is limited to V~11. Brightest samples(P1, P2, P3, V<11) are the most scientifically rewarding and they will drive the choice of the LD Plato fields. Using databases from Ammons, Belikov, Ofek, etc. we can extract only the >F5 dwarfs and buildtarget density maps to see if and where the requirements are met. As expected, the late-type dwarfs are not strongly concentrated toward the disk, their density varying only by a factor ~3 (field: ~20)‏

  12. Target densities for the Plato Field North The northern region shows a density of P1 targets in the range 3.5-9/deg2 (requirement: 5.5 deg2). By averaging the counts over 2000 deg2, the science requirement is met for every choice of the field centered on b < 30.

  13. Target densities for the Plato Field North PLATO field

  14. Target densities for the Plato Field South The southern region shows an overall density similar to the northern field. By averaging the counts over 2000 deg2, the requirement is met for fields centered on b <~ 30, with more counts on the regions l<270 (Vela).

  15. The Hipparcos catalogue provides reliable parallaxes down to V=7.3 (completeness limit) but includes also most of V<8 stars. We selected >F5V dwarfs and subgiants by a simple cut on the absolute CMD, to pose a lower limit to the number of potential targets in the Plato stellar sample #2 (~500/PF are required)‏ Sample #2 (V<8): Hipparcos The ~22,000 selected targets are uniformly distributed across the sky (as expected), giving a density of ~0.5 stars/deg2► ~1000 targets for each ~2000 deg2 Plato Field, not dependent upon the chosen FOV.

  16. Stellar classification for fainter Plato targets (V > 11) must wait forthcoming catalogues like APASS or SkyMapper which will provide all-sky, deep, accurate broad-band photometry (for SkyMapper and LSST, also with UV and medium-band magnitudes). JHK photometry from 2MASS is already precise enough for the PIC. Cutri et al (2006)‏ V=14 K2V NOTE: we need also information on activity, when available

  17. How Can GAIA Help PLATO? Two main issues we started to address: • Crowding • Scanning Law

  18. Blue Photometry RVS Astrometry Crowding is likely not an issue for astrometry for PLATO targets. It might be a problem for BP, RP and RVS Problem needs to be studied in more details

  19. Is the scanning law a problem? It might be, in particular for the early release catalog data. It depends on the selected PLATO fields

  20. The GOG Data Generator - Number counts - Object lists - Simulations of intermediate and end-of-mission Gaia data

  21. AGISLab A scaled-down version of Gaia’s Astrometric Global Iterative Solution • Wewilluse some toolsdevelopedby the DPAC (Gaia Consortium) toget a reliable estimate of the Gaia measurements and accuracies (parallax, star parameters,...), and usethemfor PIC purposes. • Note that there is still time to define the early release catalog parameters. We need to assess what PLATO needs from GAIA ERCs and discuss this with GAIA team. • GAIA output data and accuracy estimate shall be used to develop tools for the identification of PIC targets and their basic parameters

  22. PLATO Target Characterization Basic Parameters 1. First definition of parameter list, based also on COROT and KEPLER experience 2. Identify sources of parameters, inc data + evolutionarymodels 3. Assess feasibility wrt target list 4. Assess performance and completeness for eachparameter

  23. What shall be done during next year 1. Analysis of available (and forthcoming) astrometric, photometric, spectroscopic, variability, stellar activity, etc catalogs to identify those useful for PIC 2. Identification of the first PLATO long term monitoring field 3. Study of GAIA expected performances for the GAIA Early Release Catalog (GERC), and exploitation of the use of GAIA for PIC target selection and characterization 4. Definition the criteria and of the algorithms for PIC target selection 5. Definition of PIC parameters, and parameters determination tools

More Related