Astrophysical false alarms in high contrast imaging surveys

Transcription

1 Astrophysical false alarms in high contrast imaging surveys The SPHERE/NIRSUR case G. Chauvin IPAG Institut de Planétologie et Astrophysique de Grenoble P. Delorme (IPAG), A. Vigan, A. Zurlo, C. Moutou (LAM), M. Bonnefoy (MPIA), M. Bonavita,, S. Desidera, D. Mesa (INAF/Padova), and the SPHERE consortium Planet Validation DRH Workshop Workshop Heidelberg LAM 13-15th May Apr

2 Outline I- SPHERE/NIRSUR survey II- Lessons from the past III- Classes of contaminants IV- False alarm diagnostics V- Adopted strategy Planet Validation DRH Workshop Workshop Heidelberg LAM 13-15th May Apr

3 I- SPHERE/NIRSUR VLT/SPHERE ((Beuzit et al. 08) Scientific Goal: High-Contrast Imager for Giant Planets & Disks Description: - SAXO, XAO system (ITTM-DM and DTTS, PTTS) - NIR (YJHK): IRDIS (Dual imaging Spectrograph) and IFU 3D-spectroscopy - VIS: ZIMPOL (Imaging Polarimeter) - Coronagraphs: Classical Lyot, A4P and ALC - Differential imaging capabilities Planet Validation Workshop LAM 13-15th May 2013

4 I- SPHERE/NIRSUR Planet Validation Workshop LAM 13-15th May 2013

5 FoV I- SPHERE/NIRSUR ZIMPOL IRDIS IFS Sq 3.5 (instantaneous) Up to 4 radius (mosaic) Sq 11 Sq 1.77 Spectral Range μm μm /1.65 μm Spectral information Linear Polarisation BB, NB Simultaneous on same detector, x 2 arms, exchangeable Coronography: no /4Q / Lyot Rotation at Nasmyth: Pupil-stab. (instrument fixed wrt tel.) Field-stab (slit spectro, long DIT ) No rotation: minimize crosstalk ) BB, NB Slit spectro: 50/400 Simultaneous dual beam, exchangeable Planet Validation Workshop LAM 13-15th May / 30 AO sensitivity for high contrast: R <9.5 for NIR; R<9 for R; R<7.8 for whole VIS Separation with improved contrast: 2-20 λ/d, ie mas in R, or mas in H Mode switching: not VIS and NIR in same night x

6 I- SPHERE/NIRSUR SPHERE GTO 260 nights over 4 6yrs Scientific programs: NIRSUR:. Disks (20n). Reflected Light (10n). NIRSUR (200n). SS & Evolved stars (10n). Add/Tests (10n) Survey of >400 nearby stars (AFGKM and <1 Gyr) Occurrence of giant planets at wide orbits (>10 AU) Giant planet atmospheres, Evolution, Planetary systems Dynamics Planet Validation Workshop LAM 13-15th May 2013

7 I- SPHERE/NIRSUR High-Contrast Imaging of Exoplanets 1/ XAO: Atmospheric turbulence (90% Strehl in H-band) 2/ Diffraction pattern: Halo suppression 3/ Quasi-static instrumental aberrations & post-processing XAO, Sr~90% Diffraction + static aberration correction Speckle Calibration, Differential Methods Contrast ~ DRH Workshop -4 Contrast Heidelberg ~ Apr 2010 Contrast ~ 10-7

8 I- SPHERE/NIRSUR NIRSUR Observing Strategy IRDIFS Mode: IRDIS-DBI H2H3 (12.5 FoV) & IFS-Y-J (1.77 FoV) simultaneously Atmosphere: Limiting seeing and coherence time for AO Star-brightness: AO performances (R < 9.5) Meridian-constraint: maximize field rotation for ADI Minimize the quasi-static aberrations Companion faintness: Observing sequence of 1-2hrs Dedicated calibrations: DRH Workshop photometric Heidelberg & Astrometric Apr 2010 field

9 Outline I- SPHERE/NIRSUR survey II- Lessons from the past III- Classes of contaminants IV- False alarm diagnostics V- Adopted strategy Planet Validation DRH Workshop Workshop Heidelberg LAM 13-15th May Apr

10 Past Deep Imaging Surveys II- Lessons from the past. Magnitude limit: Hlim = (H A = 8-9; ΔH=14-15) (Chauvin et al. 2010). 65 stars observed; 240 False Alarms (FAs). FA rate ~ 55% NaCo (VLT) 28 NIRSUR Workshop Padova 3 6 May 2010

11 II- Lessons from the past False alarms Field contamination from past DI surveys: Programme Instrument FoV Filter Nb b (o) Fc(%) Reference Young stars VLT/NaCo 28 H/K (Chauvin et al. 2010) Young stars HST/NICMOS 19 H (Lowrance et al. 2005) Planet hosts Keck 5 K (Luhman et al. 2002) Young & Int-old Gemini/NIRI 22 H (Lafreniere et al. 2007) Planet Validation DRH Workshop Workshop Heidelberg LAM 13-15th May Apr

12 Proper motion study of CC-1. Primary star proper & parallactic motion. Follow-up at several epochs >> co-moving object Orbital motion >> physically bound But do we want to conduct systematic follow-up observations? II- Lessons from the past Identification: Astrometric Follow-up

13 II- Lessons from the past Identification: Impact on the survey size. 200 GTO nights. Obs.Time/target. FAs Contamination (Fc). Nb Visits. Target List (Nb stars). Nb Follow-up Visits Nb Targets = Nb Visits / ( 1 + Fc) Nb Discovery Nights = 200. / ( 1 + Fc) Systematic astrometric follow-up : Fc = 50% 66n follow-up Fc = 33% 50n follow-up Planet Validation DRH Workshop Workshop Heidelberg LAM 13-15th May Apr

14 II- Lessons from the past Identification: Impact on the survey size. 200 GTO nights. Obs.Time/target. FAs Contamination (Fc). Nb Visits. Target List (Nb stars). Nb Follow-up Visits Nb Targets = Nb Visits / ( 1 + Fc) Nb Discovery Nights = 200. / ( 1 + Fc) >> Identification Strategy: impact the Nb Targets observed our chance of planet detection the statistical significance of our complete sample Planet Validation DRH Workshop Workshop Heidelberg LAM 13-15th May Apr

15 Outline I- SPHERE/NIRSUR survey II- Lessons from the past III- Classes of contaminants IV- False alarm diagnostics V- Adopted strategy Planet Validation DRH Workshop Workshop Heidelberg LAM 13-15th May Apr

16 III- Classes of contaminants 1. Solar System Bodies: (B. Carry; F. Marchis). Asteroids: km- to 100-m size, G2 solar-type spectra. TNOs: km-size bodies; H20 (CH4...) ice-composition (Barucci et al. 2005)

17 III- Classes of contaminants 1. Solar System Bodies: (B. Carry; F. Marchis). Asteroids: km- to 100-m size, G2 solar-type spectra. TNOs: km-size bodies; H20 (CH4...) ice-composition. Identification: High-proper motion: μ( /min) = 140/d(AU) >> smearing! 930mas/s main-belt (2.5 AU); 50 mas/s TNOs (50 AU) Ephemerids: - SkyBoT ( - JPL/Horizons ( >> implemented with success for NaCo, Keck!. How many asteroids/tnos FAs? (>> could simulate the expected nb) Planet DRH Workshop Heidelberg Apr 2010 NIRSUR Validation Workshop Padova LAM th 6 May

18 2. Galactic: Field Stars Galactic Population Synthesis: The Besançon Model (Robin et al. 2003) The TRILEGAL Model (Girardi et al. 2005) Predictions calibrates using Hipparcos observations and recent large scale surveys in optical and NIR. Friendly-tool to simulate Field Stars Contamination: III- Classes of contaminants Inputs: Catalogue and magnitude limit (JH...) Outputs: > Star counts / sq.deg > properties: SpT, Teff, Age, FeH, ppm... Planet DRH Workshop Heidelberg Apr 2010 NIRSUR Validation Workshop Padova LAM th 6 May

19 2. Galactic: Field Stars The NIRSUR survey simulation 597 stars from the TDB (and their gal. coordinates) Hlim = 23 (ΔH = for typ. H = 6.5) III- Classes of contaminants Cumulated star counts density Map / sq.deg (for Hlim<23)

20 2. Galactic: Field Stars NIRSUR: Cumulated star counts In average, 7 field stars (H < 23) per IRDIS FoV III- Classes of contaminants

21 2. Galactic: Field Stars III- Classes of contaminants NIRSUR: Complete survey field stars contamination 52% of IRDIS FoVs, contaminated by 1 field star with H < 23

22 2. Galactic: Field Stars NIRSUR: Contaminant predicted properties III- Classes of contaminants

23 2. Galactic: Field Stars NIRSUR: Contaminant predicted properties III- Classes of contaminants Field MS M dwarfs!

24 3. X-Galactic: (M. Turatto; P. Delorme) Low- and high-redshift galaxies HST/NICMOS deep field study Galaxies counts & morphology (H < 24) (Teplitz et al. 1998) III- Classes of contaminants

25 3. X-Galactic: (M. Turatto; P. Delorme) Low- and high-redshift galaxies HST/NICMOS deep field study Galaxies counts & morphology (H < 24) (Teplitz et al. 1998) Counts = 2.1 X-Gal/FoV IRDIS (H < 23):. Morphology: z = 0.3, 3kpc Ø = 0.6 z = 1-4, 4-8kpc Ø = III- Classes of contaminants

26 III- Classes of contaminants 3. X-Galactic: (M. Turatto; P. Delorme) QSOs (Active nucleus galaxies) Chandra Survey: 60 QSOs over 300 sq. arcmin; (Barger et al. 2002) > QSO counts: (J<23) 0.01 QSO / IRDIS FoV Low & High-z Star forming regions Giant HII regions (200pc size); At z = 0.3-4, Ø = mas Intergalactic Globular Clusters ACS Deep field (Williams et al. 2007) > IGC counts (H < 22): 0.04 IGC / IRDIS FoV High-z Super Novae SNe computation (Dahlen & Fransson et al. 1999, SNe rates) > SNe counts: SNe / IRDIS FoV

27 False alarms summary, Classe Type Contamination III- Classes of contaminants Comments (Nb/IRDIS FoV) Solar System Asteroids/TNOs? smearing, ephemerids Galactic Field Stars 7 M-stars for H = [17-25] point-like. same H2H3 color as L-type EGPs X-Gal Low & High-z Gal. 2. resolved QSOs 0.01 negligible X-SFRs? negligible IGCs 0.04 negligible SNe negligible >> Major source of astro-fas: background field M-dwarfs Planet Validation DRH Workshop Workshop Heidelberg LAM 13-15th May Apr

28 Outline I- SPHERE/NIRSUR survey II- Lessons from the past III- Classes of contaminants IV- False alarm diagnostics V- Adopted strategy Planet Validation DRH Workshop Workshop Heidelberg LAM 13-15th May Apr

29 Identification, available diagnostics: 1. Database/Preparatory observations: cross-correlation with on-line catalogues building a Deep Imaging Database 2. NIRSUR spectro-photometric diagnostics ability to identify false alarms 3. Astrometric follow-up IV- False alarms diagnostics Astrometric precision & target proper motion Planet Validation DRH Workshop Workshop Heidelberg LAM 13-15th May Apr

30 IV- False alarms diagnostics False Alarm Operation Diagramme Priority? Visit Data Analysis TDB NIRSUR Diagnostics Follow-up Detection New Un-identified Non-detection Identified Identified Identified TDB Planet DRH Workshop Heidelberg Apr 2010 NIRSUR Validation Workshop Padova LAM th 6 May

31 1. Database/Preparatory observations 1.1 Literature: compilation of published surveys (catalogue, instrument, observing mode, detection performances, source identification...) 1.2 Collecting Deep Imaging Data (DIVA) Status: currently 400 stars (300 potential targets for NIRSUR) Interface with the NIRSUR Target Database 1.3 NaCo Large Programme (Preparatory survey) ADI H-band observation: 110 new stars IV- False alarms diagnostics Planet DRH Workshop Heidelberg Apr 2010 NIRSUR Validation Workshop Padova LAM th 6 May

32 2. NIRSUR diagnostics Observing modes. IRDIS DBI: H2H3, H2, H3 photometry. IFS ( μm): Y-J Rec. photometry LRS IV- False alarms diagnostics Outer FoV IRDIS DBI (H2H3) Inner FoV IFS ( μm) DRH Workshop Heidelberg Apr 2010 NIRSUR Workshop Padova 3 6 May 2010

33 2. NIRSUR diagnostics 2.1 Outer IRDIS alone FoV IV- False alarms diagnostics Single IRDIS detection: H2 or H3 or H2H3 Cannot discriminate! Double IRDIS detection: H2 and H3 (H2 and H2H3...) Can easily discriminate cool T2 to Y EGPs from field stars. >> Problem for young L-type EGPs! >> Expect a lot of M field stars!

34 2. NIRSUR diagnostics 2.2 Inner IRDIS/IFS FoV IV- False alarms diagnostics Single IFS detection: Y-J low-res spectra (Sp. indexes, cross-libs) High SNR: can well discriminate L-,T- and Y-types from FAs. IFS Extraction simulations (Dino): >> low SNR: more difficult for L-types than T, Y-types >> Smaller FoV (less FAs) L0-type EGP, 10-6 (ΔJ = 15) at 0.5

35 IV- False alarms diagnostics 2. NIRSUR diagnostics Summary:. Outer IRDIS alone FoV. Important Nb of FAs/FoV (Fc ~ 50%). Single detection no diagnostics. Double detection no discrimination btw warm L-types (early-t) EGPs and field M stars. Inner IRDIS/IFS FoV. Less FAs/FoV (Fc of a few %). IFS detection good discrimination low S/N, more difficult for L-types. Combined IRDIS/IFS improved diagnostics DRH Workshop Heidelberg Apr 2010 NIRSUR Workshop Padova 3 6 May 2010

36 3. Astrometric Follow-up TDB, NIRSUR target proper motion IV- False alarms diagnostics Easy confirmation over a few months with a ~5mas accuracy

37 Available diagnostics summary IV- False alarms diagnostics (Contaminants: mostly field M dwarfs, 52% Outer FoV) 1. Archive/TDB: - relevant for Outer FoV - Follow-up obs. reduction to be quantified 2. NIRSUR Diagnostics: - handicap for the Outer FoV: L (early-t) type EGPs - Inner FoV: less problematic (lower contamination and better diagnostics) >> enable to derive the CC (Mass, Δproj) if bound! 3. Astrometry: - Firm identification (a few months) - But, impact Nb of targets observed

38 Outline I- SPHERE/NIRSUR survey II- Lessons from the past III- Classes of contaminants IV- False alarm diagnostics V- Adopted strategy Planet Validation DRH Workshop Workshop Heidelberg LAM 13-15th May Apr

39 Adopted strategy V- Strategy & Planet Validation 1. Scientific Goals Detection & statistical completeness 2. Sample selection: Age, distance, SpT, FeH, (Galactic latitude) Selection: Detection or Statistics driven? Expected Fc ~50% BUT, we want the Follow-up to be < 30% 3. Physical window Focus on close and low-mass companions Physical cutoff: < 200 AU (r < 4 ) and < 60 Mjup Planet Validation Workshop LAM 13-15th May 2013

40 Adopted strategy V- Strategy & Planet Validation 4. Candidate Ranking: 1/ Top-priority: CH4 or spectral signatures for Follow-up 2/ Others, focus on the closest and lightest EGPs Predicted mass & distance; Contamination Probability; Ranking: merit function with (M, a) cutoff depending on predicted M, a and Fc 5. Follow-up: Total should not follow-up more than 30% Priority according to the candidate ranking Complete on a physical distance parameter space Planet Validation Workshop LAM 13-15th May 2013

41 Outline Adopted strategy 6. Characterization: a/ Primary refined parameters (Age, d) > Alice Zurlo s Talk b/ Atmosphere IFS and IRDIS extended diagnostics (spectroscopy and additional photometric filter) c/ Predicted Physical properties (Mass) d/ Orbital properties (sma, ecc.) e/ Circumstellar environment (disk, planets ) Planet Validation Workshop LAM 13-15th May 2013