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On the Frequency of Gas Giant Planets in the Metal-Poor Regime Alessandro Sozzetti 1, D.W. Latham 2, G. Torres 2, R.P. Stefanik 2, S.G. Korzennik 2, A.P.

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Presentation on theme: "On the Frequency of Gas Giant Planets in the Metal-Poor Regime Alessandro Sozzetti 1, D.W. Latham 2, G. Torres 2, R.P. Stefanik 2, S.G. Korzennik 2, A.P."— Presentation transcript:

1 On the Frequency of Gas Giant Planets in the Metal-Poor Regime Alessandro Sozzetti 1, D.W. Latham 2, G. Torres 2, R.P. Stefanik 2, S.G. Korzennik 2, A.P. Boss 3, B.W. Carney 4, J.B. Laird 5 (1) INAF/OATo - (2) CfA - (3) CIW - (4) UNC - (5) BGSU

2 Pisa, 6 May 2009 Core Accretion & Disk Instability * Core Accretion: Bottom-Up! Accumulate a 10 M  core (dust to planetesimals to runaway accretion), which accretes a massive gaseous envelope from the disk. * Disk Instability: Top-Down! Local gravitational collapse of a gaseous portion of the disk leads to a Jupiter-mass (or larger) protoplanet. The rocky core is formed almost simultaneously by sedimentation of dust grains to the center. Boss (SSRv, 2005)

3 Pisa, 6 May 2009 Ida & Lin (ApJ, 2004), Kornet et al. (A&A, 2006): “The frequency of giant planet formation by core accretion is roughly a linear function of Z” Boss (ApJL, 2002): “The frequency of giant planet formation by disk instability is remarkably insensitive to Z” N/A Do giant planets form by Core Accretion, Disk Instability, or both?

4 Pisa, 6 May 2009 HST/WFPC2 DSS Globular Cluster 47 Tucanae HST (WFPC2) observed about 34,000 stars in 47 Tuc, obtaining time series photometry over a period of 8.3 days Gilliland et. al. (ApJ 2000), Weldrake et al. (ApJ 2005) 11 Gyr, 10 6 stars [Fe/H] ~ - 0.7 No planet eclipses were seen.

5 Pisa, 6 May 2009 However… Crowding can impact giant planet formation, migration, and survivalCrowding can impact giant planet formation, migration, and survival The absence of Hot Jupiters in a metal-poor environment does not imply they don’t exist at larger radiiThe absence of Hot Jupiters in a metal-poor environment does not imply they don’t exist at larger radii GCs are not optimal Go to the field

6 Pisa, 6 May 2009 F p vs [Fe/H] Linear Dependence? Flat tail for [Fe/H] < 0.0? Low statistics for [Fe/H] < -0.5 Santos et al. (A&A, 2004): No P, K, [Fe/H] thresholds: F p ~ Z, for Z > 0.02) F p ~ const, for Z < 0.02 Fischer & Valenti (ApJ, 2005): K > 30 m/s, P 30 m/s, P < 4 yr, -0.5<[Fe/H]<0.5: Quadratic dependence? Flat tail for [Fe/H]<0.0? Low statistics for [Fe/H] < -0.5

7 Pisa, 6 May 2009 What is the dominant mode of giant planet formation? Is F p ([Fe/H]) bimodal or monotonic? Small-number statistics for [Fe/H] < -0.5 prevents one from drawing conclusions:

8 Pisa, 6 May 2009 Keck/HIRES Metal-Poor Planet Search 200 stars from the Carney-Latham and Ryan samples200 stars from the Carney-Latham and Ryan samples No close stellar companionsNo close stellar companions Cut-offs: -2.0 < [Fe/H] < -0.6, T eff < 6000 K, V < 12Cut-offs: -2.0 < [Fe/H] < -0.6, T eff < 6000 K, V < 12 Reconnaissance for gas giant planets within 2 AUReconnaissance for gas giant planets within 2 AU Campaign duration: 3 yearsCampaign duration: 3 years Sozzetti et al. (ApJ, 2006)

9 Pisa, 6 May 2009 The RV dispersion of the full sample peaks at 9 m/s Sozzetti et al. (ApJ, 2006)

10 Pisa, 6 May 2009 No clear RV trends are seen as a function of T eff, [Fe/H], and ΔT

11 Pisa, 6 May 2009 Analysis: Methodology Statistical analysis: testing for excess variability (F-test,  2 -test, Kuiper test) Statistical analysis: testing for excess variability (F-test,  2 -test, Kuiper test) Analysis of long-term (linear and curved) trends Analysis of long-term (linear and curved) trends Limits on companion mass and period from detailed simulations Limits on companion mass and period from detailed simulations Upper limits on f p and new powerful constraints on f p ([Fe/H]) in the metal-poor regime Upper limits on f p and new powerful constraints on f p ([Fe/H]) in the metal-poor regime

12 Pisa, 6 May 2009 About 6% of the stars in the sample have long-period companions Follow-up with direct infrared imaging (MMT/Clio) to determine their nature (low-mass stars or brown dwarfs) RV Variables Follow-up

13 Pisa, 6 May 2009 MMT/Clio Imaging @ 5 μm ΔM ~ 2.5 mag ΔM ~ 6.5 mag ~0.5” ~1”

14 Pisa, 6 May 2009 COMPLETENESS: - 6 observations, 3-yr baseline; - s RV = 9 m/s - 99.5% confidence level - Sensitivity to companions with 1M J 100 m/s), 1M J 100 m/s), with orbital periods between with orbital periods between a few days and 3 years a few days and 3 years - Strong dependence of detection thresholds on eccentricity thresholds on eccentricity WE FIND NONE…

15 Pisa, 6 May 2009 For n=0, N=160: For n=1, N=160: Frequency of Close-in Companions (-2.0 100 m/s, P 100 m/s, P < 3 yr, e < 0.3)

16 Pisa, 6 May 2009 Compare with the SPOCS database: b=0.99 b=1.05 b=0.89 ( σ = 134 K) ( σ = 0.12 dex) ( σ = 0.06 M SUN ) Reliability of the Atmospheric Parameters

17 Pisa, 6 May 2009 Sozzetti et al. 2009 (ApJ, in press): K > 100 m/s, P 100 m/s, P < 3 yr, -1.0<[Fe/H]<0.5:

18 Pisa, 6 May 2009 Summary We observe a dearth of gas giant planets (K > 100 m/s) within 2 AU of metal-poor stars (-2.0 < [Fe/H] < -0.6), confirming and extending previous findings The resulting average planet frequency is F p < 0.67% (1σ) F p (-1.0<[Fe/H]<-0.5) appears to be a factor of several lower than F p ([Fe/H]>0.0), but it’s indistinguishable from F p (-0.5<[Fe/H]<0.0). Is F p ([Fe/H]) bimodal or not? It is consistent with being so. However, need larger and better statistics to really discriminate… 1) Expand the sample size; 2) lower the mass sensitivity threshold; 3) search at longer periods. Next generation RV surveys and future high-precision space-borne astrometric observatories (Gaia, SIM-Lite) will help…


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