HATS-5b

HATS-5b: A Transiting Hot-Saturn from the HATSouth Survey 1

Abstract

We report the discovery of HATS-5b, a transiting hot-Saturn orbiting a G type star, by the HATSouth survey. HATS-5b has a mass of , radius of , and transits its host star with a period of  d. The radius of HATS-5b is consistent with both theoretical and empirical models. The host star has a band magnitude of 12.6, mass of , and radius of . The relatively high scale height of HATS-5b, and the bright, photometrically quiet host star, make this planet a favourable target for future transmission spectroscopy follow-up observations. We reexamine the correlations in radius, equilibrium temperature, and metallicity of the close-in gas-giants, and find hot Jupiter-mass planets to exhibit the strongest dependence between radius and equilibrium temperature. We find no significant dependence in radius and metallicity for the close-in gas-giant population.

Subject headings:
planetary systems — stars: individual (HATS-5, GSC 5897-00933) techniques: spectroscopic, photometric

1. Introduction

Transiting planets are the best characterised planets outside of our solar system. The transit geometry allow us to measure the mass, radius, and characterise the atmosphere (e.g. Charbonneau et al., 2002; Deming et al., 2005) and dynamics (e.g. Queloz et al., 2000) of individual planets. As a result the of discoveries from wide-field ground and space-based photometric surveys (e.g. Bakos et al., 2004; Pollacco et al., 2006; Borucki et al., 2010; Bakos et al., 2013), statistical studies have revealed that close-in gas-giants are rare (e.g. Howard et al., 2012; Fressin et al., 2013), have relatively dark albedos (e.g. Cowan & Agol, 2011), and are found preferentially around metal-rich stars (e.g. Santos et al., 2004; Buchhave et al., 2012).

Previous studies have also explored effect of irradiation and composition in inflating the radius of gas giants (e.g. Guillot et al., 2006; Enoch et al., 2011; Béky et al., 2011; Enoch et al., 2012). In particular, Enoch et al. (2011, 2012) found that the radius of Saturn-mass planets are more dependent on metallicity than Jupiter-mass planets, revealing a mass dependence to the inflation mechanisms.

Intensive ground-based follow-up observations are extremely important for the characterisation of transiting gas-giants. Due to the mass degeneracy in the gas-giant regime, Saturns, Jupiters, and brown dwarfs cannot be distinguished from discovery transit photometry alone. The mass degeneracy is a major limitation against using the Kepler candidate sample to study mass-dependent statistics of close-in gas-giant planets. The rarity of close-in gas giants, and the relative difficulty of characterising hot-Saturns compared to hot-Jupiters, leaves the hot-Saturn regime still poorly explored. Of the 299 confirmed transiting planets38, only 23 have masses in range of Saturn and are found in close-in orbits . As a result, our statistical understanding of the hot-Saturn population is relatively less mature.

In this study, we report the discovery of the transiting hot-Saturn HATS-5b by the HATSouth survey. The HATSouth discovery, photometric and spectroscopic follow-up observations are detailed in Section 2. Analyses of the results, including derivation of host star parameters, global modelling of the data, blend analyses, and constraints on the wavelength-radius relationship, are described in Section 3. In Section 4, we revisit some of the statistical trends for the close-in gas-giant population, and discuss HATS-5b in the context of the known hot-Saturns and hot-Jupiters.

2. Observations

2.1. Photometric detection

The transit signal around HATS-5 was first detected from photometric observations by the HATSouth survey (Bakos et al., 2013). HATSouth is a network of identical, fully-robotic telescopes located at three sites spread around the Southern Hemisphere, allowing continuous coverage of the surveyed fields. Altogether 8066 observations of HATS-5 were obtained by the HATSouth units HS-1 in Chile, HS-3 in Namibia, and HS-5 in Australia from September 2009 to December 2010. Each unit consists of four 0.18 m f/2.8 Takahasi astrographs and Apogee 4K4K U16M Alta CCD cameras. Each telescope has a field of view of , with a pixel scale of . The observations are performed with 4 minute exposures through the Sloan filter.

Discussions of the HATSouth photometric reduction and candidate identification process can be found in detail in Bakos et al. (2013) and Penev et al. (2013). Aperture photometry was performed and detrended using External Parameter Decorrelation (EPD, Bakos et al., 2007) and Trend Filtering Algorithm (TFA, Kovács et al., 2005). Transit signals were identified using the Box-fitting Least Squares analysis (BLS, Kovács et al., 2002). Table 1 summarises the photometric observations for HATS-5. The HATSouth discovery light curve is plotted in Figure 1.

Facility Date(s) Number of Images 39 Cadence (s) 40 Filter
HS-1 (Chile) 2009 Nov–2010 Dec 3953 290 Sloan 
HS-3 (Namibia) 2009 Sep–2010 Dec 3241 288 Sloan 
HS-5 (Australia) 2010 Sep–2010 Dec 900 287 Sloan 
ESO/MPG 2.2 m/GROND 2012 Oct 10 178 93 Sloan 
ESO/MPG 2.2 m/GROND 2012 Oct 10 107 93 Sloan 
ESO/MPG 2.2 m/GROND 2012 Oct 10 214 93 Sloan 
ESO/MPG 2.2 m/GROND 2012 Oct 10 211 93 Sloan 
ESO/MPG 2.2 m/GROND 2012 Dec 11 159 144 Sloan 
ESO/MPG 2.2 m/GROND 2012 Dec 11 160 144 Sloan 
ESO/MPG 2.2 m/GROND 2012 Dec 11 162 144 Sloan 
ESO/MPG 2.2 m/GROND 2012 Dec 11 162 144 Sloan 
Table 1 Summary of photometric observations
Figure 1.— HATSouth -band discovery light curve, unbinned, and folded with a period of  days, as per the analysis in Section 3. Solid line shows the best fit transit model. The lower panel shows the transit region of the light curve. Dark filled points represent the light curve binned at 0.002 in phase.

2.2. Spectroscopy

Spectroscopic confirmation of HATS-5b consisted of separate reconnaissance observations to exclude most stellar binary false-positive scenarios that can mimic the transit signal of an exoplanet. High resolution, high signal-to-noise measurements of the radial velocity (RV) variation for HATS-5 were then obtained to confirm the planetary status of HATS-5b. The spectroscopic follow-up observations are presented in Table 2.

Low resolution reconnaissance observations were performed using the Wide Field Spectrograph (WiFeS, Dopita et al., 2007) on the ANU 2.3 m telescope at Siding Spring Observatory, Australia. A flux calibrated spectrum was obtained at to provide an initial spectral classification of HATS-5 as an G-dwarf with , , and . These stellar parameters are later refined by higher resolution observations (Section 3). Multi-epoch observations at confirmed the candidate did not exhibit RV variations. Such velocity variations are indicative of eclipsing stellar binaries, which have so far made up of HATSouth candidates. Details of the WiFeS follow-up procedure and stellar binary identification process can be found in Bayliss et al. (2013) and Zhou et al. (2013). Candidates that pass the WiFeS vetting process are passed on to higher resolution observations.

HATS-5 received nine high resolution () reconnaissance RV observations with the CORALIE spectrograph on the Swiss Leonard Euler 1.2 m telescope at La Silla Observatory, Chile, and fourteen observations with the FEROS spectrograph on the ESO/MPG 2.2 m telescope at La Silla. Detailed descriptions of the acquisition, reduction, and analyses of the CORALIE and FEROS observations can be found in the previous HATSouth discovery papers (Penev et al., 2013; Mohler-Fischer et al., 2013). Velocities from these observations allowed us to constrain the RV orbit semi-amplitude to be .

The upper limit RV constraints from CORALIE, FEROS, and WiFeS indicated that HATS-5b is a low density gas-giant. High signal-to-noise, high resolution observations were required to determine the RV orbit of the system. Velocities of HATS-5 were obtained Planet Finding Spectrograph (PFS) on the 6.5 m Magellan Baade telescope at Las Campanas Observatory, Chile, and the High Dispersion Spectrograph (HDS) on the 8.2 m Subaru telescope at Manua Kea Observatory, Hawaii. The PFS and HDS velocities and bisector spans are presented in Table 3, the RV orbit is plotted in Figure 2.

The Subaru/HDS (Noguchi et al., 2002) observations were carried out on the nights of 19–22 Sep 2012 UT. Observations were made using an I cell on four of the nights (Kambe et al., 2002), and without the I cell on one of the nights. We used the KV370 filter, the slit, and the StdI2b setup, yielding spectra with a resolution of and wavelength coverage of 3500–6200 Å. On each night we obtained three consecutive observations yielding a total S/N per resolution element of . The observations are split into three to reduce the impact of cosmic ray contamination and changes in the barycentric velocity correction over the course of an exposure. The I–free observations were used to create a template spectrum needed to measure precise relative RV values from the observations made with the I cell. The individual spectra were reduced to RV measurements using the procedure of Sato et al. (2002, 2012), which in turn is based on the method of Butler et al. (1996). Additionally we measured spectral line bisectors following Bakos et al. (2007) for each observation. The root-mean-squared (RMS) scatter of the HDS velocities from the best fit Keplerian curve is .

HATS-5 was also observed with the Carnegie Planet Finder Spectrograph (PFS, Crane et al., 2010) on Magellan II at Las Campanas Observatory, Chile on the UT nights of 2012 December 28-31, 2013 February 21, and 2013 February 4. We obtained one iodine-free spectrum, and all other spectra were taken using the iodine cell and a slit-width of 0.5. To increase the signal-to-noise of each spectrum we read-out with 22 binning and in slow readout mode. Consecutive pairs of 20 min exposures were taken on each night. The RV for each spectrum was determined using the spectral synthesis technique detailed in Butler et al. (1996). The (RMS) scatter of the PFS velocities from the best fit Keplerian curve is .

Telescope/Instrument Date Range Number of Observations Resolution Observing Mode
Reconnaissance
ANU 2.3 m/WiFeS 2012 Aug 4 1 3000 RECON Spec41
ANU 2.3 m/WiFeS 2012 Aug 4–6 3 7000 RECON RV42
Euler 1.2 m/Coralie 2012 Aug 21–2013 Feb 27 9 60000 ThAr/RECON RV
ESO/MPG 2.2 m/FEROS 2012 Nov 21–2013 Feb 27 14 48000 ThAr/RECON RV
High resolution radial velocity
Subaru 8.2 m/HDS 2012 Sep 20–22 9 60000 I/RV43
Magellan 6.5 m/PFS 2012 Dec 28–2013 Mar 4 12 76000 I/RV
Table 2 Summary of spectroscopic observations
Figure 2.— Top panel: Phased radial velocities (RVs) from Magellan/PFS are plotted as dark filled circles, Subaru/HDS as open triangles. The best fit model is plotted by the solid line. The best fit absolute velocity offset from each instrument has been subtracted from the observations. Middle panel: Residuals of the RV measurements from the best fit model. The error bars have been inflated such that the per degree of freedom is unity for each instrument. Bottom panel: Bisector spans (BS) are plotted for velocities from Subaru/HDS. Note the different scales for each panel.
BJD RV44 45 BS Phase Instrument
(2 400 000) () () ()
Subaru (I free) 46
Subaru (I free)
Subaru (I free)
Subaru
Subaru
Subaru
Subaru
Subaru
Subaru
Subaru
Subaru
Subaru
PFS
PFS
PFS
PFS
PFS
PFS
PFS
PFS
PFS
PFS
PFS
PFS
[-1.5ex]
Table 3 Relative radial velocities and bisector span measurements of HATS-5.

2.3. Photometric follow-up observations

High precision photometric follow-ups of a partial and a full transit of HATS-5b were performed on 2012 October 10 and 2012 December 11, respectively, using GROND on the ESO/MPG 2.2 m telescope (Greiner et al., 2008). The GROND imager provides simultaneous photometric monitoring in four optical bands over a field of view at sampling. Details of the GROND observation strategy, reduction, and photometry procedure can be found in Penev et al. (2013) and Mohler-Fischer et al. (2013). The GROND light curves are presented in Table 4 and plotted in Figure 3.

Figure 3.— Left: GROND follow-up transit light curves in the -, -, - and -band are plotted. The light curves have been treated with EPD simultaneous to the transit fitting (Section 3). The best fit model is plotted as a solid line for each observation. Right: Residuals for each transit observation is plotted.
BJD Mag47 Mag(orig)48 Filter Instrument
    (2 400 000)
HS
HS
HS
HS
HS
HS
HS
HS
HS
HS
[-1.5ex]

Note. – This table is available in a machine-readable form in the online journal. A portion is shown here for guidance regarding its form and content.

Table 4Differential photometry of HATS-5

3. Analysis

The stellar parameters for HATS-5 are derived from the PFS iodine-free spectrum using the Stellar Parameter Classification (SPC) process described in Buchhave et al. (2012). The derived values for effective temperature, surface gravity, metallicity, and projected rotational velocity are , , , and , respectively. The surface gravity is later confirmed from transit light curve fitting as per Sozzetti et al. (2007). The SPC derived stellar parameters agree with the classifications made by the reconnaissance spectroscopic observations to within in , 0.4 dex in , and 0.2 dex in .

To derive the system parameters, we performed a global analysis of the HATSouth discovery light curves, follow-up photometry from GROND, and RV orbit measurements from PFS and HDS. The best fit parameters and posteriors are determined using a Markov chain Monte Carlo analysis, the global analysis procedure is fully described in Bakos et al. (2010) and Penev et al. (2013). Following Sozzetti et al. (2007), we use the stellar density from the light curve in the global fit and the spectroscopic stellar parameters, and , to sample from the Yonsei-Yale theoretical isochrones (Yi et al., 2001), deriving the stellar mass and radius for HATS-5. The resulting from the isochrone sampling matches the spectroscopic from SPC. The full list of final spectroscopic and derived stellar properties are presented in Table 5, the fitted system parameters and derived planet properties in Table 6.

To rule out the possibility that HATS-5 is a blended eclipsing stellar binary system, rather than a transiting planet system, we carried out a blend analysis following Hartman et al. (2011). Based on the light curves, spectroscopically determined atmospheric parameters, and absolute photometry, we are able to exclude scenarios involving a stellar binary blended with a third star (either physically associated, or not associated with the binary) with 7 confidence. In order to fit the light curves, the blend scenarios require a combination of stars with redder broad-band colours than are observed. Moreover, the best-fit blend model would produce RV variations of several km s and bisector variations of several hundred m s, which are substantially greater than the observed variations. We conclude that the observations of HATS-5 are best explained by a model consisting of a planet transiting a star.

To search for rotational modulations of the host star, we perform a Lomb-Scargle (Lomb, 1976; Scargle, 1982) analysis of the HATSouth discovery light curves, with the transits masked. No statistically significant peaks were identified in the TFA light curves. The expected rotation period from the spectroscopic measurement is 34 days, which is difficult to measure from ground-based photometry (most of the HATSouth photometric data for HATS-5b were gathered over months). We find no emission features in the Calcium H and K lines in the iodine free HDS and PFS spectra, indicating minimal chromospheric activity. The slow rotation rate and the lack of chromospheric activity are both consistent with the isochrone age estimate for HATS-5.

Figure 4.— Model isochrones from Yi et al. (2001) for HATS-5 are plotted. The isochrones for = +, ages of 0.2 Gyr (lowest dashed line), and 1 to 13 Gyr in 1 Gyr increments are shown from left to right. The SPC values for and  are marked by the open triangle, the and confidence ellipsoids are marked by solid lines.
        Parameter Value Source

Catalogue Information
    GSC 5897-00933
    2MASS 04285348-2128548
    RA (J2000) 2MASS
    DEC (J2000) 2MASS
Spectroscopic properties
     (K) SPC49
     SPC
     () SPC
Photometric properties
     (mag) APASS
     (mag) APASS
     (mag) 2MASS
     (mag) 2MASS
     (mag) 2MASS
Derived properties
     () YY++SPC 50
     () YY++SPC
     (cgs) YY++SPC
     () YY++SPC
     (mag) YY++SPC
     (mag,ESO) YY++SPC
    Age (Gyr) YY++SPC
    Distance (pc) YY++SPC
Table 5 Stellar parameters for HATS-5
               Parameter Value

Light curve parameters
    (days)
    () 51
    (days) 52
    (days) 53
   
   54
   
   
    (deg)
Limb-darkening coefficients 55
    (linear term)
    (quadratic term)
   
   
   
   
RV parameters
    ()
   
   
   
   
   
   
   PFS RV jitter ()56
   HDS RV jitter ()
Planetary parameters
    ()
    ()
    57
    ()
    (cgs)
    (AU)
    (K)
   58
    () 59
Table 6Orbital and planetary parameters

3.1. Constraining the radius–wavelength dependency of HATS-5b

Multi-band transit observations by GROND can provide constraints on the dependency between planet radius and wavelength (e.g. Nikolov et al., 2013; Mancini et al., 2013), and potentially probe for molecular absorption and Rayleigh scattering features in the transmission spectrum of a planet. We performed a separate fitting of the GROND full transit data from 2012 December 11, simultaneously fitting for the transit parameters , , and , and the individual for each passband. The fitting is performed using the JKTEBOP eclipsing binary model (Nelson & Davis, 1972; Southworth et al., 2004), with both quadratic limb darkening coefficients fixed to that of Claret (2004), and freed and parameterised according to Kipping (2013). The best fit parameters and uncertainties are explored by the emcee implementation of a Markov chain Monte Carlo routine (Foreman-Mackey et al., 2012) under Python. Simultaneous EPD is performed on the residuals for each iteration with a linear combination of the first order terms for time, target star X position, Y position, full width at half maximum, and airmass. The final values are consistent with each other to within errors for the fixed and free limb darkening coefficient analyses.

The deviation from mean radius for each passband is plotted in Figure 5. For comparison, we also plot the wavelength-radius variation of HD 189733b, as measured using the Hubble Space Telescope (HST) by Pont et al. (2008); Sing et al. (2011), and scaled to match the scale height (500 km) and of HATS-5b, assuming an H dominated atmosphere (following Snellen et al., 2008). HD 189733b is a pL class planet according to Fortney et al. (2008), with a mildy irradiated atmosphere that is potentially similar to that of HATS-5b. The results of the GROND observations are consistent with both a null detection of atmospheric features and that expected from the scaled measurements of HD 189733b. We do not see obvious star spot crossing events in the transit light curve, although unocculted spots can also cause a slope in the broadband measurements (e.g. Pont et al., 2008; Sing et al., 2011). Whilst we do not detect any atmospheric features on HATS-5b, the large scale height makes HATS-5b an appealing target for future transmission spectroscopy observations. Future observations in the bluer -band may also reveal opacity variations in the atmosphere by H Rayleigh scattering (e.g. Sing et al., 2011, 2013; Jordán et al., 2013; Nascimbeni et al., 2013).

Figure 5.— Variations in over the optical passbands for the GROND full transit on 2012 December 11. A mean radius ratio has been subtracted for each passband. The radius ratios from the limb darkening fixed (blue) and free (red) analyses are plotted. We also plot the transmission spectrum of HD 189733b as observed using HST by Pont et al. (2008); Sing et al. (2011), and scaled to match the scale height and radius ratio of HATS-5b. The transmission curves for each filter are plotted at the bottom.

4. Discussion

We presented the discovery of HATS-5b, a transiting hot-Saturn with mass of and radius of . HATS-5b is the the lowest mass and radius planet to date reported by the HATSouth survey. The host star is a quiet, slowly rotating G-dwarf with a stellar mass of and radius of . The mass and radius of HATS-5b are plotted in the context of existing close-in transiting gas giants in Figure 6.

Figure 6.— The mass–radius distribution of transiting gas giants60 (,  d) are plotted. HATS-5b is marked in red. Confirmed planets with masses and radii are plotted in gray. The isochrone from Fortney et al. (2007) for 4.5 Gyr old gas-giant planets, with core sizes, orbiting 0.045 AU from the host star, is shown by solid line.

The radius of HATS-5b is consistent with the model of an irradiated gas-giant that formed via core accretion (Fortney et al., 2007). The radius is also consistent within to the empirical radius relationship for Saturn-mass planets from Enoch et al. (2012). We examine below the empirical factors that affect the radius of irradiated gas-giants.

4.1. The –radius relationship

A number of previous studies have investigated the relationship between the planet radius distribution, host star metallicity, and levels of insolation (e.g. Guillot et al., 2006; Enoch et al., 2011; Béky et al., 2011; Enoch et al., 2012). The factors that impact the radius of a gas giant should be mass dependent. For example, the level insolation should have a less significant impact on the radius of the denser, more massive gas giants and brown dwarfs than on the less dense Saturn-mass planets. Here, we revisit the mass dependence of the planet radius on the host star metallicity and the planet equilibrium temperature.

Figure 7.— The correlation between planet radius, equilibrium temperature and metallicity are plotted. For each mass bin of size 20, we calculate the correlation coefficients and (Equation 1). The vertical error bars are derived from bootstrapping the sample. The horizontal error bars show the extent of each mass bin.

We bin the planet population into samples of 20, and perform a least squares fit for a linear dependence between radius, mass, equilibrium temperature , and metallicity:

(1)

where the magnitude of and are used to judge the level of correlation for and [Fe/H], respectively. takes into account a linear dependence between mass and radius within the mass bin. is an arbitrary offset in the fit. The errors in the coefficients are derived by bootstrapping the analysis within each mass bin. Since each mass bin covers a relatively small mass range, a linear dependence is sufficient (see Figure 7 for the sizes of each mass bin). We find a peak in the mass dependence of the correlation at , and a general lack of overall correlation between and . The correlation coefficients are plotted against their respective mass bins in Figure 7. We repeated the exercise using only planets with solar-mass hosts (), to reduce any potential selection effects in the target selection and spectral classifications of the surveys. Smaller planets are found in longer periods (e.g. Mazeh et al., 2005; Davis & Wheatley, 2009), biasing the -mass distribution. To reduce the effect of the bias, we re-perform the analysis using only mildy irradiated planets . In addition, the radius- dependence is non-linear over the general population (Demory & Seager, 2011), limiting the range has the added benefit of reducing effect of the non-linear dependence on the analysis. In all cases we find the peak dependence to to be , and a lack of dependence on [Fe/H].

We also perform the same analysis for the entire population of hot gas-giants, fitting for a second order polynomial in mass-radius, and linear dependence to and . We find a strong correlation in with , and an insignificant correlation in , with . Increasing the order of the polynomial does not affect the coefficient values within errors. We find the overall dependence to to be weak at best. Miller & Fortney (2011) suggests that the -radius dependence is more prominent for the least irradiated planets, we limit the analysis to planets with , but still find a lack of correlation with , with and .

We find the radius of Saturn-mass planets are less affected by their equilibrium temperature than Jupiter-mass planets, in agreement with the Singular Value Decomposition analysis performed by Enoch et al. (2012). In addition, we also find that the radius of planets with are also less dependent on equilibrium temperature. This effect is reproduced by the isochrones from Fortney et al. (2007). The isochrones can also reproduce a drop in the correlation strength between irradiation and radius for the least massive gas-giants (), but require the presence of a large core (). Interestingly, we find no statistically significant dependence of radius on the host star metallicity, contrary to previous examinations (e.g. Guillot et al., 2006; Béky et al., 2011; Enoch et al., 2011, 2012). It is not clear how the host star metallicity affects the metallicity and radius of the planet. A higher metallicity disk may produce planets with more massive cores, leading to a smaller overall radius (e.g. Guillot et al., 2006), but a higher opacity atmosphere is more efficient at retaining heat, reducing the rate of contraction, leading to a more inflated radius (e.g. Burrows et al., 2007, 2011).

Development of the HATSouth project was funded by NSF MRI grant NSF/AST-0723074, operations are supported by NASA grant NNX12AH91H, and follow-up observations receive partial support from grant NSF/AST-1108686. Work at the Australian National University is supported by ARC Laureate Fellowship Grant FL0992131. Followup observations with the ESO 2.2 m/FEROS instrument were performed under MPI guaranteed time (P087.A-9014(A), P088.A-9008(A), P089.A-9008(A)) and Chilean time (P087.C-0508(A)). A.J. acknowledges support from FONDECYT project 1130857, BASAL CATA PFB-06, and the Millennium Science Initiative, Chilean Ministry of Economy (Millenium Institute of Astrophysics MAS and Nucleus P10-022-F). V.S. acknowledges support form BASAL CATA PFB-06. M.R. acknowledges support from FONDECYT postdoctoral fellowship No3120097. R.B. and N.E. acknowledge support from CONICYT-PCHA/Doctorado Nacional and Fondecyt project 1130857. This work is based on observations made with ESO Telescopes at the La Silla Observatory under programme IDs P087.A-9014(A), P088.A-9008(A), P089.A-9008(A), P087.C-0508(A), 089.A-9006(A), and We acknowledge the use of the AAVSO Photometric All-Sky Survey (APASS), funded by the Robert Martin Ayers Sciences Fund, and the SIMBAD database, operated at CDS, Strasbourg, France. Operations at the MPG/ESO 2.2 m Telescope are jointly performed by the Max Planck Gesellschaft and the European Southern Observatory. The imaging system GROND has been built by the high-energy group of MPE in collaboration with the LSW Tautenburg and ESO. We thank Régis Lachaume for his technical assistance during the observations at the MPG/ESO 2.2 m Telescope. Australian access to the Magellan Telescopes was supported through the National Collaborative Research Infrastructure Strategy of the Australian Federal Government. We thank Albert Jahnke, Toni Hanke (HESS), Peter Conroy (MSO) for their contributions to the HATSouth project.

Footnotes

  1. affiliation: The HATSouth network is operated by a collaboration consisting of Princeton University (PU), the Max Planck Institute für Astronomie (MPIA), and the Australian National University (ANU). The station at Las Campanas Observatory (LCO) of the Carnegie Institute is operated by PU in conjunction with collaborators at the Pontificia Universidad Católica de Chile (PUC), the station at the High Energy Spectroscopic Survey (HESS) site is operated in conjunction with MPIA, and the station at Siding Spring Observatory (SSO) is operated jointly with ANU.
  2. affiliation: Research School of Astronomy and Astrophysics, Australian National University, Canberra, ACT 2611, Australia; email: george.zhou@anu.edu.au
  3. affiliation: Research School of Astronomy and Astrophysics, Australian National University, Canberra, ACT 2611, Australia; email: george.zhou@anu.edu.au
  4. affiliation: Department of Astrophysical Sciences, Princeton University, NJ 08544, USA
  5. affiliation: Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA
  6. affiliation: Department of Astrophysical Sciences, Princeton University, NJ 08544, USA
  7. affiliation: Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA
  8. affiliation: Alfred P. Sloan Research Fellow
  9. affiliation: Packard Fellow
  10. affiliation: Department of Astrophysical Sciences, Princeton University, NJ 08544, USA
  11. affiliation: Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA
  12. affiliation: Departamento de Astronomía y Astrofísica, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, 7820436 Macul, Santiago, Chile
  13. affiliation: Max Planck Institute for Astronomy, Heidelberg, Germany
  14. affiliation: Max Planck Institute for Astronomy, Heidelberg, Germany
  15. affiliation: Department of Astrophysical Sciences, Princeton University, NJ 08544, USA
  16. affiliation: Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA
  17. affiliation: Max Planck Institute for Astronomy, Heidelberg, Germany
  18. affiliation: Departamento de Astronomía y Astrofísica, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, 7820436 Macul, Santiago, Chile
  19. affiliation: Departamento de Astronomía y Astrofísica, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, 7820436 Macul, Santiago, Chile
  20. affiliation: Niels Bohr Institute, Copenhagen University, Denmark
  21. affiliation: Max Planck Institute for Astronomy, Heidelberg, Germany
  22. affiliation: Departamento de Astronomía y Astrofísica, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, 7820436 Macul, Santiago, Chile
  23. affiliation: Departamento de Astronomía y Astrofísica, Pontificia Universidad Católica de Chile, Av. Vicuña Mackenna 4860, 7820436 Macul, Santiago, Chile
  24. affiliation: Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA
  25. affiliation: Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA
  26. affiliation: Research School of Astronomy and Astrophysics, Australian National University, Canberra, ACT 2611, Australia; email: george.zhou@anu.edu.au
  27. affiliation: Department of Terrestrial Magnetism, Carnegie Institution of Washington, 5241 Broad Branch Road NW, Washington, DC 20015-1305, USA
  28. affiliation: The Observatories of the Carnegie Institution of Washington, 813 Santa Barbara Street, Pasadena, CA 91101, USA
  29. affiliation: The Observatories of the Carnegie Institution of Washington, 813 Santa Barbara Street, Pasadena, CA 91101, USA
  30. affiliation: The Observatories of the Carnegie Institution of Washington, 813 Santa Barbara Street, Pasadena, CA 91101, USA
  31. affiliation: Department of Earth and Planetary Sciences, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8551
  32. affiliation: Max Planck Institute for Astronomy, Heidelberg, Germany
  33. affiliation: Hungarian Astronomical Association, Budapest, Hungary
  34. affiliation: Hungarian Astronomical Association, Budapest, Hungary
  35. affiliation: Hungarian Astronomical Association, Budapest, Hungary
  36. affiliation: Astrophysics Group, School of Physics, University of Exeter, Stocker Road, Exeter EX4 4QL, UK
  37. affiliation: Max Planck Institute for Astronomy, Heidelberg, Germany
  38. exoplanets.org, 21 Dec 2013
  39. Outlying exposures have been discarded.
  40. Mode time difference between points in the light curve. Uniform sampling was not possible due to visibility, weather, pauses.
  41. Reconnaissance observations used for initial spectral classifications
  42. Reconnaissance observations used to constrain the radial velocity variations
  43. High precision radial velocities to determine the spectroscopic orbit of the planet
  44. An instrumental offset in the velocities from each instrument was fitted for and subtracted in the analysis and the values presented in this table. Observations without an RV measurement are I-free template observations, for which only the bisector (BS) is measured.
  45. Internal errors excluding the component of astrophysical/instrumental jitter considered in Section 3.
  46. HDS template observations made without the Iodine cell. We only measure the BS values for these observations.
  47. Magnitudes have the out-of-transit level subtracted. HATSouth magnitudes (HS) have been treated with EPD and TFA prior to the transit fitting. The detrending and potential blending may cause the HATSouth transit to be up to 8% shallower than the true transit. Follow-up light curves from GROND have been treated with EPD simultaneous to the transit fitting.
  48. Pre-EPD magnitudes are presented for the follow-up light curves.
  49. SPC: The stellar parameters are derived from the PFS iodine-free spectrum using the Stellar Parameter Classification (SPC) pipeline (Buchhave et al., 2012). These parameters also have small dependences on the global model fit and isochrone search iterations.
  50. YY++SPC: Based on the YY isochrones (Yi et al., 2001),  as a luminosity indicator, and the SPC results.
  51. : Reference epoch of mid transit that minimizes the correlation with the orbital period. BJD is calculated from UTC. : total transit duration, time between first to last contact; : ingress/egress time, time between first and second, or third and fourth contact.
  52. : Reference epoch of mid transit that minimizes the correlation with the orbital period. BJD is calculated from UTC. : total transit duration, time between first to last contact; : ingress/egress time, time between first and second, or third and fourth contact.
  53. : Reference epoch of mid transit that minimizes the correlation with the orbital period. BJD is calculated from UTC. : total transit duration, time between first to last contact; : ingress/egress time, time between first and second, or third and fourth contact.
  54. Reciprocal of the half duration of the transit used as a jump parameter in our MCMC analysis in place of . It is related to by the expression (Bakos et al., 2010).
  55. Values for a quadratic law given separately for the Sloan , , and filters. These values were adopted from the tabulations by Claret (2004) according to the spectroscopic (SPC) parameters listed in Table 5.
  56. This jitter was added in quadrature to the RV uncertainties for each instrument such that for the observations from that instrument. In the case of HDS, , so no jitter was added.
  57. Correlation coefficient between the planetary mass  and radius .
  58. The Safronov number is given by (see Hansen & Barman, 2007).
  59. Incoming flux per unit surface area, averaged over the orbit.
  60. As of 12 Dec 2013, exoplanets.org

References

  1. Bakos, G., Noyes, R. W., Kovács, G., et al. 2004, PASP, 116, 266
  2. Bakos, G. Á., Kovács, G., Torres, G., et al. 2007, ApJ, 670, 826
  3. Bakos, G. Á., Torres, G., Pál, A., et al. 2010, ApJ, 710, 1724
  4. Bakos, G. Á., Csubry, Z., Penev, K., et al. 2013, PASP, 125, 154
  5. Bayliss, D., Zhou, G., Penev, K., et al. 2013, AJ, 146, 113
  6. Béky, B., Bakos, G. Á., Hartman, J., et al. 2011, ApJ, 734, 109
  7. Borucki, W. J., Koch, D., Basri, G., et al. 2010, Science, 327, 977
  8. Buchhave, L. A., Latham, D. W., Johansen, A., et al. 2012, Nature, 486, 375
  9. Burrows, A., Heng, K., & Nampaisarn, T. 2011, ApJ, 736, 47
  10. Burrows, A., Hubeny, I., Budaj, J., & Hubbard, W. B. 2007, ApJ, 661, 502
  11. Butler, R. P., Marcy, G. W., Williams, E., et al. 1996, PASP, 108, 500
  12. Charbonneau, D., Brown, T. M., Noyes, R. W., & Gilliland, R. L. 2002, ApJ, 568, 377
  13. Claret, A. 2004, A&A, 428, 1001
  14. Cowan, N. B., & Agol, E. 2011, ApJ, 729, 54
  15. Crane, J. D., Shectman, S. A., Butler, R. P., et al. 2010, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 7735, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series
  16. Davis, T. A., & Wheatley, P. J. 2009, MNRAS, 396, 1012
  17. Deming, D., Seager, S., Richardson, L. J., & Harrington, J. 2005, Nature, 434, 740
  18. Demory, B.-O., & Seager, S. 2011, ApJS, 197, 12
  19. Dopita, M., Hart, J., McGregor, P., et al. 2007, Ap&SS, 310, 255
  20. Enoch, B., Collier Cameron, A., & Horne, K. 2012, A&A, 540, A99
  21. Enoch, B., Cameron, A. C., Anderson, D. R., et al. 2011, MNRAS, 410, 1631
  22. Foreman-Mackey, D., Hogg, D. W., Lang, D., & Goodman, J. 2012, ArXiv e-prints, 1202.3665
  23. Fortney, J. J., Lodders, K., Marley, M. S., & Freedman, R. S. 2008, ApJ, 678, 1419
  24. Fortney, J. J., Marley, M. S., & Barnes, J. W. 2007, ApJ, 659, 1661
  25. Fressin, F., Torres, G., Charbonneau, D., et al. 2013, ApJ, 766, 81
  26. Greiner, J., Bornemann, W., Clemens, C., et al. 2008, PASP, 120, 405
  27. Guillot, T., Santos, N. C., Pont, F., et al. 2006, A&A, 453, L21
  28. Hansen, B. M. S., & Barman, T. 2007, ApJ, 671, 861
  29. Hartman, J. D., Bakos, G. Á., Torres, G., et al. 2011, ApJ, 742, 59
  30. Howard, A. W., Marcy, G. W., Bryson, S. T., et al. 2012, ApJS, 201, 15
  31. Jordán, A., Espinoza, N., Rabus, M., et al. 2013, ApJ, 778, 184
  32. Kambe, E., Sato, B., Takeda, Y., et al. 2002, PASJ, 54, 865
  33. Kipping, D. M. 2013, MNRAS, 435, 2152
  34. Kovács, G., Bakos, G., & Noyes, R. W. 2005, MNRAS, 356, 557
  35. Kovács, G., Zucker, S., & Mazeh, T. 2002, A&A, 391, 369
  36. Lomb, N. R. 1976, Ap&SS, 39, 447
  37. Mancini, L., Ciceri, S., Chen, G., et al. 2013, MNRAS, 436, 2
  38. Mazeh, T., Zucker, S., & Pont, F. 2005, MNRAS, 356, 955
  39. Miller, N., & Fortney, J. J. 2011, ApJ, 736, L29
  40. Mohler-Fischer, M., Mancini, L., Hartman, J. D., et al. 2013, A&A, 558, A55
  41. Nascimbeni, V., Piotto, G., Pagano, I., et al. 2013, A&A, 559, A32
  42. Nelson, B., & Davis, W. D. 1972, ApJ, 174, 617
  43. Nikolov, N., Chen, G., Fortney, J. J., et al. 2013, A&A, 553, A26
  44. Noguchi, K., Aoki, W., Kawanomoto, S., et al. 2002, PASJ, 54, 855
  45. Penev, K., Bakos, G. Á., Bayliss, D., et al. 2013, AJ, 145, 5
  46. Pollacco, D. L., Skillen, I., Collier Cameron, A., et al. 2006, PASP, 118, 1407
  47. Pont, F., Knutson, H., Gilliland, R. L., Moutou, C., & Charbonneau, D. 2008, MNRAS, 385, 109
  48. Queloz, D., Eggenberger, A., Mayor, M., et al. 2000, A&A, 359, L13
  49. Santos, N. C., Israelian, G., & Mayor, M. 2004, A&A, 415, 1153
  50. Sato, B., Kambe, E., Takeda, Y., Izumiura, H., & Ando, H. 2002, PASJ, 54, 873
  51. Sato, B., Hartman, J. D., Bakos, G. Á., et al. 2012, PASJ, 64, 97
  52. Scargle, J. D. 1982, ApJ, 263, 835
  53. Sing, D. K., Pont, F., Aigrain, S., et al. 2011, MNRAS, 416, 1443
  54. Sing, D. K., Lecavelier des Etangs, A., Fortney, J. J., et al. 2013, MNRAS, 436, 2956
  55. Snellen, I. A. G., Albrecht, S., de Mooij, E. J. W., & Le Poole, R. S. 2008, A&A, 487, 357
  56. Southworth, J., Maxted, P. F. L., & Smalley, B. 2004, MNRAS, 351, 1277
  57. Sozzetti, A., Torres, G., Charbonneau, D., et al. 2007, ApJ, 664, 1190
  58. Yi, S., Demarque, P., Kim, Y.-C., et al. 2001, ApJS, 136, 417
  59. Zhou, G., Bayliss, D., Hartman, J. D., et al. 2013, ArXiv e-prints, 1310.7591
Comments 0
Request Comment
You are adding the first comment!
How to quickly get a good reply:
  • Give credit where it’s due by listing out the positive aspects of a paper before getting into which changes should be made.
  • Be specific in your critique, and provide supporting evidence with appropriate references to substantiate general statements.
  • Your comment should inspire ideas to flow and help the author improves the paper.

The better we are at sharing our knowledge with each other, the faster we move forward.
""
The feedback must be of minumum 40 characters
Add comment
Cancel
Loading ...
103227
This is a comment super asjknd jkasnjk adsnkj
Upvote
Downvote
""
The feedback must be of minumum 40 characters
The feedback must be of minumum 40 characters
Submit
Cancel

You are asking your first question!
How to quickly get a good answer:
  • Keep your question short and to the point
  • Check for grammar or spelling errors.
  • Phrase it like a question
Test
Test description