UV Emission from Exoplanet Hosts

An Ultraviolet Investigation of Activity on Exoplanet Host Stars

Abstract

Using the far-UV (FUV) and near-UV (NUV) photometry from the NASA Galaxy Evolution Explorer (GALEX), we searched for evidence of increased stellar activity due to tidal and/or magnetic star-planet interactions (SPI) in the 272 of known FGK planetary hosts observed by GALEX. With the increased sensitivity of GALEX, we are able probe systems with lower activity levels and at larger distances than what has been done to date with X-ray satellites. We compared samples of stars with close-in planets (a 0.1 AU) to those with far-out planets (a 0.5 AU) and looked for correlations of excess activity with other system parameters. This statistical investigation found no clear correlations with , , nor , in contrast to some X-ray and Ca II studies. However, there is tentative evidence (at a level of 1.8-) that stars with RV-detected close-in planets are more FUV-active than stars with far-out planets, in agreement with several published X-ray and Ca II results. The case is strengthened to a level of significance of 2.3- when transit-detected close-in planets are included. This is most likely because the RV-selected sample of stars is significantly less active than the field population of comparable stars, while the transit-selected sample is similarly active. Given the factor of 2–3 scatter in fractional FUV luminosity for a given stellar effective temperature, it is necessary to conduct a time-resolved study of the planet hosts in order to better characterize their UV variability and generate a firmer statistical result.

stars: exoplanet hosts, stars: late-type, activity
2

1 Introduction

1.1 Magnetic Star-Planet Interactions

Planetary systems characterized by giant planets located a few stellar radii from their parent stars (“hot Jupiters”) make up 20% of all known exoplanetary systems. For these mature hot Jupiter systems several studies (e.g. Shkolnik et al. 2003, 2005, 2008; Saar et al. 2008; Walker et al. 2008; Pagano et al. 2009; Lanza 2009, 2010; Pillitteri et al. 2010) have independently converged on the same scenario: a short-period planet can induce activity on the photosphere and upper atmosphere of its host star, making the star itself a probe of its planet.

The first such monitoring campaign of chromospheric emission from hot Jupiter host stars revealed that stellar activity tracers vary with the planet’s orbital period rather than the star’s rotation for several systems (Shkolnik et al. 2003, 2005; Gurdemir et al. 2012). Pillitteri et al. (2011) reported repeated coronal X-ray flares from HD 189733 at the same orbital phase. These planet-phased phenomena are interpreted as evidence for magnetic star-planet interactions (SPI) induced by the magnetized planet (Lanza, 2008, 2009; Cohen et al., 2009). The roles of magnetic fields (both stellar and planetary) in the formation and migration of giant planets are currently rarely evoked and never precisely described because of a lack of data and the complexity of the processes involved. In fact, the strength of any exoplanetary fields is completely unknown and only inferred by making comparisons with Jupiter, while direct measurements using radio emission have not yet succeeded (e.g. Lecavelier Des Etangs et al. 2011).

Magnetic SPI in hot Jupiter systems is detectable because the planets in general lie within the Alfvén radius of their parent stars (10 R). Within this distance, the Alfvén speed is higher than the stellar wind speed, thereby allowing direct magnetic interaction with the stellar surface. If a hot Jupiter is magnetized, its magnetosphere interacts with the open coronal fields of its star throughout its orbital motion, potentially through magnetic reconnection (Lanza, 2008, 2009; Cohen et al., 2009), propagation of Alfvén waves within the stellar wind (Preusse et al., 2006; Kopp et al., 2011), and/or the generation of an electron beam which strikes the base of a stellar corona (Gu & Suzuki 2009). Lanza (2011) considers also a planetary magnetic field with more realistic, non-uniform stellar magnetic field configurations in order to explain possible evidence for SPI as revealed by the photospheric magnetic activity in some of the CoRoT planet hosts.

These studies demonstrate the need to understand the host star’s magnetic field and activity. The existing models of magnetic SPI generally give a dissipated power depending on the coronal field strength , the strength of the planetary field , and the relative velocity of the planet with respect to the coronal field lines . Considering the treatment of Lanza (2009), this gives a dissipated power of

Since the strength of the stellar field can be derived from spectropolarimetric measurements or estimated from spectroscopic activity/rotation diagnostics (e.g. Collier Cameron & Jianke 1994; Fares et al. 2012), and the orbital parameters of the systems are known, we can derive relative values of the planetary field strength from observations of the excess power radiated by a chromospheric/coronal hot spot (E. Shkolnik, in preparation).

Both the star’s and the planet’s magnetic field need to be of some minimum strength in order for the SPI phenomenon to be observed. This explains the null detection of planet-phased stellar activity on WASP-18 by Miller et al. (2012), since the star has an extremely weak field based on the fact that it is the least active, i.e. has the lowest log(),3 of all known planets hosts. Conversely, the HD 189733 system has the strongest detected SPI emission to date (Shkolnik et al., 2008) as well as the strongest stellar magnetic field measurement of 40 G. (Fares et al., 2010).

1.2 Planetary Effects on Stellar Angular Momentum Evolution

It is well-known that main-sequence FGK stars have magnetized stellar winds, which act as brakes to the stellar rotation, and thus decrease the global stellar activity. This produces the useful age-rotation-activity relationships (e.g. Barnes 2007; Mamajek & Hillenbrand 2008). However, in addition to magnetic SPI, tidal interactions in hot Jupiter systems may also increase the star’s activity levels by tidally spinning up the star until the two bodies are tidal locked, e.g.  Boo, CoRoT-4 (Catala et al., 2007; Aigrain et al., 2008). If a hot Jupiter is affecting the star’s angular momentum, then the age-activity relation of these systems will systematically underestimate the star’s age, rendering “gyrochronology” inapplicable to such systems.

Pont (2009) and Brown et al. (2011) presented empirical evidence for excess rotation of the host stars compared to evolutionary models in several transiting systems presumed to be due to tidal spin-up of the star caused by its planet. Additional evidence of this using two hot Jupiter systems has been reported by Schröter et al. (2011) and Pillitteri et al. (2010, 2011). Both of these studies did not detect X-ray emission from known M dwarf companions to their relatively active planet hosts (CoRoT-2 and HD 189733, respectively). This lack of X-ray emission indicates that the systems are 2 Gyr old (West et al. 2008), but the activity-rotation age of the planet hosts are 100–300 Myr for CoRoT-2 and 600 Myr for HD 189733. These discrepancies would be resolved if the excess rotation and activity on the primaries were due to interactions with the close-in giant planets, and not their proposed youth.

Lanza (2010) showed that tides in these systems may be too weak to spin-up the star, and provided an alternative explanation for the excess stellar rotation. He proposed that interactions between the planetary field and stellar coronal field lead to a stellar magnetic field topology with predominantly closed field lines, thereby limiting the stellar wind flow and consequent angular momentum loss. Lanza adopted an analytic linear force-free model to compute the radial extent of the corona and its angular momentum loss rate. He found that stars with magnetized hot Jupiters experience angular momentum loss at a significantly slower pace than similar stars without such massive planets. This reduction in angular momentum loss due to the interaction between the stellar and planetary magnetic fields is confirmed by the MHD calculations of Cohen et al. (2009, 2010) and Vidotto et al. (2011).

1.3 Are stars with hot Jupiters more active than stars with cold Jupiters?

As the number of known exoplanets with published orbital parameters begins to climb, statistical studies of the ensemble become an effective and efficient way to study exoplanetary systems. Correlations between stellar activity and planet properties were first shown for a sample of only 13 stars in Shkolnik et al. (2005) and Shkolnik et al. (2008) who showed that short-term variability observed in the chromospheric Ca II H & K emission correlated with the ratio of the minimum planetary mass to the rotational orbital period, a value proportional to the planet’s magnetic field strength (Tholen et al., 2000; Kivelson et al., 2002). More recently Hartman (2010) showed that the Ca II emission, as measured by log(), of a sample of transiting systems correlates with the planet’s surface gravity, although an explanation is not provided. Knutson et al. (2010) found a correlation between the log() of the star and presence of the stratosphere on the planet, likely due to the increased UV flux received by planets orbiting more active stars, which destroys the compounds responsible for the formation of the observed temperature inversions. And most recently, Krejčová & Budaj (2012) presented evidence of larger log() for stars with close-in planets compared to stars with far-out planets. This is in agreement with Gonzalez (2011) and yet contrary to Canto Martins et al. (2011).

Over the past few years, a parallel debate in the literature has arisen about correlations between stellar X-ray emission and planet properties. Kashyap et al. (2008) studied the X-ray properties of 46 main-sequence stars with exoplanets. They showed that in a volume-limited sample, those stars with massive planets within 0.15 AU have 4 times the X-ray emission of those stars with Jupiter-mass planets orbiting with AU. After correction for what they attributed to selection effects, the enhancement was still a factor of two. They speculated that this enhanced activity on the parent star may be induced by magnetic interactions with the close-in giant planet.

Poppenhaeger et al. (2010) repeated a similar X-ray analysis with 72 planet hosts ranging from F to M stars (including main-sequence and giant stars), but did not see the same effect in two samples: AU and AU. However, a significant correlation did appear between X-ray luminosity and the ratio between the planet mass and semi-major axis (sin/), i.e. massive, close-in planets do tend to orbit more X-ray luminous stars. They assume this correlation is due to the selection bias of the radial velocity (RV) planet search method. Scharf (2010) studied a sample of 29 exoplanet hosts detected by ROSAT, and although he saw no significant difference in between two samples, AU and AU, he did report a striking correlation between and sin in the first sample. Poppenhaeger & Schmitt (2011) showed that this result is likely due to the selection effects of the flux limit of the X-ray data used and possibly the intrinsic planet detectability of the RV method. Indeed it is easier to find smaller and more distant planets around less active stars, however, both Scharf (2010) and Hartman (2010) demonstrate that for at least stars with planets greater than 0.1 M orbiting within 2 AU, no significant detection bias of the RV method exists.

In this paper we approach the question of whether or not stars with close-in planets statistically have higher-than-expected stellar activity using a different activity diagnostic, FUV and NUV photometry from NASA’s Galaxy Evolution Explorer (GALEX; Martin et al. 2005), providing a new resource that enables a major expansion of the study of stellar activity on exoplanets hosts.

2 Galex Observations of Exoplanet Host Stars

The GALEX satellite was launched on April 28, 2003 and has imaged approximately 3/4 of the sky simultaneously in two UV bands: near-UV (NUV) 1750–2750 Å and far-UV (FUV) 1350–1750 Å, with angular resolutions of 5″ and 6.5″, respectively, across a 1.25 field of view. The full description of the instrumental performance is presented by Morrissey et al. (2005). In addition to a medium and a deep imaging survey (MIS, DIS), covering 1000 and 100 square degrees, respectively, the GALEX mission has produced an All-sky Imaging Survey (AIS) in both UV bands which is archived at the Multi-mission Archive at the Space Telescope Science Institute (MAST).4 The NUV and FUV fluxes and magnitudes averaged over the entire exposure are produced by the standard GALEX Data Analysis Pipeline (ver. 4.0) operated at the Caltech Science Operations Center (Morrissey et al., 2007). The data presented in this paper made use of the sixth data release (GR6), which includes the three surveys plus publicly available data from Guest Investigator (GII) programs.

For stars hotter than about 5250 K, the flux in the GALEX bandpasses is made up predominantly from continuum emission (Smith & Redenbaugh, 2010) with additional flux provided by strong emission lines (C IV, C II, Si IV, He II) originating from the corona, transition region and chromosphere. Cooler stars have FUV and NUV fluxes strongly dominated by stellar activity (e.g. Robinson et al. 2005; Welsh et al. 2006; Pagano 2009). This makes GALEX an excellent tool with which to study stellar activity, especially since GALEX can detect FGK (and early Ms) at great distances than the existing X-ray missions, out to 150 pc for the FUV and between 20 and 500 pc, depending of  for the NUV (Findeisen & Hillenbrand, 2010; Shkolnik et al., 2011).

2.1 The Sample

As of November 2012, orbital parameters of 641 extrasolar planets orbiting 523 stars were published in the literature, and conveniently compiled in the Exoplanet Data Explorer (http://www.exoplanets.org; Wright et al. 2011). We cross-matched this sample of planet hosts against the GALEX archive using a 30 search radius. We limit our analysis to only F, G, and K stars ( between 4500 and 6700 K) that do not have stellar companions within the GALEX PSF diameter (30). A histogram of the semi-major axes of the inner-most planets around stars observed by GALEX is shown in Figure 1.5 The median positional offset was only 1.9, small compared to the reported pointing error of 10.

Table 1 lists the relevant data for each star observed by GALEX as part of the GR6 data release including FUV and NUV fluxes, and , and fractional luminosities (/ and /). The reported fluxes use the auto aperture of the GALEX pipeline and are deemed reliable as long as they agree to within 20% with the pipeline’s aper_7 aperture (Morrissey et al., 2007). There are many potential artifacts reported by the GALEX archive and one needs to be cautious with edge effects, bright star halos, detector ghosts, hot spots and saturation in order to extract reliable photometry.

Of the 272 FGK stars in the sample observed by GALEX, all were detected in the NUV bandpass, yet only 82 of them were not saturated or of good photometric quality. Fifty-two of these were detected by the transit method and 30 were discovered with the RV method. As the transit-detected systems tend to lie further away, fewer of them are saturated. Those detected with the RV method are closer and brighter, and thus the unsaturated NUV detections tend to lie toward the fainter and cooler end of the distribution (5500 K). Only 13 stars have both reliable FUV and NUV detections. The FUV observations provide 128 targets with reliable photometry plus 86 upper limits. This sample is 2–4 times larger than the X-ray samples used by Kashyap et al. (2008), Scharf (2010), and Poppenhaeger et al. (2010).

3 Results

In Figures 2 and 3, we plot the fractional FUV and NUV luminosity, log() and log(), for the planet hosts as a function of . The dependence of each on  is clear due to the large contribution of photospheric flux in these GALEX bandpasses. However, at a given , the scatter spans a factor of 2–3 likely due to differences in intrinsic stellar activity, uncertainties in , and metallicity variations between sources. This distribution of FUV and NUV fluxes is also probably affected by the fact that the data consist of a single observation for each star. Yet we know such stars exhibit stellar activity on both short and long-term time scales, e.g. magnetic breaking with age, stellar activity cycles, rotational modulation, and perhaps the SPI effects of known and unknown close-in planets described in Section 1.

In order to search for differences in activity levels with semi-major axis of a system’s inner-most planet, we separated the sample of exoplanet hosts into two bins: AU and AU. We chose AU for the “close-in” planetary systems for two reasons:

1) A Jupiter-mass planet within 0.1 AU may tidally spin-up the star with a stellar synchronization time scale less than 10 Gyr. Beyond 0.1 AU, the tidal interaction is so weak that no stellar spin-up is expected. Tidal heating of the stellar upper atmosphere is also unexpected beyond this distance (Cuntz et al., 2000).

2) If any SPI is dominated by magnetic SPI, then the Alfvén radius for sun-like stars of ages 1 Gyr is also within 0.1 AU (Preusse et al., 2006), and we therefore do not expect any increased stellar activity due to magnetic interactions between the planet and the star to be observable beyond this distance.

The “far-out” sample is limited by 0.5 AU to make sure uncertainties in Alfvén radii are accommodated while the outer limit of 2 AU shields the analysis from potential observing biases. As mentioned above, past studies have shown that within this distance no significant planet-detection biases exist for the RV-discovered planets with minimum planet mass sin 0.1 M. Transit detections have been strongly biased towards close-in planets leaving us with no confirmed transiting planets with FUV detections in our far-out sample. This will be aided in the future with Kepler observations which will eventually provide confirmed planets in distant orbits6 around stars with UV observations. In fact, recent GALEX NUV observations have been carried out of the entire Kepler field so we will be able to revisit these questions for transit-detected planets in the very near future (J. Lloyd, personal communication).

3.1 FUV detections

In the FUV bandpass, we are able to make comparisons with the magnitude-complete and kinematically unbiased sample of the nearest F and G (and some K) dwarfs compiled by the Geneva-Copenhagen survey (GCS; Holmberg et al. 2009). To make the fairest comparisons between samples, we removed close binaries and giants, and also limited the metallicity range of the GCS sample to that of the planet hosts: -0.25 [Fe/H] 0.6. Of the remaining stars, 1141 have reliable FUV detections.

Of the known planet hosts, there are 34 stars with reliable FUV detections in the “close-in” sample, of which 18 are detected with the RV method and 16 with the transit method. The “far-out” sample consists of 44 stars all detected with the RV method. Upper limits are also provided for 86 of the transit-detected systems who generally lie further away from the Sun than the brighter, RV-detected systems.

We searched for activity differences between the close-in and far-out samples, as well as for correlations in the excess FUV emission with planetary system properties to compare with those previously published in the literature using X-ray detections. In order to do this, we removed the FUV temperature dependence by fitting the following second-order polynomial the GCS sample:

We then searched for correlations between the residual FUV luminosities (log()) with planet properties, namely log(), , and for the close-in planets. We find no clear dependence on any of these (Figures 4 and 5) as has been reported in the past using X-ray luminosities (Kashyap et al. 2008; Poppenhaeger et al. 2010; Scharf 2010). This may be due to the difficulties in accurately subtracting the photospheric contribution of the FUV flux, which is not a problem for X-ray studies. X-ray emission is a direct diagnostic of coronal activity alone, whereas the residual FUV flux is composed of emission lines originating in the star’s corona, transition region and chromosphere. In addition, the scatter of the GCS comparison sample spans a factor of 2–3 implying that there are intrinsic stellar variations which are likely drowning out any statistically detectable SPI effects.

When comparing the close-in and far-out samples, a Kolmogorov-Smirnov (K-S) test reveals evidence that the stars with close-in planets do indeed have higher levels of FUV emission compared to stars with far-out planets (, , 2.3-). And if the same test is done with only the RV-detected planets, the results weaken to (1.8-), . It is important to note that entire sample of RV-detected planet hosts is significantly less active in the FUV than the field population with , pointing to the observational bias towards looking for planets around relatively quiescent and slowly rotating stars compared to the field. On the other hand, the FUV detections of transit-detected systems, all of which host planets within 0.1 AU, are indistinguishable from the field sample with , and are notably more active than the RV-selected sample. This is also apparent in the comparison of the  values of the RV and transit samples where , . This points to the relative lack of selection bias toward inactive stars of the transit method compared to RV method. This is expected as only a few RVs are necessary to confirm the transiting planet candidate, nor will the RV signal be attributed to stellar activity when the period and phasing is already determined by the transit. Therefore stars with promising planetary transit signals are followed up by RV observations regardless if they are more active than the typical RV planet search targets and are not subject to same very low-activity criteria.

Even though in general it is easier to find more massive planets around more active stars, there is a range for which sufficient RV precision is achieved such that the selection effects are minimized (or even non-existent): planets with masses greater than 0.1 M orbiting within 2 AU (e.g. Hartman 2010; Scharf 2010). Unfortunately, reducing the RV-detected planet sample to these ranges leaves only 9 stars in the close-in sample, making statistical comparison with the FUV detections not very meaningful. However, comparing the published  values of the close-in (22 targets) and far-out samples (81 targets) does not yield a significant difference (, ). This is in agreement with Canto Martins et al. (2011) yet disagrees with Gonzalez (2011).

Although our full data set suggests that stars with closer-in planets are be more active than stars with far-out planets, it remains highly probable that this is due to the selection biases of the planet detection methods. More studies designed specifically to address this question are required. It is necessary to conduct a time-resolved study of the planet hosts discovered by a single method in order to better characterize their UV variability.

3.2 NUV detections

A comparison of the exoplanet hosts with the GCS sample is not possible as nearly all of the stars in the GCS sample are saturated in the NUV. In fact, most of the RV-detected planet hosts are also saturated in the NUV as they are typically brighter than the those stars with planets detected using the transit method. However, there are 63 NUV detections of stars with transit detected planets (Figure 3), all with planets within 0.1 AU. As we showed in Section 3.1, the transit sample is comparable in activity levels to the field using the FUV observations and thus we fitted a polynomial to the NUV detections of the transit sample only to remove the  dependence. The function is:

We searched the residual NUV flux (log()) of the transit systems for correlations with planet properties log(), , and . Again, no clear correlations were observed (Figures 6 and 7). Clearer answers may emerge from the forthcoming analyses of the dedicated multi-epoch and deep GALEX/NUV observations of the Kepler candidates (J. Lloyd, personal communication) which include a wide range of semi-major axes (Batalha et al., 2012).

4 Summary

Using the FUV and NUV photometry the GALEX surveys, we searched for evidence of increased stellar activity due to tidal and/or magnetic SPI in the 272 planetary systems observed by GALEX. With the increased sensitivity of GALEX, we are able probe systems with lower activity levels and at larger distances than what has been done to date with X-ray satellites.

After correcting for the FUV and NUV dependence on , we compared samples of stars with close-in planets (a 0.1 AU) to those with far-out planets (0.5 a 2 AU ) and looked for correlations of activity with other system parameters, i.e. , , and . This statistical investigation found no clear correlations in either the RV-detected or transit-detected samples. However, there is tentative evidence (1.8-) that stars with RV-detected close-in planets are more FUV-active than stars with far-out planets, in agreement with several published X-ray and Ca II results. The case is strengthened to 2.3- when transit-detected close-in planets are included. This is most likely a result of the fact that the RV-selected sample of stars is significantly less active than the field population of comparable stars while the transit-selected sample is similarly active.

Even by limiting samples to a range where selection biases are not significant, the single-visit nature of all-sky UV and X-ray surveys pose a problem to such samples as they record only a snapshot observation per star, and do not account for changes in intrinsic stellar activity levels. With a factor of 2–3 scatter in fractional FUV luminosity for a given , it is necessary to conduct a time-resolved study of the planet hosts in order to better characterize their UV variability and generate a firmer statistical result. With the recent completion of a dedicated GALEX-NUV multi-epoch survey of the Kepler field, we will be able to re-evaluate these results with a much larger, and less biased, dataset.

E.S thanks stimulating discussion with G. Anglada-Escudé, A. C. Cameron, A.N. Lanza, A. Weinberger, K. R. Covey and T. Barman. Also thanks to the GALEX/MAST archive developers for their quick responses to all queries. This material is based upon work supported by the NASA/GALEX grant program under Cooperative Agreement No. NNX12AC19G issued through the Office of Space Science. This research has made use of the VizieR catalogue access tool, CDS, Strasbourg, France (Ochsenbein et al., 2000).
Figure 1: A histogram of semi-major axes of the inner-most planet for all confirmed exoplanetary systems (4500   6700 K) to date (black empty bars). Those observed by GALEX are shown in blue.

Figure 2: The fraction FUV luminosities as a function of effective temperature for RV- (grey) and transit-detected (red) exoplanetary systems. The GCS sample of field stars is shown in black with its the polynomial fit. See text for details.
Figure 3: The fractional NUV luminosities as a function of effective temperature for exoplanet hosts detected by GALEX with good photometry. Most of the RV-detected planet hosts, as well as the GCS field stars, are saturated in the NUV bandpass.
Figure 4: Residual FUV luminosities as a function of the semi-major axis of the inner planet mass.

Figure 5: The residual fractional FUV luminosity as a function of the mass of the inner most planet for the close-in sample ( 0.1 AU; left) and the ratio of the mass to semi-major axis (right).

Figure 6: Residual NUV luminosities as a function of semi-major axis of inner most planet. Note all transit-detected planets detected by GALEX have AU.

Figure 7: The residual fractional NUV luminosity as a function of of the inner most planet (left) and the ratio of the inner planet mass to the semi-major axis (right) for the transit-detected systems. Note all transit-detected planets detected by GALEX have AU.
Star/Planet7 Disc. 8 9 10 GALEX 11 12 log(/)13 log(/)14 NOTE15
ID Method AU M K Survey Jy Jy
HD 142 b RV 1.043 1.31 6249 AIS 855.08 21.77 sat. -5.771 0.011 5.4 K5 comp. [1]
WASP-44 b Tran. 0.035 0.89 5410 AIS 4 63.06 3.17 -5.246 -3.961 0.022 NUV artifact
WASP-32 b Tran. 0.039 3.54 6100 GII 3.54 0.38 1245.32 3.94 -5.916 0.047 -3.283 0.001
WASP-26 b Tran. 0.04 1.01 5950 AIS 7.2 1.79 1112.56 12.56 -5.636 0.108 -3.36 0.005
HD 1461 b RV 0.064 0.02 5765 AIS 59.18 5.11 sat. -6.607 0.037
WASP-1 b Tran. 0.039 0.83 6110 AIS 4 816.44 11.7 -5.68 -3.284 0.006
WASP-45 b Tran. 0.041 1 5140 MIS 1 57.42 1.35 -6.223 -4.377 0.01
HD 2039 b RV 2.198 5.92 5941 AIS 16.37 2.91 sat. -6.178 0.077
HIP 2247 b RV 1.339 5.12 4714 AIS 4 249.61 10.67 -6.746 -4.864 0.019
HD 2638 b RV 0.044 0.48 5192 AIS 4 1014.9 18.96 -6.703 -4.211 0.008
HAT-P-16 b Tran. 0.041 4.2 6158 NGS 6.21 0.74 2043.47 5.81 -5.862 0.052 -3.257 0.001
HD 3651 b RV 0.295 0.23 5221 AIS 44.94 6.16 sat. -7.038 0.059
HD 4208 b RV 1.654 0.81 5600 AIS 20.03 2.84 sat. -6.606 0.061
HD 4203 b RV 1.165 2.08 5702 AIS 4.83 2.3 3192.77 33.07 -6.846 0.207 -3.939 0.004
HD 4313 b RV 1.178 2.35 4991 AIS edge
HAT-P-28 b Tran. 0.043 0.63 5680 AIS 4 61.17 4.49 -5.235 -3.964 0.032
HD 5319 b RV 1.747 1.94 5052 MIS 2.32 0.36 1536.05 4.59 -7.532 0.067 -4.625 0.001
HD 5388 b RV 1.763 1.97 6297 AIS 512.5 15.08 sat. -5.556 0.013
HD 5891 b RV 0.724 6.78 4907 AIS 4 1340.88 16.75 -7.272 -4.659 0.005
HD 6434 b RV 0.142 0.4 5835 AIS 40.51 4.83 sat. -6.321 0.052
HIP 5158 b RV 0.888 1.43 4962 AIS 4 174.19 8.02 -6.483 -4.757 0.02
HD 6718 b RV 3.554 1.56 5746 AIS 13.56 3.81 sat. -6.499 0.122 bad phot.
HD 7199 b RV 1.362 0.3 5386 AIS 9.24 3.29 sat. -6.845 0.155 bad phot.
HD 7449 b RV 2.34 1.31 6024 AIS 86.06 9.78 sat. -6.065 0.049
HD 7924 b RV 0.057 0.03 5177 AIS 21.35 3.44 sat. -6.863 0.07
HD 8535 b RV 2.445 0.68 6136 AIS 102.58 12.58 sat. -5.893 0.053
HD 8574 b RV 0.757 1.81 6050 AIS 138.17 8.34 sat. -6.002 0.026
HD 9446 b RV 0.189 0.7 5793 AIS 15.1 3.73 sat. -6.434 0.107 bad phot.
WASP-18 b Tran. 0.02 10.06 6400 AIS 41.35 4.11 sat. -5.613 0.043
HD 10180 b RV 0.022 0 5911 AIS 42.23 3.38 sat. -6.441 0.035
HD 10697 b RV 2.132 6.24 5680 GII 64.11 1.48 sat. -6.7 0.01
HD 11506 b RV 2.605 4.73 6058 AIS edge
HD 11964 c RV 0.228 0.08 5349 MIS 24.79 1.39 sat. -7.09 0.024 29.7 K7 comp. [1]
HD 12661 b RV 0.838 2.34 5743 AIS edge
HD 13931 b RV 5.149 1.88 5829 AIS 37.17 6.18 sat. -6.386 0.072
HD 16141 b RV 0.356 0.25 5794 AIS 63.64 5.1 sat. -6.472 0.035 6.2 M3 comp. [1]
30 Ari B b RV 0.995 9.88 6300 AIS 636.76 17.95 sat. -5.345 0.012
HD 16417 b RV 0.135 0.07 5817 AIS 195.12 11.28 sat. -6.402 0.025
81 Cet b RV 2.539 5.34 4785 AIS 32.95 5.87 sat. -7.343 0.077
HD 16760 b RV 1.087 13.29 5620 NGS 9.81 1.14 sat. -6.529 0.05
iota Hor b RV 0.924 2.05 6097 AIS 1017.78 22.16 sat. -5.816 0.009
WASP-50 b Tran. 0.029 1.46 5400 MIS 1 233.84 2.23 -6.378 -3.922 0.004
HD 18742 b RV 1.927 2.72 5048 AIS 4 2917.28 32.12 -7.34 -4.39 0.005
WASP-11 b Tran. 0.044 0.54 4800 AIS 4 60.8 4.07 -5.786 -4.517 0.029
HIP 14810 d RV 1.886 0.58 5485 AIS 9.52 3.55 sat. -6.631 0.162 bad phot.
HD 19994 b RV 1.306 1.33 6188 MIS 1 sat. -8.959 2.5 M comp. [1]
HAT-P-25 b Tran. 0.047 0.57 5500 AIS 4 26.55 5.02 -5.256 -4.347 0.082
HD 20782 b RV 1.357 1.76 5758 AIS 47.07 4.85 sat. -6.39 0.045
HD 20868 b RV 0.947 2.01 4795 AIS 4 210 6.56 -6.555 -4.748 0.014
WASP-22 b Tran. 0.047 0.56 6000 AIS 4 660.85 10.96 -5.62 -3.315 0.007
epsilon Eri b RV 3.376 1.05 5146 AIS 4 sat. -8.964
HD 23127 b RV 2.319 1.4 5752 AIS 11.43 2.13 sat. -6.505 0.081
HD 23079 b RV 1.595 2.44 5927 GII 109.77 5.01 sat. -6.111 0.02
HD 23596 b RV 2.772 7.74 5904 AIS 72.8 7.28 sat. -6.225 0.043
HD 24040 b RV 4.565 3.84 5853 AIS 35.16 6.27 sat. -6.456 0.077 bad phot.
HD 25171 b RV 3.031 0.96 6160 AIS 100.72 6.91 sat. -5.873 0.03
epsilon Ret b RV 1.267 1.55 4846 AIS sat. sat. 13.8 faint comp. [1]
HD 27894 b RV 0.122 0.62 4875 AIS 4 438.44 8.99 -6.762 -4.635 0.009
XO-3 b Tran. 0.048 13.05 6429 AIS 210.55 9.97 sat. -4.694 0.021
HD 28254 b RV 2.148 1.16 5664 AIS 12.31 3.86 sat. -6.842 0.136
HAT-P-15 b Tran. 0.096 1.95 5568 AIS 4 79.61 7.02 -5.681 -4.295 0.038
HD 28185 b RV 1.023 5.8 5656 AIS 19.9 4.69 sat. -6.591 0.102 bad phot.
HD 28678 b RV 1.251 1.71 5076 AIS 4 1367.7 21.53 -7.188 -4.567 0.007
HD 30177 b RV 3.808 9.69 5607 AIS 4 sat. -7.05
HD 30856 b RV 2.035 1.86 4982 AIS 4 2461.03 24.96 -7.299 -4.423 0.004
HD 31253 b RV 1.261 0.5 5960 AIS edge
HD 33283 b RV 0.145 0.33 5995 AIS 24.8 2.98 sat. -6.372 0.052
HD 38283 b RV 1.024 0.34 5998 NGS 144.54 2.43 sat. -6.161 0.007
HD 39091 b RV 3.347 10.09 5950 AIS 355.48 19.2 sat. -6.184
HD 40307 b RV 0.047 0.01 4977 AIS 7.39 2.36 sat. -7.388 0.138
WASP-49 b Tran. 0.038 0.38 5600 AIS edge
HD 43691 b RV 0.242 2.5 6200 AIS 66.11 5.64 sat. -5.824 0.037
HD 44219 b RV 1.187 0.59 5752 GII 20.92 1.42 sat. -6.612 0.029 bad phot.
HD 45350 b RV 1.944 1.84 5616 AIS 10.09 2.62 sat. -6.854 0.113 bad phot.
6 Lyn b RV 2.186 2.21 4978 AIS 24.22 3.42 sat. -7.355 0.061
HD 47186 b RV 0.05 0.07 5675 AIS 44.98 7.44 sat. -6.315 0.072
HD 49674 b RV 0.057 0.1 5662 AIS 15.09 2.72 sat. -6.596 0.078 bad phot.
HAT-P-9 b Tran. 0.053 0.78 6350 AIS 4 753.74 12.78 -5.449 -3.087 0.007 NUV artifact
XO-4 b Tran. 0.055 1.6 5653 AIS 17.55 4.23 sat. -5.437 0.105
HAT-P-20 b Tran. 0.036 7.28 4595 AIS 4 43.95 3.59 -6.071 -4.943 0.035
HD 63454 b RV 0.036 0.38 4841 AIS 9.65 3.71 565.2 9.22 -6.392 0.167 -4.537 0.007 bad phot.
XO-5 b Tran. 0.051 1.15 5510 AIS 4.16 1.71 133.84 5.53 -5.558 0.178 -3.963 0.018 bad phot.
XO-2 b Tran. 0.037 0.57 5340 MIS 1 203.11 2.36 -6.566 -4.172 0.005
HD 66428 b RV 3.143 2.75 5752 AIS 13.09 4.13 sat. -6.589 0.137
HAT-P-35 b Tran. 0.05 1.05 6096 AIS 4 520.81 10.86 -5.409 -3.207 0.009 NUV artifact
HAT-P-30 b Tran. 0.042 0.71 6304 AIS 9.09 2.31 sat. -5.857 0.11
HD 68988 b RV 0.069 1.8 5960 AIS 22.4 5.55 sat. -6.362 0.108
HD 69830 b RV 0.078 0.03 5360 AIS 61.57 6.33 sat. -6.864
HD 73534 b RV 3.068 1.1 5041 MIS 3.97 0.68 1329.28 6.23 -7.213 0.074 -4.601 0.002 bad phot.
HAT-P-13 b Tran. 0.043 0.85 5653 MIS 1.14 0.27 757.79 3.3 -6.703 0.103 -3.794 0.002 bad phot.
WASP-36 b Tran. 0.026 2.26 5881 AIS 4 334.83 11.99 -5.321 -3.312 0.016
55 Cnc e RV 0.015 0.03 5196 MIS 38.95 1.81 sat. -7.079 0.02
HD 75898 b RV 1.189 2.52 6021 GII 37.3 1.92 sat. -6.116 0.022
HD 79498 b RV 3.133 1.35 5740 AIS 18.69 4.71 sat. -6.52 0.109
WASP-13 b Tran. 0.054 0.48 5826 NGS 3.63 0.62 2150.37 7.5 -6.261 0.074 -3.401 0.002
HD 80606 b RV 0.447 3.89 5573 NGS 3.31 0.16 2687.28 1.87 -6.881 0.021 -3.885 0 NUV arti.; 20.6 G5 comp. [1]
HD 81040 b RV 1.937 6.88 5700 AIS 45.68 4.2 sat. -6.264 0.04
HD 81688 b RV 0.811 2.69 4753 AIS 108.8 10.68 sat. -6.915 0.043
HD 82943 c RV 0.743 1.99 5997 AIS 135.46 8.87 sat. -6.244 0.028
HD 82886 b RV 1.581 1.31 5112 AIS 4.7 1.76 sat. -7.329 0.163 bad phot.
HD 86081 b RV 0.035 1.5 6028 AIS 20.28 4.77 sat. -6.193 0.102 bad phot.
HD 86264 b RV 2.841 6.63 6326 AIS 284.96 11.33 sat. -5.553 0.017
BD -08 2823 b RV 0.056 0.05 4746 AIS 4 297.25 10.76 -6.588 -4.63 0.016
HD 87883 b RV 3.576 1.76 4958 AIS 21.52 5 3278.87 36.35 -6.743 0.101 -4.473 0.005
HD 88133 b RV 0.047 0.3 5494 AIS 6.57 2.05 sat. -7.009 0.135 bad phot.
HD 89307 b RV 3.266 1.79 5898 AIS 98.65 10.34 sat. -6.201 0.045
HD 89744 b RV 0.918 8.47 6291 AIS 593.17 27.85 sat. -5.916 0.02
HAT-P-22 b Tran. 0.041 2.15 5302 AIS 4 812.93 16.75 -6.549 -4.154 0.009
24 Sex b RV 1.338 1.65 5098 AIS 13.29 2.41 sat. -7.345 0.079
HD 90156 b RV 0.25 0.06 5599 AIS 42.25 4.46 sat. -6.63 0.046
HD 92788 b RV 0.951 3.56 5836 AIS 21.01 5.58 sat. -6.76 0.115
HD 93083 b RV 0.477 0.37 4995 AIS 4 1742.92 19.74 -7.165 -4.439 0.005
BD -10 3166 b RV 0.044 0.43 5393 AIS 4 666.49 11.91 -6.418 -4.11 0.008
HD 95089 b RV 1.45 1.24 4894 MIS 2.9 0.64 2061.96 7.98 -7.475 0.095 -4.537 0.002
47 UMa b RV 2.101 2.55 5882 AIS 490.96 26.52 sat. -6.283 0.023
47 UMa c RV 3.572 0.55 5882 AIS 490.96 26.52 sat. -6.283 0.023
WASP-34 b Tran. 0.052 0.58 5700 AIS 4 1340.11 17.14 -6.289 -3.677 0.006
HD 96063 b RV 0.999 0.92 5148 AIS 9.24 3.66 3062.56 24.98 -6.799 0.172 -4.191 0.004 bad phot.
HD 96167 b RV 1.347 0.68 5770 AIS 11.9 4.08 sat. -6.687 0.149
HD 97658 b RV 0.081 0.02 5170 AIS 9.62 3.4 sat. -6.98 0.153 bad phot.
WASP-31 b Tran. 0.047 0.48 6302 AIS 5.03 1.79 1283.18 16.4 -5.601 0.154 -3.108 0.006 bad phot.
HD 98219 b RV 1.23 1.83 4992 AIS 4 1953.11 15.88 -7.241 -4.465 0.004
HD 99109 b RV 1.108 0.5 5272 MIS 3.5 0.63 1335.27 4.79 -6.866 0.078 -4.197 0.002
HAT-P-21 b Tran. 0.049 4.07 5588 AIS 4 436.07 12.6 -5.733 -3.609 0.013
HD 99492 b RV 0.122 0.11 4955 MIS 7.47 0.41 2668.82 4.84 -7.215 -4.575 28.6 K0 comp. [1]
HD 99706 b RV 2.134 1.4 4932 AIS edge
HD 100655 b RV 0.765 1.67 4861 AIS 12.99 4.34 sat. -7.416 0.145
HD 100777 b RV 1.034 1.17 5582 AIS 12.26 3.87 sat. -6.56 0.137
HIP 57274 b RV 0.071 0.04 4640 AIS 4 452.6 13.56 -7.005 -4.864 0.013
HD 102195 b RV 0.048 0.45 5291 MIS 22.85 1.44 sat. -6.462 0.027
HD 102329 b RV 2.07 5.87 4830 MIS 3.11 0.64 1131.68 5.63 -7.47 0.089 -4.822 0.002
HD 102956 b RV 0.081 0.95 5054 AIS 4.76 1.38 2524.29 13.98 -7.233 0.125 -4.422 0.002 bad phot.
HD 103197 b RV 0.249 0.1 5303 AIS 4 913.37 23.26 -6.693 -4.248 0.011
HD 106252 b RV 2.611 6.96 5870 AIS 53.66 8.55 sat. -6.31 0.069
HD 106270 b RV 4.367 11.03 5638 AIS 18.49 4.43 sat. -6.681 0.104
HD 107148 b RV 0.27 0.21 5797 AIS 16.84 4.07 sat. -6.57 0.105 bad phot.
11 Com b RV 1.294 19.43 4742 AIS 49.14 7.2 sat. -7.542 0.064 10.4 faint comp. [2]
HD 108863 b RV 1.398 2.56 4956 AIS 4 2029.9 28.96 -7.389 -4.597 0.006
HD 108874 b RV 1.035 1.29 5551 GII 5.12 0.59 sat. -6.807 0.05
HD 108874 c RV 2.72 1.03 5551 GII 5.12 0.59 sat. -6.807 0.05
HD 109246 b RV 0.328 0.77 5844 GII 11.6 0.72 sat. -6.438 0.027
HAT-P-36 b Tran. 0.024 1.83 5560 AIS 4 186.07 11.06 -5.507 -3.753 0.026
WASP-41 b Tran. 0.04 0.93 5450 AIS 4 331.88 6.72 -5.801 -3.795 0.009
WASP-42 b Tran. 0.055 0.5 5200 AIS 4 46.75 5.81 -5.529 -4.374 0.054 NUV artifact
WASP-25 b Tran. 0.047 0.58 5750 AIS 4 322.44 7.99 -5.67 -3.677 0.011
HD 114762 b RV 0.363 11.64 5953 GII edge; 3.3 M6 comp. [3]
HD 114783 b RV 1.16 1.11 5135 AIS 12.73 2.01 sat. -6.945 0.068 bad phot.
HD 114729 b RV 2.102 0.94 5821 AIS 111.02 14.92 sat. -6.296 0.058 8.1 faint comp. [1]
61 Vir b RV 0.05 0.02 5571 AIS 222.15 13.26 sat. -6.755
HD 116029 b RV 1.746 2.14 4951 AIS 4 1619.7 26.75 -7.331 -4.637 0.007
70 Vir b RV 0.484 7.46 5545 AIS 199.35 16.1 sat. -6.737 0.035
HD 117207 b RV 3.738 1.82 5724 AIS 34.34 4.51 sat. -6.569 0.057
HD 118203 b RV 0.07 2.14 5600 AIS 31.23 5.71 sat. -6.286 0.079
Qatar-2 b Tran. 0.022 2.48 4645 AIS 4 8.2 3.53 -5.269 -4.87 0.187
HAT-P-12 b Tran. 0.038 0.21 4650 AIS 4 15.48 3.43 -5.462 -4.788 0.096
HAT-P-26 b Tran. 0.048 0.06 5079 MIS 1 93.28 1.67 -6.39 -4.333 0.008
WASP-16 b Tran. 0.042 0.84 5700 AIS 4 454.55 14.87 -5.902 -3.76 0.014
HD 125612 c RV 0.052 0.06 5897 AIS 25.27 5 sat. -6.093 0.086
HD 126614 A b RV 2.368 0.39 5585 AIS 4 2170.99 29.77 -6.897 -4.075 0.006
WASP-39 b Tran. 0.049 0.28 5400 MIS 1 168.89 1.65 -6.205 -3.891 0.004
WASP-14 b Tran. 0.037 7.65 6475 AIS 82.18 9.24 sat. -5.165 0.049
HD 128311 b RV 1.086 1.46 4965 AIS 38.24 6.13 3450.72 37.67 -6.545 0.07 -4.503 0.005
HD 130322 b RV 0.09 1.04 5308 MIS 17.64 1.4 sat. -6.572 0.035
WASP-37 b Tran. 0.045 1.79 5800 MIS 1 379.52 3.47 -5.938 -3.272 0.004
HAT-P-27 b Tran. 0.04 0.61 5246 MIS 1 78.31 1.63 -6.195 -4.214 0.009
HD 131496 b RV 2.112 2.24 4927 GII 3 1637.43 8.52 -7.492 -4.668 0.002
HD 132406 b RV 1.982 5.6 5885 AIS 10.62 3.12 sat. -6.739 0.128
HD 132563 B b RV 2.624 1.49 5985 AIS 70.88 5.38 sat. -5.423 0.033 1.4 G2 SB comp. [4]
WASP-24 b Tran. 0.037 1.08 6075 MIS 2.46 0.48 1231.08 5.06 -6.069 0.084 -3.282 0.002 bad phot.
HD 134987 b RV 0.808 1.56 5750 AIS 55.07 5.78 sat. -6.677 0.046
HD 136118 b RV 2.333 11.68 6097 AIS 210.43 15.67 sat. -5.896 0.032
HD 136418 b RV 1.291 1.99 4972 AIS 7.74 2.65 2754.51 21.65 -10.044 -7.406 0.003 NUV artifact
HAT-P-4 b Tran. 0.044 0.67 5860 AIS 4 829.21 11.48 -5.91 -3.507 0.006
iota Dra b RV 1.531 12.72 4545 AIS 121.54 9.62 sat. -7.776 0.034
HD 137510 b RV 1.868 26.36 5966 AIS 200.16 11.22 sat. -6.182 0.024
HD 137388 b RV 0.889 0.23 5240 AIS 4 1873.11 28.09 -6.966 -4.208 0.007
kappa CrB b RV 2.801 2.01 4970 AIS 47.37 4.68 sat. -7.533 0.043 23.2 faint comp. [2]
HD 142245 b RV 2.776 1.89 4878 AIS edge
rho CrB b RV 0.226 1.06 5823 AIS 4 sat. -8.252
XO-1 b Tran. 0.049 0.92 5750 AIS 4 764.11 13.01 -5.941 -3.573 0.007
HD 145457 b RV 0.763 2.97 4757 AIS 10.2 3.93 sat. -7.497 0.167 bad phot.
14 Her b RV 2.934 5.21 5388 MIS 17.7 1.32 sat. -7.15 0.032
WASP-38 b Tran. 0.075 2.69 6150 AIS 25.65 3.93 sat. -5.804 0.066
HAT-P-2 b Tran. 0.068 8.86 6290 GII 142.43 3.02 sat. -5.335 0.009
HD 149026 b RV 0.043 0.36 6160 AIS 43.2 5.68 sat. -6.083 0.057
HD 150706 b RV 6.734 2.84 5961 AIS 149.05 12.16 sat. -6.016 0.035
HD 152581 b RV 1.489 1.51 5155 AIS 5.66 2.68 2874.63 30.81 -6.951 -4.158 0.005 bad phot.
HD 154345 b RV 4.214 0.96 5468 AIS 21.94 5.38 sat. -6.986
HAT-P-18 b Tran. 0.056 0.2 4803 MIS 1 40.31 0.95 -6.053 -4.361 0.01 NUV artifact
HD 155358 b RV 0.627 0.82 5760 AIS 152.38 11.03 sat. -5.919 0.031 blend
HD 156279 b RV 0.495 9.78 5453 AIS 6.71 2.05 sat. -6.976 0.133
HD 156668 b RV 0.05 0.01 4850 MIS 1 1062.76 5.9 -7.765 -4.652 0.002
HAT-P-14 b Tran. 0.061 2.22 6600 AIS 72.56 6.97 sat. -5.122 0.042
HD 156846 b RV 1.118 11.01 6138 GII 173.63 2.83 sat. -6.148 0.007 5.1 M4 comp. [5]
mu Ara d RV 0.093 0.03 5784 AIS 215.35 10.35 sat. -6.61 0.021
TrES-3 b Tran. 0.023 1.87 5650 AIS 4 217.94 8.73 -5.474 -3.651 0.017 NUV artifact
TrES-4 b Tran. 0.051 0.91 6200 AIS 6.73 2.01 1066.8 17.25 -5.516 0.13 -3.23 0.007
HD 163607 b RV 0.359 0.77 5543 AIS 15.46 4.13 sat. -6.592 0.116 bad phot.
HD 164509 b RV 0.878 0.48 5922 GII 27.4 2.02 sat. -6.281 0.032
HD 167042 b RV 1.317 1.7 5010 AIS 15.67 2.64 sat. -7.548 0.073
HAT-P-5 b Tran. 0.041 1.05 5960 AIS 4 423.48 11.62 -5.598 -3.486 0.012
WASP-58 b Tran. 0.056 0.89 5800 AIS 4 988.12 23.03 -5.738 -3.258 0.01
HD 170469 b RV 2.235 0.67 5810 AIS 12.21 4.41 sat. -6.677 0.157 bad phot.
WASP-3 b Tran. 0.031 2 6400 AIS 15.28 5.62 sat. -5.549 0.16
HD 175167 b RV 2.401 7.78 5548 AIS 10.67 3.23 sat. -6.79 0.131
Kepler-30 b Tran. 0.186 0 5498 AIS 4 11.95 3.2 incomplete incomplete
Kepler-38 b Tran. 0.43 5623 GII 3 0.93 0.35 incomplete incomplete bad phot.
Kepler-14 b Tran. 0.081 8.41 6395 GII 7.01 1.27 1268.88 4.33 -5.326 0.079 -2.981 0.001 NUV artifact
HD 179079 b RV 0.12 0.08 5724 AIS 20.31 4 sat. -6.523 0.085 bad phot.
Kepler-7 b Tran. 0.062 0.44 5933 GII 3 199.55 1.5 incomplete incomplete
HD 179949 b RV 0.044 0.9 6168 AIS edge
Kepler-33 b Tran. 0.068 5904 AIS 4 61.59 4.73 -4.879 -3.605 0.033 NUV artifact
Kepler-22 b Tran. 0.849 0 5518 AIS 4 490.32 11.27 incomplete incomplete
HD 180902 b RV 1.378 1.56 4975 AIS 4 2341.31 22.26 -7.382 -4.528 0.004 NUV artifact
HD 181342 b RV 1.734 3 4975 AIS 10.2 3.57 2136.88 24.7 -7.008 0.152 -4.6 0.005 NUV artifact
HD 181720 b RV 1.847 0.37 5781 AIS 38.95 5.29 sat. -6.251 0.059
WASP-48 b Tran. 0.034 0.97 5920 AIS 4 1059.54 14.52 -5.724 -3.214 0.006
Kepler-36 b Tran. 0.115 5911 GII 3 780.62 3 -5.728 -3.226 0.002
Kepler-28 b Tran. 0.058 0 4590 GII 3 6.61 0.62 incomplete incomplete
Kepler-27 b Tran. 0.105 0 5400 GII 3 3.94 0.8 incomplete incomplete bad phot.
Kepler-31 c Tran. 0.255 0 6340 GII 3 34.64 0.8 incomplete incomplete NUV artifact
Kepler-47 b Tran. 0.268 5636 GII 3 14.21 1.27 incomplete incomplete NUV artifact
Kepler-15 b Tran. 0.057 0.66 5515 AIS 4 37.25 3.87 incomplete incomplete
Kepler-51 b Tran. 0.248 5803 AIS 4 37.45 5.57 incomplete incomplete
Kepler-40 b Tran. 0.081 2.18 6510 GII edge
Kepler-6 b Tran. 0.046 0.67 5647 AIS 4 74.85 5.78 incomplete incomplete
HD 187085 b RV 2.028 0.8 6075 AIS 124.03 9.15 sat. -6.008 0.032
Qatar-1 b Tran. 0.023 1.08 4861 AIS 4 19.6 2.03 -5.399 -4.622 0.045
GJ 785 b RV 0.319 0.07 5144 AIS 54.19 6.1 sat. -7.073 0.049
HD 192699 b RV 1.148 2.4 5220 AIS 17.36 3.6 sat. -7.255 0.09 bad phot.
TrES-5 b Tran. 0.025 1.77 5171 MIS 1 16.47 2.14 -5.598 -4.294 0.056
HAT-P-23 b Tran. 0.023 2.09 5905 AIS 4 322.01 10.78 -5.599 -3.606 0.015 NUV artifact
WASP-2 b Tran. 0.031 0.9 5200 AIS 4 97.89 3.81 -5.748 -4.272 0.017
18 Del b RV 2.575 10.21 4979 AIS 67.93 5.98 sat. -7.043 0.038
HD 200964 b RV 1.597 1.84 5164 AIS 18.9 4.37 sat. -7.186 0.1 bad phot.
BD +14 4559 b RV 0.776 1.52 4814 NGS 1.07 0.34 359.79 1 -7.228 0.137 -4.616 0.001 NUV artifact
WASP-46 b Tran. 0.024 2.08 5620 AIS 20.17 3.66 258.54 8.28 -4.546 0.079 -3.352 0.014 NUV artifact
HD 202206 b RV 0.812 16.82 5788 AIS 24.95 3.91 sat. -6.377 0.068
HD 204313 b RV 3.071 3.5 5767 AIS 18.66 3.66 sat. -6.535 0.085
HD 204313 d RV 3.945 1.61 5760 AIS 18.66 3.66 sat. -6.529 0.085
HD 205739 b RV 0.895 1.49 6176 MIS 43 1.3 sat. -5.924 0.013
HAT-P-17 b Tran. 0.088 0.53 5246 AIS 4 493.32 8.74 -6.243 -4.065 0.008
HD 206610 b RV 1.633 2.23 4849 MIS 1.76 0.44 956.69 4.53 -7.542 0.109 -4.721 0.002 bad phot.
HD 209458 b RV 0.047 0.69 6065 AIS 62.53 5.29 sat. -6.135 0.037
HD 210702 b RV 1.203 1.96 5010 AIS 20.25 4.41 sat. -7.37 0.095
HD 212771 b RV 1.064 2.25 4877 AIS 4.78 1.99 sat. -7.319 0.181
HD 212301 b RV 0.034 0.4 5998 AIS 93.93 5.18 sat. -5.919 0.024 4.3 M3 comp. [6]
HD 213240 b RV 1.885 4.53 5968 AIS 95.1 6.71 sat. -6.296 0.031
HD 215497 b RV 0.047 0.02 5113 AIS 4 894.18 10.26 -6.871 -4.434 0.005 NUV artifact
HAT-P-8 b Tran. 0.045 1.29 6200 AIS 11.47 2.88 sat. -5.792 0.109
tau Gru b RV 2.518 1.21 5999 AIS 211.28 12.88 sat. -6.254 0.026
HD 216437 b RV 2.486 2.17 5849 AIS 120.01 11.19 sat. -6.505 0.04
HD 216770 b RV 0.456 0.65 5423 GII 7.91 0.66 sat. -6.888 0.036
51 Peg b RV 0.052 0.46 5787 AIS 190.68 9.59 sat. -6.543 0.022
HD 217107 b RV 0.075 1.4 5704 AIS 44 5.06 sat. -6.898 0.05
HD 217786 b RV 2.379 13.19 5966 GII 52.44 1.35 sat. -6.127 0.011
HD 218566 b RV 0.687 0.21 4820 AIS 4 989.09 19.03 -7.08 -4.6 0.008
WASP-21 b Tran. 0.052 0.3 5800 AIS 4 939.21 15.5 -5.786 -3.328 0.007
WASP-6 b Tran. 0.043 0.52 5450 AIS 4 189.12 7.66 -5.649 -3.888 0.018
WASP-10 b Tran. 0.038 3.19 4675 AIS 4 30.22 3.24 -5.517 -4.552 0.047
WASP-59 b Tran. 0.07 0.86 4650 AIS 4 7.9 3.05 -5.547 -5.164 0.167 NUV artifact
HD 219828 b RV 0.052 0.06 5891 AIS 25.09 3.93 sat. -6.384 0.068
HD 220773 b RV 4.943 1.45 5940 NGS 68.67 2.18 sat. -6.333 0.014
HD 221287 b RV 1.25 3.12 6304 AIS 171.47 9.23 sat. -5.623 0.023
HD 222155 b RV 5.139 2.03 5765 MIS 37.07 4.66 sat. -6.597 0.055
HD 222582 b RV 1.337 7.63 5727 AIS 25.14 2.85 sat. -6.534 0.049
WASP-60 b Tran. 0.053 5900 AIS 4 281.41 8.18 -5.538 -3.604 0.013
WASP-29 b Tran. 0.046 0.24 4800 AIS 4 55.18 2.77 -6.033 -4.806 0.022
WASP-5 b Tran. 0.027 1.62 5880 AIS 4 255.39 6.95 -5.499 -3.607 0.012
WASP-8 b Tran. 0.08 2.14 5600 AIS 5.06 1.66 1631.91 12.75 -6.404 0.142 -3.808 0.003 NUV arti.; 4.8 faint comp. [7]
HD 224693 b RV 0.192 0.71 6037 AIS 27.31 3.73 sat. -6.261 0.059
Table 1: Planet and stellar data for GALEX detected stars16

Footnotes

  1. affiliation: Based on observations made with the NASA Galaxy Evolution Explorer. Galex is operated for NASA by the California Institute of Technology under NASA contract NAS5-98034.
  2. slugcomment: Accepted to ApJ
  3. The log() index is the ratio of the chromospheric emission of the Ca II H & K lines to the bolometric flux of the star (Noyes et al., 1984).
  4. One can query the GALEX archive through either CasJobs (http://mastweb.stsci.edu/gcasjobs/) or a web tool called GalexView (http://galex.stsci.edu/galexview/).
  5. The bimodal distribution of the semi-major axis distribution is to due to a combination of both astrophysical effects and selection biases. The outer boundary drops off due to the incompleteness of RV surveys. The inner peak around 0.03 AU is likely due to the selection biases of finding lower mass planets closer in to the star and the inherently high frequency of lower-mass planets. And the peak between 1 and 2 AU is explained by Alexander & Pascucci (2012) as being possibly due to the protoplanetary disk clearing by photoevaporation.
  6. To date, three Kepler planets have been confirmed with AU, one of which has been observed with GALEX, but only an upper limit is provided in the FUV.
  7. Table ordered by R.A.
  8. Data are listed only for the inner most planet of the multi-planet systems. Masses are minimum masses for non-transiting planets. Planet and stellar parameters come from the Exoplanet Data Explorer (Wright et al., 2011).
  9. Data are listed only for the inner most planet of the multi-planet systems. Masses are minimum masses for non-transiting planets. Planet and stellar parameters come from the Exoplanet Data Explorer (Wright et al., 2011).
  10. Data are listed only for the inner most planet of the multi-planet systems. Masses are minimum masses for non-transiting planets. Planet and stellar parameters come from the Exoplanet Data Explorer (Wright et al., 2011).
  11. FUV and NUV fluxes listed as “sat.” are saturated using the published counts-per-second limits per detector in Morrissey et al. (2007). These are 34 cps and 108 cps for the FUV and NUV detectors, respectively.
  12. FUV and NUV fluxes listed as “sat.” are saturated using the published counts-per-second limits per detector in Morrissey et al. (2007). These are 34 cps and 108 cps for the FUV and NUV detectors, respectively.
  13. Bolometric corrections, were calculated using Equations 17 and 18 of Masana et al. (2006). For those stars lacking literature values needed calculate , the fractional luminosities are left “incomplete”.
  14. Bolometric corrections, were calculated using Equations 17 and 18 of Masana et al. (2006). For those stars lacking literature values needed calculate , the fractional luminosities are left “incomplete”.
  15. Notes on GALEX photometry. “Bad phot.” refers to a 20% difference in flux calculated using the “aper_auto” and “aper_7” apertures in the GALEX pipeline. “NUV artifact” refers to flags 2 returned the the GALEX pipeline and should be used with caution. Binary blend are reported for those stars with relatively bright companions within 30. Note that stars with any of these flags were not used in the analyses presented in this paper. The references for the close binaries are: [1] Raghavan et al. (2006), [2] Eggleton & Tokovinin (2008), [3] Patience et al. (2002), [4] Desidera et al. (2011), [5] Tamuz et al. (2008), [6] Mugrauer & Neuhäuser (2009), [7] Queloz et al. (2010).
  16. Table ordered by R.A.

References

  1. Aigrain, S., et al. 2008, A&A, 488, L43
  2. Alexander, R. D., & Pascucci, I. 2012, MNRAS, 422, L82
  3. Barnes, S. A. 2007, ApJ, 669, 1167
  4. Batalha, N. M., et al. 2012, ArXiv e-prints
  5. Brown, D. J. A., Collier Cameron, A., Hall, C., Hebb, L., & Smalley, B. 2011, MNRAS, 415, 605
  6. Canto Martins, B. L., Das Chagas, M. L., Alves, S., Leão, I. C., de Souza Neto, L. P., & de Medeiros, J. R. 2011, A&A, 530, A73+
  7. Catala, C., Donati, J.-F., Shkolnik, E., Bohlender, D., & Alecian, E. 2007, MNRAS, 374, L42
  8. Cohen, O., Drake, J. J., Kashyap, V. L., Saar, S. H., Sokolov, I. V., Manchester, W. B., Hansen, K. C., & Gombosi, T. I. 2009, ApJ, 704, L85
  9. Cohen, O., Drake, J. J., Kashyap, V. L., Sokolov, I. V., & Gombosi, T. I. 2010, ApJ, 723, L64
  10. Collier Cameron, A., & Jianke, L. 1994, MNRAS, 269, 1099
  11. Cuntz, M., Saar, S. H., & Musielak, Z. E. 2000, ApJ, 533, L151
  12. Desidera, S., et al. 2011, A&A, 533, A90
  13. Eggleton, P. P., & Tokovinin, A. A. 2008, MNRAS, 389, 869
  14. Fares, R., et al. 2012, ArXiv e-prints
  15. —. 2010, MNRAS, 406, 409
  16. Findeisen, K., & Hillenbrand, L. 2010, AJ, 139, 1338
  17. Gonzalez, G. 2011, MNRAS, 416, L80
  18. Gu, P.-G., & Suzuki, T. K. 2009, ApJ, 705, 1189
  19. Gurdemir, L., Redfield, S., & Cuntz, M. 2012, ArXiv e-prints
  20. Hartman, J. D. 2010, ApJ, 717, L138
  21. Holmberg, J., Nordström, B., & Andersen, J. 2009, A&A, 501, 941
  22. Kashyap, V. L., Drake, J. J., & Saar, S. H. 2008, ApJ, 687, 1339
  23. Kivelson, M. G., Khurana, K. K., & Volwerk, M. 2002, Icarus, 157, 507
  24. Knutson, H. A., Howard, A. W., & Isaacson, H. 2010, ApJ, 720, 1569
  25. Kopp, A., Schilp, S., & Preusse, S. 2011, ApJ, 729, 116
  26. Krejčová, T., & Budaj, J. 2012, A&A, 540, A82
  27. Lanza, A. F. 2008, A&A, 487, 1163
  28. —. 2009, A&A, 505, 339
  29. —. 2010, A&A, 512, A77+
  30. —. 2011, Ap&SS, 658
  31. Lecavelier Des Etangs, A., Sirothia, S. K., Gopal-Krishna, & Zarka, P. 2011, A&A, 533, A50
  32. Mamajek, E. E., & Hillenbrand, L. A. 2008, ApJ, 687, 1264
  33. Martin, D. C., et al. 2005, ApJ, 619, L1
  34. Masana, E., Jordi, C., & Ribas, I. 2006, A&A, 450, 735
  35. Miller, B. P., Gallo, E., Wright, J. T., & Dupree, A. K. 2012, ApJ, 754, 137
  36. Morrissey, P., et al. 2007, ApJS, 173, 682
  37. —. 2005, ApJ, 619, L7
  38. Mugrauer, M., & Neuhäuser, R. 2009, A&A, 494, 373
  39. Noyes, R. W., Hartmann, L. W., Baliunas, S. L., Duncan, D. K., & Vaughan, A. H. 1984, ApJ, 279, 763
  40. Ochsenbein, F., Bauer, P., & Marcout, J. 2000, A&AS, 143, 23
  41. Pagano, I. 2009, Ap&SS, 320, 115
  42. Pagano, I., Lanza, A. F., Leto, G., Messina, S., Barge, P., & Baglin, A. 2009, Earth Moon and Planets, 105, 373
  43. Patience, J., et al. 2002, ApJ, 581, 654
  44. Pillitteri, I., Günther, H. M., Wolk, S. J., Kashyap, V. L., & Cohen, O. 2011, ApJ, 741, L18+
  45. Pillitteri, I., Wolk, S. J., Cohen, O., Kashyap, V., Knutson, H., Lisse, C. M., & Henry, G. W. 2010, ApJ, 722, 1216
  46. Pont, F. 2009, MNRAS, 396, 1789
  47. Poppenhaeger, K., Robrade, J., & Schmitt, J. H. M. M. 2010, A&A, 515, A98+
  48. Poppenhaeger, K., & Schmitt, J. H. M. M. 2011, ApJ, 735, 59
  49. Preusse, S., Kopp, A., Büchner, J., & Motschmann, U. 2006, A&A, 460, 317
  50. Queloz, D., et al. 2010, A&A, 517, L1
  51. Raghavan, D., Henry, T. J., Mason, B. D., Subasavage, J. P., Jao, W.-C., Beaulieu, T. D., & Hambly, N. C. 2006, ApJ, 646, 523
  52. Robinson, R. D., et al. 2005, ApJ, 633, 447
  53. Saar, S. H., Cuntz, M., Kashyap, V. L., & Hall, J. C. 2008, in IAU Symposium, Vol. 249, IAU Symposium, ed. Y.-S. Sun, S. Ferraz-Mello, & J.-L. Zhou, 79–81
  54. Scharf, C. A. 2010, ApJ, 722, 1547
  55. Schröter, S., Czesla, S., Wolter, U., Müller, H. M., Huber, K. F., & Schmitt, J. H. M. M. 2011, A&A, 532, A3+
  56. Shkolnik, E., Bohlender, D. A., Walker, G. A. H., & Collier Cameron, A. 2008, ApJ, 676, 628
  57. Shkolnik, E., Walker, G. A. H., & Bohlender, D. A. 2003, ApJ, 597, 1092
  58. Shkolnik, E., Walker, G. A. H., Bohlender, D. A., Gu, P.-G., & Kürster, M. 2005, ApJ, 622, 1075
  59. Shkolnik, E. L., Liu, M. C., Reid, I. N., Dupuy, T., & Weinberger, A. J. 2011, ApJ, 727, 6, 12 pp
  60. Smith, G. H., & Redenbaugh, A. K. 2010, PASP, 122, 1303
  61. Tamuz, O., et al. 2008, A&A, 480, L33
  62. Tholen, D. J., Tejfel, V. G., & Cox, A. N. 2000, Planets and Satellites, ed. Cox, A. N., 293
  63. Vidotto, A. A., Jardine, M., Opher, M., Donati, J. F., & Gombosi, T. I. 2011, MNRAS, 412, 351
  64. Walker, G. A. H., et al. 2008, A&A, 482, 691
  65. Welsh, B. Y., et al. 2006, A&A, 458, 921
  66. West, A. A., Hawley, S. L., Bochanski, J. J., Covey, K. R., Reid, I. N., Dhital, S., Hilton, E. J., & Masuda, M. 2008, AJ, 135, 785
  67. Wright, J. T., et al. 2011, PASP, 123, 412
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