LRG-BEASTS

Low Resolution Ground-Based Exoplanet Atmosphere Survey using Transmission Spectroscopy

The goal of the Low Resolution Ground-Based Exoplanet Survey using Transmission Spectroscopy (LRG-BEASTS, “large beasts”) is to provide a large sample of optical transmission spectra of hot Jupiter atmospheres. Ground-based studies are often limited by systematics and not photon noise. For this reason, LRG-BEASTS is pioneering the use of 4-metre class telescopes to perform these observations. Specifically, LRG-BEASTS acquires data using the low-resolution (R = 300) grism spectrographs ACAM on the 4.2m William Herschel Telescope (WHT) in La Palma, and EFOSC2 on the 3.6m New Technology Telescope (NTT), La Silla.

Hot Jupiter atmosphere have been observed to show a remarkable diversity with a continuum from clear to cloudy atmospheres [2]. LRG-BEASTS is sampling from a broad range of parameter space and will aid in the understanding of this diversity.

The James Webb Space Telescope will provide ground-breaking sensitivity in the infrared which will allow for the identification of molecules in the atmospheres of Earth-like exoplanets, including the potential for detections of bio-signatures. However, it’s wavelength coverage will not be able to provide transmission spectra in the optical, which provides significantly tighter constraints on the abundances derived from infrared spectra alone (e.g. [1]). Furthermore, optical data are necessary to the constrain the effects of clouds and hazes on the transmission spectrum. Therefore, optical data, together with infrared data, is crucial for a more complete understanding of an exoplanet’s atmosphere.

The sample

The figure above shows the LRG-BEASTS sample. These 17 planets cover a wide range of parameter space from ~0.2 to 1.5 Jupiter masses and ~800 to 2500K. This broad parameter space will allow us to analyse how the atmospheric properties vary as functions of these parameters. There is evidence that hotter planets are more likely to be cloud- and haze-free as compared to cooler planets. At equilibrium temperatures below ~1200K, CH4 is the main carbon-bearing molecule and photolysis of this molecule produces hydrocarbons which are the precursors of soot [3]. Therefore, photochemical hazes are often found at these temperatures (e.g. [4]).

At higher equilibrium temperatures, photochemical hazes are predicted to be less prevalent but aerosols in the form of condensate clouds can still exist. These clouds can produce a range of slopes in optical transmission spectra, even in the hottest exoplanets (e.g. [5]). At hotter temperatures still (> 2000K), TiO and VO have recently been observed in hot Jupiter atmospheres (e.g. [6,7]), having been predicted to be important [8] as they are prominent features in late-type stars.

The LRG-BEASTS sample will allow us to test for the presence of these features and molecules as a function of temperature.

The results

The figure above shows the published results to date and demonstrates our ability to obtain a precision of around 1 atmospheric scale height with a 4 metre telescope. For all planets, the best fitting atmospheric forward model is plotted.

Our latest result was work performed by my master’s student at the CfA, Lili Alderson. By combining three LRG-BEASTS transits acquired using the WHT, Lili constructed the transmission spectrum of the hot-Saturn WASP-21b (Alderson et al., 2020). Our transmission spectrum covers a wavelength range of 4635-9000A at a median precision of 197ppm (less than 1 atmospheric scale height). We find sodium absorption at greater than 4 sigma confidence in addition to a steep scattering slope, akin to that in HD189733b’s atmosphere. We rule out stellar activity as the cause of the slope we see and attribute it to the presence of aerosols in the planet’s atmosphere. We find no evidence for potassium absorption, meaning WASP-21b joins the growing list of planets with only one of the alkali metals present.

Prior to this, we combined a new WHT/ACAM transmission spectrum of WASP-39b with data from VLT, HST and Spitzer (Kirk et al., 2019). The retrievals we ran on these data retrieved a highly super-solar metallicity atmosphere (282 +65 -58 x solar) driven by the large amplitude water feature [1]. This result highlighted the concerning impact that different retrieval algorithms can have on the inferred atmospheric metallicity.

For WASP-80b, we ruled out a previously claimed potassium detection, instead finding a hazy atmosphere consistent with GTC results (Kirk et al., 2018). It’s relatively cool temperature of ~850K is consistent with the photolysis of methane leading to photochemical hazes, which was presented above.

In the case of WASP-52b, we found clouds in the atmosphere of WASP-52b using ULTRACAM (Kirk et al., 2016), which was consistent with our later ACAM study (Louden et al., 2017). Our ULTRACAM study (Kirk et al., 2016) also revealed an in-transit anomaly which we deduced to be a result of the planet occulting a hot spot on the stellar surface. This was the first evidence of a facula crossing during an exoplanet transit. Since this study, a facula crossing has also been observed in a transit of the hot Jupiter WASP-19b, which was observed as part of the ACCESS survey [9].

In the atmosphere of HAT-P-18b, we detected a clear Rayleigh scattering slope resulting from a high altitude haze in the planet’s atmosphere (Kirk et al., 2017). This was only the second discovery of a Rayleigh slope in a hot Jupiter atmosphere from the ground. It’s equilibrium temperature is similar to WASP-80b (see Figure 1) and again highlights the prevalence of photochemical hazes in relatively-cool hot Jupiter atmospheres.

News

Our results have also been highlighted by the Isaac Newton Group of Telescopes. Their press release concerning LRG-BEASTS can be found here.

References

1 Wakeford, H. R., Sing, D. K., Deming, D., et al. 2018, AJ, 155, 29

2 Sing, D. K., Fortney, J. J., Nikolov, N., et al. 2016, Nature, 529, 59

3 Morley, C. V., Fortney, J. J., Marley, M. S., et al. 2015, ApJ, 815, 110

4 Kirk, J., Wheatley, P. J., Louden, T., et al. 2017, MNRAS, 468, 3907

5 Wakeford, H. R., & Sing, D. K. 2015, A&A, 573, A122

6 Nugroho, S. K., Kawahara, H., Masuda, K., et al. 2017, AJ, 154, 221

7 Evans, T. M., Sing, D. K., Goyal, J. M., et al. 2018, AJ, 156, 283

8 Fortney, J. J., Lodders, K., Marley, M. S., et al. 2008, ApJ, 678, 1419

9 Espinoza, N., Rackham, B. V., Jordan, A., et al. 2019, MNRAS, 482, 2065

Last updated: 10 July 2020