0.94 - 2.42 micron ground-based transmission spectra of the hot-Jupiter HD-189733b

TL;DR

This study demonstrates that ground-based telescopes can produce reliable transmission spectra of exoplanets, with results consistent with space-based data, highlighting their potential as a complementary observational tool.

Contribution

The paper shows that high-quality transmission spectra of HD-189733b can be obtained from ground-based observations using Fourier analysis and de-trending, even with a single good night of data.

Findings

Ground-based spectra match space-based observations in the same wavelength range.

Detrending techniques effectively reduce auto-correlative noise.

Water vapor is identified as the dominant atmospheric component.

Abstract

We present here new transmission spectra of the hot Jupiter HD-189733b using the SpeX instrument on the NASA Infrared Telescope Facility. We obtained two nights of observations where we recorded the primary transit of the planet in the J-, H- and K-bands simultaneously, covering a spectral range from 0.94 to 2.42 {\mu}m. We used Fourier analysis and other de-trending techniques validated previously on other datasets to clean the data. We tested the statistical significance of our results by calculating the auto-correlation function, and we found that, after the detrending, auto-correlative noise is diminished at most frequencies. Additionally, we repeated our analysis on the out-of-transit data only, showing that the residual telluric contamination is well within the error bars. While these techniques are very efficient when multiple nights of observations are combined together, our results prove that even one good night of observations is enough to provide statistically meaningful data. Our observed spectra are consistent with space-based data recorded in the same wavelength interval by multiple instruments, indicating that ground-based facilities are becoming a viable and complementary option to spaceborne observatories. The best fit to the features in our data was obtained with water vapor. Our error bars are not small enough to address the presence of additional molecules, however by combining the information contained in other datasets with our results, it is possible to explain all the available observations with a modelled atmospheric spectrum containing water vapor, methane, carbon monoxide and hazes/clouds.