Transmission spectroscopy of the inflated exo-Saturn HAT-P-19b

We observed the Saturn-mass and Jupiter-sized exoplanet HAT-P-19b to refine its transit parameters and ephemeris as well as to shed first light on its transmission spectrum. We monitored the host star over one year to quantify its flux variability and to correct the transmission spectrum for a slope caused by starspots. A transit of HAT-P-19b was observed spectroscopically with OSIRIS at the Gran Telescopio Canarias in January 2012. The spectra of the target and the comparison star covered the wavelength range from 5600 to 7600 AA. One high-precision differential light curve was created by integrating the entire spectral flux. This white-light curve was used to derive absolute transit parameters. Furthermore, a set of light curves over wavelength was formed by a flux integration in 41 wavelength channels of 50 AA width. We analyzed these spectral light curves for chromatic variations of transit depth. The transit fit of the combined white-light curve yields a refined value of the planet-to-star radius ratio of 0.1390 pm 0.0012 and an inclination of 88.89 pm 0.32 degrees. After a re-analysis of published data, we refine the orbital period to 4.0087844 pm 0.0000015 days. We obtain a flat transmission spectrum without significant additional absorption at any wavelength or any slope. However, our accuracy is not sufficient to significantly rule out the presence of a pressure-broadened sodium feature. Our photometric monitoring campaign allowed for an estimate of the stellar rotation period of 35.5 pm 2.5 days and an improved age estimate of 5.5^+1.8_-1.3 Gyr by gyrochronology.Comment: 14 pages, 9 figures, Accepted for publication in A&

First light of the VLT planet finder SPHERE. I. Detection and characterization of the sub-stellar companion GJ 758 B

GJ758 B is a brown dwarf companion to a nearby (15.76 pc) solar-type, metal-rich (M/H = +0.2 dex) main-sequence star (G9V) that was discovered with Subaru/HiCIAO in 2009. From previous studies, it has drawn attention as being the coldest (~600K) companion ever directly imaged around a neighboring star. We present new high-contrast data obtained during the commissioning of the SPHERE instrument at the VLT. The data was obtained in Y-, J-, H-, and Ks-bands with the dual-band imaging (DBI) mode of IRDIS, providing a broad coverage of the full near-infrared (near-IR) range at higher contrast and better spectral sampling than previously reported. In this new set of high-quality data, we report the re-detection of the companion, as well as the first detection of a new candidate closer-in to the star. We use the new 8 photometric points for an extended comparison of GJ758 B with empirical objects and 4 families of atmospheric models. From comparison to empirical object, we estimate a T8 spectral type, but none of the comparison object can accurately represent the observed near-IR fluxes of GJ758 B. From comparison to atmospheric models, we attribute a Teff = 600K $\pm$ 100K, but we find that no atmospheric model can adequately fit all the fluxes of GJ758 B. The photometry of the new candidate companion is broadly consistent with L-type objects, but a second epoch with improved photometry is necessary to clarify its status. The new astrometry of GJ758 B shows a significant proper motion since the last epoch. We use this result to improve the determination of the orbital characteristics using two fitting approaches, Least-Square Monte Carlo and Markov Chain Monte Carlo. Finally, we analyze the sensitivity of our data to additional closer-in companions and reject the possibility of other massive brown dwarf companions down to 4-5 AU. [abridged]Comment: 20 pages, 15 figures. Accepted for publication in A&

Geometric accuracy evaluation of mobile terrestrial LIDAR surveys with supporting algorithms

Mobile Mapping System (MMS) technology is widely used for many applications, hence quantifying its accuracy is a very important and essential task and is a primary focus of this research. In general, to perfrom geometric accuracy evaluation of MMS data, validation points/features are needed. A method is needed to capture a point feature off the roadway in a position where a target on the ground surface would not be visible to the scanner. In this study, eight sphere targets with 14 diameter were placed on the shoulder of the roadway over validation points on the ground. The sphere targets were constructed from injection molded spherical light fixtures. Through a calibration process, they were verified as consistent in size and shape at the 1 mm level. The targets were scanned by four different MMSs (two of design grade and two of asset grade) on two established Test Sites representing different roadway environments (highway and urban settings). Two different selectable data rates (250 KHz and 500 KHz) were also exercised in the data collection as well as two different vehicle driving techniques for data collection (with and without acceleration while the vehicle is turning). Absolute and relative accuracy of the dataset obtained from MMS are of interest. All of these characteristics and factors have been geometrically evaluated through the developed procedures. An automatic sphere target detection/estimation algorithm was developed to detect and extract the scanned sphere target points by eliminating most of the adjacent non-sphere points via a 3D Hough transform process. Following this, the sphere center is robustly located through estimation via L1-norm minimization which allows outliers (ex. tribrach points) to be detected and automatically eliminated. Subsequently the final sphere target center is estimated through least squares. This procedure is robust to several sources of non-random noise. Through error propagation, the precision of the center point estimation is SE90 = 0.20 cm (radius for spherical error, 90%). The case of disturbed targets was able to be detected with the results from this algorithm as well. Although such geometric targets have been widely used in static laser scanning, their use in Mobile Mapping has not been thoroughly studied. Another contribution from this research is that L1-estimation has been applied to all methods of forming condition equations. Those are indirect observations (line fitting), observations only (level network), and mixed model (dependent relative orientation of stereo pair images) problems. Existing published work has exclusively been applied to the indirect observations form of condition equation representation. In this test, outliers which were intentionally added to observations of all the problems were correctly detected. Additionally, L1-estimation was implemented to each of the problems by two different approaches: 1) by using a linear programming approach solved by the simplex method, 2) by a brute force method (exhaustive search for all possible sets of solutions). Results from both approaches are identical. This has verified the idea that the linear programming approach can be used as a convenient tool for implementing L1-estimation for all methods of forming the condition equations