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Register a new userData processing on simulated data for SHARK-NIR
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A robust post processing technique is mandatory to analyse the coronagraphic high contrast imaging data. Angular Differential Imaging (ADI) and Principal Component Analysis (PCA) are the most used approaches to suppress the quasi-static structure in the Point Spread Function (PSF) in order to revealing planets at different separations from the host star. The focus of this work is to apply these two data reduction techniques to obtain the best limit detection for each coronagraphic setting that has been simulated for the SHARK-NIR, a coronagraphic camera that will be implemented at the Large Binocular Telescope (LBT). We investigated different seeing conditions ($0.4-1$) for stellar magnitude ranging from R=6 to R=14, with particular care in finding the best compromise between quasi-static speckle subtraction and planet detection.
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The Gaia Data Release 2 contains the 1st release of radial velocities complementing the kinematic data of a sample of about 7 million relatively bright, late-type stars. Aims: This paper provides a detailed description of the Gaia spectroscopic data processing pipeline, and of the approach adopted to derive the radial velocities presented in DR2. Methods: The pipeline must perform four main tasks: (i) clean and reduce the spectra observed with the Radial Velocity Spectrometer (RVS); (ii) calibrate the RVS instrument, including wavelength, straylight, line-spread function, bias non-uniformity, and photometric zeropoint; (iii) extract the radial velocities; and (iv) verify the accuracy and precision of the results. The radial velocity of a star is obtained through a fit of the RVS spectrum relative to an appropriate synthetic template spectrum. An additional task of the spectroscopic pipeline was to provide 1st-order estimates of the stellar atmospheric parameters required to select such template spectra. We describe the pipeline features and present the detailed calibration algorithms and software solutions we used to produce the radial velocities published in DR2. Results: The spectroscopic processing pipeline produced median radial velocities for Gaia stars with narrow-band near-IR magnitude Grvs < 12 (i.e. brighter than V~13). Stars identified as double-lined spectroscopic binaries were removed from the pipeline, while variable stars, single-lined, and non-detected double-lined spectroscopic binaries were treated as single stars. The scatter in radial velocity among different observations of a same star, also published in DR2, provides information about radial velocity variability. For the hottest (Teff > 7000 K) and coolest (Teff < 3500 K) stars, the accuracy and precision of the stellar parameter estimates are not sufficient to allow selection of appropriate templates. [Abridged]
The direct detection and characterization of planetary and substellar companions at small angular separations is a rapidly advancing field. Dedicated high-contrast imaging instruments deliver unprecedented sensitivity, enabling detailed insights into the atmospheres of young low-mass companions. In addition, improvements in data reduction and PSF subtraction algorithms are equally relevant for maximizing the scientific yield, both from new and archival data sets. We aim at developing a generic and modular data reduction pipeline for processing and analysis of high-contrast imaging data obtained with pupil-stabilized observations. The package should be scalable and robust for future implementations and in particular well suitable for the 3-5 micron wavelength range where typically (ten) thousands of frames have to be processed and an accurate subtraction of the thermal background emission is critical. PynPoint is written in Python 2.7 and applies various image processing techniques, as well as statistical tools for analyzing the data, building on open-source Python packages. The current version of PynPoint has evolved from an earlier version that was developed as a PSF subtraction tool based on PCA. The architecture of PynPoint has been redesigned with the core functionalities decoupled from the pipeline modules. Modules have been implemented for dedicated processing and analysis steps, including background subtraction, frame registration, PSF subtraction, photometric and astrometric measurements, and estimation of detection limits. The pipeline package enables end-to-end data reduction of pupil-stabilized data and supports classical dithering and coronagraphic data sets. As an example, we processed archival VLT/NACO L and M data of beta Pic b and reassessed the planets brightness and position with an MCMC analysis, and we provide a derivation of the photometric error budget.
SHARK-NIR is one of the two coronagraphic instruments proposed for the Large Binocular Telescope. Together with SHARK-VIS (performing coronagraphic imaging in the visible domain), it will offer the possibility to do binocular observations combining direct imaging, coronagraphic imaging and coronagraphic low resolution spectroscopy in a wide wavelength domain, going from 0.5{mu}m to 1.7{mu}m. Additionally, the contemporary usage of LMIRCam, the coronagraphic LBTI NIR camera, working from K to L band, will extend even more the covered wavelength range. In January 2017 SHARK-NIR underwent a successful final design review, which endorsed the instrument for construction and future implementation at LBT. We report here the final design of the instrument, which foresees two intermediate pupil planes and three focal planes to accomodate a certain number of coronagraphic techniques, selected to maximize the instrument contrast at various distances from the star. Exo-Planets search and characterization has been the science case driving the instrument design, but the SOUL upgrade of the LBT AO will increase the instrument performance in the faint end regime, allowing to do galactic (jets and disks) and extra-galactic (AGN and QSO) science on a relatively wide sample of targets, normally not reachable in other similar facilities.
The hunt for Earth analogue planets orbiting Sun-like stars has forced the introduction of novel methods to detect signals at, or below, the level of the intrinsic noise of the observations. We present a new global periodogram method that returns more information than the classic Lomb-Scargle periodogram method for radial velocity signal detection. Our method uses the Minimum Mean Squared Error as a framework to determine the optimal number of genuine signals present in a radial velocity timeseries using a global search algorithm, meaning we can discard noise spikes from the data before follow-up analysis. This method also allows us to determine the phase and amplitude of the signals we detect, meaning we can track these quantities as a function of time to test if the signals are stationary or non-stationary. We apply our method to the radial velocity data for GJ876 as a test system to highlight how the phase information can be used to select against non-stationary sources of detected signals in radial velocity data, such as rotational modulation of star spots. Analysis of this system yields two new statistically significant signals in the combined Keck and HARPS velocities with periods of 10 and 15 days. Although a planet with a period of 15 days would relate to a Laplace resonant chain configuration with three of the other planets (8:4:2:1), we stress that follow-up dynamical analyses are needed to test the reliability of such a six planet system.
We describe the processing of the 531 billion raw data samples from the High Frequency Instrument (hereafter HFI), which we performed to produce six temperature maps from the first 473 days of Planck-HFI survey data. These maps provide an accurate rendition of the sky emission at 100, 143, 217, 353, 545, and 857 GHz with an angular resolution ranging from 9.7 to 4.6 arcmin. The detector noise per (effective) beam solid angle is respectively, 10, 6, 12 and 39 microKelvin in HFI four lowest frequency channel (100--353 GHz) and 13 and 14 kJy/sr for the 545 and 857 GHz channels. Using the 143 GHz channel as a reference, these two high frequency channels are intercalibrated within 5% and the 353 GHz relative calibration is at the percent level. The 100 and 217 GHz channels, which together with the 143 GHz channel determine the high-multipole part of the CMB power spectrum (50 < l <2500), are intercalibrated at better than 0.2 %.
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