In-flight photometry extraction of PLATO targets

Abstract

Context. The ESA PLATO space mission is devoted to unveiling and characterizing new extrasolar planets and their host stars. This mission will encompass a very large (>2100 deg2) field of view, granting it the potential to survey up to one million stars depending on the final observation strategy. The telemetry budget of the spacecraft cannot handle transmitting individual images for such a huge stellar sample at the right cadence, so the development of an appropriate strategy to perform on-board data reduction is mandatory. Aims. We employ mask-based (aperture) photometry to produce stellar light curves in flight. Our aim is thus to find the mask model that optimizes the scientific performance of the reduced data. Methods. We considered three distinct aperture models: binary mask, weighted Gaussian mask, and weighted gradient mask giving lowest noise-to-signal ratio, computed through a novel direct method. Each model was tested on synthetic images generated for 50 000 potential PLATO targets. We extracted the stellar population from the Gaia DR2 catalogue. An innovative criterion was adopted for choosing between different mask models. We designated as optimal the model providing the best compromise between sensitivity to detect true and false planet transits. We determined the optimal model based on simulated noise-to-signal ratio and frequency of threshold crossing events. Results. Our results show that, although the binary mask statistically presents a few percent higher noise-to-signal ratio compared to weighted masks, both strategies have very similar efficiency in detecting legitimate planet transits. When it comes to avoiding spurious signals from contaminant stars however the binary mask statistically collects considerably less contaminant flux than weighted masks, thereby allowing the former to deliver up to ∼30% less false transit signatures at 7.1σ detection threshold. Conclusions. Our proposed approach for choosing apertures has been proven to be decisive for the determination of a mask model capable to provide near maximum planet yield and substantially reduced occurrence of false positives for the PLATO mission. Overall, this work constitutes an important step in the design of both on-board and on-ground science data processing pipelines.

The PLATO Solar-like Light-curve Simulator

“…Our objective here is to quantify the instrumental sources of error, namely the systematic error and the random noise, and to implement them into PSLS. For the former, a set of simulations at CCD pixel level is carried out while for the random noise we rely on the work made by Marchiori et al (2019) as explained in Sect. 4.4.…”

“…Photometry extraction is performed on-board by integrating the stellar flux over a collection of pixels called the aperture or the mask. Different strategies for determining the most adequate aperture shape have been the subject of a detailed study (Marchiori et al 2019), leading to the adoption of binary masks as the best compromise between NSR and stellar contamination ratio. For a given target, its associated binary mask is defined as the subset of the imagette pixels giving the minimum noise-tosignal ratio.…”

“…The calculation of the NSR takes into account the various sources of noise described above and also the fact that the shape of the PSF varies across the field of view. The latest version of the instrument parameters were also considered (details will be given in Marchiori et al 2019). Typical values of the NSR are given in Table 2 for a single camera and 24 cameras as a function of the PLATO magnitude, P, which is defined in Marchiori et al (2019) and is by definition directly connected to the flux collected by a PLATO camera.…”

“…The latest version of the instrument parameters were also considered (details will be given in Marchiori et al 2019). Typical values of the NSR are given in Table 2 for a single camera and 24 cameras as a function of the PLATO magnitude, P, which is defined in Marchiori et al (2019) and is by definition directly connected to the flux collected by a PLATO camera. For comparison with the mission specifications (Rauer et al 2014), we also provide the V magnitude, which is defined here as the flux collected in the Johnson V filter for a reference PLATO target of T eff = 6000 K.…”

On attempting to automate the identification of mixed dipole modes for subgiant stars

“…A major challenge of the ESA PLATO mission is to derive stellar ages to better than 10% (Rauer et al 2014) for the sample 1 of stars that are brighter than m V = 11 magnitude and with an instrumental noise that is lower than 50 ppm h −1/2 , provided with the 24 cameras (Marchiori et al 2019;Moreno et al 2019). The derivation of the stellar age is obtained by comparing theoretical mode frequencies to the observed mode frequencies (Lebreton et al 2014).…”