Data, Calibration and Processing of Thermal Infrared Data from the LisR ISS Mission

Longwave Infrared Sensing demonstratoR (LisR) mission is a longwave infrared camera which is flying on board the International Space Station (ISS), launched in February 2022 with first light in early March 2022. This demonstrator, developed by the founders of ConstellR at Fraunhofer Institute of High Speed Dynamics in Freiburg/ Germany, is a platform to demonstrate the capabilities of cryo-cooled long wave infrared detectors from space. The goal of this mission is to derive high-accuracy Land Surface Temperature (LST) information used for better planning and efficiency in the agricultural sector. This information is critical in order to ensure the sustainability of global food supplies. LisR is the precursor of a full satellite constellation called HiVE which is planned to deliver high temporal, spatial and spectral resolution thermal and VisNir information from space from the end of 2023 onwards. The demonstrator mainly consists of a cryo-cooled thermal infrared frame camera, a free form optical assembly and an on board data processing unit. It images the earth’s surface in two longwave infrared bands which allows the derivation of highly accurate Land Surface Temperature information with high spatial resolution. The main industries benefitting of such data are, but not only, the global agricultural sector, food supply chains, sustainable finance and insurance industries which can monitor and optimize the water cycle of global food production with this information. Besides a brief description of the instrument itself the envisaged presentation will detail: • the pre-launch laboratory characterization of the instrument for spectral resolution, spatial resolution and the MTF characterization, • the laboratory absolute radiometric measurements, • the available data products, • the operational radiometric and geometric correction and processing algorithms and pipeline, • the algorithm used to derive Land Surface temperature from absolute calibrated and orthorectified radiance data, • the initial image quality and accuracy assessments, • the initial in-flight absolute radiometric characterization and calibration and finally, • an insight into the planned constellation of multispectral vis/nir/tir satellites

CHIPS: The Carina High-contrast Imaging Project of massive Stars

The formation of massive stars remains one of the most intriguing questions in as- trophysics today. The main limitations result from the difficulty to obtain direct observational constraints on the formation process itself. In this context, the Carina High-contrast Imaging Project of massive Stars (CHIPS) aims to observe all 80+ O stars in the Carina nebula using the new VLT 2nd-generation extreme-AO instrument SPHERE. This instrument offers unprece- dented imaging contrast allowing us to detect the faintest companions around massive stars. These novel observational constraints will help to discriminate between the different formation scenarios by comparing their predictions for companion statistics and properties.status: publishe

VIP: A Python package for high-contrast imaging

International audienc

VIP: A Python package for high-contrast imaging

International audienc

Towards constraints on massive galactic stars using VLT/SPHERE with high-contrast imaging

While the formation of massive stars remains heavily debated, it is nowadays clear that the formation scenarios need to account for the high-degree of multiplicity of these objects that has been observed by recent studies. Here we introduce the Carina High-contrast Imaging Project for massive Stars (CHIPS) that aims to obtain coronagraphic observations of massive stars in the Carina region using VLT/SPHERE. We illustrate the capabilities of SPHERE for massive stars by focusing on the QZ Car system. We detect 19 sources, most of them for the first time, within a 7x7′′ field of view. We show that contrast better than 9 mag can be achieved at separation larger than 200 mas. We also investigate avenues to obtain a first characterisation of the detected sources by fitting their source energy distribution with pre-main sequence stellar atmosphere modelsstatus: publishe

Carina High-contrast Imaging Project for massive Stars (CHIPS). I. Methodology and proof of concept on QZ Car (HD93206)

Context. Massive stars like company. However, low-mass companions have remained extremely difficult to detect at angular separations (ρ) smaller than 1" (approx. 1000-3000 au, considering the typical distance to nearby massive stars) given the large brightness contrast between the companion and the central star. Constraints on the low-mass end of the companions mass-function for massive stars are needed, however, for helping, for example, to distinguish among the various scenarios that describe the formation of massive stars. Aims. With the aim of obtaining a statistically significant constraint on the presence of low-mass companions beyond the typical detection limit of current surveys (∆mag ≲ 5 at ρ ≲ 1"), we initiated a survey of O and Wolf-Rayet stars in the Carina region using the Spectro-Polarimetric High-contrast Exoplanet REsearch (SPHERE) coronagraphic instrument on the Very Large Telescope (VLT). In this, the first paper of the series, we aim to introduce the survey, to present the methodology and to demonstrate the capability of SPHERE for massive stars using the multiple system QZ Car. Methods. We obtained VLT-SPHERE snapshot observations in the IRDIFS_EXT mode, which combines the IFS and IRDIS sub-systems and simultaneously provides us four-dimensional (4D) data cubes in two different fields-of-view: 1.73"x1.73" for IFS (39spectral channels across the YJH bands) and 12"x12" for IRDIS (two spectral channels across the K band). Angular- and spectral-differential imaging techniques as well as PSF-fitting were applied to detect and measure the relative flux of the companions in each spectral channel. The latter were then flux-calibrated using theoretical SED models of the central object and compared to a grid of ATLAS9 atmosphere model and (pre-)main-sequence evolutionary tracks, providing a first estimate of the physical properties of the detected companions. Results. Detection limits of 9 mag at ρ>200 mas for IFS, and as faint as 13 mag at ρ>1′′.8 for IRDIS (corresponding to sub-solar masses for potential companions), can be reached in snapshot observations of only a few minutes integration times, allowing us to detect 19 sources around the QZ Car system. All but two are reported here for the first time. With near-IR magnitude contrasts in the range of 4 to 7.5 mag, the three brightest sources (Ab, Ad, and E) are most likely to be physically bound. They have masses in the range of 2 to 12 M⊙and are potentially co-eval with QZ Car central system. The remaining sources have flux contrast of1.5x10⁵ to 9.5x10⁶ (∆K≈ 11 to 13 mag). Their presence can be explained by the local source density and they are, thus, likely to be chance alignments. If they were members of the Carina nebula, they would be sub-solar-mass pre-main sequence stars. Conclusions. Based on this proof of concept, we show that the VLT/SPHERE allows us to reach the sub-solar mass regime of the companion mass function. It paves the way for this type of observation with a large sample of massive stars to provide novel constraints on the multiplicity of massive stars in a region of the parameter space that has remained inaccessible so far.status: publishe

CHIPS: The Carina High-contrast Imaging Project of massive Stars

The formation of massive stars remains one of the most intriguing questions in astrophysics today. The main limitations result from the difficulty to obtain direct observational constraints on the formation process itself. In this context, the Carina High-contrast Imaging Project of massive Stars (CHIPS) aims to observe all 80+ O stars in the Carina nebula using the new VLT 2nd-generation extreme-AO instrument SPHERE. This instrument offers unprecedented imaging contrast allowing us to detect the faintest companions around massive stars. These novel observational constraints will help to discriminate between the different formation scenarios by comparing their predictions for companion statistics and properties