The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) (www.RubinObservatory.org) is a groundbreaking telescope facility located in Chile. First observations of the deep and dynamic universe began in 2024 with first look images unveiling in June 2025. The observatory will deliver an unprecedented astronomical dataset, offering immense discovery potential. Rubin Observatory is designed to perform a deep, wide-field survey of the sky by capturing repeat images every few nights across multiple spectral bands over a ten-year period, resulting in astronomical catalogs far larger than any previously available. Our work involves contributions to both the development of instrumentation and the detection and analysis of celestial objects.
The Vera C. Rubin Observatory is unique in several ways: its advanced mirrors, the world’s largest digital camera, and powerful data processing capabilities will enable a survey that captures billions of objects and measures their properties. The resulting data will be used to create a detailed and deep three-dimensional map, offering a new view of the Universe. This map will support the study of the expansion of the Universe, the tracking of transient phenomena, the exploration of the Milky Way, and the detection of near-Earth asteroids.
Our team was involved in the analysis of instrumental effects within LSST and the properties of the sensors. This research focused on three main topics: the analysis of hits by X-ray photons from a 55Fe source, the characterization of surface features on ITL devices and their effect on local UV quantum efficiency, and the investigation of the 'tree rings' effect.
Tree rings (in Fig 3. the left-hand image) is one of the major sensor effects affecting modern thick fully depleted CCDs, caused by the peculiarities of silicon wafer manufacturing process. The growing of a mono-crystal silicon boule leads to a circularly symmetric variation of the dopant concentration. This results in an occurrence of a parasitic electric field in the direction orthogonal to the drift of photoelectrons causing a systematic displacement from their nominal trajectories towards the CCD gates. The effect thus appears as the formation of tree-ring-like patterns visible in the images taken at a uniform illumination (so called "flat field" images). As a consequence, it leads to the position-dependent distortions of the point spread function, along with systematic position-dependent astrometric shifts. All this may impact the performance of LSST survey in detection and characterisation of various fine astrophysical effects of object shape distortion (including the weak lensing statistics, which is a crucial observable to be pursued by the LSST), and thus requires precise understanding and thorough laboratory investigation.
The X-ray photons emitted by the 55Fe isotope are useful tool for photosensor response studies. They provide well defined signal in terms of both, the energy deposited and the size of the area where electron-hole pairs are created. The measurements obtained with this method are used to verify the gain of the sensor and its local variations. The shape of the hits can be used for diagnostic purposes as it is sensitive to the charge transfer inefficiency and local sensor properties.
The surface features on ITL devices occur at short wavelengths, between 320nm and 400nm, and manifest themselves as the appearance of "stains" on the flat field measurements (the right-hand image in Fig. 3). The photons in UV are absorbed so close to the surface that they interact with any monolayers of material on the surface of the sensor. The surface can be covered by an extra layer of dust and poorly formed oxide of silicon due to the etching of the backside surface. This absorption can create some disturbance in backside charging and can change the local UV quantum efficiency. Studying the spatial variations of quantum efficiency allows providing a handle on some very important parameters for LSST photometry.
Members of our group are actively contributing to the Transients and Variable Stars (TVS) science collaboration. We are developing and implementing real-time transient characterization and classification algorithms, including methods for detecting off-axis (orphan) gamma-ray bursts, and for identifying active galactic nuclei (AGNs) and tidal disruption events (TDEs). We develop and apply machine learning techniques to classify TDEs based on the properties of their light curves. Another topic of interest is the study of features in low surface brightness galaxies. A large part of our work is integrated into the FINK broker to support alert processing and multi-messenger follow-up.
