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N. Nakhjiri

Publications and source records attributed to N. Nakhjiri.

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The Array Control and Data Acquisition software of the Cherenkov Telescope Array Observatory

The Cherenkov Telescope Array Observatory (CTAO) aims to advance knowledge of the gamma-ray sky as the largest gamma-ray observatory ever built. The CTAO will be deployed at two sites, one in the Northern Hemisphere and the other in the Southern Hemisphere, containing telescopes of three sizes to cover different energy domains. Commissioning of the prototype CTAO Large-Sized Telescope (LST-1) is being finalized at the northern site, while three additional LSTs are under construction. Additional calibration and environmental monitoring instruments, such as laser imaging detection and ranging (LIDAR) systems and weather stations, will support telescope operations. The Array Control and Data Acquisition (ACADA) system serves as the central element for on-site CTAO operations. ACADA controls, supervises, and handles the data generated by the telescopes and the auxiliary instruments. It drives the efficient planning and execution of observations while managing the multi-gigabit-per-second data streams produced by each CTAO telescope. The ACADA system contains the CTAO Science Alert Generation Pipeline - a real-time data processing and analysis pipeline, dedicated to automatically generating science alert candidates as data are acquired. These science alerts, along with external alerts received from other scientific instruments, are managed by the Transients Handler (TH) component. The TH informs ACADA's Short-Term Scheduler (STS) about relevant science alerts, enabling modification of ongoing observations on sub-minute timescales. This capability for rapid response, combined with the fast slewing of CTAO telescopes, makes the Observatory an excellent instrument for studying high-impact astronomical transients.

astro-ph.IM

Ariel mission planning. Scheduling the survey of a thousand exoplanets

Automatic scheduling techniques are becoming a crucial tool for the efficient planning of large astronomical surveys. A specific scheduling method is being designed and developed for the Atmospheric Remote-sensing Infrared Exoplanet Large-survey (Ariel) mission planning based on a hybrid meta-heuristic algorithm with global optimization capability to ensure obtaining satisfying results fulfilling all mission constraints. We used this method to simulate the Ariel mission plan, to assess the feasibility of its scientific goals, and to study the outcome of different science scenarios. We conclude that Ariel will be able to fulfill the scientific objectives, i.e. characterizing ~1000 exoplanet atmospheres, with a total exposure time representing about 75-80% of the mission lifetime. We demonstrate that it is possible to include phase curve observations for a sample of targets or to increase the number of studied exoplanets within the mission lifetime. Finally, around 12-15% of the time can still be used for non-time constrained observations.

astro-ph.IM