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Register a new userSOXS End-to-End simulator: development and applications for pipeline design
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We present the development of the End-to-End simulator for the SOXS instrument at the ESO-NTT 3.5-m telescope. SOXS will be a spectroscopic facility, made by two arms high efficiency spectrographs, able to cover the spectral range 350-2000 nm with resolving power R=4500. The E2E model allows to simulate the propagation of photons starting from the scientific target of interest up to the detectors. The outputs of the simulator are synthetic frames, which will be mainly exploited for optimizing the pipeline development and possibly assisting for proper alignment and integration phases in laboratory and at the telescope. In this paper, we will detail the architecture of the simulator and the computational model, which are strongly characterized by modularity and flexibility. Synthetic spectral formats, related to different seeing and observing conditions, and calibration frames to be ingested by the pipeline are also presented.
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Realistic synthetic observations of theoretical source models are essential for our understanding of real observational data. In using synthetic data, one can verify the extent to which source parameters can be recovered and evaluate how various data corruption effects can be calibrated. These studies are important when proposing observations of new sources, in the characterization of the capabilities of new or upgraded instruments, and when verifying model-based theoretical predictions in a comparison with observational data. We present the SYnthetic Measurement creator for long Baseline Arrays (SYMBA), a novel synthetic data generation pipeline for Very Long Baseline Interferometry (VLBI) observations. SYMBA takes into account several realistic atmospheric, instrumental, and calibration effects. We used SYMBA to create synthetic observations for the Event Horizon Telescope (EHT), a mm VLBI array, which has recently captured the first image of a black hole shadow. After testing SYMBA with simple source and corruption models, we study the importance of including all corruption and calibration effects. Based on two example general relativistic magnetohydrodynamics (GRMHD) model images of M87, we performed case studies to assess the attainable image quality with the current and future EHT array for different weather conditions. The results show that the effects of atmospheric and instrumental corruptions on the measured visibilities are significant. Despite these effects, we demonstrate how the overall structure of the input models can be recovered robustly after performing calibration steps. With the planned addition of new stations to the EHT array, images could be reconstructed with higher angular resolution and dynamic range. In our case study, these improvements allowed for a distinction between a thermal and a non-thermal GRMHD model based on salient features in reconstructed images.
MeerKATHI is the current development name for a radio-interferometric data reduction pipeline, assembled by an international collaboration. We create a publicly available end-to-end continuum- and line imaging pipeline for MeerKAT and other radio telescopes. We implement advanced techniques that are suitable for producing high-dynamic-range continuum images and spectroscopic data cubes. Using containerization, our pipeline is platform-independent. Furthermore, we are applying a standardized approach for using a number of different of advanced software suites, partly developed within our group. We aim to use distributed computing approaches throughout our pipeline to enable the user to reduce larger data sets like those provided by radio telescopes such as MeerKAT. The pipeline also delivers a set of imaging quality metrics that give the user the opportunity to efficiently assess the data quality.
We present the development of a machine learning based pipeline to fully automate the calibration of the frequency comb used to read out optical/IR Microwave Kinetic Inductance Detector (MKID) arrays. This process involves determining the resonant frequency and optimal drive power of every pixel (i.e. resonator) in the array, which is typically done manually. Modern optical/IR MKID arrays, such as DARKNESS (DARK-speckle Near-infrared Energy-resolving Superconducting Spectrophotometer) and MEC (MKID Exoplanet Camera), contain 10-20,000 pixels, making the calibration process extremely time consuming; each 2000 pixel feedline requires 4-6 hours of manual tuning. Here we present a pipeline which uses a single convolutional neural network (CNN) to perform both resonator identification and tuning simultaneously. We find that our pipeline has performance equal to that of the manual tuning process, and requires just twelve minutes of computational time per feedline.
SOXS is a new spectrograph for the New Technology Telescope (NTT), optimized for transient and variable objects, covering a wide wavelength range from 350 to 2000 nm. SOXS is equipped with a calibration unit that will be used to remove the instrument signatures and to provide wavelength calibration to the data. The calibration unit will employ seven calibration lamps: a quartz-tungsten-halogen and a deuterium lamp for the flat-field correction, a ThAr lamp and four pencil-style rare-gas lamps for the wavelength calibration. The light from the calibration lamps is injected into the spectrograph mimicking the f/11 input beam of the NTT, by using an integrating sphere and a custom doublet. The oversized illumination patch covers the length of the spectrograph slit homogeneously, with $< 1%$ variation. The optics also supports the second mode of the unit, the star-simulator mode that emulates a point source by utilizing a pinhole mask. Switching between the direct illumination and pinhole modes is performed by a linear stage. A safety interlock switches off the main power when the lamp box cover is removed, preventing accidental UV exposure to the service personnel. All power supplies and control modules are located in an electronic rack at a distance from the telescope platform. In this presentation we describe the optical, mechanical, and electrical designs of the SOXS calibration unit, and report the status of development in which the unit is currently in the test and verification stage.
The recently developed JWST Exoplanet Observation Simulator (JexoSim) simulates transit spectroscopic observations of exoplanets by JWST with each of its four instruments using a time-domain approach. Previously we reported the validation of JexoSim against Pandexo and instrument team simulators. In the present study, we report a substantially enhanced version, JexoSim 2.0, which improves on the original version through incorporation of new noise sources, enhanced treatment of stellar and planetary signals and instrumental effects, as well as improved user-operability and optimisations for increased speed and efficiency. A near complete set of instrument modes for exoplanet time-series observations is now included. In this paper we report the implementation of JexoSim 2.0 and assess performance metrics for JWST in end-member scenarios using the hot Jupiter HD 209458 b and the mini-Neptune K2-18 b. We show how JexoSim can be used to compare performance across the different JWST instruments, selecting an optimal combination of instrument and subarray modes, producing synthetic transmission spectra for each planet. These studies indicate that the 1.4 {mu}m water feature detected in the atmosphere of K2-18 b using the Hubble WFC3 might be observable in just one transit observation with JWST with either NIRISS or NIRSpec. JexoSim 2.0 can be used to investigate the impact of complex noise and systematic effects on the final spectrum, plan observations and test the feasibility of novel science cases for JWST. It can also be customised for other astrophysical applications beyond exoplanet spectroscopy. JexoSim 2.0 is now available for use by the scientific community.
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