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Context: The NIRSpec instrument for the James Webb Space Telescope (JWST) can be operated in multiobject (MOS), long-slit, and integral field (IFU) mode with spectral resolutions from 100 to 2700. Its MOS mode uses about a quarter of a million individually addressable minislits for object selection, covering a field of view of $sim$9 $mathrm{arcmin}^2$. Aims: The pipeline used to extract wavelength-calibrated spectra from NIRSpec detector images relies heavily on a model of NIRSpec optical geometry. We demonstrate how dedicated calibration data from a small subset of NIRSpec modes and apertures can be used to optimize this parametric model to the necessary levels of fidelity. Methods: Following an iterative procedure, the initial fiducial values of the model parameters are manually adjusted and then automatically optimized, so that the model predicted location of the images and spectral lines from the fixed slits, the IFU, and a small subset of the MOS apertures matches their measured location in the main optical planes of the instrument. Results: The NIRSpec parametric model is able to reproduce the spatial and spectral position of the input spectra with high fidelity. The intrinsic accuracy (1-sigma, RMS) of the model, as measured from the extracted calibration spectra, is better than 1/10 of a pixel along the spatial direction and better than 1/20 of a resolution element in the spectral direction for all of the grating-based spectral modes. This is fully consistent with the corresponding allocation in the spatial and spectral calibration budgets of NIRSpec.
The Near-Infrared Spectrograph (NIRSpec) is one of four instruments aboard the James Webb Space Telescope (JWST). NIRSpec is developed by ESA with AIRBUS Defence & Space as prime contractor. The calibration of its various observing modes is a fundamental step to achieve the mission science goals and provide users with the best quality data from early on in the mission. Extensive testing of NIRSpec on the ground, aided by a detailed model of the instrument, allow us to derive initial corrections for the foreseeable calibrations. We present a snapshot of the current calibration scheme that will be revisited once JWST is in orbit.
The focal plane of the NIRSpec instrument on board the James Webb Space Telescope (JWST) is equipped with two Teledyne H2RG near-IR detectors, state-of-the-art HgCdTe sensors with excellent noise performance. Once JWST is in space, however, the noise level in NIRSpec exposures will be affected by the cosmic ray (CR) fluence at the JWST orbit and our ability to detect CR hits and to mitigate their effect. We have simulated the effect of CRs on NIRSpec detectors by injecting realistic CR events onto dark exposures that were recently acquired during the JWST cryo-vacuum test campaign undertaken at Johnson Space Flight Center. Here we present the method we have implemented to detect the hits in the exposure integration cubes, to reject the affected data points within our ramp-to-slope processing pipeline (the prototype of the NIRSpec official pipeline), and assess the performance of this method for different choices of the algorithm parameters. Using the optimal parameter set to reject CR hits from the data, we estimate that, for an exposure length of 1,000 s, the presence of CRs in space will lead to an increase of typically ~7% in the detector noise level with respect to the on-ground performance, and the corresponding decrease in the limiting sensitivity of the instrument, for the medium and high-spectral resolution modes.
In August 2015, the CALorimetric Electron Telescope (CALET), designed for long exposure observations of high energy cosmic rays, docked with the International Space Station (ISS) and shortly thereafter began tocollect data. CALET will measure the cosmic ray electron spectrum over the energy range of 1 GeV to 20 TeV with a very high resolution of 2% above 100 GeV, based on a dedicated instrument incorporating an exceptionally thick 30 radiation-length calorimeter with both total absorption and imaging (TASC and IMC) units. Each TASC readout channel must be carefully calibrated over the extremely wide dynamic range of CALET that spans six orders of magnitude in order to obtain a degree of calibration accuracy matching the resolution of energy measurements. These calibrations consist of calculating the conversion factors between ADC units and energy deposits, ensuring linearity over each gain range, and providing a seamless transition between neighboring gain ranges. This paper describes these calibration methods in detail, along with the resulting data and associated accuracies. The results presented in this paper show that a sufficient accuracy was achieved for the calibrations of each channel in order to obtain a suitable resolution over the entire dynamic range of the electron spectrum measurement.
We present a novel population-based Bayesian inference approach to model the average and population variance of spatial distribution of a set of observables from ensemble analysis of low signal-to-noise ratio measurements. The method consists of (1) inferring the average profile using Gaussian Processes and (2) computing the covariance of the profile observables given a set of independent variables. Our model is computationally efficient and capable of inferring average profiles of a large population size from noisy measurements, without stacking and binning data nor parameterizing the shape of the mean profile. We demonstrate the performance of our method using dark matter, gas and stellar profiles extracted from hydrodynamical cosmological simulations of galaxy formation. Population Profile Estimator (PoPE) is publicly available in a GitHub repository. Our new method should be useful for measuring the spatial distribution and internal structure of a variety of astrophysical systems using large astronomical surveys.
High dynamic-range imagers aim to block out or null light from a very bright primary star to make it possible to detect and measure far fainter companions; in real systems a small fraction of the primary light is scattered, diffracted, and unocculted. We introduce S4, a flexible data-driven model for the unocculted (and highly speckled) light in the P1640 spectroscopic coronograph. The model uses Principal Components Analysis (PCA) to capture the spatial structure and wavelength dependence of the speckles but not the signal produced by any companion. Consequently, the residual typically includes the companion signal. The companion can thus be found by filtering this error signal with a fixed companion model. The approach is sensitive to companions that are of order a percent of the brightness of the speckles, or up to $10^{-7}$ times the brightness of the primary star. This outperforms existing methods by a factor of 2-3 and is close to the shot-noise physical limit.