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Register a new userPandeia: A Multi-mission Exposure Time Calculator for JWST and WFIRST
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Added by
Klaus Martin Pontoppidan
Publication date
2017
fields
Physics
and research's language is
English
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Pandeia is the exposure time calculator (ETC) system developed for the James Webb Space Telescope (JWST) that will be used for creating JWST proposals. It includes a simulation-hybrid Python engine that calculates the two-dimensional pixel-by-pixel signal and noise properties of the JWST instruments. This allows for appropriate handling of realistic point spread functions, MULTIACCUM detector readouts, correlated detector readnoise, and multiple photometric and spectral extraction strategies. Pandeia includes support for all the JWST observing modes, including imaging, slitted/slitless spectroscopy, integral field spectroscopy, and coronagraphy. Its highly modular, data-driven design makes it easily adaptable to other observatories. An implementation for use with WFIRST is also available.
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This document describes the exposure time calculator for the Wide-Field Infrared Survey Telescope (WFIRST) high-latitude survey. The calculator works in both imaging and spectroscopic modes. In addition to the standard ETC functions (e.g. background and S/N determination), the calculator integrates over the galaxy population and forecasts the density and redshift distribution of galaxy shapes usable for weak lensing (in imaging mode) and the detected emission lines (in spectroscopic mode). The source code is made available for public use.
WFIRST is the highest priority space mission of the Decadal review, however, it is unlikely to begin in this decade primarily due to a anticipated NASA budget that is unlikely to have sufficient resources to fund such a mission. For this reason we present a lower cost mission that accomplishes all of the WFIRST science as described in the Design Reference Mission 1 with a probe class design. This is effort is motivated by a desire to begin WFIRST in a timely manner and within a budget that can fit within the assets available to NASA on a realistic basis. The design utilizes dichroics to form four focal planes all having the same field of view to use the majority of available photons from a 1.2 meter telescope.
JWST transmission and emission spectra will provide invaluable glimpses of transiting exoplanet atmospheres, including possible biosignatures. This promising science from JWST, however, will require exquisite precision and understanding of systematic errors that can impact the time series of planets crossing in front of and behind their host stars. Here, we provide estimates of the random noise sources affecting JWST NIRCam time-series data on the integration-to-integration level. We find that 1/f noise can limit the precision of grism time series for 2 groups (230 ppm to 1000 ppm depending on the extraction method and extraction parameters), but will average down like the square root of N frames/reads. The current NIRCam grism time series mode is especially affected by 1/f noise because its GRISMR dispersion direction is parallel to the detector fast-read direction, but could be alleviated in the GRISMC direction. Care should be taken to include as many frames as possible per visit to reduce this 1/f noise source: thus, we recommend the smallest detector subarray sizes one can tolerate, 4 output channels and readout modes that minimize the number of skipped frames (RAPID or BRIGHT2). We also describe a covariance weighting scheme that can significantly lower the contributions from 1/f noise as compared to sum extraction. We evaluate the noise introduced by pre-amplifier offsets, random telegraph noise, and high dark current RC pixels and find that these are correctable below 10 ppm once background subtraction and pixel masking are performed. We explore systematic error sources in a companion paper.
JWST holds great promise in characterizing atmospheres of transiting exoplanets, potentially providing insights into Earth-sized planets within the habitable zones of M dwarf host stars if photon-limited performance can be achieved. Here, we discuss the systematic error sources that are expected to be present in grism time series observations with the NIRCam instrument. We find that pointing jitter and high gain antenna moves on top of the detectors subpixel crosshatch patterns will produce relatively small variations (less than 6 parts per million, ppm). The time-dependent aperture losses due to thermal instabilities in the optics can also be kept to below 2 ppm. To achieve these low noise sources, it is important to employ a sufficiently large (more than 1.1 arcseconds) extraction aperture. Persistence due to charge trapping will have a minor (less than 3 ppm) effect on time series 20 minutes into an exposure and is expected to play a much smaller role than it does for the HST WFC3 detectors. We expect temperature fluctuations to be less than 3 ppm. In total, our estimated noise floor from known systematic error sources is only 9 ppm per visit. We do however urge caution as unknown systematic error sources could be present in flight and will only be measurable on astrophysical sources like quiescent stars. We find that reciprocity failure may introduce a perennial instrument offset at the 40 ppm level, so corrections may be needed when stitching together a multi-instrument multi-observatory spectrum over wide wavelength ranges.
The Simons Observatory (SO) is an upcoming experiment that will study temperature and polarization fluctuations in the cosmic microwave background (CMB) from the Atacama Desert in Chile. SO will field both a large aperture telescope (LAT) and an array of small aperture telescopes (SATs) that will observe in six bands with center frequencies spanning from 27 to 270~GHz. Key considerations during the SO design phase are vast, including the number of cameras per telescope, focal plane magnification and pixel density, in-band optical power and camera throughput, detector parameter tolerances, and scan strategy optimization. To inform the SO design in a rapid, organized, and traceable manner, we have created a Python-based sensitivity calculator with several state-of-the-art features, including detector-to-detector optical white-noise correlations, a handling of simulated and measured bandpasses, and propagation of low-level parameter uncertainties to uncertainty in on-sky noise performance. We discuss the mathematics of the sensitivity calculation, the calculators object-oriented structure and key features, how it has informed the design of SO, and how it can enhance instrument design in the broader CMB community, particularly for CMB-S4.
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