Limits on routine wavefront sensing with NIRCam on JWST

Abstract

The James Webb Space Telescope (JWST) will be a segmented, deployable, infrared-optimized 6.5m space telescope. Its active primary segments will be aligned, co-phased, and then fine-tuned in order to deliver image quality sufficient for the telescope's intended scientific goals. Wavefront sensing used to drive this fine tuning will come from the analysis of defocussed phase diverse images taken with its near-IR science camera, NIRCam. Here we concentrate on routine maintenance of the JWST primary, as might be expected to occur on a more or less monthly timescale after the telescope is commissioned. We carry out an end-to-end optical and wavefront sensing simulation, starting from the primary mirror figure, calculating a noiseless point-spread function as it would appear on the detector, inject noise sources due to photon statistics, as well as detector and electronics characteristics (as measured in Rockwell HAWAII-2RG detectors in the lab), and reduce the data with a simple scheme to create one realization of a full wavefront sensing operation. We generate JWST point-spread functions for a given OPD map on a JWST pupil with -6, -3, 3, and 6 waves of focus, and simulate three realizations of the same exposure. We start with a mirror figure that provides a point-spread function (PSF) that is just under the acceptable specification for JWST's Strehl ratio, which is 80% at 2 microns in NIRCam. We do not include zodiacal light, diffuse sources, or contamination by other stars in our simulation. Our up-the-ramp exposures include a model of cosmic ray contamination of the data. We calibrate the image to account for dark current and flat field variation, and process the images with an implementation of the Misell-Gerchberg-Saxton algorithm assuming a known pupil support function. Our entire process is described here, to document a tool that helps to verify our intended method of maintaining the JWST PSF within specificatiuons during routine science operations.