Finding High-Redshift Galaxies with JWST
Abstract
One of the primary goals for the upcoming James Webb Space Telescope (JWST) is to observe the first galaxies. Recent studies have predicted that JWST will be capable of finding galaxies out to a redshift of 15 for an idealized, ultra-deep survey with an area of 200 arcmin2. Estimates typically focus on the average case, assuming a random distribution of galaxies across the observed field. The first and most massive galaxies, however, are expected to be tightly clustered, an effect known as cosmic variance. We therefore investigate the effects of cosmic variance on attempts to discover high redshift galaxies with JWST. We consider both idealized surveys and more realistic survey designs, such as the fields planned in the JADES GTO. We find that very few surveys will be close to average, so that typically a JWST survey will not be able to observe galaxies out to the redshifts which have been predicted. Instead, a survey will find none of these galaxies a majority of the time, and a random pointing of JWST which on average will find one such galaxy is predicted to detect a high redshift galaxy as rarely as 30% of the time, with multiple such galaxies often found in fields where at least one appears. To optimize the utility of JWST for observing high redshift galaxies, it will therefore be critical to develop strategies to account for the effects of cosmic variance. We evaluate the improvement possible from using gravitational lensing to find galaxies that would otherwise be too faint to observe, the most successful strategy with the Hubble Space Telescope. However, a more efficient plan would be to use a parallel survey, first combatting cosmic variance by observing a large number of independent pointings to find the rare fields with very high-redshift targets, then taking advantage of cosmic variance to conduct ultra-deep observations on those fields and find the many additional high-redshift galaxies which are likely to appear.
- Publication:
-
American Astronomical Society Meeting Abstracts #235
- Pub Date:
- January 2020
- Bibcode:
- 2020AAS...23520711L