JWST Early Release Science Program TEMPLATES: Targeting Extremely Magnified Panchromatic Lensed Arcs and their Extended Star formation

TL;DR

TEMPLATES is a JWST program studying gravitationally lensed galaxies at z=1.3-4.2, providing diagnostics of star formation, stellar populations, and physical conditions, while establishing best practices for IFU observations.

Contribution

This paper introduces the TEMPLATES program, demonstrating JWST's capabilities for detailed galaxy evolution studies and establishing data reduction and observation strategies.

Findings

Spectral diagnostics for star formation and stellar populations obtained.

Spatial mapping of star formation and physical conditions achieved.

Technical guidelines for JWST IFU data reduction established.

Abstract

This paper gives an overview of TEMPLATES, a JWST Early Release Science program that targeted four extremely bright, gravitationally lensed galaxies: two extremely dusty, two with low attenuation, as templates for galaxy evolution studies with JWST. TEMPLATES obtains a common set of spectral diagnostics for these 1.3 < z < 4.2 galaxies, in particular H alpha, Paschen alpha, and the rest-frame optical and near-infrared continua. In addition, two of the four targets have JWST coverage of [O III] 5007 Angstrom and H beta; the other two targets have have JWST coverage of PAH 3.3 micron and complementary ALMA data covering the [C II] 158 micron emission line. The science goals of TEMPLATES are to demonstrate attenuation-robust diagnostics of star formation, map the distribution of star formation, compare the young and old stellar populations, and measure the physical conditions of star formation and their spatial variation across the galaxies. In addition, TEMPLATES has technical goals to establish best practices for the Integral Field Units (IFU) within the NIRSpec and MIRI instruments, both in terms of observing strategy and in terms of data reduction. The paper describes TEMPLATES's observing program, scientific and technical goals, data reduction methods, and deliverables, including high-level data products and data reduction cookbooks.