Mission Overview
Systematic Mid-infrared Instrument Legacy Extragalactic Survey ("SMILES")
Primary Investigator: George Rieke
HLSP Authors: Stacey Alberts, Jianwei Lyu, Irene Shivaei
Released: 2024-08-22
Updated: 2024-08-22
Primary Reference(s): Alberts et al. 2024, Rieke et al. 2024
DOI: 10.17909/et3f-zd57
Citations: See ADS Metrics
Source Data:
- MAST Portal DOI
- JWST GTO Proposal: 1207
The SMILES RGB image and footprint in the GOODS-S field
A F1500W, F1000W, F560W RGB image of SMILES
The zoomed-in areas show 40"x40" regions in HST F606W, NIRCam F444W, and matched MIRI and Spitzer bands, [F770W and IRAC Ch 4, top] and matched MIRI and MIPS bands [F2100W and MIPS24, bottom]. MIRI's resolution at 7.7um is only 2x coarser than NIRCam/F444W and ~7x finer than IRAC. This gain at 21um compared to MIPS allows MIRI to be background- rather than confusion-limited across its wavelength range. Cutout sets are shown at the same stretch.
The footprint of SMILES in the GOODS-S/HUDF region
(left) The SMILES MIRI imaging footprint (red) in the GOODS-S/HUDF region relative to a subset of the ancillary datasets available: JADES/NIRCam Deep and Medium imaging (Rieke et al., 2023, Eisenstein et al., 2023) and JADES/MIRI Deep parallels (Alberts et al., 2024, in prep), JEMS NIRCam medium band imaging (Williams et al., 2023), FRESCO NIRCam grism and imaging (Oesch et al., 2023), the HST WFC3 F160W footprint (Grogin et al., 2011), JVLA 6 and 3 GHz imaging out to the half-power radius (Alberts et al., 2020), and Chandra 7 Ms X-ray imaging (Luo et al., 2017). (right) A zoom-in of the SMILES field showing the three SMILES/NIRSpec MSA pointings with targets assigned to slits marked.
Overview
The Systematic Mid-infrared Instrument Legacy Extragalactic Survey (SMILES) is a multi-band JWST/MIRI imaging survey of the GOODS-S/HUDF region with NIRSpec spectroscopic follow-up. SMILES covers an area of 34 arcmin2 in 8 MIRI bands from 5.6-25.5um (F560W, F770W, F1000W, F1280W, F1500W, F1800W, F2100W, F2550W) plus three NIRSpec Micro-Shutter Array (MSA) masks (Figure 1). Data release 1 (DR1) presents the 8 MIRI mosaics, which have been reduced with custom background subtraction and astrometric corrections (Alberts et al. 2024). These mosaics reach 5 sigma point source sensitivities of 0.2 - 18 uJy (25.6 - 20.9 AB). In addition, a clean catalog with 3,096 sources detected at ≥ 4 sigma in either F560W or F770W is presented. Forced photometry is provided in all other bands, whether the source is detected or not. Cleaning of the catalog, to remove false positives due to noise peaks or cosmic ray showers, was performed using JADES DR2 NIRCam imaging, which is available over the majority of the SMILES area (see Alberts et al. 2024 for details).
Data Products
The SMILES MIRI imaging mosaics have a pixel scale of 0.06” and include SCI, ERR, EXP, and WHT extensions.
The SMILES DR1 photometric catalog contains 3,096 sources. Measurements are provided in all bands for sources detected at ≥ 4 sigma in F560W or F770W, with false positives identified and removed using ultra-deep NIRCam imaging from JADES (see Alberts et al. 2024 for details). Flux densities and their associated uncertainties are provided in 5 circular apertures (CIRC3-7, with r = 0.25, 0.3, 0.35, 0.5, 0.6”, respectively) and 2.5x scaled Kron apertures.
Data file naming convention:
hlsp_smiles_jwst_<instrument>_goodss_<filter>_<version>_<data-file-type>.fits
where:
- <instrument> is the instrument ("miri")
- <filter> is the filter or "multi" for the photometric catalog
- <version> is the version number ("v1.0")
Data file types:
_drz.fits |
Image mosaic |
_catalog.fits |
Photometric catalog |
Data Access
MAST Portal and Astroquery
All observations are available in the MAST Portal and astroquery. Set the 'Provenance Name' filter to SMILES in the Portal Advanced Search to match all observations. The observations can also be retrieved programmatically using the astroquery.mast module. The code example below retrieves all products.
from astroquery.mast import Observations
all_obs = Observations.query_criteria(provenance_name="smiles")
data_products = Observations.get_product_list(all_obs)
Observations.download_products(data_products)
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A web-based interface for cross-mission searches of data at MAST or the Virtual Observatory.
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Search for and download SMILES data products programmatically in Python.
