Mission Overview
CANDELS NIRWL F160W Mosaics ("CANDELSNIRWL")
Primary Investigator: Kyle Finner
HLSP Authors: Kyle Finner, BoMee Lee, Ranga-Ram Chary, M. James Jee, Christopher Hirata, Giuseppe Congedo, Peter Taylor, Kim Hyeonghan
Released: 2024-03-26
Updated: 2024-03-26
Primary Reference(s): Finner et al. 2023
DOI: 10.17909/f6hb-ez10
Citations: See ADS Statistics
Source Data:
Overview
The NIRWL team has prepared new mosaics covering the CANDELS fields: The UltraDeep Survey (UDS), GOODS South (GS), GOODS North (GN), The Extended Groth Strip (EGS), and the Cosmological Evolution Survey (COSMOS) in the HST F160W filter. The mosaics are drizzled to a pixel scale of 0.05’’ using the Gaussian kernel. The mosaics are aligned to the Gaia DR3 catalog to ±0.02 arcsec. Proper motions were included when aligning the frames to Gaia DR3. These mosaics have been corrected for systematic astrometric misalignments found in previous versions of the CANDELS F160W mosaics.
These carefully aligned mosaics have been created to perform a weak lensing analysis and search for large-scale overdensities. The spatially and temporally varying PSF of each mosaic has been constructed from the individual frames and characterized in the team's primary paper, Finner et al. (2023). Systematic effects that can affect galaxy shape measurements on the NIRWL mosaics are investigated.
Data Products
Data file naming convention:
hlsp_candelsnirwl_hst_wfc3-ir_<field>_f160w_v1.0_<prodType>.fits
where:
- <field> is a CANDELS field, one of "uds", "gs", "gn", "egs", and "cosmos"
- <prodType> is one of "sci", "wht", or "rms".
Data file types:
_sci.fits | Science image, the output of the Drizzle algorithm, and is in counts/s |
_wht.fits | Weight image, the output of the Drizzle algorithm |
_rms.fits | RMS image created by (weight image)-1/2 |
Data Access
All observations are available in the MAST Portal and astroquery. Set the 'Provenance Name' filter to CANDELSNIRWL in the Portal Advanced Search to match all observations. The weight and RMS images can be downloaded with their science image as a bundle or individually retrieved by selecting the download basket. 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="candelsnirwl")
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 retrieve CANDELSNIRWL data products programmatically.