############################## ### CEERS Data Release 1.0 ### ############################## Date Released: XX September, 2025 Here we provide our team's updated reductions of the full set of CEERS NIRCam imaging: ten pointings obtained in parallel to primary NIRSpec MSA or MIRI Imaging, plus one module of the NIRCam imaging obtained in parallel from program 2750 (PI Arrabal Haro). Four of the pointings (5, 7, 8 and 9) were also observed with NIRCam WFSS, and so we include the SW F115W imaging and the F356W direct imaging in the mosaics for those pointings. Our data products will be available soon at MAST as a High Level Science Product via DOI 10.17909/z7p0-8481. ############ ### Summary Instrument: NIRCam Mode: Imaging Calibration Pipeline Used: jwst v1.13.4 CRDS Context pmap: 1195 Target: NIRCam pointings 1, 2, 3, 6 (in parallel with prime MIRI Imaging); NIRCam Pointings 4, 5, 7, 8, 9, 10 (in parallel with prime NIRSpec MSA), with additional SW F115W imaging and F356W direct imaging in NIRCam WFSS pointings 5, 7, 8 and 9; NIRCam module A from DDT 2750 (in parallel to prime NIRSpec MSA) Filters: SW F115W, F150W, F200W; LW F277W, F356W, F410M, F444W Readout: MEDIUM8 (MIRI and NIRSpec parallels), SHALLOW4 (WFSS imaging) Observation specification: 5, 6 or 9 groups, 1 integration Dithers: 3-point dither in each filter (defined by the MIRI and NIRSpec primary observations); 4-point dither for F115W imaging in WFSS pointings (defined by MIRI parallels), direct and out-of-field imaging in F115W and F356W in WFSS pointings Contact: Micaela Bagley (mbagley@utexas.edu) Steven Finkelstein (stevenf@astro.as.utexas.edu) ############################################## ### Full CEERS NIRCam Imaging and Reduction This 1.0 data release includes CEERS NIRCam pointings 1-10, obtained in parallel to prime NIRSpec MSA and MIRI Imaging Observations. We also include the SW F115W and direct imaging in F356W obtained as part of the NIRCam WFSS observations in pointings 5, 7, 8 and 9, and module A of DDT 2750 (obtained in parallel to prime NIRSpec MSA). We provide full field mosaics as well as individual mosaics for each pointing. The mosaics are on a pixel scale of 0.03"/pix, and so the zeropoint is 28.08652 AB mag. The mosaics are pixel-aligned across all filters. We also provide pixel-aligned images in all available HST filters for each pointing. Each mosaic is a gzipped FITS file with 13 extensions, described below. The gzipped files are each ~1.3-2 GB and unzip to ~2.2-3.2 GB (~4.5 GB for the F115W mosaics in the fields with extra imaging from the WFSS observations. For each pointing, we also provide a gzipped tarball (tar.gz) containing mosaics for all filters, including HST. These tarballs are ~15-20 GB. We have reduced the raw images through the JWST Calibration Pipeline (v1.13.4) with custom modifications and reduction steps designed to address additional features and challenges with the data such as snowballs, wisps, 1/f noise, and astrometric alignment. We provide all scripts necessary to reproduce our reduction on GitHub at https://github.com/ceers/ceers-nircam. The data reduction is described in detail in Bagley et al. (2023, ApJL, 946, 12). (https://ui.adsabs.harvard.edu/abs/2023ApJ...946L..12B/abstract) Please cite this paper if you use the reduced images or reduction scripts for your project. We note that we have not made any corrections for correlated noise. As a result, there will be a difference between the RMS measured on the science images and that from the error arrays, and the ERR maps will require some additional scaling to account for this. ####################### ### Directory Contents ## Full field mosaics ## Individual pointing mosaics Mosaics for each pointing are stored in separate directories. The NIRCam mosaic filenames are of the form: [pointing]/hlsp_ceers_jwst_nircam_[pointing]_[filter]_v1_i2d.fits where: - [pointing] is one of 'nircam1', 'nircam2', ... 'nircam10' - [filter] is one of 'f115w', 'f150w', 'f200w', 'f277w', 'f356w', 'f410m', or 'f444w' The HST mosaic filenames are of the form: egs_all_[instrument]_[filter]_030mas_v1.9_[pointing]_mef.fits where: - [instrument] is either 'acs_wfc' or 'wfc3_ir', - [filter] is one of 'f606w', 'f814w', 'f105w', 'f125w', 'f140w', or 'f160w' - [pointing] is one of 'nircam4', 'nircam5', 'nircam7', 'nircam8', 'nircam9' or 'nircam10' The gzipped tarballs [pointing].tar.gz include both the NIRCam and HST mosaics. #################### ### File structure The NIRCam images are multi-extension fits files with 13 extensions: 0. PRIMARY header 1. SCI_BKSUB - 2D background-subtracted science image 2. SCI - 2D science image (not background subtracted) 3. ERR - 2D array of uncertainties, given as standard deviation and constructed as the sum in quadrature of the resampled variance maps 4. CON - 2D context image, encoding info about which input images contribution to each output pixel 5. WHT - 2D weight image giving the relative weight of the output pixels, constructed from the VAR_RNOISE map during resampling 6. VAR_POISSON - 2D variance array based on Poisson noise only 7. VAR_RNOISE - 2D variance array based on read noise only 8. VAR_FLAT - 2D variance array based on uncertainty in the flat-field 9. BKGD - 2D background model subtracted from the science image 10. BKGMASK - the tiered source mask used to create the background 11. HDRTAB - table containing metadata (FITS keyword values) for all the input images 12. ASDF - metadata for the JWST data model For more information on JWST file names and extension explanations, see: jwst-pipeline.readthedocs.io/en/latest/jwst/data_products/science_products.html JWST images can be read in several ways. For example, with astropy: >>> from astropy.io import fits >>> with fits.open('hlsp_ceers_jwst_nircam_nircam4_f115w_v1_i2d.fits') as hdu: ... hdu.info() Or using the jwst datamodels: >>> from jwst.datamodels import ImageModel >>> with ImageModel('hlsp_ceers_jwst_nircam_nircam4_f115w_v1_i2d.fits.gz') as im: ... im.info() For more information on JWST Data Models, see: jwst-pipeline.readthedocs.io/en/latest/jwst/user_documentation/datamodels.html The HST drizzled science images (*mef.fits) are multi-extension fits files with 6 extensions: 0. PRIMARY header 1. SCI_BKSUB - 2D background-subtracted science image 2. SCI - 2D science image (not background subtracted) 3. RMS - 2D RMS map 4. BKGD - 2D background model subtracted from the science image 5. BKGMASK - the tiered source mask used to create the background Note that the RMS maps in the WFC3/IR filters are a newer version (v1.9.1), which correct a problem in the v1.9 WFC3/IR RMS maps that were not properly scaled by the exposure time.