Clamato2017: Igm Lyman-Alpha Forest Tomography Survey Public Data Release Of Spectra And Maps

<strong>CLAMATO 2017 Data Release 1 </strong> Public release: 2017 October 9 Uploaded to Zenodo on 2018 June 19th after acceptance for publication in ApJS By Khee-Gan Lee ([e-mail]) and collaborators Supporting paper: https://arxiv.org/abs/1710.02894 These are data products associated with the first data release of the COSMOS Lyman-Alpha Mapping And Tomography Observations (CLAMATO) survey with the Keck-I telescope, which mapped 3D Lyman-alpha forest absorption at 2.05&lt;z&lt;2.55 within the COSMOS field. The following is the summary of the main products:<br> - Source catalog (CL2017_VALUEADDED_RELEASE_20171009.TXT)<br> - Reduced spectra, in /spec_v0/ (blue) and /spec_v0_red (red) sub-directories<br> - Continuum-fitted 2.05&lt;z&lt;2.55 Lyman-alpha forest pixel data (pixel_data.bin)<br> - Wiener-reconstructed 3D absorption map (map_2017_v3.bin) Versions:<br> v0 (not public): Initial rough extraction for 2.15&lt;z&lt;2.55 <br> v1 (not public): Extended redshift range to 2.05&lt;z&lt;2.55 <br> v2 (not public): Caught bug that caused wrong [RA,Dec] for ~4-5 objects<br> v3 (released 2017 Oct 9): Fixed bug that caused wrong aspect ratio in output map<br> v4 (released 2018 Mar 29): Fixed bug that caused negative continua in some spectra <br> <strong>Redshift Catalog and Spectra</strong> We provide our redshift catalog and reduced spectra obtained with Keck-I/LRIS The source catalog is provided in the ASCII file CL2017_VALUEADDED_RELEASE_20171009.TXT, with the following columns: - BLUE_SPEC: Blue spectrum filename (in /spec_v0/ sub-directory)<br> - TOMO_ID: CLAMATO ID number<br> - GMAG: g-magnitude (AB) per Capak et al 2007 photometric catalog<br> - CONF: Redshift confidence grade: see https://arxiv.org/abs/1710.02894<br> - ZSPEC: Spectroscopic redshift as determined from CLAMATO spectrum<br> - QSO: QSO flag (1 if QSO, 0 if non-QSO)<br> - RA: R.A. in degrees (J2000)<br> - DEC: Dec in degrees (J2000)<br> - S/N_1: Estimated Lya-forest S/N at 2.05&lt;z&lt;2.15, -9.0 denotes no estimate<br> - S/N_2: Estimated Lya-forest S/N at 2.15&lt;z&lt;2.35, -9.0 denotes no estimate<br> - S/N_2: Estimated Lya-forest S/N at 2.35&lt;z&lt;2.55, -9.0 denotes no estimate<br> - S/N_RED: Estimated S/N over restframe 1250 ang &lt; lambda &lt; 1350 ang, -9.0 denotes no estimate<br> - TOMOFLAG: Flag on whether sightline was used in tomographic map (0 for no, 1 for yes)<br> - EXPTIME: Exposure time on the spectrum, in seconds (aggregate)<br> - RED_SPEC: Red spectrum filename (in /spec_v0_red/ sub-directory), 'NA' if doesn't exist The tarballs spec_v0.tar.gz and spec_v0_red.tar.gz include all the reduced spectra from LRIS-Blue and LRIS-Red, respectively. The individual LRIS spectra are provided in FITS format, with the following HDU Extensions:<br> - HDU0: Object spectral flux density, in units of 10^{-17} ergs/s/cm^2/angstrom<br> - HDU1: Noise standard deviation<br> - HDU2: Pixel Wavelengths in angstroms <strong>Pixel Data </strong> The binary file PIXEL_DATA_v4.BIN stores the concatenated Lyman-alpha forest pixels at 2.05&lt;z&lt;2.55 that have been extracted from the 1D spectra and continuum-fitted. The first value in the binary is a 32-bit integer specifying the number of pixels (64332), followed by 5 double-precision floating point (64-bit) vectors storing the x, y, z, sigma_f, and delta_f of the pixels. An example python script to read pixel_data is as follows:<br> import numpy as np<br> with open('CLAMATO2017_public/pixel_data_v4.bin','r') as f:<br> npix = np.fromfile(f, dtype=np.int32, count=1)<br> f.seek(4)<br> pixel_data = np.fromfile(f,dtype=np.float64).reshape((npix,5)) LIST_TOMO_INPUT_2017.TXT is a summary file of corresponding to PIXEL_DATA.BIN, listing the [x,y,z] position of the sightlines that contributed to the file as well as, in the final two columns, the index range that can be used to grab the relevant pixels from the concatenated pixel list. <strong>Tomographic Map</strong> The Wiener-reconstructed map of the 2.05&lt;z&lt;2.55 IGM within the CLAMATO field is the result of applying the dachshund algorithm (http://github.com/caseywstark/dachshund) to PIXEL_DATA.BIN, with the configuration file INPUT.CFG . (Caveat: the version of PIXEL_DATA.BIN here is not actually the right version to directly input into the dachshund code: the first integer in this file should not be present for input to dachshund). The reconstructed map is MAP_2017_V4.BIN, which is a 60x48x876 = 2552880 pixel double-precision binary with. The dimension that changes fastest is the z-dimension (876 pixels per dimension), followed by the y-dimension (48 pixels per dimension) and x-dimension (60 per dimension). Each map pixel represents a 0.5Mpc/h comoving voxel of the Ly-alpha forest absorption. See the Appendix of https://arxiv.org/abs/1710.02894 for the conversion factors to assume to switch between pixel/voxel and [RA, Dec, redshift]. The file MAP_2017_V4_SM2.0.BIN is the same map, but smoothed with a R=2Mpc/h Gaussian kernel.