Dataset Open Access

Lyman-alpha tomographic map of the large-scale matter distribution using the eBOSS - Stripe 82 data

Corentin Ravoux; Eric Armengaud

Lyman-alpha tomography map using DR16 eBOSS data

This data release contains products associated to the Lyman-alpha large-scale tomographic map realized with the 16th data release of SDSS-eBOSS. The densest Lyman-alpha forest set of eBOSS in the Stripe 82 field is used : 220 deg2 wide field with a 37 deg-2 density. A Lyman-alpha flux contrast map over a volume of 0.94 h-3Gpc3 is obtained. Voids and protoclusters are detected in this portion of the sky.

For more details : see https://arxiv.org/abs/2004.01448

All the data detailed below can be opened by using the short python script read_data_release.py.

Pixels and map data

The pixel file pixels_lya_tomography_stripe82.bin was used to create the Lya tomographic map map_lya_tomography_stripe82.bin by using the dachshund algorithm (https://github.com/caseywstark/dachshund).

Pixel and map file are in the binary numpy format. Pixels are created from 8999 Lya forests positioned from -43° to +45° in the RA(J2000) direction, from -1.25° to +1.25° in the DEC(J2000) direction and from z=2.1 to z=3.2. The (RA,DEC,z) coordinates are converted to (X,Y,Z) coordinates in Mpc.h-1. The pixel file shares the same origin than the map.

The map is also a binary numpy file. It contains a (6354,181,834) Mpc.h-1 cube of Lyman-alpha flux contrast with a pixel shape (2928,90,417). The origin of the map (0,0,0) corresponds to the coordinates RA=-43°, DEC=-1.25° and z=2.1 and in the cube coordinate to (X,Y,Z)=(0,0,0) Mpc.h-1.

Note that to obtain this map, the pixel file was first separated to parallelize the tomographic procedure. In comparison to the map detailed in the linked article, this map is rebinned to be less voluminous. Furthermore, a mask is applied to the map where the distance to the nearest line-of-sight of the pixel file is below 20 Mpc.h-1. At these locations, map flux contrast is put to 0.

 

Derived catalog data

Voids and proto-cluster searches are applied to the tomographic map. The results of this procedure, along with additional catalog cut is given in this data release. Catalogs of voids (catalog_voids_lya_stripe82_*.fits) and proto-clusters (catalog_protoclusters_lya_stripe82_*.fits) are given in the (X,Y,Z) and (RA,DEC,z) coordinates of the map, sharing the same origin. The catalogs are in the FITS format which can be opened with the fitsio python library.

Files (1.0 GB)
Name Size
catalog_protoclusters_lya_stripe82_mpc.fits
md5:6f7b2498ce070af8e5c1e6eb49f5ee13
8.6 kB Download
catalog_protoclusters_lya_stripe82_radecz.fits
md5:1c301ca962dbfaa232de4d1b60c7b32a
8.6 kB Download
catalog_voids_lya_stripe82_mpc.fits
md5:708885114c673657ce23107fdfe976e0
74.9 kB Download
catalog_voids_lya_stripe82_radecz.fits
md5:bc4a5595f2d413907adb4ae4796a46cb
74.9 kB Download
map_lya_tomography_stripe82.bin
md5:9ecaaf82ca77f83a56ece11042c4ea53
879.1 MB Download
pixels_lya_tomography_stripe82.bin
md5:74bbf6ac1086c7dd1a45605cd4752a17
129.4 MB Download
read_data_release.py
md5:ee19594626fafcc1cc4d93f7775567d7
2.4 kB Download
  • Ravoux et al. (2020), data associated with arxiv.org:2004.01448

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