RayGalGroupSims Relativistic Halo Catalogs and Light-Cone Data

The RayGalGroupSims suite consists of a set of N-body simulations of different cosmological models, which have been specifically designed to generate high resolution halo catalogs in redshift-space (light-cone) taking into account for all observable relativistic effects to first order in the weak field approximation.

To date we have realised two runs for LCDM and wCDM scenarios with parameters set to the WMAP-7 best-fit cosmological model (and within the Planck 2-sigma level contours). The simulations cover a (2625 Mpc/h)3 volume with Np=40963 particles (the mass resolution is about 1.88 ·1010 Msun/h in LCDM and 2.01·1010 in wCDM).

Full-sky light-cone data in the redshift range z ~ [0,0.5] are generated during the simulation run without the use of replica.

We also produce narrow light-cones: 1) an intermediate light-cone in the redshift range z ~ [0, 2] with a rotation of φ = 25 deg and θ = 25 deg, with a 50 x 50 deg² f.o.v; 2) a deep light-cone in the redshift range z ~ [0, 10] with a rotation of φ = 17 deg and θ = 25 deg, with a 20 x 20 deg² f.o.v

Halos in the light-cone have been detected with pFoF. Their apparent position in the sky has been computed using a ray-tracing method to account for all relativistic effects (redshift & angular perturbations) at first order in the weak field approximation. These include: Doppler effect, gravitational distortions, transverse Doppler, Integrated Sachs-Wolfe & Rees-Sciama effect, weak lensing effects. The distortion matrix computed using a ray-bundle approach is also provided with the halo catalogs.

Hereafter, we provide the links to light-cone data (i.e. as observed).

If you are interested in snapshot data you can go there.


Information about the RayGal cosmological models can be found here

Simulation data:


Examples of RayGal Images


List of Publications Using RayGal Data

Link to previous data release

v00001 (Breton et al. 2019)

Known issues

Known issues

RayGal team

Raygal team


If you use these data, we kindly ask you to cite the two following papers: Breton et al. 2019 (link); Rasera et al., 2021 (link).

We acknowledge financial support from the DIM ACAV of the Région Île-de-France, the Action fédératriceee Cosmologie et structuration de l’univers as well as the JSPS Grant L16519. This work was granted access to HPC resources of TGCC/CINES through allocations made by GENCI Grand Equipement National de Calcul Intensif under the allocations 2016-042287, 2017-A0010402287, 2018-A0030402287, 2019-A0050402287 and 2020-A0070402287. AT acknowledges the support from MEXT/JSPS KAKENHI Grant Nos. JP17H06359, JP20H05861, JP21H01081, and JST AIP Acceleration Research Grant No. JP20317829, Japan. We thank Enea Di Dio for pointing out the “hidden” Class options to tune, S. Prunet for help on MPGRAFIC and Polspice, R. Teyssier for help on Ramses, B. Li for sharing his TSC routine, C. Murray for useful comments on the catalogues, J. Adamek for tips about Healpix. We also thank J.-M. Alimi, S. Colombi, I. Achitouv and A.Le Brun for fruitful discussions. We deeply thank Stéphane Mene for tremendeous efforts in making the local servers working at LUTH