S16A Shape Catalog – Data Products (PDR2)

Weak lensing mass maps (Oguri et al. 2018)

Weak lensing mass maps of HSC S16A six patches constructed using the Kaiser-Squires inversion method. The smoothing scale is 2 arcmin. See Oguri et al. (2018) for more details. For each patch, both E- and B-mode maps and their S/N maps are included. A quick explanation is found in the header of each fits file.

Cosmic shear measurements using pseudo-Cl method and chains (Hikage et al. 2019)

Cosmic shear measurements were carried out using the pseudo-Cl approach in Hikage et al. (2019). The corresponding measurements and chains are made available here. When using the above data, please cite the paper by Hikage et al. 2019, PASJ, 71, 43 (arXiv:1809.09148).

These provide band powers of tomographic lensing spectra l(l+1)C_l/2pi. We adopt 4-bin tomographic analysis and then the number of lensing spectra including auto and cross spectra becomes 10 in total. Each spectrum has 6 data points.

This provides the 1sigma error of the above data vector.

This provides the analytically estimated covariance in the best-fit cosmology (details are in the Appendix 2 of Hikage et al. 2019). The side-length of the matrix is 60 = 6 multipoles times 10 tomographic spectra.

Equally weighted posterior samples generated from multinest samplers in different setups:

Cosmic shear measurements using two point correlation method and chains (Hamana et al. 2020)

Cosmic shear measurements were carried out using the real space two point correlation function approach in Hamana et al. (2020). The corresponding measurements and chains are made available here.  For questions or requests for other data products, please contact Takashi Hamana (hamana.tk at nao.ac.jp). When using the above data, please cite the paper by Hamana et al. 2020, PASJ, 72, 1.

Two point correlation functions are provided for a 4 bin tomographic analysis (1×1, 1×2, 1×3, 1×4, 2×2, 2×3, 2×4, 3×3, 3×4, 4×4) are in the file xi_+ and xi_-. The PSF systematics data vectors can be found in xi_+^{pp, pq, qq}.

This provides the covariance estimated from mock catalogs (details are in Shirasaki et al. 2019).

These provide the source redshift distributions based on reweighting the COSMOS photometric redshift samples.

Equally weighted posterior samples generated from multinest samplers in different setups:

Cosmic shear mock catalogs (Shirasaki et al. 2019)

The full sky ray tracing simulations of Takahashi et al. (2017), were used to generate 2268 mock catalogs for the Subaru HSC survey first-year shear catalog (Shirasaki et al. 2019). The details of the catalog production process is found in Shirasaki et al. (2019), arXiv:1901.09488. The mock data has the following contents:

  • col1: tract ID
  • col2: an integer number for debug
  • col3: object ID
  • col4: RA [deg]
  • col5: dec [deg]
  • col6: e_1 (ellipticity)
  • col7: e_2 (ellipticity)
  • col8: shear_1 (lensing shear w/o any shape noises)
  • col9: shear_2 (lensing shear w/o any shape noises)
  • col10: kappa (lensing convergence)
  • col11: lensing weight
  • col12: source redshift

Note that the source redshift of each mock galaxy follows the photo-z posterior distribution by the MLZ algorithm (Tanaka et al 2017). For galaxies without the MLZ photo-z information, the source redshift (col12) was set equal to -1. The catalogs total 1.7 TB in size and can be downloaded using this script.

The halo catalogs used in order to create the lensing mocks can be found here.