23 citations · 61 across the 10 of their papers we have counts for
11 papers
Anisotropic redshift distributions in photometric galaxy clustering and their cosmological impact
Zekang Zhang, Yunhe Wang, Daniel Gruen +4
Photometric galaxy clustering is a major probe of large-scale structure whose interpretation relies on accurate characterization of the galaxy redshift distribution, . Standa…
GalSBI: Forward Modelling Galaxy Clustering and Population
Silvan Fischbacher, Luca Tortorelli, Tomasz Kacprzak +1
Forward modelling is a powerful approach for analyzing large-scale structure surveys. For this purpose, we extend the GalSBI framework to jointly model the galaxy population and cl…
ProMage: fast galaxy magnitudes emulation combining SED forward-modelling and machine learning
Luca Tortorelli, Silvan Fischbacher, Aaron S. G. Robotham +2
We present ProMage, a feed-forward neural network that emulates the computation of observer- and rest-frame magnitudes from the generative galaxy SED package ProSpect. The network…
GalSBI-SPS: a stellar population synthesis-based galaxy population model for cosmology and galaxy evolution applications
Luca Tortorelli, Silvan Fischbacher, Daniel Grün +4
Next generation photometric and spectroscopic surveys will enable unprecedented tests of the concordance cosmological model and of galaxy formation and evolution. Fully exploiting…
SHAM-OT: Rapid Subhalo Abundance Matching with Optimal Transport
Silvan Fischbacher, Tomasz Kacprzak, Luis Fernando Machado Poletti Valle +1
Subhalo abundance matching (SHAM) is widely used for connecting galaxies to dark matter haloes. In SHAM, galaxies and (sub-)haloes are sorted according to their mass (or mass proxy…
galsbi: A Python package for the GalSBI galaxy population model
Silvan Fischbacher, Beatrice Moser, Tomasz Kacprzak +5
Large-scale structure surveys measure the shapes and positions of millions of galaxies in order to constrain the cosmological model with high precision. The resulting large data vo…
UFig v1: The ultra-fast image generator
Silvan Fischbacher, Beatrice Moser, Tomasz Kacprzak +8
With the rise of simulation-based inference (SBI) methods, simulations need to be fast as well as realistic. is a public Python package that simulates astronomic…
GalSBI: Phenomenological galaxy population model for cosmology using simulation-based inference
Silvan Fischbacher, Tomasz Kacprzak, Luca Tortorelli +4
We present GalSBI, a phenomenological model of the galaxy population for cosmological applications using simulation-based inference. The model is based on analytical parametrizatio…
Simulation-based inference of deep fields: galaxy population model and redshift distributions
Beatrice Moser, Tomasz Kacprzak, Silvan Fischbacher +3
Accurate redshift calibration is required to obtain unbiased cosmological information from large-scale galaxy surveys. In a forward modelling approach, the redshift distribution n(…
Redshift requirements for cosmic shear with intrinsic alignment
Silvan Fischbacher, Tomasz Kacprzak, Jonathan Blazek +1
Intrinsic alignment (IA) modelling and photometric redshift estimation are two of the main sources of systematic uncertainty in weak lensing surveys. We investigate the impact of r…
Towards a full CDM map-based analysis for weak lensing surveys
Dominik Zürcher, Janis Fluri, Virginia Ajani +3
The next generation of weak lensing surveys will measure the matter distribution of the local Universe with unprecedented precision, allowing the resolution of non-Gaussian feature…