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20102026
most citedNonlinear Evolution of Cosmological Structures in Warm Dark Matter Models

283 citations · 4k across the 56 of their papers we have counts for

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Showing 2022Show all

7 papers · 1 filter

astro-ph.CO2022★ 18 cited

Constraining dark matter decays with cosmic microwave background and weak lensing shear observations

Jozef Bucko, Sambit K. Giri, Aurel Schneider

From observations at low and high redshifts, it is well known that the bulk of dark matter (DM) has to be stable or at least very long-lived. However, the possibility that a small…

astro-ph.CO2022★ 26 cited

Euclid: Modelling massive neutrinos in cosmology -- a code comparison

J. Adamek, R. E. Angulo, C. Arnold +133

The measurement of the absolute neutrino mass scale from cosmological large-scale clustering data is one of the key science goals of the Euclid mission. Such a measurement relies o…

astro-ph.CO2022★ 13 cited

Suppressing variance in 21-cm signal simulations during reionization

Sambit K. Giri, Aurel Schneider, Francisco Maion +1

Current best limits on the 21-cm signal during reionization are provided at large scales (100 Mpc). To model these scales, enormous simulation volumes are required which a…

astro-ph.CO2022★ 35 cited

CosmoGridV1: a simulated CDM theory prediction for map-level cosmological inference

Tomasz Kacprzak, Janis Fluri, Aurel Schneider +2

We present CosmoGridV1: a large set of lightcone simulations for map-level cosmological inference with probes of large scale structure. It is designed for cosmological parameter me…

astro-ph.CO2022★ 25 cited

Modeling HI at the field level

Andrej Obuljen, Marko Simonović, Aurel Schneider +1

We use an analytical forward model based on perturbation theory to predict the neutral hydrogen (HI) overdensity maps at low redshifts. We investigate its performance by comparing…

astro-ph.CO2022★ 52 cited

A Full CDM Analysis of KiDS-1000 Weak Lensing Maps using Deep Learning

Janis Fluri, Tomasz Kacprzak, Aurelien Lucchi +3

We present a full forward-modeled CDM analysis of the KiDS-1000 weak lensing maps using graph-convolutional neural networks (GCNN). Utilizing the , a novel m…