The amount and complexity of data delivered by modern galaxy surveys has been steadily
increasing over the past years. New facilities will soon provide imaging and spectra of …

Many domains of science have developed complex simulations to describe phenomena of
interest. While these simulations provide high-fidelity models, they are poorly suited for …

The dawn of the twenty-first century came with very positive prospects for gravity, cosmology,
and astrophysics. Technological progress made it possible for cosmology to enter to its …

The CAMELS Project: Cosmology and Astrophysics with Machine-learning Simulations -
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The Quijote Simulations - IOPscience This site uses cookies. By continuing to use this site you
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Cosmic inflation provides a window to the highest energy densities accessible in nature, far
beyond those achievable in any realistic terrestrial experiment. Theoretical insights into the …

We present cosmological constraints from a simulation-based inference (SBI) analysis of
galaxy clustering from the SimBIG forward modeling framework. SimBIG leverages the …

In many cosmological inference problems, the likelihood (the probability of the observed
data as a function of the unknown parameters) is unknown or intractable. This necessitates …

Likelihood-free methods perform parameter inference in stochastic simulator models where
evaluating the likelihood is intractable but sampling synthetic data is possible. One class of …

While astrophysical and cosmological probes provide a remarkably precise and consistent
picture of the quantity and general properties of dark matter, its fundamental nature remains …