4 papers
Probing the baryonic--dark matter connection in galaxy clusters using X-rays with gated recurrent unit neural networks
Asif Iqbal, Subhabrata Majumdar, Weiguang Cui +3
Accurate cluster mass measurements are crucial for cosmology, yet conventional hydrostatic equilibrium (HSE) methods can suffer from systematic biases, particularly in dynamically…
The Three Hundred Project: Validating inference from mock X-ray and millimetre analyses of galaxy clusters
F. De Luca, H. Bourdin, P. Mazzotta +6
Measurements of thermodynamical quantities in galaxy clusters are differently affected by simplified modelling of radially averaged observables in the X-ray and millimetre bands. T…
Deriving accurate galaxy cluster masses using X-ray thermodynamic profiles and graph neural networks
Asif Iqbal, Subhabrata Majumdar, Elena Rasia +4
Precise determination of galaxy cluster masses is crucial for establishing reliable mass-observable scaling relations in cluster cosmology. We employ graph neural networks (GNNs) t…
Predicting Halo Formation Time Using Machine Learning
Atulit Srivastava, Weiguang Cui, Daniel de Andres +3
Context:Halo formation time, which quantifies the mass assembly history of dark-matter halos, directly impacts galaxy properties and evolution. Although not directly observable, it…