activity
20202026
most citedSimulation-based inference of dynamical galaxy cluster masses with 3D convolutional neural networks

31 citations · 44 across the 5 of their papers we have counts for

collaborators

5 papers

astro-ph.CO2026

Follow-up of SN 2025wny I: Space-based Observations of the First Multiply-imaged Superluminous Supernova

Ariel Goobar, Joel Johansson, Edvard Mörtsell +21

We present space-based follow-up observations of the superluminous Type I supernova (SLSN-I) SN 2025wny at redshift , gravitationally lensed by two galaxies at redsh…

astro-ph.CO2026

A Natural Telescope: Discovery of the Strongly Lensed Type II SN 2025mkn at

Cameron Lemon, Ariel Goobar, Joel Johansson +90

We present the discovery of SN 2025mkn, a gravitationally lensed Type II supernova. First detected as a blue transient in ZTF, 0.83 from a elliptical gala…

astro-ph.IM2025★ 1 cited

Inferring the Hubble Constant Using Simulated Strongly Lensed Supernovae and Neural Network Ensembles

Gonçalo Gonçalves, Nikki Arendse, Doogesh Kodi Ramanah +1

Strongly lensed supernovae are a promising new probe to obtain independent measurements of the Hubble constant (). In this work, we employ simulated gravitationally lensed T…

astro-ph.IM2021★ 12 cited

AI-driven spatio-temporal engine for finding gravitationally lensed type Ia supernovae

Doogesh Kodi Ramanah, Nikki Arendse, Radosław Wojtak

We present a spatio-temporal AI framework that concurrently exploits both the spatial and time-variable features of gravitationally lensed supernovae in optical images to ultimatel…

astro-ph.CO2020★ 31 cited

Simulation-based inference of dynamical galaxy cluster masses with 3D convolutional neural networks

Doogesh Kodi Ramanah, Radosław Wojtak, Nikki Arendse

We present a simulation-based inference framework using a convolutional neural network to infer dynamical masses of galaxy clusters from their observed 3D projected phase-space dis…