55 citations · 158 across the 26 of their papers we have counts for
8 papers · 1 filter
Multi-branch classification of diffuse cluster radio emission from the LOFAR two-metre sky survey
Markus Bredberg, Emma Tolley
Context. Galaxy clusters sometimes host synchrotron radiation on scales of approximately 100 kpc to approximately 1 Mpc, with a surface brightness only a few times the image noise.…
Cosmo-SPINN: Fuzzy Dark Matter Simulations with Physics-Informed Generative Networks
Ashutosh Kumar Mishra, Emma Tolley, Nicolas Cerardi
Generative machine learning models have recently emerged as powerful tools for producing cosmological simulations. However, many existing emulators do not explicitly enforce the un…
Foreground Characterization and Mitigation in the Observations of the CD/EoR with the SKA
Philip Bull, Jacob Burba, Emilio Ceccotti +20
The Square Kilometre Array (SKA), with its unprecedented sensitivity, frequency coverage, and large collecting area, is poised to revolutionize our understanding of the Cosmic Dawn…
Probing the Fundamental Nature of Particle Dark Matter
Marco Regis, Aritra Basu, Geoff Beck +7
Understanding the fundamental nature of dark matter (DM) is one of the most significant scientific challenges of our time. A compelling hypothesis is that DM consists of a new, yet…
Solving the Cosmological Vlasov-Poisson Equations with Physics-Informed Kolmogorov-Arnold Networks
Nicolas Cerardi, Emma Tolley, Ashutosh Mishra
Cold dark matter (CDM) evolves as a collisionless fluid under the Vlasov-Poisson equations, but N-body simulations approximate this evolution by discretising the distribution funct…
SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks
Ashutosh Kumar Mishra, Emma Tolley
Physics-Informed Neural Networks (PINNs) have emerged as a powerful tool for solving differential equations by integrating physical laws into the learning process. This work levera…