1 citations · 1 across the 5 of their papers we have counts for
5 papers
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…
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…
Radio Halo Detection in MWA Data using Deep Neural Networks and Generative Data Augmentation
Ashutosh K. Mishra, Emma Tolley, Shreyam Parth Krishna +1
Detecting diffuse radio emission, such as from halos, in galaxy clusters is crucial for understanding large-scale structure formation in the universe. Traditional methods, which re…
Combining summary statistics with simulation-based inference for the 21 cm signal from the Epoch of Reionization
Benoit Semelin, Romain Mériot, Ashutosh Mishra +1
The 21 cm signal from the Epoch of Reionization will be observed with the up-coming Square Kilometer Array (SKA). SKA should yield a full tomography of the signal which opens the p…