46 citations · 64 across the 6 of their papers we have counts for
4 papers
Fourier Neural Operator for Plasma Modelling
Vignesh Gopakumar, Stanislas Pamela, Lorenzo Zanisi +3
Predicting plasma evolution within a Tokamak is crucial to building a sustainable fusion reactor. Whether in the simulation space or within the experimental domain, the capability…
Fourier-RNNs for Modelling Noisy Physics Data
Vignesh Gopakumar, Stanislas Pamela, Lorenzo Zanisi
Classical sequential models employed in time-series prediction rely on learning the mappings from the past to the future instances by way of a hidden state. The Hidden states chara…
Testing the key role of the stellar mass-halo mass relation in galaxy merger rates and morphologies via DECODE, a novel Discrete statistical sEmi-empiriCal mODEl
Hao Fu, Francesco Shankar, Mohammadreza Ayromlou +19
The relative roles of mergers and star formation in regulating galaxy growth are still a matter of intense debate. We here present our DECODE, a new Discrete statistical sEmi-empir…
Probing black hole accretion tracks, scaling relations and radiative efficiencies from stacked X-ray active galactic nuclei
Francesco Shankar, David H. Weinberg, Christopher Marsden +25
The masses of supermassive black holes at the centres of local galaxies appear to be tightly correlated with the mass and velocity dispersions of their galactic hosts. However, the…