107 citations · 813 across the 31 of their papers we have counts for
28 papers
Extremal learning: extremizing the output of a neural network in regression problems
Zakaria Patel, Markus Rummel
Neural networks allow us to model complex relationships between variables. We show how to efficiently find extrema of a trained neural network in regression problems. Finding the e…
Nuclear Predictions for Spectroscopy without Nuclear Errors
C. P. Burgess, P. Hayman, Markus Rummel +1
Nuclear-structure effects often provide an irreducible theory error that prevents using precision atomic measurements to test fundamental theory. We apply newly developed effective…
Precision Nuclear-Spin Effects in Atoms: EFT Methods for Reducing Theory Errors
L. Zalavari, C. P. Burgess, P. Hayman +1
We use effective field theory to compute the influence of nuclear structure on precision calculations of atomic energy levels. As usual, the EFT's effective couplings correspond to…
Constraining Fundamental Physics with the Event Horizon Telescope
Markus Rummel, C. P. Burgess
We show how Event Horizon Telescope (EHT) observations of the supermassive object at the center of M87 can constrain deviations from General Relativity (GR) in a relatively model-i…
Improving Statistical Sensitivity of X-ray Searches for Axion-Like Particles
Joseph P. Conlon, Markus Rummel
X-ray observations of bright AGNs in or behind galaxy clusters offer unique capabilities to constrain axion-like particles (ALPs). Existing analysis technique rely on measurements…
Effective Field Theory of Black Hole Echoes
C. P. Burgess, Ryan Plestid, Markus Rummel
Gravitational wave `echoes' during black-hole merging events have been advocated as possible signals of modifications to gravity in the strong-field (but semiclassical) regime. In…