158 citations · 216 across the 5 of their papers we have counts for
18 papers
Bring the noise: exact inference from noisy simulations in collider physics
Christopher Chang, Benjamin Farmer, Andrew Fowlie +1
We rely on Monte Carlo (MC) simulations to interpret searches for new physics at the Large Hadron Collider (LHC) and elsewhere. These simulations result in noisy and approximate es…
PhaseTracer2: from the effective potential to gravitational waves
Peter Athron, Csaba Balazs, Andrew Fowlie +4
In recent years, the prospect of detecting gravitational waves sourced from a strongly first-order cosmological phase transition has emerged as one of the most exciting frontiers o…
A comparison of Bayesian sampling algorithms for high-dimensional particle physics and cosmology applications
Joshua Albert, Csaba Balazs, Andrew Fowlie +4
For several decades now, Bayesian inference techniques have been applied to theories of particle physics, cosmology and astrophysics to obtain the probability density functions of…
Nested sampling for physical scientists
Greg Ashton, Noam Bernstein, Johannes Buchner +20
We review Skilling's nested sampling (NS) algorithm for Bayesian inference and more broadly multi-dimensional integration. After recapitulating the principles of NS, we survey deve…
Comment on "Reproducibility and Replication of Experimental Particle Physics Results"
Andrew Fowlie
I would like to thank Junk and Lyons (arXiv:2009.06864) for beginning a discussion about replication in high-energy physics (HEP). Junk and Lyons ultimately argue that HEP learned…
A comparison of optimisation algorithms for high-dimensional particle and astrophysics applications
The DarkMachines High Dimensional Sampling Group, Csaba Balázs, Melissa van Beekveld +18
Optimisation problems are ubiquitous in particle and astrophysics, and involve locating the optimum of a complicated function of many parameters that may be computationally expensi…