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LIGO A: Detector Design and Science Prospects Beyond A+
L. Sun, K. Kuns, B. J. J. Slagmolen +1153
We present the LIGO A detector concept, an upgrade for the LIGO observatories based on room-temperature interferometers beyond the fifth observing run (O5). Building on th…
Scalable Gaussian Processes for Integrated and Overlapping Measurements Via Augmented State Space Models
Ryan A. Rubenzahl, Soichiro Hattori, Simo Särkkä +4
Astronomical measurements are often integrated over finite exposures, which can obscure latent variability on comparable timescales. Correctly accounting for exposure integration w…
Precision Requirements for Monte Carlo Sums within Hierarchical Bayesian Inference
Reed Essick, Will Farr
Hierarchical Bayesian inference is often conducted with estimates of the target distribution derived from Monte Carlo sums over samples from separate analyses of parts of the hiera…
Inferring the properties of a population of compact binaries in presence of selection effects
Salvatore Vitale, Davide Gerosa, Will M. Farr +1
Shortly after a new class of objects is discovered, the attention shifts from the properties of the individual sources to the question of their origin: do all sources come from the…
emcee v3: A Python ensemble sampling toolkit for affine-invariant MCMC
Daniel Foreman-Mackey, Will M. Farr, Manodeep Sinha +10
emcee is a Python library implementing a class of affine-invariant ensemble samplers for Markov chain Monte Carlo (MCMC). This package has been widely applied to probabilistic mode…
Accuracy Requirements for Empirically-Measured Selection Functions
Will M. Farr
I give formulas for the accuracy to which a selection function must be measured via Monte-Carlo injections in order to have un-biased population inference. The number of found inje…