Andrew-Systematics

LIGO has detected heavy binary black holes. By measuring the BH masses and spins, we get clues into how massive stars evolve, interact, and end their lives. These clues rely on inferences about the BH binary from the observed GW signal, obtained by comparing models for the signal to the observed data. Because of the difficulty in solving GR exactly, these models are approximations, and these inferences imperfect

How reliable are our conclusions? In a new paper, we try to demonstrate the potential effect of systematic modeling error. We first compare two such models to one another, finding not-infrequent disagreement. We generate synthetic signals, and draw distinctly different conclusions depending on which model we use to interpret our data. So, we show by concrete example that under suitable circumstances, inferences drawn from any one model can be biased.

For experts We compare SEOBNRv3 and IMRPv2 on the posteriors of real and synthetic events. We find significant disagreement between the two models, particularly for high spin. For GW151226, disagreements are substantial and frequent.

For more information, see

• Williamson et al Systematic challenges for future gravitational wave measurements of precessing binary black holes , available at arxiv.org