SAMSI Poised to Help Hone Gravitational Wave Astronomy, Astronomers' New Sense
With renovations to LIGO nearing completion, gravitational wave data analysis was quickly identified as a focus area, along with exoplanets (which are detected via time series measurements), synoptic surveys (an emerging mode of large-scale automated time-domain observing), and cosmology. In September 2015, scientists gathered at SAMSI to plan the 2016-17 Program on Statistical, Mathematical and Computational Methods for Astronomy (ASTRO). The planning team included LIGO scientists who had only just learned of the candidate detection, and had to keep it secret until confirmed.
Of five working groups planned for the ASTRO program, four will address LIGO data analysis challenges, in concert with related challenges in other areas of time-domain astronomy (a fifth working group will focus on statistical problems in cosmology). One working group will study the potential role of new stochastic process models for analysis of time series data from LIGO and exoplanet surveys, particularly models that abandon the simplifying assumptions of stationarity and Gaussianity underlying most currently-used methods. Another working group will focus on gravitational wave and exoplanet signal detection, and how best to use detected signals for demographic studies (for example, to infer the prevalence and diversity of binary black hole systems, and other sources of LIGO signals). A third working group will address the data-theory interface in the regime of computationally expensive theoretical calculations, where it is impossible to directly compute detailed predictions for every candidate model for the data. Numerical general relativity calculations of binary black hole mergers are a motivating example; similar challenges arise in cosmology.
Finally, a working group on synoptic time-domain surveys will address how to find electromagnetic counterparts to gravitational wave sources. Black hole binary mergers, by their very nature, are essentially invisible electromagnetically. But astronomers expect LIGO to detect other types of events that synoptic surveys could capture electromagnetically, providing opportunities for synergistic multimessenger astronomy. These include such exotic phenomena as merging binary neutron stars, and mergers between black holes and ordinary stars, neutron stars, or white dwarf stars. In addition, gigantic stellar explosions, such as those producing supernovae or gamma-ray bursts, may produce detectable gravitational waves. In a tantalizing twist of fate, astronomers have observed all of these types of objects, and presumed that the first LIGO events would come from such already-known systems. Instead, the first LIGO signal was from a type of system hitherto undetected. What other surprises might this new ear on the sky reveal to us?
SAMSI and Astronomy
The ASTRO program is just the latest of several productive programs SAMSI has hosted to build interdisciplinary partnerships between astronomers, statisticians, and mathematicians. The first such program was the 2006 Spring Program on Astrostatistics (also led by Babu). It, too, included working groups addressing problems in gravitational wave and exoplanet astronomy. Many participants built long-lived collaborations at SAMSI; several are helping to organize the forthcoming ASTRO program. SAMSI's 2012-13 Program on Statistical and Computational Methodology for Massive Datasets included a week-long Workshop on Astrostatistics, organized by Babu, exploring the intersection of astronomy and "big data." In the summer of 2013, exoplanet astronomer Eric Ford (Penn State University) led a three-week program, Modern Statistical and Computational Methods for Analysis of Kepler Data. It spawned an independent ExoStats2014 workshop, and one of that program's working groups continues to meet two and a half years later. Finally, the ASTRO program's working group on inference with computationally expensive models will build on expertise gained from the 2006-07 Program on Development, Assessment and Utilization of Complex Computer Models, and the 2011-12 Programs on Uncertainty Quantification; participants from both of those programs are on the ASTRO planning team.