Low Latency Detection of Massive Black Hole Binaries

TL;DR

This paper presents a low latency data analysis pipeline for detecting massive black hole binary mergers with space-based gravitational wave detectors, enabling rapid localization and aiding electromagnetic counterpart searches.

Contribution

The authors develop a computationally efficient pipeline that analyzes months of data in hours, improving real-time detection capabilities for massive black hole mergers.

Findings

Pipeline analyzes months of data in hours on a standard laptop.

Performance demonstrated using simulated LISA data from the Data Challenge.

Effective in low latency detection and localization of black hole mergers.

Abstract

The next decade is expected to see the launch of one or more space based gravitational wave detectors: the European lead Laser Interferometer Space Antenna (LISA); and one or more Chinese mission concepts, Taiji and TianQin. One of the primary scientific targets for these missions are the mergers of black holes with masses between $10^3 M_\odot$ and $10^8 M_\odot$. These systems may produce detectable electromagnetic signatures in additional to gravitational waves due to the presence of gas in mini-disks around each black hole, and a circumbinary disk surrounding the system. The electromagnetic emission may occur before, during and after the merger. In order to have the best chance of capturing all phases of the emission it is imperative that the gravitational wave signals can be detected in low latency, and used to produce reliable estimates for the sky location and distance to help guide the search for counterparts. The low latency detection also provides a starting point for the ``global fit'' of the myriad signals that are simultaneously present in the data. Here a low latency analysis pipeline is presented that is capable of analyzing months of data in just a few hours using a laptop from the last decade. The problem of performing a global fit is avoided by whitening out the bright foreground produced by nearby galactic binaries. The performance of the pipeline is illustrated using simulated data from the LISA Data Challenge.