Predicting Super Massive Black Hole Collisions Using LISA

Author:

Warden Chris

Abstract

LISA (Laser Interferometer Space Antenna) is due for launch in the 2030s. Its goal is to observe gravitational waves in the 10-4 to 10-1 Hz band. This frequency band contains signals from colliding Super Massive Black Holes, objects with masses in the range of millions, even billions, that of our own suns mass. These SMBHs are thought to lie at the heart of most, if not all galaxies. By understanding the physics of the underlying processes, and what LISA 'sees', we can predict when these mergers will occur. This would allow us to observe the merger directly in the EM spectrum, observing the light emitted from the merging accretion discs. This could yield a potentially vast amount of information about the composition and formation of these huge objects. In this project we explore some of the potential variations of the signals detected, and show that we can detect the merger several days prior to it occurring.

Publisher

Information Physics Institute

Reference22 articles.

1. LIGO Lab | Caltech. n.d. What are Gravitational Waves?. [online] Available at:

2. Abbott, B. et al. GW150914: First results from the search for binary black hole coalescence with Advanced LIGO. Physical Review D, 93(12).

3. Sci.esa.int. 2017. ESA Science & Technology - Gravitational wave mission selected, planet-hunting mission moves forward. [online] Available at: .

4. Science.nasa.gov. n.d. Black Holes | Science Mission Directorate. [online] Available at: https://science.nasa.gov/astrophysics/focus-areas/black-holes

5. Bozza, V., 2009. Gravitational Lensing by Black Holes. General Relativity and Gravitation, 42(9).

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