Abstract

We present the FastEMRIWaveforms (FEW) package, a collection of tools to build and analyze extreme mass ratio inspiral (EMRI) waveforms. Here, we expand on the Physical Review Letter that introduced the first fast and accurate fully-relativistic EMRI waveform template model. We discuss the construction of the overall framework; constituent modules; and the general methods used to accelerate EMRI waveforms. Because the fully relativistic FEW model waveforms are for now limited to eccentric orbits in the Schwarzschild spacetime, we also introduce an improved Augmented Analytic Kludge (AAK) model that describes generic Kerr inspirals. Both waveform models can be accelerated using graphics processing unit (GPU) hardware. With the GPU-accelerated waveforms in hand, a variety of studies are performed including an analysis of EMRI mode content, template mismatch, and fully Bayesian Markov Chain Monte Carlo-based EMRI parameter estimation. We find relativistic EMRI waveform templates can be generated with fewer harmonic modes ($\sim10-100$) without biasing signal extraction. However, we show for the first time that extraction of a relativistic injection with semi-relativistic amplitudes can lead to strong bias and anomalous structure in the posterior distribution for certain regions of parameter space.

Highlights

  • Gravitational wave observations from ground-based detectors are providing many new insights into the relativistic universe [1,2]

  • With the graphics processing unit (GPU)-accelerated waveforms in hand, a variety of studies are performed including an analysis of extreme mass ratio inspiral (EMRI) mode content, template mismatch, and fully Bayesian Markov Chain Monte Carlo-based EMRI parameter estimation

  • We find relativistic EMRI waveform templates can be generated with fewer harmonic modes (∼10–100) without biasing signal extraction

Read more

Summary

INTRODUCTION

Gravitational wave observations from ground-based detectors are providing many new insights into the relativistic universe [1,2]. Extracting this wealth of information from the LISA data stream will be a challenging task for two key reasons: (i) we require the waveform templates to have a phase error ΔΦ ≲ 1=ρ; this can be as small as ΔΦ ≲ 1=100 for a loud EMRI [20], and (ii) in order to search across the large parameter space we need waveforms that can be generated in less than a second These two requirements have led to the development of two classes of EMRI models: gravitational self-force models for accuracy and “kludge” models for speed. Our first fully relativistic EMRI waveform model is for nonrotating black holes but our modular computational framework is set up for generic inspirals To showcase this we add the augmented analytic kludge (AAK) to the framework with an updated 5PN inspiral model and GPU acceleration.

EMRI WAVEFORM OVERVIEW
Generating detector-frame waveforms for data analysis
FAST EMRI WAVEFORMS FRAMEWORK
Fast trajectory module
Amplitude module
Waveform summation module
Utility modules
Overall code design
ADIABATIC SCHWARZSCHILD ECCENTRIC WAVEFORMS
Flux-driven trajectories
RomanNet amplitude generation
Slow reference waveform
AN IMPROVED AUGMENTED ANALYTIC KLUDGE
GRAVITATIONAL WAVE ANALYSIS
Harmonic mode analysis
Mismatch analysis
Waveform timing
Intrinsic posterior analysis
DISCUSSION AND FUTURE
Improvements to the phase accuracy of the models
Signal and data analysis
VIII. CONCLUSION
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call