Evidence for eccentricity in the population of binary black holes observed by LIGO-Virgo-KAGRA (2404.14286v2)

Abstract: Binary black holes (BBHs) in eccentric orbits produce distinct modulations the emitted gravitational waves (GWs). The measurement of orbital eccentricity can provide robust evidence for dynamical binary formation channels. We analyze 57 GW events from the first, second and third observing runs of the LIGO-Virgo-KAGRA (LVK) Collaboration using a multipolar aligned-spin inspiral-merger-ringdown waveform model with two eccentric parameters: eccentricity and relativistic anomaly. This is made computationally feasible with the machine-learning code DINGO which accelerates inference by 2-3 orders of magnitude compared to traditional inference. First, we find eccentric aligned-spin versus quasi-circular aligned-spin $\log_{10}$ Bayes factors of 1.84 to 4.75 (depending on the glitch mitigation) for GW200129, 3.0 for GW190701 and 1.77 for GW200208_22. We measure $e_{\text{gw}, 10Hz}$ to be $0.27_{-0.12}^{+0.10}$ to $0.17_{-0.13}^{+0.14}$ for GW200129, $0.35_{-0.11}^{+0.32}$ for GW190701 and $0.35_{-0.21}^{+0.18}$ for GW200208_22. Second, we find $\log_{10}$ Bayes factors between the eccentric aligned-spin versus quasi-circular precessing-spin hypothesis between 1.43 and 4.92 for GW200129, 2.61 for GW190701 and 1.23 for GW200208_22. Third, our analysis does not show evidence for eccentricity in GW190521, which has an eccentric aligned-spin against quasi-circular aligned-spin $\log_{10}$ Bayes factor of 0.04. Fourth, we estimate that if we neglect the spin-precession and use an astrophysical prior, the probability of one out of the 57 events being eccentric is greater than 99.5% or $(100 - 8.4 \times 10^{-4})$% (depending on the glitch mitigation). Fifth, we study the impact on parameter estimation when neglecting either eccentricity or higher modes in eccentric models. These results underscore the importance of including eccentric parameters in the characterization of BBHs for GW detectors.

• The paper presents evidence for orbital eccentricity in binary black hole mergers via advanced waveform models and machine-learning techniques.
• It uses the DINGO technique on 57 GW events to highlight eccentricity in specific cases like GW200129 and GW190701.
• The study underscores the role of robust data cleaning and model selection in understanding black hole formation channels.

Analysis of Eccentricity in the Population of Binary Black Holes Observed by LIGO-Virgo-KAGRA

The paper "Evidence for eccentricity in the population of binary black holes observed by LIGO-Virgo-KAGRA" by Gupte et al. presents an investigation into the evidence of eccentric orbital motion within binary black holes (BBHs). Utilizing gravitational wave (GW) data from the LIGO-Virgo-KAGRA (LVK) collaboration, the paper employs a multipolar aligned-spin inspiral-merger-ringdown waveform model, SEOBNRv4EHM, to explore the presence of eccentricity across observed events.

Overview

The ability to detect and measure the orbital eccentricity in BBHs offers critical insights into their formation channels, distinguishing between isolated vs. dynamical interactions in dense stellar environments. The paper analyzes 57 GW events from the LVK’s first three observing runs, leveraging the SEOBNRv4EHM model to sample on both the eccentricity and relativistic anomaly, parameters not traditionally included in earlier waveform analyses.

Methodology

To analyze the detection data efficiently, the paper applies DINGO, a machine-learning technique that significantly speeds up the inference process. This approach enables rapid computations that would otherwise require substantial time and computational resources. A uniform prior on initial orbital eccentricity is used, allowing the authors to infer parameters consistently across events.

Key Findings

1. Eccentricity in Binary Black Holes: Evidence for non-negligible orbital eccentricity is found particularly in events GW200129, GW190701, and GW200208_22. These events show log Bayes factors indicating preferential fitting towards models considering eccentric features.
2. Impact of Glitch Mitigation: Notably, the paper shows strong variations in inferred eccentricity due to different glitch mitigation techniques employed during analysis, emphasizing the importance of robust data cleaning methods in GW astronomy.
3. Comparison with Precession Models: Despite using an eccentric model, the paper examines whether precessional effects, which mimic eccentricity, could dominate the interpretation. With support for eccentric features persisting, the paper underscores the indispensability of including eccentric parameters in the analysis.
4. Parameter Biases: The research reveals biases in chirp mass and effective spin when eccentricity is neglected, illustrating the importance of including these parameters when estimating the source properties of BBH mergers.

Implications

The implications of these findings are manifold. Eccentricity detection in BBH mergers can potentially reveal significant insights about their dynamical environments and improve our understanding of stellar interactions in dense clusters. Furthermore, the identification of eccentric features in GW signals emphasizes the necessity for advanced waveform models in the ongoing advancement of GW astronomy.

Future Directions

The paper paves the way for several avenues of future research. Enhanced models that incorporate both precessional and eccentric effects will be essential for more precise characterizations. Additionally, the integration of these models into real-time GW data analysis pipelines could improve the accuracy of BBH parameter estimations and enrich our comprehension of the underlying astrophysical processes.

In conclusion, the paper highlights the need for meticulous model selection and data handling in GW observations, advocating for the systematic inclusion of eccentric parameters in BBH investigations to refine the characterization of their formation and evolution.