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This content will become publicly available on May 28, 2026

Title: Properties of “Lite” Intermediate-mass Black Hole Candidates in LIGO-Virgo’s Third Observing Run
Abstract Over a hundred gravitational-wave (GW) detections and candidates have been reported from the first three observing runs of the Advanced LIGO-Virgo-KAGRA (LVK) detectors. Among these, the most intriguing events are binary black hole mergers that result in a “lite” intermediate-mass black hole (IMBH) of ∼102M, such as GW170502 and GW190521. In this study, we investigate 11 GW candidates from LVK’s third observing run with total detector-frame masses in the lite IMBH range. Using the Bayesian inference algorithmRIFT, we systematically analyze these candidates with three state-of-the-art waveform models that incorporate higher harmonics, which are crucial for resolving lite IMBHs in LVK data. For each candidate, we infer the premerger and postmerger black hole masses in the source frame, along with black hole spin projections across all three models. Under the assumption that these are binary black hole mergers, our analysis finds that five have a postmerger lite IMBH with masses ranging from 110 to 350Mwith over 90% confidence interval. Additionally, we note that one of their premerger black holes is within the pair-instability supernova mass gap (60–120M), and two premerger black holes are above the mass gap. Furthermore, we report discrepancies among the three waveform models in intrinsic parameters, with at least three GW candidates showing deviations beyond accepted statistical limits. While the astrophysical certainty of these candidates cannot be established, our study provides a foundation to probe the lite IMBH population that emerge within the low-frequency noise spectrum of LVK detectors.  more » « less
Award ID(s):
2012057
PAR ID:
10615788
Author(s) / Creator(s):
; ; ; ; ; ; ;
Publisher / Repository:
American Astronomical Society
Date Published:
Journal Name:
The Astrophysical Journal Letters
Volume:
985
Issue:
2
ISSN:
2041-8205
Page Range / eLocation ID:
L37
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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