Context.Identifying black holes is essential for our understanding of the development of stars and can reveal novel principles of physics. Gravitational microlensing provides an exceptional opportunity to examine an undetectable population of black holes in the Milky Way. In particular, long-lasting events are likely to be associated with massive lenses, including black holes. Aims.We present an analysis of the Gaia18ajz microlensing event reported by the Gaia Science Alerts system. Gaia18ajz is a long-timescale event exhibiting features indicative of the annual microlensing parallax effect. Our objective is to estimate its lens parameters based on the best-fitting model. Methods.We used photometric data obtained from the Gaia satellite and terrestrial observatories to investigate a variety of microlensing models and calculate the most probable mass and distance to the lens, taking into consideration a Galactic model as a prior. Subsequently, we applied a mass–brightness relation to evaluate the likelihood that the lens is a main sequence star. We also describe theDarkLensCode(DLC), an open-source routine that computes the distribution of probable lens mass, distance, and luminosity employing the Galaxy priors on stellar density and velocity for microlensing events with detected microlensing parallax. Results.We modelled the Gaia18ajz event and found its two possible models, the most probable Einstein timescales for which are 316−30+36days and 299−22+25days. Applying Galaxy priors for stellar density and motion, we calculated a most probable lens mass of 4.9−2.3+5.4 M⊙located at 1.14−0.57+0.75 kpc, and a less probably mass of 11.1−4.7+10.3 M⊙located at 1.31−0.60+0.80 kpc. Our analysis of the blended light suggests that the lens is likely a dark remnant of stellar evolution rather than a main sequence star.
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Physical Models for the Astrophysical Population of Black Holes: Application to the Bump in the Mass Distribution of Gravitational-wave Sources
Abstract Gravitational-wave observations of binary black holes have revealed unexpected structure in the black hole mass distribution. Previous studies employ physically motivated phenomenological models and infer the parameters that control the features of the mass distribution that are allowed in their model, associating the constraints on those parameters with their physical motivations a posteriori. In this work, we take an alternative approach in which we introduce a model parameterizing the underlying stellar and core-collapse physics and obtaining the remnant black hole distribution as a derived by-product. In doing so, we constrain the stellar physics necessary to explain the astrophysical distribution of black hole properties under a given model. We apply this to the mapping between initial mass and remnant black hole mass, accounting for mass-dependent mass loss using a simple parameterized description. Allowing the parameters of the initial mass–remnant mass relationship to evolve with redshift permits correlated and physically reasonable changes to features in the mass function. We find that the current data are consistent with no redshift evolution in the core–remnant mass relationship, but place only weak constraints on the change of these parameters. This procedure can be applied to modeling any physical process underlying the astrophysical distribution. We illustrate this by applying our model to the pulsational pair instability supernova (PPISN) process, previously proposed as an explanation for the observed excess of black holes at ∼35M⊙. Placing constraints on the reaction rates necessary to explain the PPISN parameters, we concur with previous results in the literature that the peak observed at ∼35M⊙is unlikely to be a signature from the PPISN process as presently understood.
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- Award ID(s):
- 2207758
- PAR ID:
- 10555478
- Publisher / Repository:
- DOI PREFIX: 10.3847
- Date Published:
- Journal Name:
- The Astrophysical Journal
- Volume:
- 976
- Issue:
- 1
- ISSN:
- 0004-637X
- Format(s):
- Medium: X Size: Article No. 121
- Size(s):
- Article No. 121
- Sponsoring Org:
- National Science Foundation
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