scholarly journals Formation of the First Two Black Hole–Neutron Star Mergers (GW200115 and GW200105) from Isolated Binary Evolution

2021 ◽  
Vol 920 (1) ◽  
pp. L13
Author(s):  
Floor S. Broekgaarden ◽  
Edo Berger
2000 ◽  
Vol 15 (30) ◽  
pp. 4871-4875 ◽  
Author(s):  
SIMON F. PORTEGIES ZWART ◽  
STEPHEN L. W. MCMILLAN

Black holes become the most massive objects early in the evolution of star clusters. Dynamical relaxation then causes them to sink to the cluster core, where they form binaries which become more tightly bound by superelastic encounters with other cluster members. Ultimately, these binaries are ejected from the cluster. The majority of escaping black-hole binaries have orbital periods short enough and eccentricities high enough that the emission of gravitational waves causes them to coalesce within a few billion years. The rate at which such collisions occur is on the order of 10-7 per year per cubic megaparsec. This implies event rates for gravitational-wave detectors substantially greater than current estimates of the corresponding rates from neutron-star mergers or black-hole mergers stemming from pure binary evolution.


Author(s):  
Filippo Santoliquido ◽  
Michela Mapelli ◽  
Nicola Giacobbo ◽  
Yann Bouffanais ◽  
M Celeste Artale

Abstract We evaluate the redshift distribution of binary black hole (BBH), black hole – neutron star binary (BHNS) and binary neutron star (BNS) mergers, exploring the main sources of uncertainty: star formation rate (SFR) density, metallicity evolution, common envelope, mass transfer via Roche lobe overflow, natal kicks, core-collapse supernova model and initial mass function. Among binary evolution processes, uncertainties on common envelope ejection have a major impact: the local merger rate density of BNSs varies from ∼103 to ∼20 Gpc−3 yr−1 if we change the common envelope efficiency parameter from αCE = 7 to 0.5, while the local merger rates of BBHs and BHNSs vary by a factor of ∼2 − 3. The BBH merger rate changes by one order of magnitude, when 1σ uncertainties on metallicity evolution are taken into account. In contrast, the BNS merger rate is almost insensitive to metallicity. Hence, BNSs are the ideal test bed to put constraints on uncertain binary evolution processes, such as common envelope and natal kicks. Only models assuming values of αCE ≳ 2 and moderately low natal kicks (depending on the ejected mass and the SN mechanism), result in a local BNS merger rate density within the 90% credible interval inferred from the second gravitational-wave transient catalogue.


2021 ◽  
Vol 502 (1) ◽  
pp. L72-L78
Author(s):  
K Mohamed ◽  
E Sonbas ◽  
K S Dhuga ◽  
E Göğüş ◽  
A Tuncer ◽  
...  

ABSTRACT Similar to black hole X-ray binary transients, hysteresis-like state transitions are also seen in some neutron-star X-ray binaries. Using a method based on wavelets and light curves constructed from archival Rossi X-ray Timing Explorer observations, we extract a minimal timescale over the complete range of transitions for 4U 1608-52 during the 2002 and 2007 outbursts and the 1999 and 2000 outbursts for Aql X-1. We present evidence for a strong positive correlation between this minimal timescale and a similar timescale extracted from the corresponding power spectra of these sources.


2021 ◽  
Vol 103 (6) ◽  
Author(s):  
Francois Foucart ◽  
Alexander Chernoglazov ◽  
Michael Boyle ◽  
Tanja Hinderer ◽  
Max Miller ◽  
...  

Author(s):  
R Pattnaik ◽  
K Sharma ◽  
K Alabarta ◽  
D Altamirano ◽  
M Chakraborty ◽  
...  

Abstract Low Mass X-ray binaries (LMXBs) are binary systems where one of the components is either a black hole or a neutron star and the other is a less massive star. It is challenging to unambiguously determine whether a LMXB hosts a black hole or a neutron star. In the last few decades, multiple observational works have tried, with different levels of success, to address this problem. In this paper, we explore the use of machine learning to tackle this observational challenge. We train a random forest classifier to identify the type of compact object using the energy spectrum in the energy range 5-25 keV obtained from the Rossi X-ray Timing Explorer archive. We report an average accuracy of 87±13% in classifying the spectra of LMXB sources. We further use the trained model for predicting the classes for LMXB systems with unknown or ambiguous classification. With the ever-increasing volume of astronomical data in the X-ray domain from present and upcoming missions (e.g., SWIFT, XMM-Newton, XARM, ATHENA, NICER), such methods can be extremely useful for faster and robust classification of X-ray sources and can also be deployed as part of the data reduction pipeline.


2015 ◽  
Vol 115 (23) ◽  
Author(s):  
Chris L. Fryer ◽  
F. G. Oliveira ◽  
J. A. Rueda ◽  
R. Ruffini

2021 ◽  
Vol 103 (12) ◽  
Author(s):  
Andreas Bauswein ◽  
Sebastian Blacker ◽  
Georgios Lioutas ◽  
Theodoros Soultanis ◽  
Vimal Vijayan ◽  
...  

2008 ◽  
Author(s):  
Masaru Shibata ◽  
Keisuke Taniguchi ◽  
Koji Uryū ◽  
Ye-Fei Yuan ◽  
Xiang-Dong Li ◽  
...  

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