Periodic Reporting for period 1 - DEMOBLACK (Demography of black hole binaries in the era of gravitational wave astronomy)
Reporting period: 2018-11-01 to 2020-04-30
DEMOBLACK aims to address this question by means of innovative numerical models. We will study two main scenarios: the formation of binary black holes via isolated binary evolution and their possible dynamical formation in star clusters. Reconstructing the formation pathways of binary black holes is one of the most urgent steps to take if we want to interpret gravitational-wave observations. To achieve this long-term goal, DEMOBLACK will
i) develop a novel approach to population-synthesis simulations of binary evolution;
ii) perform hydrodynamical and N-body simulations of star clusters with realistic initial conditions and advanced population-synthesis calculations;
iii) investigate the evolution of binary black holes across cosmic time;
iv) use a new Bayesian inference framework to predict the distribution of masses, spins, eccentricities and merger rates of gravitational-wave sources observed by LIGO and Virgo at design sensitivity and by future gravitational-wave detectors (Einstein Telescope and Cosmic Explorer).
– We have completed the development of the new version of the SEVN code with binary star evolution processes. The new code has been successfully used for an innovative study of binary black hole demography from isolated binaries (Spera et al. 2019, MNRAS).
– We have included rotating stellar models in SEVN and we have studied their impact on the maximum mass of black holes from single stellar evolution (Mapelli et al. 2020, ApJ, in press).
– We have explored a new prescription for the outcome of core-collapse supernova explosions in our population-synthesis code SEVN (Mapelli et al. 2020, ApJ, in press).
– We have implemented new prescriptions for natal kicks. The new prescriptions allow us to recover the merger-rate density of binary compact objects inferred from LIGO-Virgo data and are consistent with the proper motions of Galactic binary pulsars (Giacobbo & Mapelli, ApJ, submitted)
1b. Hydrodynamical simulations:
– We have run a large set of hydrodynamical simulations to produce realistic initial conditions for the dynamical simulations (Ballone et al., MNRAS, submitted)
WORK-PACKAGE 2: Stellar dynamics
– We have performed a coupling between the direct N-body code nbody6++GPU and our population-synthesis code MOBSE (we are currently working to perform a similar implementation for SEVN). The implementation has been presented in Di Carlo et al. (2019a).
– With the new code, we have performed the largest set of direct N-body simulations with population synthesis ever performed to study binary black holes: >7000 simulations of massive young star clusters and >75’000 simulations of small young star clusters. We have found that star cluster dynamics has a crucial impact on the mass function of binary black holes. This study has led to one peer-reviewed publication (Di Carlo et al. 2019a). Two additional publications are in preparation (Rastello et al, Di Carlo et al).
– With the new code we have discovered a new possible formation channel for binary black holes in the pair instability mass gap (Di Carlo et al. 2019b, submitted).
WORK-PACKAGE 3: Cosmological context
1a. Cosmological simulations
– We have developed a numerical model that couples binary black hole catalogues from population synthesis with the Illustris and the EAGLE cosmological simulations. The new model is a powerful tool to estimate the merger rate density as a function of time and to predict the properties of host galaxies. With this code,
– we have investigated the properties of binary compact objects across cosmic time (Mapelli et al. 2019, MNRAS);
– we have estimated the cosmic merger rate evolution in early-type and late-type galaxies (Artale et al. 2019a, MNRAS; Artale et al. 2019b, MNRAS, in press);
– we have done a preliminary characterization of the host galaxies across cosmic time (Toffano et al. 2019, MNRAS; Artale et al. 2019b, MNRAS, in press). This study is important for low-latency search and for ranking the possible host galaxies in the uncertainty box of gravitational-wave detectors.
1b. Data-driven model
– We developed a new data-driven code to estimate cosmic merger rate evolution in a very fast way (Baibhav et al. 2019; Santoliquido et al., in preparation). This fast model allows us to efficiently scan the full parameter space.
WORK-PACKAGE 4: Learning from observations
– We have developed a new hierarchical Bayesian inference tool to i) convert the results of our models into mock gravitational-wave events; ii) calculate the Bayesian odds ratios for different models; iii) calculate the mixture fraction assuming that part of the observed events are dynamical and part are isolated.
The final goal of this new tool is to infer from LIGO-Virgo data the fraction of events that have dynamical vs isolated origin.
– In Bouffanais et al. 2019, we have first tested the Bayesian inference tool on the dynamical simulations by Di Carlo et al. (2019a).
a) MASS OF BLACK HOLES:
– We predict that the mass of a black hole strongly depends on the equatorial rotation of its progenitor star (Mapelli et al. 2020).
– We highlight the dramatic impact of the hydrogen envelope on the final mass of a black hole. Black holes with mass > 40 Msun can form from massive slow-rotating metal-poor single stars only if a large fraction of their residual hydrogen envelope is allowed to collapse.
– In Di Carlo et al. (2019a) and Bouffanais et al. (2019), we demonstrated that dynamics in young star clusters plays a major role to shape the mass function of binary black holes. This will enable us to differentiate between dynamical and isolated formation channel by the end of the project.
– In Di Carlo et al. (2019a, 2019b), we predicted the formation, via stellar mergers, of black holes in the pair instability mass gap. Observing such black holes would be an exquisite proof of the dynamical formation channel.
b) REDSHIFT EVOLUTION:
– Mapelli et al. (2019) predict very mild evolution of black hole mass with redshift, because of an interplay between the mass spectrum of binary black holes and the delay time distribution.
c) HOST GALAXIES:
Artale et al. (2019a, 2019b) show that the merger rate density per galaxy correlates with the mass of the host galaxy. We also find a correlation with the star formation rate and the metallicity, but these correlations are much weaker. This result has crucial implications for the identification of host galaxies of gravitational-wave events, because it means that massive galaxies have a higher probability to host a gravitational-wave event than dwarf galaxies.
d) INNOVATIVE CODES FOR ASTROPHYSICS:
Our codes (SEVN and MOBSE, the algorithm to generate initial conditions for dynamical simulations and the tool for Bayesian inference) provide a new approach to computational astrophysics.