arXiv subjects

Mario Pasquato

Publications and source records attributed to Mario Pasquato.

At least 55 records · Page 3Linked to original sources

arXiv2020

Different Fates of Young Star Clusters After Gas Expulsion

We identify structures of the young star cluster NGC 2232 in the solar neighborhood (323.0 pc), and a newly discovered star cluster LP 2439 (289.1 pc). Member candidates are identified using the Gaia DR2 sky position, parallax and proper motion data, by an unsupervised machine learning method, \textsc{StarGO}. Member contamination from the Galactic disk is further removed using the color magnitude diagram. The four identified groups (NGC 2232, LP 2439 and two filamentary structures) of stars are coeval with an age of 25 Myr and were likely formed in the same giant molecular cloud. We correct the distance asymmetry from the parallax error with a Bayesian method. The 3D morphology shows the two spherical distributions of clusters NGC 2232 and LP 2439. Two filamentary structures are spatially and kinematically connected to NGC 2232. Both NGC 2232 and LP 2439 are expanding. The expansion is more significant in LP 2439, generating a loose spatial distribution with shallow volume number and mass density profiles. The expansion is suggested to be mainly driven by gas expulsion. NGC 2232, with 73~percent of the cluster mass bound, is currently experiencing a process of re-virialization, However, LP 2439, with 52 percent cluster mass being unbound, may fully dissolve in the near future. The different survivability traces different dynamical states of NGC 2232 and LP 2439 prior to the onset of gas expulsion. NGC 2232 may have been substructured and subvirial, while LP 2439 may either have been virial/supervirial, or it has experienced a much faster rate of gas removal.

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arXiv2020

Binary black holes in young star clusters: the impact of metallicity

Young star clusters are the most common birth-place of massive stars and are dynamically active environments. Here, we study the formation of black holes (BHs) and binary black holes (BBHs) in young star clusters, by means of 6000 N-body simulations coupled with binary population synthesis. We probe three different stellar metallicities (Z=0.02, 0.002 and 0.0002) and two initial density regimes (density at the half-mass radius $ρ_{\rm h}\ge{}3.4\times10^4$ and $\ge{1.5\times10^2}$ M$_\odot$ pc$^{-3}$ in dense and loose star clusters, respectively). Metal-poor clusters tend to form more massive BHs than metal-rich ones. We find $\sim{}6$, $\sim{}2$, and $<1$% of BHs with mass $m_{\rm BH}>60$ M$_\odot$ at Z=0.0002, 0.002 and 0.02, respectively. In metal-poor clusters, we form intermediate-mass BHs with mass up to $\sim{}320$ M$_\odot$. BBH mergers born via dynamical exchanges (exchanged BBHs) can be more massive than BBH mergers formed from binary evolution: the former (latter) reach total mass up to $\sim{}140$ M$_\odot$ ($\sim{}80$ M$_\odot$). The most massive BBH merger in our simulations has primary mass $\sim{}88$ M$_\odot$, inside the pair-instability mass gap, and a mass ratio of $\sim{}0.5$. Only BBHs born in young star clusters from metal-poor progenitors can match the masses of GW170729, the most massive event in O1 and O2, and those of GW190412, the first unequal-mass merger. We estimate a local BBH merger rate density $\sim{}110$ and $\sim{}55$ Gpc$^{-3}$ yr$^{-1}$, if we assume that all stars form in loose and dense star clusters, respectively.

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arXiv2020

An astrophysically motivated ranking criterion for low-latency electromagnetic follow-up of gravitational wave events

We investigate the properties of the host galaxies of compact binary mergers across cosmic time. To this end, we combine population synthesis simulations together with galaxy catalogues from the hydrodynamical cosmological simulation EAGLE to derive the properties of the host galaxies of binary neutron star (BNS), black hole-neutron star (BHNS) and binary black hole (BBH) mergers. Within this framework, we derive the host galaxy probability, i.e., the probability that a galaxy hosts a compact binary coalescence as a function of its stellar mass, star formation rate, $K_s$ magnitude and $B$ magnitude. This quantity is particularly important for low-latency searches of gravitational wave (GW) sources as it provides a way to rank galaxies lying inside the credible region in the sky of a given GW detection, hence reducing the number of viable host candidates. Furthermore, even if no electromagnetic counterpart is detected, the proposed ranking criterion can still be used to classify the galaxies contained in the error box. Our results show that massive galaxies (or equivalently galaxies with a high luminosity in $K_s$ band) have a higher probability of hosting BNS, BHNS, and BBH mergers. We provide the probabilities in a suitable format to be implemented in future low-latency searches.

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arXiv2019

Mass and star formation rate of the host galaxies of compact binary mergers across cosmic time

We investigate the properties of the host galaxies of compact binary mergers across cosmic time, by means of population-synthesis simulations combined with galaxy catalogues from the EAGLE suite. We analyze the merger rate per galaxy of binary neutron stars (BNSs), black hole--neutron star binaries (BHNSs) and binary black holes (BBHs) from redshift zero up to redshift six. The binary merger rate per galaxy strongly correlates with the stellar mass of the host galaxy at any redshift considered here. This correlation is significantly steeper for BNSs than for both BHNSs and BBHs. Moreover, we find that the merger rate per galaxy depends also on host galaxy's star formation rate and metallicity. We derive a robust fitting formula that relates the merger rate per galaxy with galaxy's star formation rate, stellar mass and metallicity at different redshifts. The typical masses of the host galaxies increase significantly as redshift decreases, as a consequence of the interplay between delay time distribution of compact binaries and cosmic assembly of galaxies. Finally, we study the evolution of the merger rate density with redshift. At low redshift ($z\leq{}0.1$) early-type galaxies give a larger contribution to the merger rate density than late-type galaxies. This trend reverts at $z\ge{}1$.

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arXiv2019

Radial Dependence of the Proto-Globular Cluster Contribution to the Milky Way Formation

Recent interpretation of the color$-$magnitude diagrams of the Milky Way (MW) bulge has suggested that the observed double red-clump feature can be a natural consequence of He-enhanced stellar populations in the MW bulge. This implies that globular clusters (GCs), where the He-enhanced second-generation (SG) stars can be efficiently created, are the most likely candidate contributors of He-rich stars to the MW bulge. We extend this idea to the Galactic inner halo and investigate the fraction of the SG stars as a function of the Galactocentric distance. We use bluer blue-horizontal branch (bBHB) stars, which are assumed to be originated from He-rich SG populations, as proxies of SG stars, and find that the fraction of bBHB stars increases with decreasing Galactocentric distance. Simulations of the GC evolution in the MW tidal field qualitatively support the observed trend of bBHB enhancement in the inner halo. In these simulations, the increasing tidal force with decreasing Galactocentric distance leads to stripping of stars not only from the outskirts but also from the central regions of GCs, where SG stars are more abundant. We discuss the implication and prospect of our findings concerning the formation history of the bulge and inner halo of the MW.

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arXiv2019

Stellar-Mass Black Holes in Globular Clusters: Dynamical Consequences and Observational Signatures

Sizeable number of stellar-mass black holes (BHs) in globular clusters (GCs) can strongly influence the dynamical evolution and observational properties of their host cluster. Using results from a large set of numerical simulations, we identify the key ingredients needed to sustain a sizeable population of BHs in GCs up to a Hubble time. We find that while BH natal kick prescriptions are essential in determining the initial retention fraction of BHs in GCs, the long-term survival of BHs is determined by the size, initial central density and half-mass relaxation time of the GC. Simulated GC models that contain many BHs are characterized by relatively low central surface brightness, large half-light and core radii values. We also discuss novel ways to compare simulated results with available observational data to identify GCs that are most likely to contain many BHs.

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arXiv2019

Analytical solutions for the dynamical clock A+ indicator in a toy model of pure dynamical friction

Blue straggler stars are more massive than the average star in globular clusters, as they originate from the merger of two stars. Consequently, they experience dynamical friction, progressively sinking to the cluster center. Recently, several indicators of the degree of dynamical relaxation of a globular cluster have been proposed, based on the observed radial distribution of blue straggler stars. The most successful is the Alessandrini indicator, or A+ for short, which is the integral of the cumulative distribution of the blue straggler stars minus that of a lighter reference population. A+ correlates with the dynamical age of a cluster both in realistic simulations and in observations. Here I calculate the temporal dependence of the A+ indicator analytically in a simplified model of the evolution of the blue straggler star distribution under dynamical friction only.

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arXiv2019

Further properties of the dynamical clock A+ indicator in a toy model of pure dynamical friction

The Alessandrini A$+$ indicator is a quantitative measure of star cluster dynamical evolution based on the mass-segregation of blue straggler stars. A$+$ is defined as the integral of the cumulative distribution of blue straggler stars with the radius measured in logarithmic scale, minus a term related to the reference population used. In a companion paper I introduced a simplified model of dynamical friction and calculated the A$+$ indicator analytically. Here I show further properties of the time evolution of A$+$, focusing in particular on the physical interpretation of its time derivative $d{A^+}/dt$. I find that $d{A^+}/dt$ is the mean of the reciprocal dyamical friction timescale, weighted by the density of blue straggler stars. I show that it is non-negative (as expected based on monotonicity) due to the density of blue-straggler stars being non-negative and that, for a dynamical friction timescale that is non-decreasing with radius, $d{A^+}/dt$ is also non-decreasing with time, making the A$+$ indicator a convex function.

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arXiv2019

Multiple Stellar Populations in NGC 2808: a Case Study for Cluster Analysis

In the massive globular cluster NGC 2808, RGB stars form at least five distinct groups in the so-called chromosome map photometric plane, arguably corresponding to different stellar populations. While a human expert can separate the groups by eye relatively easily, algorithmic approaches are desirable for reproducibility and for handling a larger sample of globular clusters. Unfortunately, cluster analysis algorithms often produced unsatisfactory results. Here we apply a range of non-parametric clustering algorithms to the NGC 2808 RGB dataset: partitioning (k-means, Partitioning Around Medoids - PAM), hierarchical (AGglomerative NESting - AGNES, DIvisive ANAlysis - DIANA), and density based (Density-Based Spatial Clustering of Applications with Noise - DBSCAN, Ordering Points To Identify the Clustering Struture - OPTICS). For each algorithm we discuss different choices of the relevant hyperparameters and their impact on the resulting clustering. We find that AGNES produces results that are most similar to the expectations of a human expert, depending on the prescription used for joining adjacent groups - linkage. Among the linkage prescriptions we tested, Ward's method performs best, and average linkage obtains comparable results only if outliers are removed beforehand. We recommend using AGNES with Ward's method or similar linkages in future studies to automatically identify stellar populations in the chromosome map plane.

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arXiv2019

Finding Black Holes with Black Boxes -- Using Machine Learning to Identify Globular Clusters with Black Hole Subsystems

Machine learning is a powerful technique, becoming increasingly popular in astrophysics. In this paper, we apply machine learning to more than a thousand globular cluster (GC) models simulated as part of the 'MOCCA-Survey Database I' project in order to correlate present-day observable properties with the presence of a subsystem of stellar mass black holes (BHs). The machine learning model is then applied to available observed parameters for Galactic GCs to identify which of them that are most likely to be hosting a sizeable number of BHs and reveal insights into what properties lead to the formation of BH subsystems. With our machine learning model, we were able to shortlist 21 Galactic GCs that are most likely to contain a BH subsystem. We show that the clusters shortlisted by the machine learning classifier include those in which BH candidates have been observed (M22, M10 and NGC 3201) and that our results line up well with independent simulations and previous studies that manually compared simulated GC models with observed properties of Galactic GCs. These results can be useful for observers searching for elusive stellar mass BH candidates in GCs and further our understanding of the role BHs play in GC evolution. In addition, we have released an online tool that allows one to get predictions from our model after they input observable properties.

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arXiv2019

Clustering clusters: unsupervised machine learning on globular cluster structural parameters

Globular Clusters (GCs) have historically been subdivided in either two (disk/halo) or three (disk/inner-halo/outer-halo) groups based on their orbital, chemical and internal physical properties. The qualitative nature of this subdivision makes it impossible to determine whether the natural number of groups is actually two, three, or more. In this paper we use cluster analysis on the $(\log M, \log σ_0, \log R_e, [Fe/H], \log | Z |)$ space to show that the intrinsic number of GC groups is actually either $k=2$ or $k=3$, with the latter being favored albeit non-significantly. In the $k=2$ case, the Partitioning Around Medoids (PAM) clustering algorithm recovers a metal-poor halo GC group and a metal-rich disk GC group. With $k=3$ the three groups can be interpreted as disk/inner-halo/outer-halo families. For each group we obtain a medoid, i.e. a representative element (NGC $6352$, NGC $5986$, and NGC $5466$ for the disk, inner halo, and outer halo respectively), and a measure of how strongly each GC is associated to its group, the so-called silhouette width. Using the latter, we find a correlation with age for both disk and outer halo GCs where the stronger the association of a GC with the disk (outer halo) group, the younger (older) it is.

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arXiv2019

Merging black holes in young star clusters

Searching for distinctive signatures, which characterize different formation channels of binary black holes (BBHs), is a crucial step towards the interpretation of current and future gravitational wave detections. Here, we investigate the demography of merging BBHs in young star clusters (SCs), which are the nursery of massive stars. We performed $4\times{} 10^3$ N-body simulations of SCs with metallicity $Z=0.002$, initial binary fraction $0.4$ and fractal initial conditions, to mimic the clumpiness of star forming regions. Our simulations include a novel population-synthesis approach based on the code MOBSE. We find that SC dynamics does not affect the merger rate significantly, but leaves a strong fingerprint on the properties of merging BBHs. More than 50 % of merging BBHs in young SCs form by dynamical exchanges in the first few Myr. Dynamically formed merging BBHs are significantly heavier than merging BBHs in isolated binaries: merging BBHs with total mass up to $\sim{}120$ M$_\odot$ form in young SCs, while the maximum total mass of merging BBHs in isolated binaries with the same metallicity is only $\sim{}70$ M$_\odot$. Merging BBHs born via dynamical exchanges tend to have smaller mass ratios than BBHs in isolated binaries. Furthermore, SC dynamics speeds up the merger: the delay time between star formation and coalescence is significantly shorter in young SCs. In our simulations, massive systems such as GW170729 form only via dynamical exchanges. Finally $\sim{}2$ % of merging BBHs in young SCs have mass in the pair-instability mass gap ($\sim{}60-120$ M$_\odot$). This represents a unique fingerprint of merging BBHs in SCs.

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arXiv2018

Blue Straggler Bimodality: a Brownian Motion Model

The shape of the radial distribution of Blue Straggler Stars (BSS), when normalized to a reference population of Horizontal Branch (HB) stars, has been found to be a powerful indicator of the dynamical evolution reached by a Globular Cluster (GC). In particular, observations suggest that the BSS distribution bimodality is modulated by the dynamical age of the host GC, with dynamically unrelaxed GCs showing a flat BSS distribution, and more relaxed GCs showing a minimum at a radius that increases for increasing dynamical age, resulting in a natural dynamical clock. While direct N-body simulations are able to reproduce the general trend, thus supporting its dynamical origin, the migration of the minimum of the distribution appears to be noisy and not well defined. Here we show that a simple unidimensional model based on dynamical friction (drift) and Brownian motion (diffusion) correctly reproduces the qualitative motion of the minimum, without adjustable parameters except for the BSS to HB stars mass-ratio. Differential dynamical friction effects combine with diffusion in creating a bimodality in the BSS distribution and determining its evolution, driving the migration of the minimum to larger radii over time. The diffusion coefficient is strongly constrained by the need to reproduce the migratory behaviour of the minimum, and the radial dependence of diffusion set by fundamental physical arguments automatically satisfies this constraint. Therefore, our model appears to capture the fluctuation-dissipation dynamics that underpins the dynamical clock.

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arXiv2018

Weighing the IMBH candidate CO-0.40-0.22* in the Galactic Centre

The high velocity gradient observed in the compact cloud CO-0.40-0.22, at a projected distance of 60 pc from the centre of the Milky Way, has led its discoverers to identify the closeby mm continuum emitter, CO-0.40-0.22*, with an intermediate mass black hole (IMBH) candidate. We describe the interaction between CO-0.40-0.22 and the IMBH, by means of a simple analytical model and of hydrodynamical simulations. Through such calculation, we obtain a lower limit to the mass of CO-0.40-0.22* of few $10^4 \times \; M_{\odot}$. This result tends to exclude the formation of such massive black hole in the proximity of the Galactic Centre. On the other hand, CO-0.40-0.22* might have been brought to such distances in cosmological timescales, if it was born in a dark matter halo or globular cluster around the Milky Way.

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arXiv2016

Reversed radial distribution trend of subpopulations in the globular clusters NGC 362 and NGC 6723

Most globular clusters (GCs) are now known to host multiple stellar populations with different light element abundances. Here we use narrow-band photometry and low-resolution spectroscopy for NGC 362 and NGC 6723 to investigate their chemical properties and radial distributions of subpopulations. We confirm that NGC 362 and NGC 6723 are among the GCs with multiple populations showing bimodal CN distribution and CN-CH anti-correlation without a significant spread in calcium abundance. These two GCs show more centrally concentrated CN-weak earlier generation stars compared to the later generation CN-strong stars. These trends are reversed with respect to those found in previous studies for many other GCs. Our findings, therefore, seem contradictory to the current scenario for the formation of multiple stellar populations, but mass segregation acting on the two subpopulations might be a possible solution to explain this reversed radial trend.

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arXiv2016

Detecting intermediate mass black holes in globular clusters with machine learning

Mergers of stellar-mass black holes were recently observed in the gravitational wave window opened by LIGO. This puts the spotlight on dense stellar systems and their ability to create intermediate-mass black holes (IMBHs) through repeated merging. Unfortunately, attempts at direct and indirect IMBH detection in star clusters in the nearby universe have proven inconclusive as of now. Indirect detection methods attempt to constrain IMBHs through their effect on star cluster photometric and kinematic observables. They are usually based on looking for a specific, physically motivated signature. While this approach is justified, it may be suboptimal in its usage of the available data. Here I present a new indirect detection method, based on machine learning, that is unaffected by these restrictions. I reduce the scientific question whether a star cluster hosts an IMBH to a classification problem in the machine learning framework. I present preliminary results to illustrate how machine learning models are trained on simulated datasets and measure their performance on previously unseen, simulated data.

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arXiv2016

Globular clusters hosting intermediate-mass black-holes: no mass-segregation based candidates

Recently, both stellar mass-segregation and binary-fractions were uniformly measured on relatively large samples of Galactic Globular Clusters (GCs). Simulations show that both sizeable binary-star populations and Intermediate-Mass Black Holes (IMBHs) quench mass-segregation in relaxed GCs. Thus mass-segregation in GCs with a reliable binary-fraction measurement is a valuable probe to constrain IMBHs. In this paper we combine mass-segregation and binary-fraction measurements from the literature to build a sample of 33 GCs (with measured core-binary fractions), and a sample of 43 GCs (with a binary fraction measurement in the area between the core radius and the half-mass radius). Within both samples we try to identify IMBH-host candidates. These should have relatively low mass-segregation, a low binary fraction (< 5%), and short (< 1 Gyr) relaxation time. Considering the core binary fraction sample, no suitable candidates emerge. If the binary fraction between the core and the half-mass radius is considered, two candidates are found, but this is likely due to statistical fluctuations. We also consider a larger sample of 54 GCs where we obtained an estimate of the core binary fraction using a predictive relation based on metallicity and integrated absolute magnitude. Also in this case no suitable candidates are found. Finally, we consider the GC core- to half-mass radius ratio, that is expected to be larger for GCs containing either an IMBH or binaries. We find that GCs with large core- to half-mass radius ratios are less mass-segregated (and show a larger binary fraction), confirming the theoretical expectation that the energy sources responsible for the large core are also quenching mass-segregation

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arXiv2016

Merged or monolithic? Using machine-learning to reconstruct the dynamical history of simulated star clusters

Context. Machine-Learning (ML) solves problems by learning patterns from data, with limited or no human guidance. In Astronomy, it is mainly applied to large observational datasets, e.g. for morphological galaxy classification. Aims. We apply ML to gravitational N-body simulations of star clusters that are either formed by merging two progenitors or evolved in isolation, planning to later identify Globular Clusters (GCs) that may have a history of merging from observational data. Methods. We create mock-observations from simulated GCs, from which we measure a set of parameters (also called features in the machine-learning field). After dimensionality reduction on the feature space, the resulting datapoints are fed to various classification algorithms. Using repeated random subsampling validation we check whether the groups identified by the algorithms correspond to the underlying physical distinction between mergers and monolithically evolved simulations. Results. The three algorithms we considered (C5.0 trees, k-nearest neighbour, and support-vector machines) all achieve a test misclassification rate of about 10% without parameter tuning, with support-vector machines slightly outperforming the others. The first principal component of feature space correlates with cluster concentration. If we exclude it from the regression, the performance of the algorithms is only slightly reduced.

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