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On Neutron Star Mergers As the Source of R-Process-Enhanced Metal-Poor Stars in the Milky Way

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On Neutron Star Mergers As the Source of R-Process-Enhanced Metal-Poor Stars in the Milky Way The Astrophysical Journal, 876:28 (10pp), 2019 May 1 https://doi.org/10.3847/1538-4357/ab1341 © 2019. The American Astronomical Society. All rights reserved. On Neutron Star Mergers as the Source of r-process-enhanced Metal-poor Stars in the Milky Way Mohammadtaher Safarzadeh , Richard Sarmento , and Evan Scannapieco School of Earth and Space Exploration, Arizona State University, USA Received 2018 October 5; revised 2019 March 22; accepted 2019 March 24; published 2019 April 30 Abstract We model the history of Galactic r-process enrichment using high-redshift, high-resolution zoom cosmological simulations of a Milky Way–type halo. We assume that all r-process sources are neutron star mergers (NSMs) with a power-law delay time distribution. We model the time to mix pollutants at subgrid scales, which allows us to better compute the properties of metal-poor (MP) and carbon-enhanced metal-poor (CEMP) stars, along with statistics of their r-process-enhanced subclasses. Our simulations underpredict the cumulative ratios of r-process- enhanced MP and CEMP stars (MP-r, CEMP-r) over MP and CEMP stars by about one order of magnitude, even when the minimum coalescence time of the double neutron stars (DNSs), tmin, is set to 1 Myr. No r-process- enhanced stars form if tmin=100 Myr. Our results show that even when we adopt the r-processyield estimates observed in GW170817, NSMs by themselves can only explain the observed frequency of r-process-enhanced -4 -1 stars if the birth rate of DNSs per unit mass of stars is boosted to »10 M . Key words: Galaxy: abundances – stars: neutron 1. Introduction rstars in the MW’s halo (Barklem et al. 2005; Abate et al. 2016). The recent aLIGO/aVirgo detection of gravitational waves In fact, the very existence of CEMP-rstars poses new from the merger of two neutron stars (GW170817; Abbott et al. challenges for the origin of r-processelements in the early 2017a) and the subsequent kilonova observed across the entire universe. These stars are believed to form at high redshifts and electromagnetic spectrum (Abbott et al. 2017b; Coulter et al. in low-mass halos where Population III stars have polluted the 2017) has confirmed that r-processelements are made in halo with their carbon-rich ejecta. In such low-mass halos, for a copious amounts in neutron star mergers (NSMs; Abbott et al. ) CEMP-r star to form, an r-process source that acts on a 2017c; Kasen et al. 2017 . This discovery could be the sine qua timescale similar to Population III stars (i.e., ≈10 Myr) is non for showing that NSMs are the primary source of r- ( ) ( ) needed Ramirez-Ruiz et al. 2015 . process elements in the Milky Way MW; Côté et al. 2018b . Could the observed statistics of different classes of r- On the other hand, while it is clear that NSMs are one of the process-enhanced stars be explained by NSMs as the sole sources of r-process enrichment, it remains an open question source of r-processin the early universe? In this study, we whether they are the most important source. To address this address this question by carrying out a set of zoom question, several theoretical studies have modeled r-proces- cosmological simulations of an MW-type halo and modeling s enrichment of an MW-type halo and its ultrafaint dwarf NSMs as the sources of the r-processmaterial. We improve on ( ) ( ) UFD satellites by NSMs. Van de Voort et al. 2015 carried crucial aspects of previous such simulations on three fronts: (i) = out a zoom simulation of an MW-type halo to z 0 and modeling the coalescence timescales of double neutron stars ( concluded that NSM events can explain the observed r- (DNSs) as drawn from distributions motivated by population process/Fe) abundance ratios assuming that an r-process mass ( −2 synthesis analyses Fryer et al. 1998; Dominik et al. 2012; of 10 Me is ejected into the interstellar medium in each NSM Behroozi et al. 2014); (ii) identifying Population III stars by event. Shen et al. (2015) studied the sites of r-processproduc- following the evolution of pristine gas in each simulation cell tion by post-processing “Eris” zoom simulations and found that with a subgrid model of turbulent mixing that is crucial for r-processelements can be incorporated into stars at very early properly identifying Population III stars, whose ejecta are the times, a result that is insensitive to modest variations in the precursor to the formation of CEMP stars (Sarmento et al. delay distribution and merger rates. Separately, Safarzadeh & 2017; Naiman et al. 2018); and (iii) adopting a high dark matter Scannapieco (2017) studied r-processenrichment in the (DM) particle mass resolution in order to resolve halos where context of UFDs and concluded that natal kicks can affect the MP and CEMP stars form in the early universe. the r-processenhancement of subsequent stellar generations. The structure of this work is as follows. In Section 2 we In each of these studies, it is observations of metal-poor describe our method in detail. In Section 3 we present our (MP) and carbon-enhanced metal-poor (CEMP) stars that are results and compare them to observations of MW halo stars. In most constraining. Such stars encode a wealth of information Section 4 we discuss our results and conclusions. Throughout about the formation of the first stars in the universe (Beers & this paper, we adopt the Planck 2015 cosmological parameters ) Christlieb 2005; Frebel & Norris 2015 , and similarly their r- (Planck Collaboration et al. 2016), where ΩM=0.308, ( ) process-enhanced subclasses MP-r and CEMP-r provide ΩΛ=0.692, and Ωb=0.048 are total matter, vacuum, and insight into the earliest r-processsources. Therefore, a baryonic densities, respectively, in units of the critical density successful theory for the source of the r-processshould be ρc, h=0.678 is the Hubble constant in units of −1 −1 able to explain the observed statistics of MP-rand CEMP- 100 km s Mpc , σ8=0.82 is the variance of linear 1 The Astrophysical Journal, 876:28 (10pp), 2019 May 1 Safarzadeh, Sarmento, & Scannapieco −1 fluctuations on the 8 h Mpc scale, ns=0.968 is the tilt of the 2.2. Star Formation and Feedback primordial power spectrum, and Y =0.24 is the primordial He The stellar particle mass in the simulation is helium fraction. =Dr 3 Δ mxN* th min , where xmin is the best resolution cell size achievable and N is drawn from a Poisson distribution 2. Method N¯ ( ) PN()=-exp( N¯ )() , 2 We used RAMSES Teyssier 2002 , a cosmological adaptive N! mesh refinement code, which implements an unsplit second- order Godunov scheme for evolving the Euler equations. where RAMSES variables are cell centered and interpolated to the cell rDx3 faces for flux calculations; these are then used by a Harten– N¯ = ,3() 3 * Lax–van Leer-Contact Riemann solver (Toro et al. 1994). rth Dxmin We performed a set of zoom cosmological simulations of an fi ò ( MW-type halo in order to address whether NSMs can be and the star formation ef ciency * was set to 0.01 Krumholz ) considered the primary source of r-processenrichment in the & Tan 2007 in our simulations. Setting Lmax, the maximum early universe. We adopted three different minimum timescales refinement in the simulation, to 24, together with = −3 for the coalescence of the DNSs: tmin=1, 10, and 100 Myr. n* 17 H cm as the threshold for star formation in the We also adopted three different energies for the NS merger cells, results in a stellar particle mass of ≈50 Me. This is 50 51 52 event and run simulations: ENSM=10 ,10 , and 10 erg. In massive enough to host the two supernovae (SNe) needed to ≈ – all cases, we stopped the simulations at z 8 9 when create a DNS. Lmax is the maximum refinement level in the reionization is complete and the formation of the MP stars simulation. A further limitation on star particle formulation is largely diminishes. The statistics of different classes of stars that no more than 90% of the cell’s gas mass can be converted displaying a high abundance of r-processelements are then ’ into stars. compared against MW s halo stars. In this study, we only modeled r-processelement production by NSMs, and slow s-process channels were not modeled. 2.1. Simulation Setup and MW Initial Conditions (ICs) Consequently, we did not model elements such as barium that have both r-processand s-process origin. Also, we did not fi To initialize our simulations, we rst ran a DM-only model Type Ia SNe because of their long average delay times simulation down to redshift zero in a periodic box with a − of the order of 200–500 Myr (Raskin et al. 2009). Given the h 1 MUSIC comoving size of 50 Mpc . ICs were generated from stellar particle mass (≈50 Me), 50% of all such particles were ( ) Hahn & Abel 2011 for a Planck 2015 cosmology. The virial assumed to host one core-collapse SN (CCSN), assigned mass and radius of the halos are derived from the HOP halo stochastically. Therefore, half of the stellar particles generated a finder (Eisenstein & Hut 1998). We used a halo mass cut of = 12 CCSN ejecting a total mass of msn 10 Me with a kinetic (1–2)×10 Meto ensure that we only identified halos with a 51 energy of ESN=10 erg 10 Myr after the star was formed. mass similar to the MW. We found 275 such halos within the The metallicity yield for each CCSN is set to η =0.1, fi SN desired mass range in our simulation box.
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