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On Neutron Star Mergers As the Source of R-Process Enhanced Draft version March 27, 2019 Preprint typeset using LATEX style emulateapj v. 12/16/11 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 Draft version March 27, 2019 ABSTRACT We model the history of Galactic r-process enrichment using high-redshift, high-resolution zoom cosmological simulations of a Milky Way (MW) 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 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 (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-process yield estimates observed in GW170817, NSMs by themselves can only explain the observed frequency of r-process enhanced stars if the birth rate of double neutron stars per unit mass of stars is boosted to −4 −1 ≈ 10 M . 1. INTRODUCTION earliest r-process sources. Therefore, a successful theory The recent aLIGO/aVirgo detection of gravitational for the source of the r-process should be able to explain waves from the merger of two neutron stars (GW170817; the observed statistics of MP-r and CEMP-r stars in the Abbott et al. 2017a), and the subsequent kilonova ob- MW's halo (Barklem et al. 2005; Abate et al. 2016). served across the entire electromagnetic spectrum (Ab- In fact, the very existence of CEMP-r stars poses new bott et al. 2017b; Coulter et al. 2017) have confirmed challenges for the origin of r-process elements in the early that r-process elements are made in copious amounts in universe. These stars are believed to form at high red- neutron star mergers (NSMs; Abbott et al. 2017c; Kasen shifts and in low mass halos where Population III (Pop. et al. 2017). This discovery could be the sine qua non for III) stars have polluted the halo with their carbon rich showing that NSMs are the primary source of r-process ejecta. In such low mass halos, for a CEMP-r star to elements in the Milky Way (C^ot´eet al. 2018b). form, an r-process source that acts on a timescale similar On the other hand, while it is clear that NSMs are one to Pop. III stars (i.e., ≈10 Myr) is needed (Ramirez-Ruiz of the sources of r-process enrichment, it remains an open et al. 2015). question if they are the most important source. To ad- Could the observed statistics of different classes of r- dress this question, several theoretical studies have mod- process enhanced stars be explained by NSMs as the sole eled r-process enrichment of a Milky Way (MW) type source of r-process in the early universe? In this study, halo and its ultra faint dwarf (UFD) satellites by NSMs. we address this question, by carrying out a set of zoom van de Voort et al.(2015a) carried out a zoom simulation cosmological simulations of a MW type halo and model- of a MW type halo to z = 0 and concluded that NSM ing NSMs as the sources of the r-process material. We events can explain the observed [r-process /Fe] abun- improve on crucial aspects of previous such simulations on three fronts: (i) Modeling the coalescence timescales dance ratios assuming 10−2M r-process mass is ejected of double neutron stars (DNSs) as drawn from distribu- into the ISM in each NSM event. Shen et al.(2015) stud- tions motivated by population synthesis analyses (Fryer ied the sites of r-process production by post-processing arXiv:1812.02779v2 [astro-ph.GA] 25 Mar 2019 et al. 1998; Dominik et al. 2012; Behroozi et al. 2014). \Eris" zoom simulations, and found that r-process ele- (ii) Identifying Pop. III stars by following the evolution of ments can be incorporated into stars at very early times, pristine gas in each simulation cell with a subgrid model a result that is insensitive to modest variations in the de- of turbulent mixing that is crucial for properly identify- lay distribution and merger rates. Separately, Safarzadeh ing Pop. III stars whose ejecta are the precursor to the & Scannapieco(2017) studied r-process enrichment in formation of CEMP stars (Sarmento et al. 2017; Naiman the context of UFDs and concluded that natal kicks can et al. 2018); (iii) Adopting a high dark matter particle affect the r-process enhancement of subsequent stellar mass resolution in order to resolve halos where the MP generations. and CEMP stars form in the early universe. In each of these studies, it is observations of metal The structure of this work is as follows: In x2 we de- poor (MP) and carbon enhanced metal poor (CEMP) scribe our method in detail. In x3 we present our results stars that are most constraining. Such stars encode a and compare them to observations of MW halo stars. wealth of information about the formation of the first In x4 we discuss our results and conclusions. Through- stars in the universe (Beers & Christlieb 2005; Frebel out this paper, we adopt the Planck 2015 cosmologi- & Norris 2015), and similarly their r-process enhanced cal parameters (Planck Collaboration et al. 2016) where subclasses (MP-r and CEMP-r ), provide insight into the ΩM = 0:308, ΩΛ = 0:692, Ωb = 0:048 are total matter, 2 vacuum, and baryonic densities, in units of the critical For the full hydrodynamic simulations, this zoom re- density ρc, h = 0:678 is the Hubble constant in units of gion is refined to a base level of 12, and 13 for two dif- 100 km/s/Mpc, σ8 = 0:82 is the variance of linear fluc- ferent sets of simulations corresponding to a dark matter −1 5 4 tuations on the 8 h Mpc scale, ns = 0:968 is the tilt particle mass of mDM≈1:2 × 10 M and 1:4 × 10 M of the primordial power spectrum, and YHe = 0:24 is the respectively. The zoom region has sides 4:4 × 4:2 × 6:4 primordial helium fraction. comoving Mpc h−1 . 2. METHOD 2.2. Star formation and feedback The stellar particle mass in the simulation is m∗ = We used ramses (Teyssier 2002), a cosmological adap- 3 tive mesh refinement (AMR) code, which implements an ρth∆xminN where ∆xmin is the best resolution cell size unsplit second-order Godunov scheme for evolving the achievable and N is drawn from a Poisson distribution Euler equations. ramses variables are cell-centered and N¯ P (N) = exp(−N¯); (2) interpolated to the cell faces for flux calculations, these N! are then used by a Harten-Lax-van Leer-Contact Rie- mann solver (Toro et al. 1994). where ρ∆x3 We performed a set of zoom cosmological simulations ¯ N = 3 ∗; (3) of a MW type halo in order to address if NSMs can be ρth∆xmin considered the primary source of r-process enrichment in and the star formation efficiency ∗ was set to 0.01 the early universe. We adopted three different minimum (Krumholz & Tan 2007) in our simulations. Setting timescales for the coalescence of the DNSs: tmin = 1, 10, Lmax, the maximum refinement in the simulation, to 24, and 100 Myrs. We also adopted three different energy for 3 50 together with n∗ = 17 H/cm as the threshold for star the NS merger event and run simulations: ENSM = 10 , 51 52 formation in the cells results in a stellar particle mass of 10 , and 10 ergs. In all cases, we stopped the simu- ≈ 50 M . This is massive enough to host the two su- lations at z ≈ 8 − 9 when reionization is complete and pernovae needed to create a double neutron star. Lmax the formation of the metal poor stars largely diminishes. is the maximum refinement level in the simulation. A The statistics of different classes of stars displaying a further limitation on star particle formulation is that no high abundance of r-process elements are then compared more than 90% of the cell's gas mass can be converted against MW's halo stars. into stars. In this study, we only modeled r-process elements pro- 2.1. Simulation setup and Milky Way initial conditions duction by NSMs and slow s-process channels were not To initialize our simulations, we first ran a dark matter modeled. Consequently, we did not model elements such only simulation down to redshift zero in a periodic box as barium that have both r-process and s-process origin. with a comoving size of 50 Mpc h−1. Initial conditions Also, we did not model SN Ia because of their long aver- (ICs) were generated from music (Hahn & Abel 2011) age delay times of the order of 200-500 Myr (Raskin et al. for a Planck 2015 cosmology. The virial mass and ra- 2009). Given the stellar particle mass (≈ 50M ), 50% of dius of the halos are derived from the HOP halo finder all such particles were assumed to host one core-collapse (Eisenstein & Hut 1998). We used a halo mass cut of supernova (CCSN), assigned stochastically.
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