Black hole mergers and blue stragglers from hierarchical triples formed in globular clusters

Hierarchical triple-star systems are expected to form frequently via close binary-binary encounters in the dense cores of globular clusters. In a sufficiently inclined triple, gravitational interactions between the inner and outer binary can cause large-amplitude oscillations in the eccentricity of the inner orbit ("Lidov-Kozai cycles"), which can lead to a collision and merger of the two inner components. In this paper we use Monte Carlo models of dense star clusters to identify all triple systems formed dynamically and we compute their evolution using a highly accurate three-body integrator which incorporates relativistic and tidal effects. We find that a large fraction of these triples evolve through a non-secular dynamical phase which can drive the inner binary to higher eccentricities than predicted by the standard secular perturbation theory (even including octupole-order terms). We place constraints on the importance of Lidov-Kozai-induced mergers for producing: (i) gravitational wave sources detectable by Advanced LIGO (aLIGO), for triples with an inner pair of stellar black holes; and (ii) blue straggler stars, for triples with main-sequence-star components. We find a realistic aLIGO detection rate of black hole mergers due to the Lidov-Kozai mechanism of 1yr^-1, with about 20% of these having a finite eccentricity when they first chirp into the aLIGO frequency band. While rare, these events are likely to dominate among eccentric compact object inspirals that are potentially detectable by aLIGO. For blue stragglers, we find that the Lidov-Kozai mechanism can contribute only up to ~10% of their total numbers in globular clusters.Comment: 17 pages, 11 Figures. Accepted for publication in Ap

A Parallel Monte Carlo Code for Simulating Collisional N-body Systems

We present a new parallel code for computing the dynamical evolution of collisional N-body systems with up to N~10^7 particles. Our code is based on the the Henon Monte Carlo method for solving the Fokker-Planck equation, and makes assumptions of spherical symmetry and dynamical equilibrium. The principal algorithmic developments involve optimizing data structures, and the introduction of a parallel random number generation scheme, as well as a parallel sorting algorithm, required to find nearest neighbors for interactions and to compute the gravitational potential. The new algorithms we introduce along with our choice of decomposition scheme minimize communication costs and ensure optimal distribution of data and workload among the processing units. The implementation uses the Message Passing Interface (MPI) library for communication, which makes it portable to many different supercomputing architectures. We validate the code by calculating the evolution of clusters with initial Plummer distribution functions up to core collapse with the number of stars, N, spanning three orders of magnitude, from 10^5 to 10^7. We find that our results are in good agreement with self-similar core-collapse solutions, and the core collapse times generally agree with expectations from the literature. Also, we observe good total energy conservation, within less than 0.04% throughout all simulations. We analyze the performance of the code, and demonstrate near-linear scaling of the runtime with the number of processors up to 64 processors for N=10^5, 128 for N=10^6 and 256 for N=10^7. The runtime reaches a saturation with the addition of more processors beyond these limits which is a characteristic of the parallel sorting algorithm. The resulting maximum speedups we achieve are approximately 60x, 100x, and 220x, respectively.Comment: 53 pages, 13 figures, accepted for publication in ApJ Supplement

Fast algorithms for the maximum clique problem on massive graphs with application to . . .

The maximum clique problem is a well known NP-Hard problem with applications in data mining, network analysis, information retrieval and many other areas related to the World Wide Web. There exist several algorithms for the problem with acceptable runtimes for certain classes of graphs, but many of them are infeasible for massive graphs. We present a new exact algorithm that employs novel pruning techniques and is able to find maximum cliques in very large, sparse graphs quickly. Extensive experiments on different kinds of synthetic and real-world graphs show that our new algorithm can be orders of magnitude faster than existing algorithms. We also present a heuristic that runs orders of magnitude faster than the exact algorithm while providing optimal or near-optimal solutions. We illustrate a simple application of the algorithms in developing methods for detection of overlapping communities in networks

Etude par R.M.N. des dialkyldithiophosphates de zinc en tant qu'additifs anti-usure dans une huile moteur : description, degradation thermique et interactions avec les autres additifs

SIGLECNRS T 56763 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc