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Register a new userSimulations of Dense Stellar Systems with the AMUSE Software Toolkit
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We describe AMUSE, the Astrophysical Multipurpose Software Environment, a programming framework designed to manage multi-scale, multi-physics simulations in a hierarchical, extensible, and internally consistent way. Constructed as a collection of individual modules, AMUSE allows computational tools for different physical domains to be easily combined into a single task. It facilitates the coupling of modules written in different languages by providing inter-language tools and a standard programming interface that represents a balance between generality and computational efficiency. The framework currently incorporates the domains of stellar dynamics, stellar evolution, gas dynamics, and radiative transfer. We present some applications of the framework and outline plans for future development of the package.
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We compile observations of the surface mass density profiles of dense stellar systems, including globular clusters in the Milky Way and nearby galaxies, massive star clusters in nearby starbursts, nuclear star clusters in dwarf spheroidals and late-type disks, ultra-compact dwarfs, and galaxy spheroids spanning the range from low-mass cusp bulges and ellipticals to massive core ellipticals. We show that in all cases the maximum stellar surface density attained in the central regions of these systems is similar, Sigma_max ~ 10^11 M_sun/kpc^2 (~20 g/cm^2), despite the fact that the systems span 7 orders of magnitude in total stellar mass M_star, 5 in effective radius R_e, and have a wide range in effective surface density M_star/R_e^2. The surface density limit is reached on a wide variety of physical scales in different systems and is thus not a limit on three-dimensional stellar density. Given the very different formation mechanisms involved in these different classes of objects, we argue that a single piece of physics likely determines Sigma_max. The radiation fields and winds produced by massive stars can have a significant influence on the formation of both star clusters and galaxies, while neither supernovae nor black hole accretion are important in star cluster formation. We thus conclude that feedback from massive stars likely accounts for the observed Sigma_max, plausibly because star formation reaches an Eddington-like flux that regulates the growth of these diverse systems. This suggests that current models of galaxy formation, which focus on feedback from supernovae and active galactic nuclei, are missing a crucial ingredient.
It is well known that numerical errors grow exponentially in $N$-body simulations of gravitational bound stellar systems, but it is not well understood how the accuracy parameters of algorithms affect the physical evolution in simulations. By using the hybrid $N$-body code, PeTar, we investigate how escapers and the structure evolution of collisional stellar systems (e.g., star clusters) depend on the accuracy of long-range and short-range interactions. We study a group of simulations of ideal low-mass star clusters in which the accuracy parameters are varied. We find that although the number of escapers is different in individual simulations, its distribution from all simulations can be described by Poisson statistics. The density profile also has a similar feature. By using a self-consistent set-up of the accuracy parameters for long- and short-range interactions, such that orbits are resolved well enough, the physical evolution of the models is identical. But when the short-range accuracy is too low, a nonphysical dynamical evolution can easily occur; this is not the case for long-range interactions. This strengthens the need to include a proper algorithm (e.g. regularization methods) in the realistic modelling of collisional stellar systems. We also demonstrate that energy-conservation is not a good indicator to monitor the quality of the simulations. The energy error of the system is controlled by the hardest binary, and thus, it may not reflect the ensemble error of the global system.
Upon their formation, dynamically cool (collapsing) star clusters will, within only a few million years, achieve stellar mass segregation for stars down to a few solar masses, simply because of gravitational two-body encounters. Since binary systems are, on average, more massive than single stars, one would expect them to also rapidly mass segregate dynamically. Contrary to these expectations and based on high-resolution Hubble Space Telescope observations, we show that the compact, 15-30 Myr-old Large Magellanic Cloud cluster NGC 1818 exhibits tantalizing hints at the >= 2 sigma level of significance (> 3 sigma if we assume a power-law secondary-to-primary mass-ratio distribution) of an increasing fraction of F-star binary systems (with combined masses of 1.3-1.6 Msun) with increasing distance from the cluster center, specifically between the inner 10 to 20 (approximately equivalent to the clusters core and half-mass radii) and the outer 60 to 80. If confirmed, this will offer support of the theoretically predicted but thus far unobserved dynamical disruption processes of the significant population of soft binary systems---with relatively low binding energies compared to the kinetic energy of their stellar members---in star clusters, which we have access to here by virtue of the clusters unique combination of youth and high stellar density.
We describe the implementation and performance of the ${rm P^3T}$ (Particle-Particle Particle-Tree) scheme for simulating dense stellar systems. In ${rm P^3T}$, the force experienced by a particle is split into short-range and long-range contributions. Short-range forces are evaluated by direct summation and integrated with the fourth order Hermite predictor-corrector method with the block timesteps. For long-range forces, we use a combination of the Barnes-Hut tree code and the leapfrog integrator. The tree part of our simulation environment is accelerated using graphical processing units (GPU), whereas the direct summation is carried out on the host CPU. Our code gives excellent performance and accuracy for star cluster simulations with a large number of particles even when the core size of the star cluster is small.
Gaia will only achieve its unprecedented measurement accuracy requirements with detailed calibration and correction for radiation damage. We present our Silvaco 3D engineering software model of the Gaia CCD pixel and two of its applications for Gaia: (1) physically interpreting supplementary buried channel (SBC) capacity measurements (pocket-pumping and first pixel response) in terms of e2v manufacturing doping alignment tolerances; and (2) deriving electron densities within a charge packet as a function of the number of constituent electrons and 3D position within the charge packet as input to microscopic models being developed to simulate radiation damage.
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