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Register a new userOn the reliability of simulations of collisional stellar systems
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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.
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This project aims at exploiting the wide-field and limiting-magnitude capabilities of the LSST to fully characterise the resolved stellar populations in/around six Local Group stellar systems of different morphological type at ~30 to ~400 kpc distance from us. We selected targets that host red giant branch (RGB) stars which are within the reach of Gaia and not yet (all) saturated with the LSST. We will use RR Lyrae stars, Cepheids, SX Phoenicis, delta Scuti stars and Long Period Variables, along with the Color Magnitude Diagram of the resolved stellar populations in these 6 systems to: i) trace their different stellar generations over a spatial extension and with a depth that only the LSST can achieve; ii) measure their distances using variable stars of different type/parent stellar population and the Tip of the RGB; iii) map their 3D structures up to the periphery of their halos; iv) search for tidal streams; and v) study their Star Formation Histories over unprecedented large fractions of their bodies. Our ultimate goals are to provide a complete picture of these nearby stellar systems all the way through to their periphery, and to directly link and cross-calibrate the Gaia and LSST projects.
Under certain rather prevalent conditions (driven by dynamical orbital evolution), a hierarchical triple stellar system can be well approximated, from the standpoint of orbital parameter estimation, as two binary star systems combined. Even under this simplifying approximation, the inference of orbital elements is a challenging technical problem because of the high dimensionality of the parameter space, and the complex relationships between those parameters and the observations (astrometry and radial velocity). In this work we propose a new methodology for the study of triple hierarchical systems using a Bayesian Markov-Chain Monte Carlo-based framework. In particular, graphical models are introduced to describe the probabilistic relationship between parameters and observations in a dynamically self-consistent way. As information sources we consider the cases of isolated astrometry, isolated radial velocity, as well as the joint case with both types of measurements. Graphical models provide a novel way of performing a factorization of the joint distribution (of parameter and observations) in terms of conditional independent components (factors), so that the estimation can be performed in a two-stage process that combines different observations sequentially. Our framework is tested against three well-studied benchmark cases of triple systems, where we determine the inner and outer orbital elements, coupled with the mutual inclination of the orbits, and the individual stellar masses, along with posterior probability (density) distributions for all these parameters. Our results are found to be consistent with previous studies. We also provide a mathematical formalism to reduce the dimensionality in the parameter space for triple hierarchical stellar systems in general.
Understanding the collapse of clouds and the formation of protoplanetary disks is essential to understanding the formation of stars and planets. Infall and accretion, the mass-aggregation processes that occur at envelope and disk scales, drive the dynamical evolution of protostars. While the observations of protostars at different stages constrain their evolutionary tracks, the impact of variability due to accretion bursts on dynamical and chemical evolution of the source is largely unknown. The lasting effects on protostellar envelopes and disks are tracked through multi-wavelength and time domain observational campaigns, requiring deep X-ray, infrared, and radio imaging and spectroscopy, at a sufficient level of spatial detail to distinguish contributions from the various substructures (i.e., envelope from disk from star from outflow). Protostellar models derived from these campaigns will illuminate the initial chemical state of protoplanetary disks during the epoch of giant planet formation. Insight from individual star formation in the Milky Way is also necessary to understand star formation rates in extragalactic sources. This cannot be achieved with ground-based observatories and is not covered by currently approved instrumentation. Requirements: High (v < 10 km/s for survey; v < 1 km/s for followup) spectral resolution capabilities with relatively rapid response times in the IR (3-500 um), X-ray (0.1-10 keV), and radio (cm) are critical to follow the course of accretion and outflow during an outburst. Complementary, AU-scale radio observations are needed to probe the disk accretion zone, and 10 AU-scale to probe chemical and kinematic structures of the disk-forming regions, and track changes in the dust, ice, and gas within protostellar envelopes.
Bow shocks and related density enhancements produced by the winds of massive stars moving through the interstellar medium provide important information regarding the motions of the stars, the properties of their stellar winds, and the characteristics of the local medium. Since bow shocks are aspherical structures, light scattering within them produces a net polarization signal even if the region is spatially unresolved. Scattering opacity arising from free electrons and dust leads to a distribution of polarized intensity across the bow shock structure. That polarization encodes information about the shape, composition, opacity, density, and ionisation state of the material within the structure. In this paper we use the Monte Carlo radiative transfer code SLIP to investigate the polarization created when photons scatter in a bow shock-shaped region of enhanced density surrounding a stellar source. We present results assuming electron scattering, and investigate the polarization behaviour as a function of optical depth, temperature, and source of photons for two different cases: pure scattering and scattering with absorption. In both regimes we consider resolved and unresolved cases. We discuss the implication of these results as well as their possible use along with observational data to constrain the properties of observed bow shock systems. In different situations and under certain assumptions, our simulations can constrain viewing angle, optical depth and temperature of the scattering region, and the relative luminosities of the star and shock.
To study the quality of stellar spectra of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) and the correctness of the corresponding stellar parameters derived by the LASP (LAMOST Stellar Parameter Pipeline), the outlier analysis method is applied to the archived AFGK stars in the fifth data release (DR5) of LAMOST. The outlier factor is defined in order to sort more than 3 million stellar spectra selected from the DR5 Stellar Parameter catalog. We propose an improved Local Outlier Factor (LOF) method based on Principal Component Analysis and Monte Carlo to enable the computation of the LOF rankings for randomly picked sub-samples that are computed in parallel by multiple computers, and finally to obtain the outlier ranking of each spectrum in the entire dataset. Totally 3,627 most outlier ranked spectra, around one-thousandth of all spectra, are selected and clustered into 10 groups, and the parameter density distribution of them conforms to the parameter distribution of LAMOST DR5, which suggests that in the whole parameter space the probability of bad spectra is uniformly distributed. By cross-matching the 3,627 spectra with APOGEE, we obtain 122 common ones. The published parameters calculated from LASP agree with APOGEE for the 122 spectra although there are bad pixels or bad flux calibrations in them. On the other hand, some outlier spectra show strong nebular contamination warning the corresponding parameters should be carefully used. A catalog and a spectral atlas of all the 3,627 outliers can be found at the link http://paperdata.china-vo.org/LY_paper/dr5Outlier/dr5Outlier_resource.zip.
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