Collisions and close encounters involving massive main-sequence stars

We study close encounters involving massive main sequence stars and the evolution of the exotic products of these encounters as common--envelope systems or possible hypernova progenitors. We show that parabolic encounters between low-- and high--mass stars and between two high--mass stars with small periastrons result in mergers on timescales of a few tens of stellar freefall times (a few tens of hours). We show that such mergers of unevolved low--mass stars with evolved high--mass stars result in little mass loss ($\sim0.01$ M$_{\odot}$) and can deliver sufficient fresh hydrogen to the core of the collision product to allow the collision product to burn for several million years. We find that grazing encounters enter a common--envelope phase which may expel the envelope of the merger product. The deposition of energy in the envelopes of our merger products causes them to swell by factors of $\sim100$. If these remnants exist in very densely-populated environments ($n\gtrsim10^{7}$ pc$^{-3}$), they will suffer further collisions which may drive off their envelopes, leaving behind hard binaries. We show that the products of collisions have cores rotating sufficiently rapidly to make them candidate hypernova/gamma--ray burst progenitors and that $\sim0.1$ of massive stars may suffer collisions, sufficient for such events to contribute significantly to the observed rates of hypernovae and gamma--ray bursts.Comment: 15 pages, 13 figures, LaTeX, to appear in MNRAS (in press

A new algorithm for modelling photoionising radiation in smoothed particle hydrodynamics

We present a new fast algorithm which allows the simulation of ionising radiation emitted from point sources to be included in high-resolution three-dimensional smoothed particle hydrodynamics simulations of star cluster formation. We employ a Str\"omgren volume technique in which we use the densities of particles near the line-of-sight between the source and a given target particle to locate the ionisation front in the direction of the target. Along with one--dimensional tests, we present fully three--dimensional comparisons of our code with the three--dimensional Monte-Carlo radiative transfer code, MOCASSIN, and show that we achieve good agreement, even in the case of highly complex density fields.Comment: 10 pages, 7 figures, submitted to MNRA

Data Mining with Newton\u27s Method.

Capable and well-organized data mining algorithms are essential and fundamental to helpful, useful, and successful knowledge discovery in databases. We discuss several data mining algorithms including genetic algorithms (GAs). In addition, we propose a modified multivariate Newton\u27s method (NM) approach to data mining of technical data. Several strategies are employed to stabilize Newton\u27s method to pathological function behavior. NM is compared to GAs and to the simplex evolutionary operation algorithm (EVOP). We find that GAs, NM, and EVOP all perform efficiently for well-behaved global optimization functions with NM providing an exponential improvement in convergence rate. For local optimization problems, we find that GAs and EVOP do not provide the desired convergence rate, accuracy, or precision compared to NM for technical data. We find that GAs are favored for their simplicity while NM would be favored for its performance