Other uses of the program 'ARGON.f90'

The purpose of this communication is to show that the program 'ARGON.f90' can be simply extended to model ionization from the excited states of atoms where the active electron has a principal quantum number less than or equal to 3. This fact is illustrated by considering a relatively simple collision involving a proton and a neutral hydrogen atom with principal quantum number n = 2. (C) 2005 Published by Elsevier B.V.

Equilibrium polymerization of cyclic carbonate oligomers. III. Chain branching and the gel transition

Ring-opening polymerization of cyclic polycarbonate oligomers, where monofunctional active sites act on difunctional monomers to produce an equilibrium distribution of rings and chains, leads to a "living polymer." Monte Carlo simulations [two-dimensional (2D) and three-dimensional (3D)] of the effects of single [J. Chem. Phys. 115, 3895 (2001)] and multiple active sites [J. Chem. Phys. 116, 7724 (2002)] are extended here to trifunctional active sites that lead to branching. Low concentrations of trifunctional particles c(3) reduce the degree of polymerization significantly in 2D, and higher concentrations (up to 32%) lead to further large changes in the phase diagram. Gel formation is observed at high total density and sizable c(3) as a continuous transition similar to percolation. Polymer and gel are much more stable in 3D than in 2D, and both the total density and the value of c(3) required to produce high molecular weight aggregates are reduced significantly. The degree of polymerization in high-density 3D systems is increased by the addition of trifunctional monomers and reduced slightly at low densities and low c(3). The presence of branching makes equilibrium states more sensitive (in 2D and 3D) to changes in temperature T. The stabilities of polymer and gel are enhanced by increasing T, and-for sufficiently high values of c(3)-there is a reversible polymer-gel transformation at a density-dependent floor temperature. (C) 2002 American Institute of Physics.

Probabilistic program analysis for parallelizing compilers

Parallelizing compilers have difficulty analysing and optimising complex code. To address this, some analysis may be delayed until run-time, and techniques such as speculative execution used. Furthermore, to enhance performance, a feedback loop may be setup between the compile time and run-time analysis systems, as in iterative compilation. To extend this, it is proposed that the run-time analysis collects information about the values of variables not already determined, and estimates a probability measure for the sampled values. These measures may be used to guide optimisations in further analyses of the program. To address the problem of variables with measures as values, this paper also presents an outline of a novel combination of previous probabilistic denotational semantics models, applied to a simple imperative language.