Statistics – Computation
Scientific paper
May 2010
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010aas...21642403g&link_type=abstract
American Astronomical Society, AAS Meeting #216, #424.03; Bulletin of the American Astronomical Society, Vol. 41, p.836
Statistics
Computation
Scientific paper
Grain-surface processes are crucial to the behavior of interstellar chemistry; a number of key molecules (including methanol, CH3OH, and methyl formate, HCOOCH3) have been found to have no viable gas-phase formation mechanisms, and many complex organic molecules detected in star-forming regions are believed to originate on dust-grain surfaces. Fully-coupled gas-phase and grain-surface interstellar chemistry is often simulated using rate equations; however, this method fails in cases where the grain chemistry behaves stochastically. So-called "exact" methods, such as Monte Carlo and/or master-equation techniques, are capable of accurately treating this behavior, but the exact methods are computationally highly expensive - prohibitively so, when considering large chemical networks and variable physical conditions.
We present a new rate-modification scheme, in which the surface chemical rates are adjusted to take account of stochastic behavior. The scheme shows excellent agreement with Monte Carlo results for a full dark-cloud chemical reaction network over a large physical parameter space. The method is also easily incorporated into existing gas-phase models, and run-times are similar to those of standard rate-equation methods. Minor inaccuracies result from the use of incomplete chemical networks, as is also the case with standard rate-equation simulations. The use of the new modified-rate method with self-consistent chemical networks provides near-perfect agreement with the exact Monte Carlo method. The new method will allow fast, accurate chemical simulations of the most physically- and chemically-complex sources in the ISM, currently impossible using other methods.
Garrod Robin
Vasyunin Anton
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