Statistics – Computation
Scientific paper
Dec 1999
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1999aas...195.3302j&link_type=abstract
American Astronomical Society, 195th AAS Meeting, #33.02; Bulletin of the American Astronomical Society, Vol. 31, p.1417
Statistics
Computation
1
Scientific paper
Novae vary in their visible luminosity by orders of magnitude over a period of months to a few years, and often show the occurrence of a large dip in their visible light, associated with the growth of carbon dust grains. The purpose of this thesis is to study the effects of hydrogenation and density inhomogeneities on the efficiency of nucleation of dust grains in novae, using a time dependent kinetic model. The hydrogenation study shows that a model of grain growth limited by photodissociation of small hydrogenated carbon molecules is effective at reproducing the grain sizes, optical depths, and grain formation temperatures observed to occur in novae. Grain sizes on the order of or less than 1 micron are predicted for weakly hydrogenated models. Optical depth is found to vary widely depending on the initial density, the luminosity of the central source, and the degree of hydrogenation of the building block molecules C2 - C8. The study of the effect of clumps in the nova outflow show that a hydrogenation limited nucleation model of grain growth in novae can with the inclusion of clumps explain the occurrence of excess infrared reradiation for models with no observable visible obscuration, provided a density enhancement of 10, in accord with spectral analysis of Nova Cyg 1992. Such a model does have limitations in reproducing the observed relation between visible obscuration (τ V) and infrared reradiation (τ IR = LIR}/L{UV), particularly for optically thick novae. This work has been supported primarily by NASA grants NAG-3144 and NAG5-3339, and in part by the Air Force Office of Scientific Research and the Shodor Education Foundation (National Computational Science Alliance, ACI-9619019 Subaward 769).
Joiner David A.
Leung Man Chun
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