Mathematics – Logic
Scientific paper
Dec 1997
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1997hst..prop.7534o&link_type=abstract
HST Proposal ID #7534
Mathematics
Logic
Hst Proposal Id #7534 Galaxies
Scientific paper
We propose to measure high quality morphological types of faint galaxies in 36 deep WFPC2 fields using unique new methods of neural network classification based on two- dimensional Fourier reconstructions of galaxy light distributions. We estimate that 9000 galaxies will be automatically classified, producing morphological number counts with errors 10 Specifically, we will:
o Carry out a systematic analysis of the morphological properties of local and distant galaxies by quantitatively measuring global galaxy asymmetries as a function of cosmic epoch, and in the process develop new two-dimensional Fourier-based neural network classification systems capable of detecting and quantifying bar and ring features.
o Improve isophotal ellipse fitting with Fourier rejection methods and create a large database to confirm our recent finding that highly flattened galaxies are rare at Ibandcge23 {or zcge1} relative to local, possibly indicating the epoch of disk formation.
o Investigate the nature of secular evolution of galaxies by analyzing - using images in a consistent rest- frame -- the frequency and properties of morphological features, such as bars and rings, over a wide range of cosmic epochs.
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