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Star Formation Studies Using AST/RO. Student: Desika Narayanan Mentor: Dr. Sung Kim Center for Astrophysics Cambridge, Massachusetts Summer 2001. Objective. -Stars are born in the pockets of Giant Molecular Clouds.
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Star Formation Studies Using AST/RO Student: Desika Narayanan Mentor: Dr. Sung Kim Center for Astrophysics Cambridge, Massachusetts Summer 2001
Objective -Stars are born in the pockets of Giant Molecular Clouds. - Photodissociation regions (PDRs) are areas in the clouds where the Far Ultraviolet light of newborn stars play an integral role in the chemistry of molecular clouds - Why study these PDRs? They regulate star formation. -Objective of scientific study: to better understand the role of PDRs in GMCs.
Mapping • Mapping Regions of Emission in: • CO (7-->6) 809 GHz • 12CI 809GHz • CO (4-->3) 460 GHz • CO (2-->1) 230 GhzClouds Studied: • Small Magallenic Cloud (East and West) • Large Magallenic Cloud • NGC 6334 (Galactic)Good mapping will hopefully indicate where star formation might be going on. Further inspection of the spectra taken at different locations will help define physical parameters such as temperature, density and elemental abundance.
Observations • Observations were made in a series of pointings. After data are reduced, and spectra obtained, these locations are used to make a contour map of emission. • All observations were made with the Antarctic Submillimeter Telescope and Remote Observatory (AST/RO) • Has the ability to observe 230, 460, 490, 806 and 809 Ghz windows • Utilizes the high and dry atmosphere of the pole's environment to improve quality of data IRAS 100 micron image P Pointings in SMC-E
Baseline Ripple • Baseline ripples caused by: -Rapid changes in atmosphere -Gain instabilities in mixer -Impedance mismatch in instrumentation (causes standing waves) • Removed by polynomial fit and subtraction in Comb • Removed by Fourier transform algorithm • Problems with polynomial fitting: -Want to fit around line to avoid removing signal (line not always clear) -Best to subtract over whole line rather than pieces to avoid rms problems down the road (difficult then to get a good fit) -High order fitting can introduce artificial features
Fourier Transforms • Used for a more serious form of sinusoidal ripple • F(s) = f(x)e-i2xspdx-Picks out sinusoidal functions with certain amplitudes and phases. • Comb plots F(s) versus frequency and allows you to remove certain components
Messy spectra with obvious emission lines • Possible line at -40 km/s?
Fourier Transform • The ripple is the spike off the chart. If we remove bright components,we can get rid of some of ripple.
4 components were removed, after the first 5 • Note the recovery of the third line
SMC Observations • Observations divided intoSMC-E and SMC-W • Each observation made in a seriesof pointings 1.7' apart (distance varies for different obs. Runs). • SMC-E and SMC-W both studied at 230 Ghz (CO J=2-->1) SMC-B
SMC Results • SMC-E had too low of a S/N to get any lines out. More observation time is needed. SMC-W had bad baseline problems that I couldn't get outSMC-W Raw Data:
SMC-W emission • Many of the pointings ended up showing nice emission
NGC 6334 (460GHz) • Measured at:-460 GHz (CO J=4-->3)-809 GHz (CO J=7-->6)-809 GHz (12CI) • Raw data was Excellent • Reductions only involved linear baseline subtraction
CO 809 Ghz (J=7-->6) • The higher transitions map traces the hotter and denser regions of the molecular cloud
12 CI (809 GHz) • .
Conclusions Personal: - I Learned about mathematical data reduction processes (ie Fourier transform, baseline fitting) - I was able to learn some of the science behind studying Star Forming regions - Mapping Techniques - Sampling Theorem Scientific: - The CO emission and 12CI emission occurs in relatively similar areas in NGC 6334
Ackowledgements -Dr. Sung Kim -AST/RO Group -CARA