Transcript Columbus 2010 Ivan Medvedev.pptx

TJ02
3-D SUBMILLIMETER SPECTROSCOPY OF
ASTRONOMICAL `WEEDS‘ - EXPERIMENTAL
AND THEORETICAL ASPECTS OF DATA
PROCESSING AND CATALOGING
–> TJ03
Ivan R. Medvedev, Sarah M. Fortman,
Christopher F. Neese, and Frank C. De Lucia
Astronomical ‘Weeds’
Class 1 Weeds1)
Methanol – CH3OH
Methyl Formate – HCOOCH3
Ethyl Cyanide
Dimethyl Ether – CH3OCH3
Ethyl Cyanide – CH3CH2CN
Class 2 Weeds1)
Vinyl Cyanide – C2H3CN
Sulfur Dioxide – SO2
Methyl Cyanide – CH3CN
Acetaldehyde – CH3CHO
Methanol
1) REPORT FROM THE WORKSHOP ON LABORATORY SPECTROSCOPY IN SUPPORT OF HERSCHEL, SOFIA, AND ALMA
Pasadena, California October 19 and 20, 2006
Experimental
• Record spectra in the temperature range 240-400 K
• Pressure ~ 1-5 mtorr (near Doppler limited line shape)
• Record spectra in the FASSST mode with post
detection bandwidth adequate for detecting a near
‘natural’ line shape
• Numerically subtract baseline
• Divide the spectrum by the baseline signal
• Take natural logarithm of the resulting data to get
naperian absorbance (Beer–Lambert law)
210-270 GHz - Heterodyne system
TE11 A SUBMILLIMETER CHEMICAL SENSOR.
Optics Letters, 35, 10, 1533 (2010)
Spectroscopic Temperature
Determination
Line Shape Function
Line Strength - S
2  E / kT
8 n L
 h / kT
A
 g ( )   ( 1  e
) g l  i ,l u e
3ch Q
i x, y, z
3
Same for every transition
•Identify a set of ‘good’ (unperturbed, not blended, not
saturated) previously assigned transitions – ‘reference’
lines
•Fit experimental intensities of the reference lines to the
cataloged values to obtain spectroscopic temperatures
and number density for every temperature scan
Pressure Broadening
ln 2
g ( ) 
e

   0 

 ln 2 

 D 
2
1   PB 


 1 
 D   D 
1%
 K K
1  ;  0.21  0.27
  
Normalizing Spectral Intensities
• Scale Absorbance spectra for each temperature
by the corresponding nL/Q parameter
Data reduction strategies
1. Fitting of the peak intensities for Line Strength
and Lower State Energy
2. Point by point fitting of every frequency slice
of the spectral data
1
2
Fitting of the peak intensities
1. Identifiable blends are
fitted to multiple Gaussians
2. Peak absorbance of each line is
then fitted to the theoretical
model to obtain line strength
and lower state energy




A
  ln S  E / kT
ln  3
 8 n L

 h / kT
 g ( )   ( 1  e
)

 3ch Q

Point by point fitting
g ( )  e
 E / kT
e
   0 

ln 2

 D 
2
e
 E / kT
e

  0 2
W
kT
e
 E / kT
e
~
 E / kT
1. This is an exact expression for an unblended Doppler limited spectral line
2. On line center the point by point and Peak fitting give the same result
Comparison with catalog and
experimental data
Comparison of the Point by Point
fitting to the experiment and catalogs
Catalogs
Fitting of
the peak intensities
Point by point
fitting,
Experimental
data

C 2 

1  e T

Absorbance( )
 C1  M 
nL
T
Q
http://splatalogue.net/
ApJ, 714, 476
Online Supplementary Materials


 ~ C3  E~
 Se T
nm 2 K1/2
C1  54.5953
amu 1/2D 2
K
C2  4.799237 10-5
MHz
K
C3  1.43877506
cm -1
Conclusions
• 3D temperature resolved spectroscopic technique provides
experimental and numerical tools for measuring line strengths
and lower state energies of every spectral transition without
spectroscopic assignment
• Latest enhancements of the numerical algorithms address the
effects of pressure broadening and spectral overlaps
• Data is cataloged as Frequency, Strength and Lower State
Energy at http://splatalogue.net/
• Point by point fitting parameters provide means to predict
entire spectra at a user specified temperature. They are
cataloged as online supplementary materials of the
Astrophysical Journal (ApJ 714 476).