WH04 NUMERICAL AND EXPERIMENTAL ASPECTS OF DATA ACQUISITION AND PROCESSING IN APPLICATION TO TEMPERATURE RESOLVED 3-D SUB-MILLIMETER SPECTROSCOPY FOR ASTROPHYSICS AND SPECTRAL ASSIGNMENT. –> WH05 Ivan R. Medvedev, Sarah M. Fortman, Christopher F. Neese, and Frank C. De Lucia

Class 1 Weeds 1) JPLCologneHitran Methanol – CH 3 OHv t =0,1 (<1 THz) Methyl Formate – HCOOCH 3 v t =0,1 (<1.7 THz) Dimethyl Ether – CH 3 OCH 3 GS (<2.2 THz) Ethyl Cyanide – CH 3 CH 2 CNGS (<3.3 THz) GS(<2.5 THz) Class 2 Weeds 1) Vinyl Cyanide – C 2 H 3 CN GS, v 11 =1, v 15 =1 (<2 THz) GS (<2 THz) Sulfur Dioxide – SO 2 GS (<7.6 THz), v 2 =1 (<5.9 THz), S 33 (<3.5 THz), S 34 (<6.8 THz) S 32, S 34 Methyl Cyanide – CH 3 CN GS, v 8 =1 (<1.8 THz) cm -1 Cyanoacetylene – HC 3 NGS (<1.05 THz) Extensive Acetaldehyde – CH 3 CHOGS, v t =0,1 (<.9 THz) TC06, TC07, WH13 Astronomical ‘Weeds’ 1) REPORT FROM THE WORKSHOP ON LABORATORY SPECTROSCOPY IN SUPPORT OF HERSCHEL, SOFIA, AND ALMA Pasadena, California October 19 and 20, 2006 MH03,TC11,TC10 WH10 TH11-13, WH08

Spectral Intensity Distribution (Ethyl Cyanide) Ground State Measurements up to 600 GHz No torsional splitting in the GS above 250 GHz (Pearson et al. ApJS, 1994)

Thermal Population of Vibrational Modes 1) of Ethyl Cyanide 1) NIST Chemistry WebBook

Ethyl Cyanide Vinyl Cyanide Methyl Formate Ethyl Cyanide, Vinyl Cyanide, Methyl Formate, Acetaldehyde will contribute more significantly to spectral congestion in THz spectral range ‘Weed’ Spectral Intensities in the THz

Methanol Dimethyl ether SO 2 Methanol, Dimethyl Ether, and SO 2 will also contribute strongly to spectral congestion at higher frequencies

THz spectroscopy

Experimental Record spectra in the temperature range K Pressure ~ 1 mtorr (near Doppler limited line shape) Record spectra in the FASSST mode with post detection bandwidth adequate for detecting 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)

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 for every temperature scan Perform analysis of the temperature dependent line profiles Experimental

Temperature Resolved 3D Spectroscopy Same for every transition We divide the spectral intensity array by the peak intensity of a specific reference transition We form this ratio for a range of experimental temperatures We then fit peak normalized line intensities to equation (1) to obtain line strength S and lower state energy E Line Strength - S (1)

Examples of Experimental Data T=395K T=250K E ref =700 cm -1 E=321 cm -1 E=688 cm -1 E=1179 cm -1

Peak Intensity Entire line profile (Gaussian or Voigt) Fitting Strategies ExperimentFitResiduals

What about blends? 1.Identifying blends Peak List analysis Line Shape analysis Analysis of fitting results for Lower State Energy and Line Strength 2. Dealing with blends Multiple peak fitting Interpolation/Extrapolation of Experimental Data

Data for the Catalogues For the astrophysical measurements within our experimental range of temperatures our data is The Answer For lines that are not blended or identifiably blended our technique provides the line strength (S) and lower state energy (E l ) Fitting of each resolution bin on the frequency axis to a polynomial function of spectroscopic temperature provides for a convenient way to archive spectroscopic data as well as ability to interpolate and extrapolate with adequate accuracy.

Acknowledgments Paul Helminger Thank you

Experimental