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CSO BROADBAND MOLECULAR LINE SURVEYS I: BENCHMARKING GOBASIC ANALYSIS SOFTWARE Mary L. Radhuber, James L. Sanders III, Jacob C. Laas, Brian M. Hays, Susanna.

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Presentation on theme: "CSO BROADBAND MOLECULAR LINE SURVEYS I: BENCHMARKING GOBASIC ANALYSIS SOFTWARE Mary L. Radhuber, James L. Sanders III, Jacob C. Laas, Brian M. Hays, Susanna."— Presentation transcript:

1 CSO BROADBAND MOLECULAR LINE SURVEYS I: BENCHMARKING GOBASIC ANALYSIS SOFTWARE Mary L. Radhuber, James L. Sanders III, Jacob C. Laas, Brian M. Hays, Susanna L. Widicus Weaver Department of Chemistry, Emory University, Atlanta, GA 30322 Darek C. Lis Division of Physics, Mathematics, and Astronomy, California Institute of Technology, Pasadena, CA 91125

2 Motivation for GOBASIC Vast broadband datasets from the CSO, ALMA, and the Herschel Space Observatory ESO/B. Tafreshi (twanight.org) ESA Jacob C. Laas Smallest CSO dataset ~ 30 GHz of data, 32 surveys now on hand

3 Motivation for GOBASIC Probed sources with many complex molecules and many components of gas ALMA ethyl cyanide overlay on Orion spectrum. Fortman, et al., NRAO/AUI/NSF, NASA Increased sensitivity leads to line dense spectra with complex line blending

4 Global analysis Simultaneous multi- molecule, multi- component fitting up to four components Iterative analysis procedure Approach of GOBASIC Time required for analysisComplexity of Analysis Import JPL/CDMS catalogs with no special formatting required Little user input necessary Fast global, derivative- free pattern search optimization Parallel processing capabilities LTE assumptions

5 Global analysis Simultaneous multi- molecule, multi- component fitting up to four components Iterative analysis procedure Approach of GOBASIC Time required for analysisComplexity of Analysis Import JPL/CDMS catalogs with no special formatting required Little user input necessary Fast global, derivative- free pattern search optimization Parallel processing capabilities LTE assumptions

6 Input deconvolved observational data and JPL/CDMS catalog

7 Internal selection of catalog data for line intensity and uncertainty limits Internal calibration of observational data for telescope efficiency and beam dilution

8 Global analysis Simultaneous multi- molecule, multi- component fitting up to four components Iterative analysis procedure Approach of GOBASIC Time required for analysisComplexity of Analysis Import JPL/CDMS catalogs with no special formatting required Little user input necessary Fast global, derivative- free pattern search optimization Parallel processing capabilities LTE assumptions

9 LTE population diagram equations from Goldsmith and Langer (1999) ApJ 517 used to simulate spectra: Pattern search optimization to minimize difference between simulated spectrum and observational spectrum:

10 Global analysis Simultaneous multi- molecule, multi- component fitting up to four components Iterative analysis procedure Approach of GOBASIC Time required for analysisComplexity of Analysis Import JPL/CDMS catalogs with no special formatting required Little user input necessary Fast global, derivative- free pattern search optimization Parallel processing capabilities LTE assumptions

11

12 Output figures show best fit simulations for each component and total simulated spectrum

13 Output files in.csv format include best fit variables with associated errors and simulated spectra for each component

14 Noiseless simulated spectral fit test. Six molecule spectrum simulated. Residual multiplied by 10 6 as to be visible.

15 Fit test on Orion showed good match to observational data and to previous analysis of Orion of Blake et al. 1986 ApJS 60.

16 CPU time ~ 7(trans) + 150e 1.3(components) Time benchmarking trials used CH 3 OH analysis on Orion broadband line survey

17 Single component methyl formate fit on CSO survey of W3. Comparison of residual vs upper state energy. Positive residual is under prediction, negative residual is over prediction. Over prediction of lower E u (K) lines with MAGIX results in skewing toward lower temperatures. Möller et al. 2013 A&A 549

18 Summary GOBASIC analysis is fast, robust, and easy with little data calibration and user input required.

19 Summary Final results are provided conveniently as graphs, simulation files, and tables of best fit parameters.

20 Summary Compared to MAGIX and rotation diagram analysis, GOBASIC is less susceptible to skewed results from incorrect line shape analysis.

21 Future Work Complete Analysis of CSO and HIFI surveys (James Sanders TI07) Expand use of GOBASIC beyond Widicus Weaver lab (Paper submitted to ApJS)

22 Acknowledgements Emory University: James G. Nagy Caltech/CSO: Thomas Phillips, Matthew Sumner, Jonas Zmuidzinas, Frank Rice, Geoffrey Blake, CSO Staff NASA Herschel OT1 Analysis Program RSA No. 1428755 Emory Chemistry Early Career Research Grant Emory SURE and SIRE Programs (funding from Howard Hughes Medical Institute Grant No. 52005873) Emory College Undergraduate Research Matching Grant

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