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Transcript of 1 Brent Harris, 3 Anthony Remijan, 1 Kevin Lehmann, 1 Brooks Pate 1 University of Virginia; 2...
1 Brent Harris, 3 Anthony Remijan, 1 Kevin Lehmann, 1 Brooks Pate1 University of Virginia; 2 Virginia Image and Video Analysis; 3 National Radio Astronomy
Observatory
Identifying Local Chemical Environments in Orion KL by Broadband Data Cube Analysis
Orion KL EVLA Demonstration ScienceK band WIDAR: 3 x 1GHz, 1.5hr integrations, 12 Dishes (Dec, 2009)
Interacting with Image Space~10 kPixel
Pixels: 96 X 96 (1’ x 1’)Synthesized beam: ~1.5”
Interacting with Spectral SpaceData Channels (Frequency): 24,012
1.5km/s or 125kHz resolutionBandwidth: 23.6 – 26.6 GHz
Final image format illustration
10,000Spectra
24,012Images
File Size: 885 MB (~220 million data points)
Spectrum: Everything behind a pixel
Broadband Spectral Diversity
Chemical variation
Energy variations
Absorption/Emission
Orion KL ALMA Demonstration ScienceBand6: 5 x 8GHz, 15min integration, 22 Dishes (Mar, 2012)
Interacting with Image Space10 kPixel
Pixels: 100 X 100 (40” x 40”)Synthesized beam: ~0.6”
Interacting with Spectral SpaceData Channels (Frequency): 76,800
0.6 km/s or 500kHz resolutionBandwidth: 213.7 – 246.6 GHz
10,000Spectra
76,800Images
File Size: 3 GB (7.680 billion data points)Raw data > 30GB
What is behind the Hot Core pixel???
Broadband Spectral Diversity
2 data sets and already a challenge
Fundamental Science
1) What chemicals are present in the ISM? (1D question)
How to use all dimensions at once???
2) What are the distinct chemical environments? (2D question, spatial resolution)
3) What is the unique composition of the chemical environments? - parent molecules and the ensuing chemistry - A 3D BROADBAND PROBLEM, BUT USUALLY TURN IT BACK INTO A 1D PROBLEM
Using the broadband interferometers
1 What Chemicals are Present?Spatial information increases confidence in line assignments…
SO2
817 – 726 , EL = 35K??? SO2
826 – 919 , EL = 42K
Want to QUANTIFY the correlation
826 – 919 Distribution
Flux (Jy/bm)
450
0
0
96
96
Pixel
Pixe
l
817 – 726 Distribution
Flux (Jy/bm)
450
0
0
96
96
Pixel
Pixe
l
Sum Methyl Formate Channels
Flux (mJy/bm
)130
0
0
0
96
96
Pixel
Pixe
l
Sum Ammonia Channels
Flux (Jy/bm)
450
00
9696
Pixel
Pixe
l
Sum OCS Channels
Flux (mJy/bm
)140
0
0
0
96
96
Pixel
Pixe
l
Sum Ammonia Channels
Flux (Jy/bm)
450
0
0
96
96
Pixel
Pixe
l
“Double Resonance” in Astronomy
Image Correlation: (Pearson’s correlation coefficient)
CH3OCHOOCSNH3 NH3
r ≈ 1 r << 1
Take a cue from Digital Image Correlation applications…statistical analysis, security, document verification
Chemical Correlation
r ≈ 1Practically perfect correlation by Pearson’s coefficient
Two oxygen containing molecules with similar distributions
Correlation SpaceImaging the spatial and spectral information together-generate a coefficient for each pair of data channels (240122)
Red – high correlation between two data channels
Diagonal – each data channel perfectly correlated to itself
Box width – line width of a spectral feature
Featureless channels can be dropped
2 Distinct Chemical Environments
*Axes are a non-linear progression of data channels (compression)
Data compression to visualize the whole dataset(only bright data channels are retained)
Correlation is NOT high between all spectral lines
Indicates two different environments (images of these data channels are very different) NOT high between all spectral lines
Comparisons of spectral features
*Axes are a non-linear progression of data channels (compression)
First 8,000 data channels Full data set compressed
Two different emission features
Comparison of Spectral Features
AmmoniaConsistent Self Correlation
MethanolIncomplete Self Correlation
What are the images at line center?
Hot Core NH3 vs Methanol Masers
NH3
Ammonia
CH3OH
Methanol
Distinctly different image and line shape
Correlation of Spectral Wings
What are the images in the wings?
Channel by Channel Imaging
80% correlation to “hot core” image (r=0.80)
Sum these channels for each of 8 methanol masing lines.
Can find many distinct environments in one spectral line.
(B)
LTE Methanol
LTE Methanol in Orion KL “Hot Core”
Found the “hot core” methanol measured by Wang et al. 2011, A&A, 527, A95 (HEXOS) Thermalized at about 120K.
Black: Methanol HC fluxvalues
Red: Simulated methanol LTE spectrum at 120K
Separated Masing spectrum from LTE
3 Chemical CompositionCo-spatial Chemistry
All of these features are co-spatial
Really a frequency axis
Extracting Co-spatial Spectra
All emission that is correlated to the hot core (blue) can be extracted from the sum spectrum over all space (black). Extended emission does not contaminate.
The doublets in the black spectrum (methyl formate) do not appear in the hot core.
Conclusions – a Data Enabled AgeThe computer storage and processing capabilities are barely compatible with data throughput at JVLA and ALMA.
Working in “correlation space” is an innovative way to address the capabilities of new technology and answer fundamental science questions.- Gives the human eye a more comprehensive view of the data- Works in a numeric space that is compatible with automation- Reduces the data set to manageable sizes- Incorporates a statistical result opposed to qualitative analysis- Pattern matching in flux space and correlation space
Correlation space analysis can be used for:- Aiding spectral assignment (pattern matching in flux or correlation)- Extracting co-spatial features- Identifying unique physical environments for a species
AcknowledgementsClare YangVirginia Imaging and Video Analysis
Crystal BroganNational Radio Astronomy Observatory
Pate LabEric HerbstUniversity of Virginia
This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-0809128
Peter Schilke
Karl Menten