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