The Spectral Correlation Function Home Page

This page contains the details and the results from the Spectral Correlation Function (SCF) and its analysis of position-position-velocity data cubes. The SCF is a diagnostic tool which scans these data cubes quantifying the similarities and differences between neighboring spectra in the cubes. We intend to use this information to probe the structure of molecular clouds in the interstellar medium (ISM).

On this page, there are two types of data cubes analyzed. First, observed cubes have been made of several physical objects through radio observations. In addition, theoretical work in MHD simulations has resulted in simulations of the ISM. These simulations can also be used to produce data cubes. Both of these types of data cubes have been analyzed using the SCF algorithm. Maps of the correlation are generated as well as histograms of the values of the SCF results. We present both of these types of data here for your exploration and analysis.

The SCF algorithm is written for IDL 4.0.1 and is compatible with IDL 5.0.x, (though not optimized). The source is available in tar format as well as text documents.

SCF Web Resources

• A short description of the SCF algorithm, emphasizing the mathematical development and the creation of maps of the correlation. (PDF format)
• A detailed description of the entire SCF project in its first implementation including background, mathematical development and techniques, interpretations of maps and basic results is available here(PDF format). Excerpts available include:
  • An introduction to the project and other approaches intended for anyone with a basic scientific background, including brief summaries of other approaches used to date. (PDF format)
  • A mathematical overview of the basic functions used and their derivation. This excerpt also includes a summary of the numerical methods used in calculations on the computer and a summary of the effects of instrumental noise on the data. (PDF format)
  • An introduction to the study of maps generated by the SCF, including the basic interpretations worked out to date. (PDF format)
• The Velocity Methods Home Page of Alyssa Goodman
• The SCF algorithm is written for IDL 4.0.1 and is compatible with IDL 5.0.x, (though not optimized). The source code is available in tar format as well in plain text format here. Please report any problems with the SCF algorithm to erosolowsky@cfa.harvard.edu.
• A recent NSF proposal regarding the SCF project is available for perusal.

Summary of SCF Results

Several data cubes have been analyzed using the SCF routines and the current results are available here.

If you have questions or comments about the SCF project or would like to submit data for analysis by the SCF algorithm, please contact agoodman@cfa.harvard.edu or erosolowsky@cfa.harvard.edu.