A Montage Word Cloud

I thought I would have a change of scenery this week and have a little fun. The other week, I posted a word cloud for my other blog, Astronomy Computing Today, so I went to the wordle web site and created a word cloud for the Montage blog. A word cloud takes the words in the blog posts since I started the blog in May 2010, and creates a graphic that gives greater prominence to words that appear more frequently in the source text.

Montage is prominent, but so are pixel and flux, rather than software engineering and computing terms. This likely reflects that the posts are more about astronomical applications of Montage and how astronomers use it, rather than the architecture of the application.

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The Difference Between The Mosaicking Features of Skyview and Montage

One of the questions we are often asked is what is the difference between Montage and the mosaic capabilities offered by the  Skyview Virtual Telescope at NASA’s High Energy Astrophysics Archive Research Center.

My colleague John Good, the Montage architect, describes the difference as follows:

“Montage is much more slavishly flux conserving than Skyview. By default Skyview uses an interpolation between neighbor input pixels to determine the output value of a pixel.  It only has one mode that is close to flux conserving and this only works exactly for certain projections where pixel edges can be treated as straight lines even after reprojection (though not a bad approximation most of the time).

Montage has been extensively tested and shown to conserve flux (to the floating-point round-off limit) for all projections.  Pixel edges are treated as spherical coordinate curves.  Also, reprojected areas for fractional pixels are preserved exactly so there are no edge effects at all when mosaicking.

Montage can be used with all standard projections in the WCS libraries. Going by the Skyview documentation, it only supports seven.  Similarly, Skyview only supports a few specific coordinate systems while Montage allows full precession (e.g. Ecliptic B1983.5 -> Equatorial J2011.0).

Montage includes an extensive set of tools for background matching over the complete set of overlapping input images based on an iterative relaxation technique

Montage is written in C for speed. The newer version of Skyview is written in Java.  When dealing with complex spherical trigonometry, C is much faster.  Skyview often looks fast, but this is mostly due to the default resampling and background handling.

Finally, Montage is broken down into a set of modules that can be
run intependantly and processing can therefore be heavily parallelized with very little effort.  In fact, Montage has been used extensively by the IT community to test large-scale parallelization and workflow environments.”

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Montage Used In Study Of Polycyclic Aromatic Hydrocarbons (PAHs)

Rosenberg et al. (2011) recently reported on a study of Polycyclic Aromatic Hydrocarbons(PAHS), which cause very strong emission line features in the mid-infrared (10 – 20 microns), in the Photo-Dissociation Region (PDR) of  NGC 7023. As part of this study, they obtained Spitzer observations of the PAH’s, and used Montage to regrid maps of the power in the emission lines as a starting point for their analysis.

IRAC 8 micron image of NGC 7023. The white box is the field of study around the PDR NGC 7023-NW.

IRAC 8 micron image of NGC 7023. The white box is the field of study around the PDR NGC 7023-NW.

Rosenberg et al. write:  “The aromatic infrared bands (AIBs) observed in the mid infrared spectrum are attributed to Polycyclic Aromatic Hydrocarbons (PAHs). We observe the NGC 7023-North West (NW) PDR in the mid-infrared (10 – 19.5 micron) using the Infrared Spectrometer (IRS), on board Spitzer. Clear variations are observed in the spectra, most notably the ratio of the 11.0 to 11.2 micron bands, the peak position of the 11.2 and 12.0 micron bands, and the degree of asymmetry of the 11.2 micron band. The observed variations appear to change as a function of position within the PDR. We aim to explain these variations by a change in the abundances of the emitting components of the PDR. A Blind Signal Separation (BSS) method, i.e. a Non-Negative Matrix Factorization algorithm is applied to separate the observed spectrum into components. Using the NASA Ames PAH IR Spectroscopic Database, these extracted signals are fit. The observed signals alone were also fit using the database and these components are compared to the BSS components. Three component signals were extracted from the observation using BSS. We attribute the three signals to ionized PAHs, neutral PAHs, and Very Small Grains (VSGs). The fit of the BSS extracted spectra with the PAH database further confirms the attribution to ionized and neutral PAHs and provides confidence in both methods for producing reliable results. The 11.0 micron feature is attributed to PAH cations while the 11.2 micron band is attributed to neutral PAHs. The VSG signal shows a characteristically asymmetric broad feature at 11.3 micron with an extended red wing. By combining the NASA Ames PAH IR Spectroscopic Database fit with the BSS method, the independent results of each method can be confirmed and some limitations of each method are overcome.”

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Discovery of diffuse emission in the galaxy cluster A1689

Vacca et al (2011) have used Montage in their investigations of the radio continuum emission in  A1689 through archival observations at 1.2 and 1.4GHz, obtained with the Very Large Array.

Total intensity radio contours of A1689 at 1.2GHz (VLA in DnC configuration) with a FWHM of 30′′ × 30′′. Vacca et al 2011.

They reported the discovery of an extended, diffuse, low-surface brightness radio emission located in the central region of the cluster. They classified the source as a radio halo, given that its physical properties are consistent with extrapolation of the properties of known radio halos.

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Montage Included In Astrophysics Source Code Library (ASCL)

Montage now has an entry in the Astrophysics Source Code Library (ASCL), housed on the discussion forum for Astronomy Picture of the Day (APOD) at http://asterisk.apod.com/viewforum.php?f=35.  The Guide states that: “The Astrophysics Source Code Library (ASCL) is a free, on-line reference library for source codes of all sizes that are of interest to astrophysicists. All ASCL source codes have been used to generate results published in or submitted to a refereed journal.” The Library also contains a collection of papers on the topic of astronomical software.

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Does Montage Conserve Flux When Changing the Image Resolution?

This question has been asked several times. It was first posed on-line by Loren Anderson on the Astrobetter page on image mosaics:

“An important note on Montage is that it does not conserve flux when changing the image resolution. For example, if you want to rebin the image to a pixel size three times larger, the flux of all point sources will decrease by a factor of 9 (3^2). Multiplying by the ratio of the pixel areas, (new_pixel_size/old_pixel_size)^2, will get you back to the original flux. This can be done via the “-x” flag in Montage’s mProject. A “conserve flux” flag in Montage, as in MIDAS, would be nice though.”

My colleague John Good responded:  “Montage is very careful to conserve flux in how it redistributes pixel content (in fact the method used for the slower reprojection algorithm does so using spherical angles even at the pixel scale). The problem arises in not being able to know whether the units of the data represent a flux or a flux density. If the former, she is correct but most of the datasets we have encountered in practice have been flux densities, where such scaling would be inappropriate.

However, if there are enough people that need rescaling like this, we would be happy to include it. It’s a trivial addition; we just try to avoid too many extraneous flags. Anyone desiring additional functionality can write to me directly.

By the way, whenever possible you should try to use mProjectPP, as it is 25-30 times faster than mProject. The former can handle any projection pair; the latter is more restrictive but for small areas can often be used even with some of the odder projections through a little mathematical trickery (creating a “distorted” tangent-plane projection that fits the image locally).”

This material first appeared on the Astrobetter site.

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What Are The “Area Files” That Are Produced With The Mosaics?

Montage returns with each mosaic an “area file” in FITS format that contains the total amount of sky area (steradians) that contributed to the value of a pixel. It weights  the output flux by the “areas” of the contributing inputs.

The Montage Reprojection algorithm, including accurate calculations of the areas of individual pixels contributing to the outoput flux of each pixel.

The Montage Reprojection algorithm, including accurate calculations of the areas of individual pixels contributing to the outoput flux of each pixel.

The file is a useful quality assurance tool and comes into play in three places:

  • Around the edges of a reprojected image, where there may be a pixel where only a tiny  area contributes to its value;
  • When the projection covers enough sky that the projection distortions onto the image plane return different areas for pixels on the edges versus in the middle; and
  • When are co-adding values from multiple images where the previous two effects require different weightings for the contributing pixels.

A concrete example will help illustrate how the values are calculated .  Suppose you reproject image A and an edge pixel in the input has a value of 1.523 but only overlaps the corresponding output pixel by 10%.The output pixel flux value would still be 1.523 but
the relative area value would only be 0.1.  A second image B covers the same output pixel with a value of 1.621 but completely, so the area is 1.0.  Then when we coadd, we want to give the coadded pixel the  value of

(1.523*0.1 + 1.621*1.0) / (0.1 + 1.00) = 1.612

i.e., weighting the output flux by the “areas” of the contributing inputs.  The “area” of the output pixel (which is now more of a weight for future use) is the combined 1.1.  If I have lots of input images for the same output location, I can easily have fairly
large “areas”.

Adapted from material prepared by Dr. John Good (IPAC)

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