"The RCW 38 region observed with IRAC on Spitzer. The plot shows a three-band false color image of the cluster, where the mosaic at each wavelength was created from the four epochs of data combined using the Montage mosaicing software. The field shows the overlap region of the four IRAC bands. Blue is 3.6μm, green is 4.5μm, and red is 8.0μm. The reddish hue at 8.0μm is due mainly to diffuse PAH emission. Emission from shocked hydrogen is visible in green. The outline of the Chandra ACIS-I field of view is overlaid as a white square." From Winston et al (2011)

They found: “..624 YSOs: 23 class 0/I and 90 flat spectrum protostars, 437 Class II stars, and 74 Class III stars. We also identify 29 (27 new) O star candidates over the IRAC field. Seventy-two stars exhibit IR-variability, including seven class 0/I and 12 flat spectrum YSOs. A further 177 tentative candidates are identified by their location in the IRAC [3.6] vs. [3.6]-[5.8] cmd. We find strong evidence of subclustering in the region. Three subclusters were identified surrounding the central cluster, with massive and variable stars in each subcluster. The central region shows evidence of distinct spatial distributions of the protostars and pre-main sequence stars. A previously detected IR cluster, DB2001 Obj36, has been established as a subcluster of RCW 38. This suggests that star formation in RCW 38 occurs over a more extended area than previously thought. The gas to dust ratio is examined using the X-ray derived hydrogen column density, NH and the K-band extinction, and found to be consistent with the diffuse ISM, in contrast with Serpens & NGC1333. We posit that the high photoionising flux of massive stars in RCW 38 affects the agglomeration of the dust grains.”

They used Montage to make mosaics of data at different wavelengths with the Spitzer MIPS and IRAC instruments and place them on a common pixel sampling, projection and coordinate system

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.

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.”

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.”

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.