Spectral and Polarization Tomography

Statistics – Applications

Scientific paper

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Scientific paper

We present simple but powerful new analysis techniques for pairs of astronomical images. These techniques are useful for isolating features that have been blended because they are along the same line of sight. In order to be separable, the features must have different spectral or polarization properties. In spectral tomography, we construct a gallery of images by varying the factor t in the equation: B_t(x,y) \equiv B_1(x,y) - t \times B_2(x,y) where B_1 and B_2 are images at two different bands. Features with a specific color, e.g., B-V = 2.5 x log(t), or spectral index alpha = log(t) x log((nu1 )/(nu2 )) will disappear from their respective tomography images. In polarization tomography, we create a gallery of single Stokes parameter images from the original Q and U images: Q_t(x,y) \equiv Q(x,y) \times cos(t) + U(x,y) \times sin(t) In such projections, even confusion from destructive interference between components can disappear. These techniques have been applied to VLA images of radio galaxies and supernova remnants, and will probably be useful in other applications as well. We will show examples of important new dynamical and spectral features in radio sources that have been uncovered with these techniques. This work is supported in part at the University of Minnesota through NSF grant AST93-18959.

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