Decoding Supernova Remnant Morphologies

We present a method for analyzing supernova remnants (SNRs) by diagnosing the drivers responsible for structure at different angular scales. Using a set of modeled remnants we demonstrate how power spectral analysis can be used to attribute which scales in a SNR are driven by RTI and which must be caused by intrinsic asymmetries in the initial explosion. We predict the power spectrum of turbulence driven by RTI and identify a dominant angular mode which represents the largest scale that efficiently grows via RTI. We find that this dominant mode relates to the density scale height in the ejecta, and therefore reveals the density profile of the SN ejecta. If there is significant structure in a SNR on angular scales larger than this mode, then it is likely caused by anisotropies in the explosion. Structure on angular scales smaller than the dominant mode exhibits a steep scaling with wavenumber might be determined by the saturation of RTI at different length scales. We also demonstrate, consistent with previous studies, that this power spectrum is independent of the magnitude and length scales of perturbations in the surrounding medium and therefore this diagnostic is unaffected by "clumpiness" in the CSM. Our method provides a new path for diagnosing the physics driving SNRs and in the future should also be performed on observed SNRs. By comparing what we learn from the power spectra of models to the power spectra of observations we can make quantitative inferences about the SN explosions from the morphology of their remnants.