A systematic meta-analysis of physical parameters of Galactic supernova remnants

TL;DR

The study compiles optical measurements of shock velocity and electron density for 64 Galactic SNRs, using a Monte Carlo approach to homogenize heterogeneous uncertainties and region-specific data. It finds that electron densities follow a log-normal distribution while shock velocities follow a positively skewed log-normal distribution, and that younger remnants exhibit larger intra-object dispersion due to clumpy ambient media. The authors compare the velocity–age trends to the Cioffi SNR evolution model, finding general agreement but substantial scatter arising from environmental complexity and evolutionary histories. The work provides a foundational population-level view of SNR physical parameters and highlights methodological limitations and future data needs to refine models of SNR evolution across different environments.

Abstract

Supernova remnants (SNRs) are the aftermath of massive stellar explosions or of a white dwarf in a binary system, representing critical phases in the life cycle of stars and playing an important role in galactic evolution. Physical properties of SNRs such as their shock velocity, density and age are important elements for constraining models for their evolution and understanding the physical processes responsible for their morphological appearance and emission processes. Our study provides, for the first time, a comprehensive statistical analysis of the physical parameters in 64 Galactic SNRs both as a population as well as regions within individual objects. These 64 objects represent the subset of the 310 known Galactic SNRs for which there are published optical data, from which we compiled their physical parameters through an exhaustive literature survey. Through a systematic statistical analysis accounting for uncertainties and/or upper and lower limits in these parameters we obtain distributions of the electron density and shock velocity in the studied SNRs and regions within them. This information is combined with constraints on their age and type. Analysis of electron density and shock velocity distributions for the entire sample of SNRs shows that they are consistent with a log-normal distribution and a skewed log-normal distribution, respectively. Within individual remnants, our study reveals that electron density and shock velocity show larger scatter in younger objects, reflecting the varying conditions of the ambient medium immediately surrounding the explosion epicenter and their impact on SNR evolution. Comparison of the dependence of the shock velocity and density on the supernova age with expectations from theoretical models shows good agreement.

Figures (11)

• Figure 1: Distribution of Galactic SNRs with available density and velocity measurements with respect to the parent sample in the catalog of Green, in terms of their angular size and age. 'Very Young', 'Young', 'Mature', and 'Old' refer to SNRs with ages $<1$ kyr, $1-5$ kyrs, $5-10$ kyrs, and $>10$ kyrs, respectively.
• Figure 2: Visualisation of the Monte Carlo sampling process used in this work. Top: Each histogram represents a sample of a thousand draws from appropriate distributions relative to the data type of each indicative shock velocity measurement of Table \ref{['tab:abc']} which is displayed at the top in units of km s$^{-1}$. Bottom:Left: The histograms combined into a single plot. Right: Combining the drawn samples for each shock velocity measurement into a single histogram and calculating the median value and standard deviation of the final sample.
• Figure 3: Electron density measurements for the different objects in our sample. Each object may have different measurements representing different regions within the remnant. Multiple measurements for a single region were grouped together according to a Monte Carlo method described in Sec. \ref{['sec:3']}. Objects G13.3-1.3, G38.7-1.3, G66.0-0.0, G67.6+0.9, G120.1+1.4, G159.6+7.3, G260.4+3.4, G284.3-1.8, and G327.6+14.6 do not have available electron density measurements in the literature. However, for a few objects, namely G120.1+1.4, G284.3-1.8, G299.2-2.9, and G327.6+14.6, pre-shock densities are reported and these are then multiplied by a factor of 4 to obtain an estimate for the post-shock density (see second to last paragraph of Sec. \ref{['sec:4']}).
• Figure 4: Shock velocity measurements for the different objects in our sample, color-coded with respect to the measurement method used. Each object may have different measurements representing different regions within the remnant. Multiple measurements for a single region were grouped together according to a Monte Carlo method described in Sec. \ref{['sec:3']}. Objects G7.7-3.7, G64.5+0.9, G67.8+0.5, G213.0-0.6, G292.0+1.8, G296.1-0.5, G296.5+10.0, G320.4-1.2, G326.3-1.8, and G332.5-5.6 do not have available shock velocity measurements in the literature.
• Figure 5: Shock velocity distribution within individual objects. Available measurements are grouped by region of SNR, so frequencies add up to the total number of regions observed per remnant. Legends show the age (in yrs) of each object, mean velocity (in km s$^{-1}$) and coefficient of variation (dimensionless) of the sample, as well as the bin size of each histogram in units of km s$^{-1}$. The latter has been adapted based on the dynamic range of the measurements. Top: Shock velocity measurements for 133 distinct regions within G327.6+14.6 from 2013Sci...340...45N. The inset shows measurements from independent studies.