For the spatial distribution in the Galaxy, the Lorimer et al. radial
distribution [L06] was used, this model together with the Z-distribution and
the spirlarm model are already implemented in the gammapy libraries
111//docs.gammapy.org/0.6/astro/population/index.html222http://docs.gammapy.org/0.6/astro/population/index.html.

##### Velocity distribution

Plot of rotation speed versus distance from the center of the Milky Way
reveals that the stars do not orbit the center of the galaxy like planets
orbiting the Sun (Keplerian rotation) but rather follow a much flatter
rotation curve. This difference implies much more mass lying far from the
Galactic Center than one would infer from stars and gas detectable at visible,
IR, and radio wavelengths. This in turn implies that most of the mass
($\sim$90%) of the galaxy is dark matter. Other spiral galaxies have similar
ratios of visible to invisible matter. Rotation of the Milky Way can be used
to determine distances of clouds along the line-of-sight. The Galaxy rotation
curve (figure 5.6) is well described by a 7th grade polynomial function whose
coefficients depends on the distance from center, it means that if we know the
distance of the cloud, we compute its velocity. Note that the velocity
calculated by this function is a rotational velocity so we need to convert in
radial velocity taking into account the Sun’s velocity.

Figure 5.6: Plot of the rotation speed versus galactocentric radius. The solid
line correspods to the polynomial function Figure 5.7: Plot of the rotation
speed versus galactocentric radius. The solid line correspods to the
polynomial function

As one can see in figure 5.7, the observed radial velocity of the cloud will
be the difference between the Sun’s component of rotation and the cloud’s
along the line-of-sight:

$V_{rad}=V\cos\alpha-V_{sun}\sin l$ (5.7)

where $V_{sun}$ is the sun’s velocity around the galactic center (220
$kms^{-1}$, V is the rotational velocity and l is the galactic longitude.
After some trigonometry calculations the radial velocity can be write as:

$V_{rad}=R_{sun}\cdot\sin(l)\cdot(\frac{V_{rot}}{r}-\frac{V_{sun}}{R_{sun}})$
(5.8)

where R is the distance from galactic center and $R_{sun}=8.5$ $kpc$

##### Mass

I had a catalog of Molecular cloud positions, without any information about
the mass of the object. To associate a reasonable mass I used the mass
distribution function derived in the Rice catalog. I considered only regions
in the solar circle (I-IV) and mass above $10^{5}M_{sun}$, since the catalog
is almost complete in these conditions. As one can see in figure 5.3 this
function is a truncated power law with index $\gamma=-1.72$. If the
differential mass distribution function is extrapolated up to the current
instrument sensitivity limit ($M_{cloud}\sim 10^{3}$) and then this function
is integrated, the number of molecular clouds obtained is 13500. This is the
number of the clouds that should be simulated. To associate randomly a mass to
each cloud, the idea was to choose a set of 13500 values on the
$N(M^{{}^{\prime}}>M)$ axis that intersect the mass distribution function and
get the corresponding mass value, then associated the mass values with the
positions of the molecular clouds.

I had all the physical parameters to compare the synthetic population of
molecular clouds with the real one. The aim of the comparison is to calibrate
the model with observations, since the Rice et al. catalog is complete only
within the restriction mentioned above, applying that restriction 156
molecular clouds were obtained, comparable with the 153 real molecular clouds
in the Rice et al. catalog. In figure 5.10 the synthetic molecular cloud
population and the MC of the Rice et al. catalog are superimpose. Figure 5.8
represent the comparison between the mass distribution of real (blue) and
synthetic (red) population of molecular clouds, the dashed black line is the
completeness limit suggest by Rice et al. In figure 5.9 are compared the
radial velocity distributions of the two populations. Executing a two sample
Kolmogorov-Smirnov test on mass, positions and radial velocity distributions,
the two population of molecular clouds (the synthetic and the real one) are
compatible, this means that in principle the Rice et al. sample could be
extract from the synthetic population.

Figure 5.8: Comparison between the mass distribution of real (blue) and
synthetic (red) molecular clouds Figure 5.9: Comparison between the radial
velocity distribution of real (blue) and synthetic (red) molecular clouds
Figure 5.10:  Galactic map of all clouds, in blue are reported all the
synthetic clouds, the pink point are for all the Rice MCs while the red and
the green point are for synthetic and real (respectively) MCs after the "Rice
cut". The Sun’s location is marked with a yellow star, and the Galactic Center
is marked with a black “x”. The dashed purple line represent the solar circle

###  5.2 Spectra of Cosmic rays in Molecular clouds

The gamma emission from the interacting supernova remnants comes from the
interaction between cosmic rays protons accelerated by the supernova shock and
the nuclei of atoms present in the molecular cloud. Reproduce the interaction
between protons and nuclei means creating the protons injection spectra and
estimate the synthetic molecular clouds density.

##### Injection spectra

Thanks to the catalog I’ve made, for each of the 16 interacting supernova
remnants confirmed up to now, all the spectral parameters of the protons
distribution are available. The idea was to create a gaussian distribution for
each parameters ($\alpha$, $\beta$, Break Energy) starting from mean and
standard deviation values of the real interacting supernova remnants (see
table 5.3).

| $\alpha$ | $\beta$ | Break Energy ($E_{b}$)
---|---|---|---
|  |  | (MeV)
Mean | 2.43 | 3.60 | $10^{5.49}$
Std | 0.21 | 0.78 | $10^{1.11}$
Table 5.3: Mean and standard deviation values of the proton power law spectra
of the real SNR.

Note that this values are not statistically very significant because of there
are few objects, therefore I assumed that if we knew much more interacting
supernova remnants their spectral parameters would be distributed following a
Gaussian curve with mean and sigma value close to those are in table 5.3. I
extracted randomly the spectral parameters value for each synthetic
interacting supernova remnants. These extracted parameters will be those of
the broken power law proton distribution for the Naima pion decay spectra
calculation, figure 5.13 and 5.12 clarify the method. I point out that the
$\beta$ index must be greater than the $\alpha$ index. This problem was solved
creating the Gaussian distribution of $\alpha-2$ instead of $\alpha$ and
extracting only positive values.

Figure 5.11: Example of the spectral parameters extraction

Figure 5.12: Example of Protons distributions and $\pi^{0}$-decay spectra
resulting from the parameters extracted

##### Molecular clouds density

Generate the synthetic interacting supernova remnants spectra requires besides
the particle distribution, the density of the target protons. As the other
this parameter must be randomly extracted from the distribution generated
starting from the observed values. Since I hadn’t the information about the
density of the target protons in the molecular clouds of real interacting
supernova remnants, I used the Rice et al. catalog. Some reasonable hypothesis
must be done, the first assumption is that the molecular clouds have the same
density everywhere, so the target protons density can be confused with the
clouds density. Another approximation is that molecular clouds are spherical.
Now using the mass and the size (diameter) of the real molecular clouds, I
calculated the density and then the mean and standard deviation values of
proton’s density. Note that, to not introduce any bias, only molecular clouds
with mass above $10^{5}M_{sun}$ are considered in the density calculation.

Figure 5.13: Density distributions of real (orange) and synthetic (blue) MCs

For calculation efficiency, I associated an injection spectra to each
synthetic molecular cloud, as if all molecular cloud have a supernova remnants
nearby. Surely not true, but this allows me to obtain the LogN-LogS of the all
synthetic interacting supernova remnants (red line in figure 5.14) that is
crucial to find a probability function that returns the correct number of
synthetic iSNR.

###  5.3 The molecular clouds - SNR association

The results is a catalog of 13500 interacting supernova remnants distributed
in the Galaxy. Certainly not all the molecular clouds have a SNR nearby,
therefore I had to estimate how many of supernova remnant-molecular cloud
systems can form in the Galaxy. I introduced a probability function that in
principle depend on the clouds mass as

$P(M_{MC})=p_{0}\cdot(\frac{M_{MC}}{m_{0}})^{\alpha}$ (5.9)

in which $M_{MC}$ is the molecular cloud mass, $m_{0}$ is the reference mass
fixed at $10^{4}\,M_{sun}$. The free parameters are $p_{0}$ (probability
parameter) and $\alpha$, by acting on these parameters the LogN-LogS curve of
all the synthetic interacting systems (i.e red line in in figure 5.14) changes
towards the curve of the real interacting supernova remnants. Since in
principle there are almost infinite pairs of parameters that reproduce the
slope on the real iSNR LogN-LogS in the completeness region, I set the
$\alpha$ exponent a priori equal to: -1, 0, 1, 2 and then for each exponent
the best $p_{0}$ value was found, results are reported in table 5.4. The best
probability values was found by making 1000 extraction from the synthetic iSNR
catalog, meaning 1000 LogN-LogS, keeping fixed the probability function
exponent and calculated the average LogN-LogS curve. The method used to
averaging 1000 curves in the completness region, is fix the flux of the real
iSNR in that region and interpolate the curves at this fixed fluxes. The
goodness of the obtained LogN-LogS is evaluated making a two sample
Kolmogorov-Smirnov test between the real interacting supernova remnants LogN-
LogS and the synthetic one in the significant region. Results reported in
figure 5.14 clarify that the only possible probability function is the flat
one (orange line, $\alpha=0,\,p_{0}=0.015$), because the linear and the
quadratic option do not reproduce the real iSNR LogN-LogS curve at all,
instead the curve with $\alpha=-1,\,p_{0}=0.07$, even if fit the real iSNR
behavior, provides $\sim$ 3000 interacting SNR in the Galaxy, about 10 times
all the supernova remnants seen in the Galaxy. For these reason I considered
only the flat probability at 1.5%, therefore, the number of the interacting
system expected in the Galaxy in this model is about 200. The next step is to
simulate each of these synthetic interacting supernova remnants with CTA to
estimate how many of these systems have flux above the CTA sensibility
threshold.

$\alpha$ | -1 | 0 | 1 | 2
---|---|---|---|---
$p_{0}$ | 0.07 | 0.015 | 0.002 | $10^{-6}$
Table 5.4: $p_{0}$ values found. Figure 5.14: LogN-LogS curves of: all the
synthetic iSNR in red color, black is for the real iSNR,
$\alpha=-1,p_{0}=0.05$ in blue, $\alpha=0,p_{0}=0.015$ in orange,
$\alpha=1,p_{0}=0.002$ in green and pink for $\alpha=2,p_{0}=10^{-6}$.

###  5.4 Repetition

Since the number of the interacting systems extracted from the synthetic iSNR
catalog depends on the realization, to exclude any possible selection effects
100 realizations were made keeping fixed probability function parameters (see
figure 5.15). As one can see in figure 5.16 the interacting system number goes
from 172 to 235 and the mean value is 202 . Basically each realization is a
set of synthetic interacting supernova remnants positions, dimensions,
spectra, integrated fluxes in 100 MeV-10TeV or 0.1-100 TeV energy bands.

Figure 5.15: LogN-LogS curves of: all the synthetic iSNR in red color, black
is for the real iSNR, 100 realization with $\alpha=1,p_{0}=0.002$ in blue
color  Figure 5.16: Distribution of the number of interacting system
extracted, the red line is the average number of iSNR extracted.

##  Chapter 6 Simulation and analysis

In general, simulating an astronomical observation consists into randomly
generate events that will be produced by both background and sources, assuming
a precise spatial and spectral model. The simulation algorithms are
implemented in ctools and are based on Monte Carlo methods. All the generated
events are weighted with the instrumental response functions (IRF) in order to
estimate the number of events that the instrument will effectively be able to
detect. The analysis tools then allow to fit this generated sample of data and
to calculate the statistical significance of them. In this way is possible to
predict the range of confidence in which the parameters of our model will be
constrained.

The likelihood L is defined as the probability of obtaining a certain result
starting from an input model. The input model is defined in a ".xml" file and
contains a description of the gamma ray sources. Each source is divided into a
spatial component, namely the celestial coordinates and the shape of the
object and a spectral component which provides the energy distribution of the
photons. In the input model we choose the free parameters, i.e. the parameters
to be fitted. The fit maximizes the likelihood. The $\chi^{2}$ is related to
the likelihood as : $\chi^{2}$= -2$log\textit{L}$ so maximize the likelihood
is equivalent to minimize the $\chi^{2}$. The input model
$M(E,\vec{p},t|\alpha)$ will be then the differential flux per unit area in
the observed region of the sky as a function of the true energy E, the true
arrival direction $\vec{p}$ and the time of observation t, that is important
for variable phenomena. The term $\alpha$ labels the free parameters of the
model. Once obtained the number of events, the flux is estimated according to:

$\Phi(E^{\prime},\vec{p},|\alpha)=\int
dEd\vec{p}R(E^{\prime},\vec{p^{\prime}}|E,\vec{p})M(E,\vec{p}|\alpha)$ (6.1)

where $R(E^{\prime},\vec{p^{\prime}}|E,\vec{p})$ are the IRFs, as described in
4.3. The more the model resembles the reality, the more probable is to find
results that are close to that model. In other words L is a test of the
goodness of the model.

The population model of interacting supernova remnants that I realized gives
the possibility to predict how many of this systems will detectable by the
Cherenkov Telescope Array and more in general by any future gamma ray
instruments. The intent of the simulations and analysis reported in this
chapter is to give an estimate of how many supernova remnants - molecular
cloud systems CTA can detect. I simulated the sources individually, in the
center of the field of view with only the CTA instrumental background,
certainly since this is an ideal case, the resulting number of detected iSNR
is overestimated but anyway it can provide a good indication on the
possibilities of CTA regarding these extended systems.

###  6.1 Simulation

In order to avoid any possible selection effect and to increase the statistic,
I simulated 10 realization randomly selected. The CTA simulation tools in
ctools (version 1.4.2) is ctobssim. Ctobssim simulates events from the input
model and the instrument response functions (IRF) using a numerical random
number generator. Both the astrophysical sources and the background are
simulated. To perform the simulation basically are required the Instrument
Response Function of CTA and the source model, both the spectral and the
spatial model. The general model is describe in ctools using a model
definition XML file. Below is a simple example of such a file comprising one
source and one background model. Source model is factorized into a spectral
(tag <spectrum>), a spatial (tags <spatialModel>) instead the instrument
response functions contain templates that describes the spatial and spectral
distribution of the background.

$M(x,y,E,t)=M_{spatial}(x,y|E)\times M_{spectral}(E)\times M_{temporal}(t)$
(6.2)

In this specific example (figure 6.1), the source component describes a
diffuse source with a spectral model imported from a file that contains the
punctually defined photons spectra. The spatial model is a source map and the
background component is the CTAIrfBackground, so only instrumental background
is considered. Model parameters are specified by a <parameter> tag with a
certain number of attributes. The name attribute gives the parameter name that
needs to be unique within a given model component. The scale attribute gives a
scaling factor that will be multiplied by the value attribute to provide the
real (physical) parameter value. The min and max attributes specify boundaries
for the value term of the parameter. And the free attribute specifies whether
a parameter should be fitted (free="1") or kept fixed (free="0") in a maximum
likelihood analysis.

Figure 6.1: Example of a source model file

To start the simulation with ctobssim another file is required, namely the
observation file. This file (see figure 6.2) contains the information about
the parameters of the simulation position of the center of the FOV, energy
boundaries, time, calibration database and irf to be used.

Figure 6.2: Example of an observation file

I randomly chose 10 realization, and I simulated each synthetic interacting
supernova remnants as explained above. Ctobssim write two files in the working
directory: events.fits and ctobssim.log. The first file contains the simulated
events in FITS format. The FITS file contain three extensions: an empty
primary image, a binary table named EVENTS that holds the events (one row per
event), and a binary table named GTI holding the Good Time Intervals. The
second file produced by ctobssim is a human readable log file that contains
information about the job execution.

I could look at the simulated sources map using ctskymap. The tool produces
the file skymap.fits which contains a sky map of the events in FITS format
(see figure 6.3). The sky map is centered on the location of the sources and
consists of 200 x 200 spatial pixels of 0.02 x 0.02 degrees in size, covering
an area of 4 deg x 4 deg. The figure 6.3 shows a few simulated interacting
supernova remnants, some of these clearly emerge from the background, instead
the others have too weak flux at TeV energies to be detectable.

Figure 6.3: Sky map of some simulated interacting supernova remnants, the
colorbar and amplitude are the same for all sources.

####  6.1.1 Spectral and spatial models

Spectra models are created as described in 5.2 and converted in $ph\cdot
cm^{-2}s^{-1}MeV^{-1}$. Thus each simulated source has a photons spectra
associated, example of simulated $\pi^{0}$-decay spectra are in figure 5.12
(right). This spectra are defined by a numerical function because it is the
simplest way to simulate a source with spectral model not defined by a
classical functional form. For the spatial model I created a source map for
each simulated interacting supernova remnants, using a python code that fills
a pixels matrix with values from 0 to 1. The filling criteria is the
projection of a sphere on a plane perpendicular to the line of sight, results
of some simulated map are in figure 6.4

Figure 6.4: Some interacting supernova remnants spatial template. The size of
the maps is 4 $\times$ 4 degree.

###  6.2 Analysis

The CTA analysis tools is ctlike that performs a maximum likelihood model
fitting on the data and gives the estimation with the relative error of the
needed parameters. It computes the detection significance, namely the TS
value. The detection significance of a source model is estimated using the so
called Test Statistic (TS) which is defined as

$TS=2(lnL(M_{s}+M_{b})-lnL(M_{b}))$ (6.3)

where $lnL(M_{s}+M_{b})$ is the log-likelihood value obtained when fitting the
source and the background together to the data, and $lnL(M_{b})$ is the log-
likelihood value obtained when fitting only the background model to the data.
Under the hypothesis that the model $M_{s}+M_{b}$ provides a satisfactory fit
of the data, TS follows a $\chi^{2}_{n}$ distribution with n degrees of
freedom, where n is the number of free parameters in the source model
component. Therefore

$p=\int^{+\infty}_{TS}\chi^{2}_{n}(x)dx$ (6.4)

gives the chance probability that the log-likelihood improves by TS/2 when
adding the source model $M_{s}$ due to statistical fluctuations only. For n=1
the significance in Gaussian sigma is given by $\sqrt{TS}$. In figure 6.3,
under each simulated interacting supernova remnants, is reported the TS values
coming from the ctlike likelihood analysis. Ctlike takes in input the model to
be fitted: spectral, spatial and background. For the spatial model I used the
same model of the simulated sources with free normalization, for the spatial
model I used a <RadialGaussian> model at fixed position but with free
$\sigma$. For the background I used only instrumental background with only the
normalization free. Ctlike generates an output model XML file that contains
the values of the best fitting model parameters. For all free parameters, an
error attribute is added providing the statistical uncertainty in the
parameter estimate. Ctlike as ctobssim write two file, the first is an xml
file that containes the best fit parameters resulting from the maximum
likelihood analysis, instead the second is a log file that contains
information registered during the analysis. In figure 6.5 is reported an
example of the analysis output.

Figure 6.5: Example of file resulting from the analysis with ctlike

###  6.3 Results

From the analysis of the 10 realization randomly extracted, I found that CTA
detect between 29 and 52 interacting supernova remnants. The detected sources
are those having a detection at 5$\sigma$ or TS > 25, (see table 6.1).

N∘ simulated sources | 194 | 198 | 191 | 211 | 216 | 181 | 199 | 212 | 214 | 211
---|---|---|---|---|---|---|---|---|---|---
N∘ detected sources | 47 | 44 | 40 | 45 | 50 | 29 | 39 | 42 | 45 | 52
Table 6.1: Number of simulated and detected sources for each realization
considered.

For example the results of the analysis of one realization are reported. I
simulated 199 interacting systems, 39 of of which have significance >
$5\sigma$. The figures 6.7 show the LogN-LogS curve of the interacting
supernova remnants detected in comparison with that of the real iSNRs and with
that of the entire realization. As expected, the logN-logS of the detected
iSNR follow the real iSNR curves, for bright sources, but extends to lower
fluxes, according with the better sensitivity expected for CTA. In figure 6.6
is reported the integrated flux between 100 GeV e 10 TeV versus the simulated
radius. The sources with TS > 25 and the non-detectable ones are separated by
an horizontal line at the CTA sensitivity until fino $\sim$ 0.1∘ namely the
CTA angular resolution. Figure 6.8 show the same behavior in all realizations.
Depending on the realization CTA detect between $\sim$ 30 and 50 synthetic
interacting supernova remnants. Taking into account that simulations and
analysis were done under ideal conditions (only one source for each simulation
and only with instrumental background) this means doubling the number of SNR /
MC systems already known.

Figure 6.6: Plot of the simulated radius versus the integrated flux from 1 to
10 TeV of the selected realization. Red symbol marks the detected sources.
Figure 6.7: LogN-LogS of the real(blue), simulated (orange) and detected
(green) iSNR. On the x-axis flux is integrated from 1 to 10 TeV.

Figure 6.8: Plot of the simulated radius versus the integrated flux from 1 to
10 TeV of all the 10 realization. Red symbol marks the detected sources.

##  Chapter 7 Conclusion

The main goal of this thesis was to create a synthetic population of Galactic
interacting supernova remnants that reflects features of the real iSNR
population. The strategy was to realize the LogN-LogS of the real interacting
supernova remnants and compared it with those obtained from the population
model. Since this sources are composed of a supernova remnants and a molecular
cloud, the population of molecular clouds and the protons injection spectra
has been reproduced separately. The synthetic population of molecular clouds
was derived from the Rice et al. catalog of real molecular clouds. The
synthetic MCs have realistic features in terms of mass and distribution in the
Galaxy. I created the synthetic protons distributions that interact within the
molecular clouds starting from the 16 spectra of the real interacting
supernova remnants. Generate the synthetic spectra requires besides the
particle distribution, the density of the target protons. Both the parameters
of the injection protons spectra and the target density of the clouds were
extracted from the gaussian distribution obtained from the real values that
are contained in the $\gamma$-SNR catalog that I’ve made. The $\gamma$-SNR
catalog contains all the SNR emitting in $\gamma$-ray. For each SNR considered
was carried out an extensive literature research of $\gamma$-ray spectra and
physical characteristics. The spectral fit was performed using a model-
independent approach, namely broken power law as protons distribution and
$\pi^{0}$-decay as radiative model. The key results of the $\gamma$-SNR
catalog was the creation of the LogN-LogS curve of the interacting supernova
remnants obtained by integrating all the interacting SNRs spectra above 100
MeV. Since not all the molecular clouds are illuminated by a supernova
remnants, a mass dependent probability function was introduced. A uniform
probability at 1.5% was the only function that, reproduce the real iSNR LogN-
LogS curve. The number of interacting systems resulting from the synthetic
iSNR depend on the realization, for this reason a large number of realizations
were made. Using the CTA simulation softwares, 10 realization were simulated
and analysed. For each ralization CTA detected between $\sim$ 30 and 50
synthetic interacting supernova remnants. CTA will the be able to extend
significantly the number of the known SNR/MC systems. This will allow to
better understand the role of SNRs in the acceleration of Galactic cosmic
rays.

### Appendix

##### Naima fitting code

Naima requires that all data set are written in ipac format, the ".ipac" file
must contain at least the folliwing information: the mean channel energy,
differential flux, upper flux error, lower flux error and upper limit flag.
Furthermore the file must contain the confidence level (cl) of the flux error
bar (cl=0.95 in this case). The first code is the initialization of the prior
function and of the broken power law that is the protons distributions. The
second code refers to the definition of the function that returns the
$\pi^{0}$-decay spectra, instead the last code is the procedute to start the
NAIMA fitting, namely the file reading and the parameters settings.

Broken power law definition Pion decay model definition Starting MCMC procedure SNR_Name | Type | Other_Names | TeVCat | l | b | Distance | Age | MC_Mass | Flux100GeV | Flux1TeV
---|---|---|---|---|---|---|---|---|---|---
|  |  |  | ∘ | ∘ | $\mathrm{kpc}$ | $\mathrm{yr}$ | $M_{sun}$ | $\mathrm{erg\,s^{-1}\,cm^{-2}}$ | $\mathrm{erg\,s^{-1}\,cm^{-2}}$
G359.1-0.5 | INT | HESSJ1745-303 | TeV J1745-303 | 358.7 | -0.65 | 7.6 | 10000.0 | 50000.0 | 4.177e-12 | 8.425e-13
HESSJ1731-347 | SHELL | HESSJ1731-347 | TeV J1732-347 | 353.54 | -0.68 | 3.2 | 14500.0 | 0.0 | 1.6595e-11 | 6.615e-12
CTB37B | SHELL | HESSJ1713-381 G348.7+0.3 | TeV J1713-382 | 348.63 | 0.38 | 13.2 | 5000.0 | 0.0 | 1.55e-13 | 4.436e-14
CTB37A | INT | G348.5+0.1 | TeV J1714-385 | 348.38 | 0.1 | 9.0 | 16000.0 | 67000.0 | 3.886e-12 | 8.347e-13
RXJ1713.7-3946 | SHELL | G347.3-0.5 | TeV J1713-397 | 347.33 | -0.48 | 1.0 | 1600.0 | 0.0 | 5.84869e-10 | 3.1538e-10
SN1006(NE) | SHELL |  | TeV J1504-418 | 327.84 | 14.56 | 1.6 | 1010.0 | 0.0 | 3.3779e-11 | 2.2221e-11
SN1006(SW) | SHELL |  | TeV J1504-421 | 327.86 | 15.35 | 1.6 | 1010.0 | 0.0 | 2.0084e-11 | 9.8858e-12
G318.2+0.1 | INT | HESSJ1457-593 | TeV J1457-594 | 318.36 | -0.44 | 9.2 | 8000.0 | 0.0 | 4.87e-13 | 8.7534e-14
RCW86 | SHELL | G315.4-2.3 MSH14-63 | TeV J1442-624 | 315.41 | -2.31 | 2.5 | 1800.0 | 0.0 | 1.3462e-11 | 5.9342e-12
G298.6-0.0 |  |  |  | 298.6 | 0.0 | 5.0 | 1000.0 | 0.0 | 5.2442e-11 | 5.1438e-11
Vela Junior | SHELL | RXJ0852.0-4622 | TeV J0852-463 | 266.28 | -1.25 | 1.0 | 3000.0 | 0.0 | 0.0 | 3.1786e-10
Puppis A |  |  |  | 260.4 | -3.4 | 2.2 | 4450.0 | 0.0 | 5.305e-12 | 7.9818e-13
IC443 | INT |  | TeV J0616+225 | 189.1 | 3.0 | 1.5 | 10000.0 | 10000.0 | 1.1617e-11 | 8.5012e-13
Tycho | SHELL |  | TeV J0025+641 | 120.1 | 1.4 | 4.5 | 400.0 | 0.0 | 0.0 | 9.4669e-14
Cas A | SHELL |  | TeV J2323+588 | 111.7 | -2.1 | 3.4 | 330.0 | 0.0 | 3.726e-12 | 8.1634e-13
Gamma Cygni |  |  |  | 78.2 | 2.1 | 1.5 | 6600.0 | 0.0 | 2.3169e-11 | 7.9406e-12
Cygnus Loop |  |  |  | 74.0 | -8.5 | 0.8 | 15000.0 | 0.0 | 1.8e-13 | 2.7842e-16
W51C | INT | G49.2-0.7 HESSJ1923+141 | TeV J1923+141 | 49.2 | -0.7 | 5.6 | 30000.0 | 190000.0 | 1.1725e-11 | 1.9496e-12
W49B | INT | G43.3-0.2 HESSJ1911+090 | TeV J1911+090 | 43.3 | -0.2 | 8.0 | 2000.0 | 1000000.0 | 5.477e-12 | 3.8876e-13
W44 | INT | G34.7-0.4 | none | 34.7 | -0.4 | 3.0 | 20000.0 | 500000.0 | 1.003e-12 | 2.8471e-14
W41 | INT | G23.3-0.3 HESSJ1834-087 | TeV J1834-087 | 23.24 | -0.33 | 4.8 | 100000.0 | 88000.0 | 6.118e-12 | 1.5368e-12
W28north | INT | HESSJ1801-233 3EGJ1800-2338 | TeV J1801-233 | 6.65 | -0.27 | 1.9 | 35000.0 | 50000.0 | 9.776e-12 | 1.4924e-12
W28A | INT | HESSJ1800-240A | TeV J1800-240A | 5.88 | -0.39 | 1.9 | 35000.0 | 40000.0 | 6.153e-12 | 2.6322e-12
W28B | INT | HESSJ1800-240B | TeV J1800-240B | 5.88 | -0.39 | 1.9 | 35000.0 | 60000.0 | 7.626e-12 | 2.8944e-12
W28C | INT | HESSJ1800-240C | TeV J1800-240C | 5.88 | -0.39 | 1.9 | 35000.0 | 20000.0 | 4.376e-12 | 2.0365e-12
G349.7+0.2 | INT |  |  | 349.7 | 0.2 | 11.5 | 1800.0 | 5000.0 | 2.8e-14 | 4.4379e-15
HESSJ1912+101 |  |  | TeV J1912+101 | 44.39 | -0.07 | 4.1 | 100000.0 | 12000.0 | 2.6006e-11 | 1.0625e-11
HESSJ1534-571 |  |  | TeV J1534-571 | 323.65 | -0.92 | 3.5 | 10000.0 | 1000.0 | 2.0676e-11 | 8.4906e-12
MSH1739 | INT |  |  | 357.7 | -0.1 | 11.8 | -1.0 | 35000.0 | 6.1e-14 | 4.57884e-16
HB21 | INT |  |  | 89.0 | 4.7 | 1.7 | 15874.0 | 55000.0 | 6e-15 | 1.3092e-17
HESSJ1614-518 | SHELL |  | TeV J1614-518 | 331.52 | -0.58 | 1.5 | 30000.0 | 0.0 | 6.4802e-11 | 2.7512e-11
W30 | INT |  |  | 8.7 | -0.1 | 4.6 | 20493.0 | 190000.0 | 4.4596e-11 | 1.1907e-11
3C 391 |  | Kes 77 |  | 31.9 | 0.0 | 7.1 | 9000.0 | 0.0 | 1.8e-14 | 1.4426e-16
CTB109 |  |  |  | 109.1 | 1.0 | 3.2 | 14000.0 | 0.0 | 2.191e-12 | 8.8208e-13
G337.0-0.1 |  | CTB 33 |  | 337.0 | -0.1 | 11.0 | 5000.0 | 0.0 | 7e-15 | 2.67153e-17
S147 |  |  |  | 180.0 | -1.7 | 1.39 | 30000.0 | 0.0 | 1.22117e-10 | 1.0661e-10
Kes17 |  |  |  | 304.6 | 0.1 | 9.7 | 14000.0 | 0.0 | 0.0 | 1.8863e-14
Catalog of $\gamma$-SNRs

## References

  * [1] V.. Acciari et al.  “Observation of Extended Very High Energy Emission from the Supernova Remnant IC 443 with VERITAS”  In _The Astrophysical Journal_ 698.2, 2009, pp. L133–L137  DOI: 10.1088/0004-637X/698/2/L133
  * [2] F. Acero et al.  “Fermi Large Area Telescope Third Source Catalog”  In _The Astrophysical Journal Supplement Series_ 218, 2015, pp. 23  DOI: 10.1088/0067-0049/218/2/23
  * [3] F. Acero et al.  “First detection of VHE $\gamma$-rays from SN 1006 by HESS”  In _Astronomy and Astrophysics_ 516, 2010, pp. A62  DOI: 10.1051/0004-6361/200913916
  * [4] F. Acero et al.  “Study of TeV shell supernova remnants at gamma-ray energies”  In _Astronomy and Astrophysics_ 580, 2015, pp. A74  DOI: 10.1051/0004-6361/201525932
  * [5] F. Acero et al.  “The First Fermi LAT Supernova Remnant Catalog”  In _The Astrophysical Journal Supplement Series_ 224, 2016, pp. 8  DOI: 10.3847/0067-0049/224/1/8
  * [6] M. Ackermann et al.  “Detection of the Characteristic Pion-Decay Signature in Supernova Remnants”  In _Science_ 339.6121, 2013, pp. 807–811  DOI: 10.1126/science.1231160
  * [7] M. Ackermann et al.  “Detection of the Characteristic Pion-Decay Signature in Supernova Remnants”  In _Science_ 339, 2013, pp. 807–811  DOI: 10.1126/science.1231160
  * [8] F.. Aharonian  “Vary High and Ultra High Energy Gamma-Rays from Giant Molecular Clouds”  In _Astrophysics and Space Science_ 180.2, 1991, pp. 305–320  DOI: 10.1007/BF00648185
  * [9] F.. Aharonian, L.’C. Drury and H.. Voelk  “GeV/TeV gamma-ray emission from dense molecular clouds overtaken by supernova shells”  In _Astronomy and Astrophysics_ 285, 1994, pp. 645–647
  * [10] F. Aharonian et al.  “Chandra and HESS observations of the supernova remnant CTB 37B”  In _Astronomy and Astrophysics_ 486.3, 2008, pp. 829–836  DOI: 10.1051/0004-6361:200809655
  * [11] F. Aharonian et al.  “Discovery of a VHE gamma-ray source coincident with the supernova remnant CTB 37A”  In _Astronomy and Astrophysics_ 490.2, 2008, pp. 685–693  DOI: 10.1051/0004-6361:200809722
  * [12] F. Aharonian et al.  “Discovery of very high energy gamma-ray emission coincident with molecular clouds in the W 28 (G6.4-0.1) field”  In _Astronomy and Astrophysics_ 481.2, 2008, pp. 401–410  DOI: 10.1051/0004-6361:20077765
  * [13] F. Aharonian et al.  “Exploring a SNR/molecular cloud association within HESS J1745-303”  In _Astronomy and Astrophysics_ 483.2, 2008, pp. 509–517  DOI: 10.1051/0004-6361:20079230
  * [14] F. Aharonian et al.  “Exploring a SNR/molecular cloud association within HESS J1745-303”  In _Astronomy and Astrophysics_ 483.2, 2008, pp. 509–517  DOI: 10.1051/0004-6361:20079230
  * [15] F. Aharonian et al.  “Primary particle acceleration above 100 TeV in the shell-type supernova remnant RX J1713.7 - 3946 with deep H.E.S.S. observations (Corrigendum)”  In _Astronomy and Astrophysics_ 531, 2011, pp. C1  DOI: 10.1051/0004-6361/20066381e
  * [16] F. Aharonian et al.  “The H.E.S.S. Survey of the Inner Galaxy in Very High Energy Gamma Rays”  In _The Astrophysical Journal_ 636.2, 2006, pp. 777–797  DOI: 10.1086/498013
  * [17] M.. Ahnen et al.  “A cut-off in the TeV gamma-ray spectrum of the SNR Cassiopeia A”  In _Monthly Notices of the Royal Astronomical Society_ 472.3, 2017, pp. 2956–2962  DOI: 10.1093/mnras/stx2079
  * [18] M. Ajello et al.  “3FHL: The Third Catalog of Hard Fermi-LAT Sources”  In _The Astrophysical Journal Supplement Series_ 232, 2017, pp. 18  DOI: 10.3847/1538-4365/aa8221
  * [19] M. Ajello et al.  “Deep Morphological and Spectral Study of the SNR RCW 86 with Fermi-LAT”  In _The Astrophysical Journal_ 819.2, 2016, pp. 98  DOI: 10.3847/0004-637X/819/2/98
  * [20] M. Ajello et al.  “Deep Morphological and Spectral Study of the SNR RCW 86 with Fermi-LAT”  In _Astrophysical Journal_ 819, 2016, pp. 98  DOI: 10.3847/0004-637X/819/2/98
  * [21] M. Ajello et al.  “Fermi Large Area Telescope Observations of the Supernova Remnant G8.7-0.1”  In _The Astrophysical Journal_ 744.1, 2012, pp. 80  DOI: 10.1088/0004-637X/744/1/80
  * [22] M. Ajello et al.  “Fermi Large Area Telescope Observations of the Supernova Remnant G8.7-0.1”  In _Astrophysical Journal_ 744.1, 2012, pp. 80  DOI: 10.1088/0004-637X/744/1/80
  * [23] Alexandre Alarie, Antoine Bilodeau and Laurent Drissen  “A hyperspectral view of Cassiopeia A”  In _Monthly Notices of the RAS_ 441.4, 2014, pp. 2996–3008  DOI: 10.1093/mnras/stu774
  * [24] J. Albert  “Discovery of VHE Gamma Radiation from IC443 with the MAGIC Telescope”  In _Astrophys. J._ 664, 2007, pp. L87–L90  DOI: 10.1086/520957
  * [25] J. Albert et al.  “Discovery of Very High Energy Gamma Radiation from IC 443 with the MAGIC Telescope”  In _The Astrophysical Journal_ 664.2, 2007, pp. L87–L90  DOI: 10.1086/520957
  * [26] J. Albert et al.  “Observation of VHE Gamma Radiation from HESS J1834-087/W41 with the MAGIC Telescope”  In _The Astrophysical Journal_ 643.1, 2006, pp. L53–L56  DOI: 10.1086/504917
  * [27] J. Aleksić et al.  “Morphological and spectral properties of the W51 region measured with the MAGIC telescopes”  In _Astronomy and Astrophysics_ 541, 2012, pp. A13  DOI: 10.1051/0004-6361/201218846
  * [28] E. Aliu et al.  “Discovery of TeV Gamma-Ray Emission toward Supernova Remnant SNR G78.2+2.1”  In _The Astrophysical Journal_ 770.2, 2013, pp. 93  DOI: 10.1088/0004-637X/770/2/93
  * [29] G.. Allen et al.  “On the Expansion Rate, Age, and Distance of the Supernova Remnant G266.2-1.2 (Vela Jr.)”  In _Astrophysical Journal_ 798, 2015, pp. 82  DOI: 10.1088/0004-637X/798/2/82
  * [30] L. Ambrogi et al.  “Spectral and morphological study of the gamma radiation of the middle-aged supernova remnant HB 21”  In _Astronomy and Astrophysics_ 623, 2019, pp. A86  DOI: 10.1051/0004-6361/201833985
  * [31] Miguel Araya  “Detection of GeV Gamma-Rays from HESS J1534-571 and Multiwavelength Implications for the Origin of the Nonthermal Emission”  In _The Astrophysical Journal_ 843.1, 2017, pp. 12  DOI: 10.3847/1538-4357/aa7261
  * [32] Miguel Araya  “Detection of GeV Gamma-Rays from HESS J1534-571 and Multiwavelength Implications for the Origin of the Nonthermal Emission”  In _Astrophysical Journal_ 843.1, 2017, pp. 12  DOI: 10.3847/1538-4357/aa7261
  * [33] S. Archambault et al.  “Gamma-Ray Observations of Tycho’s Supernova Remnant with VERITAS and Fermi”  In _The Astrophysical Journal_ 836.1, 2017, pp. 23  DOI: 10.3847/1538-4357/836/1/23
  * [34] W.. Atwood et al.  “The Large Area Telescope on the Fermi Gamma-Ray Space Telescope Mission”  In _Astrophysical Journal_ 697, 2009, pp. 1071–1102  DOI: 10.1088/0004-637X/697/2/1071
  * [35] W.. Axford, E. Leer and G. Skadron  “The acceleration of cosmic rays by shock waves”  In _International Cosmic Ray Conference_ 11, International Cosmic Ray Conference, 1977, pp. 132–137
  * [36] Aya Bamba et al.  “New identification of the mixed-morphology supernova remnant G298.6-0.0 with possible gamma-ray association”  In _Publications of the ASJ_ 68, 2016, pp. S5  DOI: 10.1093/pasj/psv096
  * [37] Werner Becker, Tobias Prinz, P. Winkler and Robert Petre  “The Proper Motion of the Central Compact Object RX J0822-4300 in the Supernova Remnant Puppis A”  In _Astrophysical Journal_ 755.2, 2012, pp. 141  DOI: 10.1088/0004-637X/755/2/141
  * [38] A.. Bell  “The acceleration of cosmic rays in shock fronts. I”  In _Monthly Notices of the RAS_ 182, 1978, pp. 147–156  DOI: 10.1093/mnras/182.2.147
  * [39] A.. Bell  “The acceleration of cosmic rays in shock fronts. II”  In _Monthly Notices of the RAS_ 182, 1978, pp. 443–455  DOI: 10.1093/mnras/182.3.443
  * [40] P… Blackett  “A possible contribution to the night sky from the Cerenkov radiation emitted by cosmic rays”  In _The Emission Spectra of the Night Sky and Aurorae_ , 1948, pp. 34
  * [41] R.. Blandford and J.. Ostriker  “Particle acceleration by astrophysical shocks”  In _Astrophysical Journal, Letters_ 221, 1978, pp. L29–L32  DOI: 10.1086/182658
  * [42] L. Blitz and P. Thaddeus  “Giant molecular complexes and OB associations. I - The Rosette molecular complex”  In _Astrophysical Journal_ 241, 1980, pp. 676–696  DOI: 10.1086/158379
  * [43] G.. Blumenthal and R.. Gould  “Bremsstrahlung, Synchrotron Radiation, and Compton Scattering of High-Energy Electrons Traversing Dilute Gases”  In _Reviews of Modern Physics_ 42, 1970, pp. 237–271  DOI: 10.1103/RevModPhys.42.237
  * [44] Harsha Blumer et al.  “X-ray and radio studies of SNR CTB 37B hosting the magnetar CXOU J171405.7-381031”  In _Monthly Notices of the RAS_ 487.4, 2019, pp. 5019–5028  DOI: 10.1093/mnras/stz1656
  * [45] F. Bocchino et al.  “A BeppoSAX and ROSAT view of the RCW86 supernova remnant”  In _Astronomy and Astrophysics_ 360, 2000, pp. 671–682  arXiv:astro-ph/0005369 [astro-ph]
  * [46] Alberto D. Bolatto, Mark Wolfire and Adam K. Leroy  “The CO-to-H2 Conversion Factor”  In _Annual Review of Astron and Astrophys_ 51.1, 2013, pp. 207–268  DOI: 10.1146/annurev-astro-082812-140944
  * [47] J. Brand and L. Blitz  “The Velocity Field of the Outer Galaxy”  In _Astronomy and Astrophysics_ 275, 1993, pp. 67
  * [48] T.. Brandt and Fermi-LAT Collaboration  “A view of supernova remnant CTB 37A with the Fermi Gamma-ray Space Telescope”  In _Advances in Space Research_ 51.2, 2013, pp. 247–252  DOI: 10.1016/j.asr.2011.07.021
  * [49] C.. Brogan and W.. Goss  “VLA Observations of the Eye of the Tornado, the High-Velocity H II Region G357.63-0.06”  In _Astronomical Journal_ 125.1, 2003, pp. 272–276  DOI: 10.1086/345387
  * [50] C.. Brogan et al.  “OH (1720 MHz) Masers: A Multiwavelength Study of the Interaction between the W51C Supernova Remnant and the W51B Star Forming Region”  In _Astrophysical Journal_ 771.2, 2013, pp. 91  DOI: 10.1088/0004-637X/771/2/91
  * [51] M. Cardillo et al.  “The supernova remnant W44: Confirmations and challenges for cosmic-ray acceleration”  In _Astronomy and Astrophysics_ 565, 2014, pp. A74  DOI: 10.1051/0004-6361/201322685
  * [52] G.. Case and D. Bhattacharya  “A New $\Sigma$-D Relation and Its Application to the Galactic Supernova Remnant Distribution”  In _Astrophysical Journal_ 504, 1998, pp. 761–772  DOI: 10.1086/306089
  * [53] Daniel Castro and Patrick Slane  “Fermi LAT Observations of Supernova Remnants Interacting with Molecular Clouds”  In _38th COSPAR Scientific Assembly_ 38, 2010, pp. 3
  * [54] Daniel Castro and Patrick Slane  “Fermi LAT Observations of Supernova Remnants Interacting with Molecular Clouds”  In _38th COSPAR Scientific Assembly_ 38, 2010, pp. 3
  * [55] Daniel Castro, Patrick Slane, Donald C. Ellison and Daniel J. Patnaude  “Fermi-LAT Observations and a Broadband Study of Supernova Remnant CTB 109”  In _The Astrophysical Journal_ 756.1, 2012, pp. 88  DOI: 10.1088/0004-637X/756/1/88
  * [56] Daniel Castro, Patrick Slane, Ashley Carlton and Enectali Figueroa-Feliciano  “Fermi-LAT Observations of Supernova Remnants Interacting with Molecular Clouds: W41, MSH 17-39, and G337.7-0.1”  In _The Astrophysical Journal_ 774.1, 2013, pp. 36  DOI: 10.1088/0004-637X/774/1/36
  * [57] F. Combes, P.. Encrenaz, R. Lucas and L. Weliachew  “Observation of the CO Molecule in the Spiral Arms of External Galaxies”  In _Astronomy and Astrophysics_ 55, 1977, pp. 311
  * [58] B. Condon, M. Lemoine-Goumard, F. Acero and H. Katagiri  “Detection of Two TeV Shell-type Remnants at GeV Energies with FERMI LAT: HESS J1731-347 and SN 1006”  In _The Astrophysical Journal_ 851.2, 2017, pp. 100  DOI: 10.3847/1538-4357/aa9be8
  * [59] S. Corbel, C. Chapuis, T.. Dame and P. Durouchoux  “The Distance to the Soft Gamma Repeater SGR 1627-41”  In _Astrophysical Journal, Letters_ 526.1, 1999, pp. L29–L32  DOI: 10.1086/312359
  * [60] Richard M. Crutcher  “Magnetic Fields in Molecular Clouds”  In _Annual Review of Astron and Astrophys_ 50, 2012, pp. 29–63  DOI: 10.1146/annurev-astro-081811-125514
  * [61] Yudong Cui, Paul K.. Yeung, P.. Tam and Gerd Pühlhofer  “Leaked GeV CRs from a Broken Shell: Explaining 9 Years of Fermi-LAT Data of SNR W28”  In _The Astrophysical Journal_ 860.1, 2018, pp. 69  DOI: 10.3847/1538-4357/aac37b
  * [62] T.. Dame et al.  “A composite CO survey of the entire Milky Way”  In _Astrophysical Journal_ 322, 1987, pp. 706–720  DOI: 10.1086/165766
  * [63] B. Dinçel et al.  “Discovery of an OB runaway star inside SNR S147”  In _Monthly Notices of the RAS_ 448.4, 2015, pp. 3196–3205  DOI: 10.1093/mnras/stv124
  * [64] M.. Dopita et al.  “Shocked Interstellar Clouds and Dust Grain Destruction in the LMC Supernova Remnant N132D”  In _strophysical Journal, Supplement_ 237, 2018, pp. 10  DOI: 10.3847/1538-4365/aac837
  * [65] Gloria Dubner and Elsa Giacani  “Radio emission from supernova remnants”  In _Astronomy and Astrophysics Reviews_ 23, 2015, pp. 3  DOI: 10.1007/s00159-015-0083-5
  * [66] S. Federici et al.  “Analysis of GeV-band $\gamma$-ray emission from supernova remnant RX J1713.7-3946”  In _Astronomy and Astrophysics_ 577, 2015, pp. A12  DOI: 10.1051/0004-6361/201424947
  * [67] Gilles Ferrand and Samar Safi-Harb  “A census of high-energy observations of Galactic supernova remnants”  In _Advances in Space Research_ 49, 2012, pp. 1313–1319  DOI: 10.1016/j.asr.2012.02.004
  * [68] Robert A. Fesen et al.  “The Cygnus Loop’s distance, properties, and environment driven morphology”  In _Monthly Notices of the RAS_ 481.2, 2018, pp. 1786–1798  DOI: 10.1093/mnras/sty2370
  * [69] Robert A. Fesen et al.  “The Expansion Asymmetry and Age of the Cassiopeia A Supernova Remnant”  In _Astrophysical Journal_ 645.1, 2006, pp. 283–292  DOI: 10.1086/504254
  * [70] Daniel Foreman-Mackey, David W. Hogg, Dustin Lang and Jonathan Goodman  “emcee: The MCMC Hammer”  In _Publications of the Astronomical Society of the Pacific_ 125, 2013, pp. 306  DOI: 10.1086/670067
  * [71] N. Fraija and M. Araya  “The Gigaelectronvolt Counterpart of VER J2019+407 in the Northern Shell of the Supernova Remnant G78.2+2.1 ($\gamma$ Cygni)”  In _The Astrophysical Journal_ 826.1, 2016, pp. 31  DOI: 10.3847/0004-637X/826/1/31
  * [72] D.. Frail et al.  “A Survey for OH (1720 MHz) Maser Emission Toward Supernova Remnants”  In _Astronomical Journal_ 111, 1996, pp. 1651  DOI: 10.1086/117904
  * [73] T. Fukuda et al.  “Interstellar Protons in the TeV $\gamma$-Ray SNR HESS J1731-347: Possible Evidence for the Coexistence of Hadronic and Leptonic $\gamma$-Rays”  In _Astrophysical Journal_ 788.1, 2014, pp. 94  DOI: 10.1088/0004-637X/788/1/94
  * [74] Y. Fukui  “Molecular and Atomic Gas in the Young TeV $\gamma$-Ray SNRs RX J1713.7-3946 and RX J0852.0-4622; Evidence for the Hadronic Production of $\gamma$-Rays”  In _Cosmic Rays in Star-Forming Environments_ 34, Astrophysics and Space Science Proceedings, 2013, pp. 249  DOI: 10.1007/978-3-642-35410-6_17
  * [75] Y. Fukui and A. Kawamura  “Molecular Clouds in Nearby Galaxies”  In _Annual Review of Astron and Astrophys_ 48, 2010, pp. 547–580  DOI: 10.1146/annurev-astro-081309-130854
  * [76] Stefan Funk  “Ground- and Space-Based Gamma-Ray Astronomy”  In _Annual Review of Nuclear and Particle Science_ 65, 2015, pp. 245–277  DOI: 10.1146/annurev-nucl-102014-022036
  * [77] Joseph D. Gelfand et al.  “Supernova Remnant Kes 17: An Efficient Cosmic Ray Accelerator inside a Molecular Cloud”  In _The Astrophysical Journal_ 777.2, 2013, pp. 148  DOI: 10.1088/0004-637X/777/2/148
  * [78] Joseph D. Gelfand et al.  “Supernova Remnant Kes 17: An Efficient Cosmic Ray Accelerator inside a Molecular Cloud”  In _Astrophysical Journal_ 777.2, 2013, pp. 148  DOI: 10.1088/0004-637X/777/2/148
  * [79] A. Giuliani et al.  “AGILE detection of GeV $\gamma$-ray emission from the SNR W28”  In _Astronomy and Astrophysics_ 516, 2010, pp. L11  DOI: 10.1051/0004-6361/201014256
  * [80] A. Giuliani et al.  “Neutral Pion Emission from Accelerated Protons in the Supernova Remnant W44”  In _ApJ Let._ 742, 2011, pp. L30  DOI: 10.1088/2041-8205/742/2/L30
  * [81] F. Gök and A. Sezer  “A deep X-ray observation of the supernova remnant G304.6+0.1 (Kes 17) using Suzaku”  In _Monthly Notices of the RAS_ 423.2, 2012, pp. 1215–1220  DOI: 10.1111/j.1365-2966.2012.20948.x
  * [82] D. Gottschall et al.  “Discovery of new TeV supernova remnant shells in the Galactic plane with H.E.S.S.”  In _6th International Symposium on High Energy Gamma-Ray Astronomy_ 1792, American Institute of Physics Conference Series, 2017, pp. 040030  DOI: 10.1063/1.4968934
  * [83] D.. Green  “VizieR Online Data Catalog: A Catalogue of Galactic Supernova Remnants (Green 2017)”  In _VizieR Online Data Catalog_ , 2017, pp. VII/278
  * [84] Xiao-Lei Guo et al.  “Detection of GeV Gamma-Ray Emission in the Direction of HESS J1731-347 with Fermi-LAT”  In _The Astrophysical Journal_ 853.1, 2018, pp. 2  DOI: 10.3847/1538-4357/aaa3f8
  * [85] Xiao-Lei Guo et al.  “Detection of GeV Gamma-Ray Emission in the Direction of HESS J1731-347 with Fermi-LAT”  In _Astrophysical Journal_ 853.1, 2018, pp. 2  DOI: 10.3847/1538-4357/aaa3f8
  * [86] H. E. S. S. Collaboration et al.  “A new SNR with TeV shell-type morphology: HESS J1731-347”  In _Astronomy and Astrophysics_ 531, 2011, pp. A81  DOI: 10.1051/0004-6361/201016425
  * [87] H. E. S. S. Collaboration et al.  “Deeper H.E.S.S. observations of Vela Junior (RX J0852.0-4622): Morphology studies and resolved spectroscopy”  In _Astronomy and Astrophysics_ 612, 2018, pp. A7  DOI: 10.1051/0004-6361/201630002
  * [88] H. E. S. S. Collaboration et al.  “Detailed spectral and morphological analysis of the shell type supernova remnant RCW 86”  In _Astronomy and Astrophysics_ 612, 2018, pp. A4  DOI: 10.1051/0004-6361/201526545
  * [89] H. E. S. S. Collaboration et al.  “H.E.S.S. detection of TeV emission from the interaction region between the supernova remnant G349.7+0.2 and a molecular cloud”  In _Astronomy and Astrophysics_ 574, 2015, pp. A100  DOI: 10.1051/0004-6361/201425070
  * [90] H. E. S. S. Collaboration et al.  “H.E.S.S. reveals a lack of TeV emission from the supernova remnant Puppis A”  In _Astronomy and Astrophysics_ 575, 2015, pp. A81  DOI: 10.1051/0004-6361/201424805
  * [91] H. E. S. S. Collaboration et al.  “Probing the gamma-ray emission from HESS J1834-087 using H.E.S.S. and Fermi LAT observations”  In _Astronomy and Astrophysics_ 574, 2015, pp. A27  DOI: 10.1051/0004-6361/201322694
  * [92] H. E. S. S. Collaboration et al.  “The supernova remnant W49B as seen with H.E.S.S. and Fermi-LAT”  In _Astronomy and Astrophysics_ 612, 2018, pp. A5  DOI: 10.1051/0004-6361/201527843
  * [93] Asami Hayato et al.  “Expansion Velocity of Ejecta in Tycho’s Supernova Remnant Measured by Doppler Broadened X-ray Line Emission”  In _Astrophysical Journal_ 725.1, 2010, pp. 894–903  DOI: 10.1088/0004-637X/725/1/894
  * [94] A.. Hillas  “Cerenkov light images of EAS produced by primary gamma”  In _19th International Cosmic Ray Conference (ICRC19), Volume 3_ 3, International Cosmic Ray Conference, 1985
  * [95] J.. Hinton and W. Hofmann  “Teraelectronvolt Astronomy”  In _Annual Review of Astron and Astrophys_ 47, 2009, pp. 523–565  DOI: 10.1146/annurev-astro-082708-101816
  * [96] P. Hofverberg et al.  “Discovery of VHE gamma-rays from the vicinity of the shell-type SNR G318.2+0.1 with H.E.S.S.”  In _25th Texas Symposium on Relativistic Astrophysics_ , 2010, pp. 196  arXiv:1104.5119
  * [97] C.. Hui et al.  “Observing two dark accelerators around the Galactic Centre with Fermi Large Area Telescope”  In _Monthly Notices of the Royal Astronomical Society_ 457.4, 2016, pp. 4262–4271  DOI: 10.1093/mnras/stw209
  * [98] M.. Issa and A.. Wolfendale  “$\gamma$ Rays from the cosmic ray irradiation of local molecular clouds”  In _Nature_ 292.5822, 1981, pp. 430–433  DOI: 10.1038/292430a0
  * [99] J.. Jackson et al.  “The Boston University-Five College Radio Astronomy Observatory Galactic Ring Survey”  In _strophysical Journal, Supplement_ 163.1, 2006, pp. 145–159  DOI: 10.1086/500091
  * [100] Bing Jiang et al.  “Cavity of Molecular Gas Associated with Supernova Remnant 3C 397”  In _Astrophysical Journal_ 712.2, 2010, pp. 1147–1156  DOI: 10.1088/0004-637X/712/2/1147
  * [101] T. Jogler and S. Funk  “Revealing W51C as a Cosmic Ray Source Using Fermi-LAT Data”  In _The Astrophysical Journal_ 816.2, 2016, pp. 100  DOI: 10.3847/0004-637X/816/2/100
  * [102] T. Jogler and S. Funk  “Revealing W51C as a Cosmic Ray Source Using Fermi-LAT Data”  In _Astrophysical Journal_ 816, 2016, pp. 100  DOI: 10.3847/0004-637X/816/2/100
  * [103] O. Kargaltsev, G.. Pavlov, N. Klingler and B. Rangelov  “Pulsar wind nebulae created by fast-moving pulsars”  In _Journal of Plasma Physics_ 83.5, 2017, pp. 635830501  DOI: 10.1017/S0022377817000630
  * [104] Oleg Kargaltsev, Blagoy Rangelov and George G. Pavlov  “Gamma-ray and X-ray Properties of Pulsar Wind Nebulae and Unidentified Galactic TeV Sources”  In _arXiv e-prints_ , 2013, pp. arXiv:1305.2552  arXiv:1305.2552 [astro-ph.HE]
  * [105] Namir E. Kassim and Kurt W. Weiler  “W30 Revealed: Separation and Analysis of Thermal and Nonthermal Emission in a Galactic Complex”  In _Astrophysical Journal_ 360, 1990, pp. 184  DOI: 10.1086/169107
  * [106] Namir E. Kassim, Paul Hertz, Schuyler D. van Dyk and Kurt W. Weiler  “X-Ray Observations of Supernova Remnants as Distance Indicators”  In _Astrophysical Journal, Letters_ 427, 1994, pp. L95  DOI: 10.1086/187373
  * [107] J. Katsuta et al.  “Fermi Large Area Telescope Observation of Supernova Remnant S147”  In _The Astrophysical Journal_ 752.2, 2012, pp. 135  DOI: 10.1088/0004-637X/752/2/135
  * [108] S.. Kelner, F.. Aharonian and V.. Bugayov  “Energy spectra of gamma rays, electrons, and neutrinos produced at proton-proton interactions in the very high energy regime”  In _Physical Review D_ 74.3, 2006, pp. 034018  DOI: 10.1103/PhysRevD.74.034018
  * [109] Charles D. Kilpatrick, John H. Bieging and George H. Rieke  “A Systematic Survey for Broadened CO Emission toward Galactic Supernova Remnants”  In _Astrophysical Journal_ 816.1, 2016, pp. 1  DOI: 10.3847/0004-637X/816/1/1
  * [110] Bon-Chul Koo and Carl Heiles  “A Survey of H i 21 Centimeter Emission Lines toward Supernova Remnants”  In _Astrophysical Journal_ 382, 1991, pp. 204  DOI: 10.1086/170709
  * [111] Roland Kothes, Bülent Uyaniker and Aylin Yar  “The Distance to Supernova Remnant CTB 109 Deduced from Its Environment”  In _Astrophysical Journal_ 576.1, 2002, pp. 169–175  DOI: 10.1086/341545
  * [112] G.. Krymskii  “A regular mechanism for the acceleration of charged particles on the front of a shock wave”  In _Akademiia Nauk SSSR Doklady_ 234, 1977, pp. 1306–1308
  * [113] S. Kumar and VERITAS Collaboration  “A detailed study of gamma-ray emission from Cassiopeia A using VERITAS”  In _34th International Cosmic Ray Conference (ICRC2015)_ 34, International Cosmic Ray Conference, 2015, pp. 760  arXiv:1508.07453 [astro-ph.HE]
  * [114] D.. Leahy and S. Ranasinghe  “Evolutionary Models for 15 Galactic Supernova Remnants with New Distances”  In _Astrophysical Journal_ 866.1, 2018, pp. 9  DOI: 10.3847/1538-4357/aade48
  * [115] J.-J. Lee et al.  “A 21 cm Spectral and Continuum Study of IC 443 Using the Very Large Array and the Arecibo Telescope”  In _Astronomical Journal_ 135, 2008, pp. 796–808  DOI: 10.1088/0004-6256/135/3/796
  * [116] M.. Longair  “High Energy Astrophysics”  In _High Energy Astrophysics, by Malcolm S. Longair, Cambridge, UK: Cambridge University Press, 2011_ , 2011
  * [117] Nigel I. Maxted et al.  “Searching for an interstellar medium association for HESS J1534 - 571”  In _Monthly Notices of the RAS_ 480.1, 2018, pp. 134–148  DOI: 10.1093/mnras/sty1797
  * [118] T. Montmerle  “On gamma-ray sources, supernova remnants, OB associations, and the origin of cosmic rays.”  In _Astrophysical Journal_ 231, 1979, pp. 95–110  DOI: 10.1086/157166
  * [119] T. Padmanabhan  “Theoretical Astrophysics - Volume 2, Stars and Stellar Systems”  In _Theoretical Astrophysics - Volume 2, Stars and Stellar Systems, by T. Padmanabhan, pp. 594. Cambridge University Press, July 2001. ISBN-10: 0521562414. ISBN-13: 9780521562416. LCCN: QB801 .P23 2001_ , 2001, pp. 594  DOI: 10.2277/0521562414
  * [120] M.. Pavlović et al.  “The Radio Surface-brightness-to-Diameter Relation for Galactic Supernova Remnants: Sample Selection and Robust Analysis with Various Fitting Offsets”  In _strophysical Journal, Supplement_ 204.1, 2013, pp. 4  DOI: 10.1088/0067-0049/204/1/4
  * [121] G. Pedaletti et al.  “On the potential of the Cherenkov Telescope Array for the study of cosmic-ray diffusion in molecular clouds”  In _Astronomy and Astrophysics_ 550, 2013, pp. A123  DOI: 10.1051/0004-6361/201220583
  * [122] G. Pivato et al.  “Fermi LAT and WMAP Observations of the Supernova Remnant HB 21”  In _The Astrophysical Journal_ 779.2, 2013, pp. 179  DOI: 10.1088/0004-637X/779/2/179
  * [123] Vladimir Ptuskin  “Propagation of galactic cosmic rays”  In _Astroparticle Physics_ 39, 2012, pp. 44–51  DOI: 10.1016/j.astropartphys.2011.11.004
  * [124] S. Ranasinghe and D.. Leahy  “Revised Distances to 21 Supernova Remnants”  In _Astronomical Journal_ 155.5, 2018, pp. 204  DOI: 10.3847/1538-3881/aab9be
  * [125] I. Reichardt et al.  “Fermi/LAT Study of the Cygnus Loop Supernova Remnant: Discovery of a Point-like Source and of Spectral Differences in its gamma-ray emission”  In _arXiv e-prints_ , 2015, pp. arXiv:1502.03053  arXiv:1502.03053 [astro-ph.HE]
  * [126] Stephen P. Reynolds  “Supernova Remnants at High Energy”  In _Annual Review of Astronomy and Astrophysics_ 46.1, 2008, pp. 89–126  DOI: 10.1146/annurev.astro.46.060407.145237
  * [127] Thomas S. Rice et al.  “A Uniform Catalog of Molecular Clouds in the Milky Way”  In _Astrophysical Journal_ 822.1, 2016, pp. 52  DOI: 10.3847/0004-637X/822/1/52
  * [128] Julia Roman-Duval et al.  “Kinematic Distances to Molecular Clouds Identified in the Galactic Ring Survey”  In _Astrophysical Journal_ 699.2, 2009, pp. 1153–1170  DOI: 10.1088/0004-637X/699/2/1153
  * [129] Shigetaka Saji et al.  “Discovery of 6.4 keV line and soft X-ray emissions from G323.7-1.0 with Suzaku”  In _Publications of the ASJ_ 70.2, 2018, pp. 23  DOI: 10.1093/pasj/psx158
  * [130] Michito Sakai, Yukie Yajima and Hironori Matsumoto  “Nature of the Unidentified TeV Source HESS J1614-518, Revealed by Suzaku and XMM-Newton Observations”  In _Publications of the ASJ_ 63, 2011, pp. S879–S887  DOI: 10.1093/pasj/63.sp3.S879
  * [131] M. Sánchez-Cruces, M. Rosado, I. Fuentes-Carrera and P. Ambrocio-Cruz  “Kinematics of the Galactic Supernova Remnant G109.1-1.0 (CTB 109)”  In _Monthly Notices of the RAS_ 473.2, 2018, pp. 1705–1717  DOI: 10.1093/mnras/stx2460
  * [132] S.. Shan et al.  “Distances of Galactic Supernova Remnants Using Red Clump Stars”  In _strophysical Journal, Supplement_ 238.2, 2018, pp. 35  DOI: 10.3847/1538-4365/aae07a
  * [133] Su-Su Shan et al.  “The distance measurements of supernova remnants in the fourth Galactic quadrant”  In _Research in Astronomy and Astrophysics_ 19.7, 2019, pp. 092  DOI: 10.1088/1674-4527/19/7/92
  * [134] Patrick Slane et al.  “Supernova Remnants Interacting with Molecular Clouds: X-Ray and Gamma-Ray Signatures”  In _Space Science Reviews_ 188.1-4, 2015, pp. 187–210  DOI: 10.1007/s11214-014-0062-6
  * [135] Yang Su et al.  “Is HESS J1912+101 Associated with an Old Supernova Remnant?”  In _Astrophysical Journal_ 845.1, 2017, pp. 48  DOI: 10.3847/1538-4357/aa7f2a
  * [136] Yang Su et al.  “Molecular Environment of the Supernova Remnant IC 443: Discovery of the Molecular Shells Surrounding the Remnant”  In _Astrophysical Journal_ 788.2, 2014, pp. 122  DOI: 10.1088/0004-637X/788/2/122
  * [137] T. Tanaka et al.  “Gamma-Ray Observations of the Supernova Remnant RX J0852.0-4622 with the Fermi Large Area Telescope”  In _The Astrophysical Journal_ 740.2, 2011, pp. L51  DOI: 10.1088/2041-8205/740/2/L51
  * [138] M. Tavani et al.  “Direct Evidence for Hadronic Cosmic-Ray Acceleration in the Supernova Remnant IC 443”  In _The Astrophysical Journal_ 710.2, 2010, pp. L151–L155  DOI: 10.1088/2041-8205/710/2/L151
  * [139] W.. Tian and D.. Leahy  “SNR G349.7+0.2: A $\gamma$-Ray Source in the Far 3 kpc Arm of the Galactic Center”  In _Astrophysical Journal, Letters_ 783.1, 2014, pp. L2  DOI: 10.1088/2041-8205/783/1/L2
  * [140] W.. Tian, Z. Li, D.. Leahy and Q.. Wang  “VLA and XMM-Newton Observations of the SNR W41/TeV Gamma-Ray Source HESS J1834-087”  In _Astrophysical Journal, Letters_ 657.1, 2007, pp. L25–L28  DOI: 10.1086/512544
  * [141] N. Tsuji and Y. Uchiyama  “Expansion measurements of supernova remnant RX J1713.7-3946”  In _Publications of the ASJ_ 68, 2016, pp. 108  DOI: 10.1093/pasj/psw102
  * [142] Yasunobu Uchiyama, Tadayuki Takahashi, Felix Aharonian and John Mattox  “ASCA View of the supernova remnant gamma Cygni (G78.2+2.1): Bremsstrahlung x-ray spectrum from loss-flattened electron distribution”  In _Astrophys. J._ 571, 2002, pp. 866  DOI: 10.1086/340121
  * [143] S.. Wakely and D. Horan  “TeVCat: An online catalog for Very High Energy Gamma-Ray Astronomy”  In _International Cosmic Ray Conference_ 3, 2008, pp. 1341–1344
  * [144] T.. Weekes et al.  “Observation of TeV gamma rays from the Crab nebula using the atmospheric Cerenkov imaging technique”  In _Astrophysical Journal_ 342, 1989, pp. 379–395  DOI: 10.1086/167599
  * [145] R.. Wilson, K.. Jefferts and A.. Penzias  “Carbon Monoxide in the Orion Nebula”  In _Astrophysical Journal, Letters_ 161, 1970, pp. L43  DOI: 10.1086/180567
  * [146] P. Winkler, Gaurav Gupta and Knox S. Long  “The SN 1006 Remnant: Optical Proper Motions, Deep Imaging, Distance, and Brightness at Maximum”  In _Astrophysical Journal_ 585.1, 2003, pp. 324–335  DOI: 10.1086/345985
  * [147] L. Woltjer  “Supernova Remnants”  In _Annual Review of Astron and Astrophys_ 10, 1972, pp. 129  DOI: 10.1146/annurev.aa.10.090172.001021
  * [148] Yu-Liang Xin et al.  “A GeV Source in the Direction of Supernova Remnant CTB 37B”  In _The Astrophysical Journal_ 817.1, 2016, pp. 64  DOI: 10.3847/0004-637X/817/1/64
  * [149] Yu-Liang Xin et al.  “Revisiting SNR Puppis A with Seven Years of Fermi Large Area Telescope Observations”  In _The Astrophysical Journal_ 843.2, 2017, pp. 90  DOI: 10.3847/1538-4357/aa74bb
  * [150] Yi Xing, Zhongxiang Wang, Xiao Zhang and Yang Chen  “The Likely Fermi Detection of the Supernova Remnant SN 1006”  In _The Astrophysical Journal_ 823.1, 2016, pp. 44  DOI: 10.3847/0004-637X/823/1/44
  * [151] Bin Yu, B.. Chen, B.. Jiang and A. Zijlstra  “Three-dimensional dust mapping of 12 supernovae remnants in the Galactic anticentre”  In _Monthly Notices of the RAS_ 488.3, 2019, pp. 3129–3142  DOI: 10.1093/mnras/stz1940
  * [152] Farhad Yusef-Zadeh and John Bally  “A non-thermal axially symmetric radio wake towards the galactic centre”  In _Nature_ 330.6147, 1987, pp. 455–458  DOI: 10.1038/330455a0
  * [153] V. Zabalza  “naima: a Python package for inference of relativistic particle energy distributions from observed nonthermal spectra”  In _Proc. of International Cosmic Ray Conference 2015_ , 2015, pp. 922  eprint: 1509.03319
  * [154] H. Zhu, W.. Tian and P. Zuo  “Supernova Remnant W49B and Its Environment”  In _Astrophysical Journal_ 793.2, 2014, pp. 95  DOI: 10.1088/0004-637X/793/2/95

kerner