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Minor grammatical and spelling changes #112

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14 changes: 7 additions & 7 deletions docs/tutorials/dt_thermal_emission.ipynb
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"source": [
"# A note on dust torus thermal emission\n",
"\n",
"agnpy is meant for calculations of non-thermal processes occurring in the jets of active galaxies. The dust torus (DT) emission is considered as a target radiation field for inverse Compton scattering or pair production.\n",
"`agnpy` is meant for calculations of non-thermal processes occurring in the jets of active galaxies. The dust torus (DT) emission is considered as a target radiation field for inverse Compton scattering or pair production.\n",
"\n",
"The contribution of the thermal emission of the DT to the overall MWL SED is usually considered in Flat Spectrum Radio Quasars (FSRQs), where still, this component is typically dominated by synchrotron radiation (see Fig. 15 in [Aleksic et al. 2016](https://ui.adsabs.harvard.edu/abs/2014A%26A...569A..46A/abstract)). The function computing the DT thermal SED in agnpy is mostly meant to check that this emission does not overtake the synchrotron one, and **not for precise modelling of the DT emission**.\n",
"The contribution of the thermal emission of the DT to the overall MWL SED is usually considered in Flat Spectrum Radio Quasars (FSRQs), where still, this component is typically dominated by synchrotron radiation (see Fig. 15 in [Aleksic et al. 2016](https://ui.adsabs.harvard.edu/abs/2014A%26A...569A..46A/abstract)). The function computing the DT thermal SED in `agnpy` is mostly meant to check that this emission does not overtake the synchrotron one, and **not for precise modelling of the DT emission**.\n",
"\n",
"In this notebook we will illustrate that the single-temperature black-body (BB) radiation computed by agnpy (in `RingDustTorus.sed_flux`) does not accurately model the thermal emission observed from a DT. At the same time, we illustrate that for the sake of the inverse Compton calculation, the even strongest approximation of the emission as monochromatic (at the BB peak) is satisfactory."
"In this notebook we will illustrate that the single-temperature black-body (BB) radiation computed by `agnpy` (in `RingDustTorus.sed_flux`) does not accurately model the thermal emission observed from a DT. At the same time, we illustrate that for the sake of the inverse Compton calculation, even the strongest approximation of the emission as monochromatic (at the BB peak) is satisfactory."
]
},
{
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"id": "77117a2d",
"metadata": {},
"source": [
"Now that we have the measured flux and an accurate model, let us try to reproduce the DT emission with a single- and multi-temperature black body, using agnpy."
"Now that we have the measured flux and an accurate model, let us try to reproduce the DT emission with a single- and multi-temperature black body, using `agnpy`."
]
},
{
Expand Down Expand Up @@ -243,17 +243,17 @@
"id": "ba392d9e",
"metadata": {},
"source": [
"It is clear that the single-temperature black body does not accureately reproduce the broad $(100-1\\,{\\rm \\mu m})$ band observed flux. It does not span the entire range of data and it peaks in the wrong energy range. A multi-temperature black body is clearly better suited to reproduces the observed DT SED."
"It is clear that the single-temperature black body does not accurately reproduce the broad $(100-1\\,{\\rm \\mu m})$ band observed flux. It does not span the entire range of data and it peaks in the wrong energy range. A multi-temperature black body is clearly better suited to reproduces the observed DT SED."
]
},
{
"cell_type": "markdown",
"id": "0adc055a",
"metadata": {},
"source": [
"## Impact on the external Compton\n",
"## Impact on external Compton scattering\n",
"\n",
"Let us consider now the impact of using a single monochromatic approximation for the DT emission in the EC calculation. Let us observe what are the differences when using a multi-temperature (always monochormatic) DT as target. To realise the latter we just re-use the previously created list of DT peaking at different temperatures and compute the EC scattering on their photon fields."
"Let us consider now the impact of using a single monochromatic approximation for the DT emission in the EC calculation by exploring the difference when using a multi-temperature (always monochormatic) DT as target. To realise the latter we just re-use the previously created list of DT peaking at different temperatures and compute the EC scattering on their photon fields."
]
},
{
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16 changes: 8 additions & 8 deletions docs/tutorials/ec_dt_gammapy_fit.ipynb
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"id": "ffcdbafd",
"metadata": {},
"source": [
"### gammapy wrapper of agnpy radiative processes\n",
"Now let us [follow the Gammapy documentation](https://docs.gammapy.org/0.18.2/tutorials/models.html#Implementing-a-Custom-Model) and define a model wrapping agnpy's functions to compute the Synchrotron, Synchrotron Self-Compton and External Compton on Dust Torus SEDs. We will assume a broken power-law electron distribution. The thermal SEDs of the Disk and the DT are added to the total flux model.\n",
"### `gammapy` wrapper of `agnpy` radiative processes\n",
"Now let us [follow the `Gammapy` documentation](https://docs.gammapy.org/0.18.2/tutorials/models.html#Implementing-a-Custom-Model) and define a model wrapping `agnpy`'s functions to compute the Synchrotron, Synchrotron Self-Compton and External Compton on Dust Torus SEDs. We will assume a broken power-law electron distribution. The thermal SEDs of the Disk and the DT are added to the total flux model.\n",
"\n",
"**NOTE:** for the parameters that vary over several orders of magnitude (i.e. normalisation and Lorentz factors of the electron distribution) it is better to provide to the fitting routine a \"scaled\" version of them (e.g. their log10), such that larger ranges might be covered with small parameters variation.\n",
"\n",
Expand Down Expand Up @@ -223,8 +223,8 @@
"id": "7cd0a5f7",
"metadata": {},
"source": [
"### Fit with gammapy\n",
"Let us start here the procedure to fit with Gammapy\n",
"### Fit with `gammapy`\n",
"Here we begin the procedure to fit with `Gammapy`.\n",
"\n",
"#### 1) load the MWL flux points \n",
"The MWL SEDs included in the default `agnpy` data are automatically readable by `Gammapy`'s `FluxPoints`"
Expand Down Expand Up @@ -262,7 +262,7 @@
"metadata": {},
"source": [
"#### 2) add systematic errors\n",
"Currently there is no function in gammapy handling systematic errors on flux points. \n",
"Currently there is no function in `Gammapy` handling systematic errors on flux points. \n",
"Let us manually add different systematic errors in different energy bands. \n",
"We assume them to be independent from the statistical ones and sum them in quadrature."
]
Expand Down Expand Up @@ -312,7 +312,7 @@
"source": [
"#### 3) perform the fit\n",
"Now we create an instance of the model wrapping the non-thermal and thermal emissions. \n",
"Let us leave free to vary the parameters describing the electron distribution and the magnetic field."
"The parameters describing the electron distribution and the magnetic field are left free to vary."
]
},
{
Expand Down Expand Up @@ -399,7 +399,7 @@
"id": "094d8387",
"metadata": {},
"source": [
"Let us define the skymodel and perform the fit"
"Let us define the skymodel and perform the fit."
]
},
{
Expand Down Expand Up @@ -604,7 +604,7 @@
"id": "9721da93",
"metadata": {},
"source": [
"#### Use Gammapy best-fit parameters and agnpy to plot the best-fit model specifying its individual components\n",
"#### Use `Gammapy` best-fit parameters and `agnpy` to plot the best-fit model specifying its individual components\n",
"We fetch the best-fit parameters for our model and we use them to specify and plot the individual spectral components."
]
},
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12 changes: 6 additions & 6 deletions docs/tutorials/ec_dt_sherpa_fit.ipynb
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Expand Up @@ -54,8 +54,8 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"### sherpa wrapper of agnpy radiative processes\n",
"Now let us [follow the sherpa documentation](https://sherpa.readthedocs.io/en/latest/model_classes/usermodel.html) and define a model wrapping agnpy's functions to compute the Synchrotron, Synchrotron Self-Compton and External Compton on Dust Torus SEDs. We will assume a broken power-law electron distribution. The thermal SEDs of the Disk and the DT are added to the total flux model.\n",
"### `sherpa` wrapper of `agnpy` radiative processes\n",
"Now let us [follow the `sherpa` documentation](https://sherpa.readthedocs.io/en/latest/model_classes/usermodel.html) and define a model wrapping agnpy's functions to compute the Synchrotron, Synchrotron Self-Compton and External Compton on Dust Torus SEDs. We will assume a broken power-law electron distribution. The thermal SEDs of the Disk and the DT are added to the total flux model.\n",
"\n",
"**NOTE:** for the parameters that vary over several orders of magnitude (i.e. normalisation and Lorentz factors of the electron distribution) it is better to provide to the fitting routine a \"scaled\" version of them (e.g. their log10), such that larger ranges might be covered with small parameters variation.\n",
"\n",
Expand Down Expand Up @@ -260,8 +260,8 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"### Fitting with sherpa\n",
"Let us start here the procedure to fit with sherpa, first we read the data and then we pass them in a `Data1D` object provided by sherpa. \n",
"### Fitting with `sherpa`\n",
"Let us start here the procedure to fit with `sherpa`, first we read the data and then we pass them in a `Data1D` object provided by `sherpa`. \n",
"We add an educated guess on systematic errors on the flux measurements in the different energy bands. "
]
},
Expand Down Expand Up @@ -308,7 +308,7 @@
"metadata": {},
"source": [
"Now we create an instance of the model wrapping the non-thermal and thermal emissions. \n",
"Let us leave free to vary the parameters describing the electron distribution and the magnetic field."
"The parameters describing the electron distribution and the magnetic field are left free to vary."
]
},
{
Expand Down Expand Up @@ -393,7 +393,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we define the Fit procedure choosing the statistics (chi2) and the minimisation method. We will fit only the data between $10^{11}\\,{\\rm Hz}$ and $10^{30}\\,{\\rm Hz}$, avoiding the lowest-energy radio data usually attributed to the extended jet emission."
"Now we define the fit procedure choosing the statistics (chi2) and the minimisation method. We will fit only the data between $10^{11}\\,{\\rm Hz}$ and $10^{30}\\,{\\rm Hz}$, avoiding the lowest-energy radio data usually attributed to the extended jet emission."
]
},
{
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12 changes: 6 additions & 6 deletions docs/tutorials/energy_densities.ipynb
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Expand Up @@ -122,7 +122,7 @@
"metadata": {},
"source": [
"Now let us simulate a point source behind the jet with the same luminosity as the disk. In the limit of large\n",
"distances the disk energy density should tend to the one of the point source. The point source behind the jet is monochromatic, we assume it has the same dimensionless energy of the photons emitted at the innermost disk radius."
"distances the disk energy density should tend to the one of the point source. The point source behind the jet is monochromatic, we assume it has the same dimensionless energy as the photons emitted at the innermost disk radius."
]
},
{
Expand Down Expand Up @@ -191,7 +191,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Let us see if also in the frame comoving with the blob the two energy densities overlap in the case of large distances. To compute the energy density in such a frame we just have to pass a `Blob` instance to the `u` function"
"Let us see if the two energy densities also overlap in the case of large distances in the frame comoving with the blob. To compute the energy density in such a frame we just have to pass a `Blob` instance to the `u` function"
]
},
{
Expand Down Expand Up @@ -285,7 +285,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"**Note** I think that the fact that the energy density ratio does not converge to 1 is due to the expression for the energy density of the Disk not being properly normalised with respect to the radius variable $R$. One in fact can see how, given the same luminosity, changing the external and internal radiuses of the disk will alter the value of $u$ at large distances. This should not be the case as, no matter how geometrically distributed is the luminosity, it should always reduce to the case of a point source at very large distances."
"**Note** I think that the fact that the energy density ratio does not converge to 1 is due to the expression for the energy density of the disk not being properly normalised with respect to the radius variable $R$. One in fact can see how, given the same luminosity, changing the external and internal radiuses of the disk will alter the value of $u$ at large distances. This should not be the case as, no matter how the luminosity is geometrically distributed, it should always reduce to the case of a point source at very large distances."
]
},
{
Expand Down Expand Up @@ -438,15 +438,15 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"as we can see in both reference frames the energy density of the BLR tends to the one of a point source behind the jet for large enough distances."
"As we can see in both reference frames the energy density of the BLR tends to the one of a point source behind the jet for large enough distances."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Ring Dust Torus\n",
"Finally let us repeat the same exercise for the Torus"
"Finally let us repeat the same exercise for the torus."
]
},
{
Expand Down Expand Up @@ -590,7 +590,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"again in both reference frames the energy density of the dust torus tends to the one of a point source behind the jet with its same luminosity."
"Again in both reference frames the energy density of the dust torus tends to the one of a point source behind the jet with its same luminosity."
]
}
],
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6 changes: 3 additions & 3 deletions docs/tutorials/external_compton.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"## Tutorial: External Compton\n",
"In this tutorial we will show how to compute the Spectral Energy Distribution produced by Compton scattering by the blob electorns of three different photon targets: a Shakura Sunyaev accretion disk, a Broad Line region represented as a spherical shell and a Dust Torus represented as a simple ring."
"## Tutorial: External Compton scattering\n",
"In this tutorial we will show how to compute the Spectral Energy Distribution produced by Compton scattering by the blob electrons of three different photon targets: a Shakura Sunyaev accretion disk, a Broad Line region represented as a spherical shell and a Dust Torus represented as a simple ring."
]
},
{
Expand Down Expand Up @@ -228,7 +228,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Similarly to the synchrotron self-Compton case, to intitialise the object that will compute the external Compton (EC) radiation, we simply pass the `Blob` and the `Target` objects to the `ExternalCompton` class. **Note** in this case also the distance `r` between the target and the emission region (in `astropy.units`) has to be specified, as this will modify the SED."
"Similarly to the synchrotron self-Compton case, to intitialise the object that will compute the external Compton (EC) radiation, we simply pass the `Blob` and the `Target` objects to the `ExternalCompton` class. **Note** in this case the distance `r` between the target and the emission region (in `astropy.units`) also has to be specified, as this will modify the SED."
]
},
{
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12 changes: 6 additions & 6 deletions docs/tutorials/ssc_gammapy_fit.ipynb
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Expand Up @@ -53,8 +53,8 @@
"id": "c685d482",
"metadata": {},
"source": [
"### gammapy wrapper of agnpy synchrotron and SSC\n",
"Now let us [follow the Gammapy documentation](https://docs.gammapy.org/0.18.2/tutorials/models.html#Implementing-a-Custom-Model) and define a custom gammapy model wrapping agnpy's functions to compute the Synchrotron and Synchrotron Self Compton SEDs. We will assume a broken power-law electron distribution.\n",
"### `gammapy` wrapper of agnpy synchrotron and SSC\n",
"Now let us [follow the Gammapy documentation](https://docs.gammapy.org/0.18.2/tutorials/models.html#Implementing-a-Custom-Model) and define a custom `gammapy` model wrapping `agnpy`'s functions to compute the Synchrotron and Synchrotron Self Compton SEDs. We will assume a broken power-law electron distribution.\n",
"\n",
"**NOTE:** for the parameters that vary over several orders of magnitude (i.e. normalisation and Lorentz factors of the electron distribution) it is better to provide to the fitting routine a \"scaled\" version of them (e.g. their log10), such that larger ranges might be covered with small parameters variation.\n",
"\n",
Expand Down Expand Up @@ -157,8 +157,8 @@
"id": "46387cd2",
"metadata": {},
"source": [
"### Fit with gammapy\n",
"Let us start here the procedure to fit with Gammapy\n",
"### Fit with `gammapy`\n",
"Here we start the procedure to fit with `Gammapy`.\n",
"\n",
"#### 1) load the MWL flux points \n",
"The MWL SEDs included in the default `agnpy` data are automatically readable by `Gammapy`'s `FluxPoints`"
Expand Down Expand Up @@ -196,7 +196,7 @@
"metadata": {},
"source": [
"#### 2) add systematic errors\n",
"Currently there is no function in gammapy handling systematic errors on flux points. \n",
"Currently there is no function in `gammapy` handling systematic errors on flux points. \n",
"Let us manually add different systematic errors in different energy bands. \n",
"We assume them to be independent from the statistical ones and sum the two in quadrature."
]
Expand Down Expand Up @@ -425,7 +425,7 @@
"id": "02efa3c2",
"metadata": {},
"source": [
"#### Use Gammapy best-fit parameters and agnpy to plot the best-fit model specifying its individual components\n",
"#### Use `Gammapy` best-fit parameters and `agnpy` to plot the best-fit model specifying its individual components\n",
"We fetch the best-fit parameters for our model and we use them to specify and plot the individual spectral components."
]
},
Expand Down
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