https://github.com/bjoernbiltzinger/pynchrotron

Implements synchrotron emission from cooling electrons

https://github.com/bjoernbiltzinger/pynchrotron

Repository

Implements synchrotron emission from cooling electrons

https://github.com/BjoernBiltzinger/pynchrotron/blob/master/

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# pynchrotron
![alt text](https://raw.githubusercontent.com/grburgess/pynchrotron/master/logo.png)

Implements synchrotron emission from cooling electrons. This is the model used in [Burgess et al (2019)](https://www.nature.com/articles/s41550-019-0911-z?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+natastron%2Frss%2Fcurrent+%28Nature+Astronomy%29&utm_content=Google+Feedfetcher). Please cite if you find this code useful for your research.

* This code gets rid of the need for GSL which was originally relied on for a quick computation of the of the synchrotron kernel which is an integral over a  Bessel function. 
* This code has been ported from GSL and written directly in python as well as accelerated with numba
* An astromodels function is also supplied for direct use in 3ML.


## Usage

```python
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
%matplotlib inline 

import pynchrotron
```

    /Users/jburgess/.environs/pynchro/lib/python3.7/site-packages/astromodels/core/parameter.py:555: UserWarning: We have set the min_value of K to 1e-99 because there was a postive transform
      warnings.warn('We have set the min_value of %s to 1e-99 because there was a postive transform' % self.path)
    /Users/jburgess/.environs/pynchro/lib/python3.7/site-packages/astromodels/core/parameter.py:555: UserWarning: We have set the min_value of xc to 1e-99 because there was a postive transform
      warnings.warn('We have set the min_value of %s to 1e-99 because there was a postive transform' % self.path)


## Create an astromodels model


```python
model = pynchrotron.SynchrotronNumerical()

model


```






description: Synchrotron emission from cooling electrions

formula: $  $

parameters: 


K: 


value: 1.0

desc: normalization

min_value: 0.0

max_value: None

unit: 

is_normalization: False

delta: 0.1

free: True





B: 


value: 100.0

desc: energy scaling

min_value: 0.01

max_value: None

unit: 

is_normalization: False

delta: 10.0

free: True





index: 


value: 3.5

desc: spectral index of electrons

min_value: 2.0

max_value: 6.0

unit: 

is_normalization: False

delta: 0.35000000000000003

free: True





gamma_min: 


value: 500000.0

desc: minimum electron lorentz factor

min_value: 1.0

max_value: None

unit: 

is_normalization: False

delta: 50000.0

free: False





gamma_cool: 


value: 90000000.0

desc: cooling time of electrons

min_value: None

max_value: None

unit: 

is_normalization: False

delta: 9000000.0

free: True





gamma_max: 


value: 100000000.0

desc: minimum electron lorentz factor

min_value: 1000000.0

max_value: None

unit: 

is_normalization: False

delta: 10000000.0

free: False





bulk_gamma: 


value: 1.0

desc: bulk Lorentz factor

min_value: 1.0

max_value: None

unit: 

is_normalization: False

delta: 0.1

free: False














## Plot the model


```python
fig, ax = plt.subplots()


ene = np.logspace(1,6,400)

ax.loglog(ene, ene**2 * model(ene))
ax.set_xlabel('energy')
ax.set_ylabel(r'$\nu F_{\nu}$')
```




    Text(0, 0.5, '$\\nu F_{\\nu}$')




![png](demo_files/demo_4_1.png)



```python
fig, ax = plt.subplots()

gamma_min = 500000.

gamma_cool = np.linspace(.1 * gamma_min, 5* gamma_min, 10)



ene = np.logspace(-1,6,400)

for gc in gamma_cool:
    model.gamma_cool = gc
    model.gamma_min = gamma_min
    
    ax.loglog(ene, ene**2 * model(ene))
ax.set_xlabel('energy')
ax.set_ylabel(r'$\nu F_{\nu}$')
```




    Text(0, 0.5, '$\\nu F_{\\nu}$')




![png](demo_files/demo_5_1.png)

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