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compscat-0.3.0
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مشاهده بیشترتوضیحات
Monte Carlo Simulation of Compton Scattering
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | compscat-0.3.0 |
| نام | compscat |
| نسخه کتابخانه | 0.3.0 |
| نگهدارنده | ['Aman Desai'] |
| ایمیل نگهدارنده | ['amanmukeshdesai@gmail.com'] |
| نویسنده | Aman Desai |
| ایمیل نویسنده | amanmukeshdesai@gmail.com |
| آدرس صفحه اصلی | https://github.com/amanmdesai/compscat |
| آدرس اینترنتی | https://pypi.org/project/compscat/ |
| مجوز | - |
# CompScat
[](https://github.com/amanmdesai/compscat/blob/master/LICENSE.txt)
[](https://github.com/amanmdesai/compscat/actions/workflows/test.yaml)
[](https://amanmdesai.github.io/compscat/)
[](https://pypi.python.org/pypi/compscat)
[](https://pypi.python.org/pypi/compscat)
[](https://doi.org/10.5281/zenodo.7192619)
## Author
Aman Desai
## Description
Monte Carlo simulation of fixed-target Compton scattering. The study has been compared with Madgraph5amc_NLO MC event generator. The full analysis can be found here [Link](https://github.com/amanmdesai/compscat/tree/master/analysis). The analysis is currently done in C++ (ROOT Framework). To analyse the Madgraph LHE file, an LHE reader deverloped [here](https://github.com/amanmdesai/LHE-Reader) is used.
## Physics
Representative Feynman diagrams for compton scattering
<p align="center">
<img alt="compton-feynman diagram 2" src="https://raw.githubusercontent.com/amanmdesai/compscat/master/analysis/images/compton.png" width="200"/>
<img alt="compton-feynman diagram 2" src="https://raw.githubusercontent.com/amanmdesai/compscat/master/analysis/images/compton2.png" width="200"/>
</p>
## Validation of CompScat
The following plots compare the final states for CompScat with the Madgraph5amc_NLO final states.
### Cross section
Evaluated using $10^6$ phase points with CompScat and using the Madgraph file as given in analysis folder.
Plot showing the cross section versus energy (with error bars):
<p align="center">
<img alt="xsec_vs_energy" src="https://raw.githubusercontent.com/amanmdesai/compscat/master/analysis/images/xsec_vs_energy.jpg" width="350"/>
</p>
| Initial Photon Energy | CompScat $\sigma$ (milibarn) | Madgraph $\sigma$ (milibarn)|
| ----------------------| --------- | ------|
| 50 MeV | 15.585 $\pm$ 0.0495 | 15.57 $\pm$ 0.037 |
| 100 MeV | 8.783 $\pm$ 0.0361 | 8.799 $\pm$ 0.028 |
| 200 MeV | 4.857 $\pm$ 0.0255 | 4.87 $\pm$ 0.019 |
| 300 MeV | 3.414 $\pm$ 0.0205 | 3.43 $\pm$ 0.0081 |
| 400 MeV | 2.669 $\pm$ 0.0185 | 2.664 $\pm$ 0.0051 |
| 500 MeV | 2.194 $\pm$ 0.0161 | 2.203 $\pm$ 0.0044 |
In the following, the initial photon energy is set to 0.1 GeV (electron is at rest).
### Photon final state kinematics
<p align="center">
<img src="https://raw.githubusercontent.com/amanmdesai/compscat/master/analysis/images/photon_energy.png" width="250" title="photon_energy" />
<img src="https://raw.githubusercontent.com/amanmdesai/compscat/master/analysis/images/photon_px.png" width="250" title="photon_px"/>
</p>
<p align="center">
<img src="https://raw.githubusercontent.com/amanmdesai/compscat/master/analysis/images/photon_py.png" width="250" title="photon_py"/>
<img src="https://raw.githubusercontent.com/amanmdesai/compscat/master/analysis/images/photon_pz.png" width="250" title="photon_pz"/>
</p>
### Electron final state kinematics
<p align="center">
<img src="https://raw.githubusercontent.com/amanmdesai/compscat/master/analysis/images/electron_energy.png" width="250" title="photon_energy">
<img src="https://raw.githubusercontent.com/amanmdesai/compscat/master/analysis/images/electron_px.png" width="250" title="photon_px">
</p>
<p align="center">
<img src="https://raw.githubusercontent.com/amanmdesai/compscat/master/analysis/images/electron_py.png" width="250" title="photon_py">
<img src="https://raw.githubusercontent.com/amanmdesai/compscat/master/analysis/images/electron_pz.png" width="250" title="photon_pz">
</p>
## Installation
Use:
```bash
pip install compscat
```
or to install from the latest branch use:
```bash
git clone https://github.com/amanmdesai/compscat.git
cd compscat
pip install .
```
## Run the generator!
Description of the example in notebooks:
To import the library use
```python
from compscat import CrossSection, SaveEvent,constants,PlotData
```
and then set the energy of the incoming photon in MeV:
```python
E = 0.1
```
The step below is the crucial step as the Cross Section is evaluated here. Only the energy is passed as an argument.
```python
w_sum, w_square, w_max = CrossSection(
E / constants.m
).integrate_xsec()
```
The script below will generate the events according to the w_max obtained above and Energy specified by the user. Moreover, the below class will also save the events (either as root or in a csv file). To save in root format use:
```python
SaveEvent(10000, w_max, E).to_root()
```
else to save them in a csv file use:
```python
SaveEvent(10000, w_max, E).to_csv()
```
Finally the scripts below will plot the data and store it as pdf. If you have saved the events in a root format use:
```python
PlotData.file("MC_compton.root")
```
else if you are using csv file, use:
```python
PlotData.file("MC_compton.csv")
```
## Evaluate the Cross section
See the notebook 'cross-section.ipynb'
## Exercises
* Evaluate the cross section of compton scattering using the `CrossSection` module for different initial proton energies. Plot the same.
* Study the final states at different energies and plot them on the same plot.
* Find the angles $\phi$ and $\theta$ of scattering.
* Make a 2D plot of the energy of photon/electron with the angle of scattering ( $\phi$ and $\theta$).
## Acknowledgements
We would like to thank Dr. Olivier Mattelaer (UCLouvain, Belgium), whose suggestion on applying cuts in the Madgraph configuration file was helpful in validation of the final states predicted by the CompScat package. We are grateful to Dr. Kilian Lieret (Princeton University, USA), whose suggestion to me about pre-commit config/python packaging (cookiecutter) was helpful in the overall formatting/structuring of the python package.
## References
1. For physics involved in the calculation, see for example, _Introduction to Elementary Particles_, David Griffiths.
2. For monte carlo techniques: _Statistical data analysis_, Glen Cowan, 1998.
3. For the equations used by the simulator see for example,
[Link](http://www.personal.soton.ac.uk/ab1u06/teaching/qft/qft1/christmas_problems/2014/XmasProb_DMillar.pdf)
4. Also see: Papaefstathiou, A. How-to: write a parton-level Monte Carlo particle physics event generator. Eur. Phys. J. Plus 135, 497 (2020).
5. Alwall, J. and others, The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations.
نیازمندی
| مقدار | نام |
|---|---|
| - | numpy |
| - | uproot |
| - | matplotlib |
| - | pandas |
نحوه نصب
نصب پکیج whl compscat-0.3.0:
pip install compscat-0.3.0.whl
نصب پکیج tar.gz compscat-0.3.0:
pip install compscat-0.3.0.tar.gz