Metadata-Version: 2.4
Name: picht
Version: 1.0.3
Summary: Electron optics simulation library using the Finite Difference Method (FDM)
Home-page: https://github.com/rolypolytoy/picht
Author: Rishiit Sharma
Author-email: Rishiit Sharma <rishiitsharma@gmail.com>
License-Expression: MIT
Project-URL: Homepage, https://github.com/rolypolytoy/picht
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Intended Audience :: Science/Research
Classifier: Development Status :: 5 - Production/Stable
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: matplotlib
Requires-Dist: scipy
Requires-Dist: numba
Requires-Dist: mendeleev
Dynamic: author
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-python

# Picht

A Python library for simulating the electrodynamics of electrons and ions through electrostatic lenses. Supports cylinder lenses, unipotential lenses, and variable beam diameters, as well as custom amounts of initial divergence/convergence. Parameterize the electrodes with the voltages you want, control the mesh size, and obtain accurate trajectories in the axisymmetric view.

You can use it to simulate electron optics, to help design electron microscopes, focused ion beam systems, or simply better understand how electrostatic lenses work. Most implementations use the paraxial ray equation for simplification, but this approximation deviates significantly from reality with angles disparate from the z-axis. We, instead, compute the electric fields in full, and then compute particle trajectories using an ODE solver. This, combined with relativistic corrections at every step, allows for a significant degree of accuracy for very high particle energies (keV, MeV scale and above). It's capable of simulating multi-lens systems with 100+ charged particles in seconds to minutes, with easy Pythonic syntax, and installation is extremely easy, with PyPi handling the extremely small amount of dependencies in its entirety.

## Installation
```bash
pip install picht
```

## Documentation

I've made a reference example that includes several electrodes and einzel lenses in the configuration of an actual scanning electron microscope's internals. 

```python
import numpy as np
from picht import IonOpticsSystem, ElectrodeConfig
import matplotlib.pyplot as plt

system = IonOpticsSystem(nr=400, nz=400, physical_size=0.4) #all grid units are in mm.


wehnelt1 = ElectrodeConfig(
    start=0,
    width=30,
    ap_start=180,
    ap_width=40,
    outer_diameter = 50,
    voltage=-10200
)
wehnelt2 = ElectrodeConfig(
    start=30,
    width=5,
    ap_start=190,
    ap_width=20,
    outer_diameter = 50,
    voltage=-10200
)
system.add_electrode(wehnelt1)
system.add_electrode(wehnelt2)
anode = ElectrodeConfig(
    start=40,
    width = 2,
    ap_start=198,
    ap_width=4,
    outer_diameter = 50,
    voltage=0
)
cathode = ElectrodeConfig(
    start=22,
    width = 2,
    ap_start=200,
    ap_width=0,
    outer_diameter = 2,
    voltage=-10000
)

system.add_electrode(anode)
system.add_einzel_lens(
    position=80.0,
    width=60.0,
    aperture_center=200.0,
    aperture_width=48.0,
    outer_diameter=50.0,
    focus_voltage=-7500
)
system.add_einzel_lens(
    position=150.0,
    width=60.0,
    aperture_center=200.0,
    aperture_width=48.0,
    outer_diameter=50.0,
    focus_voltage=-7500
)
system.add_einzel_lens(
    position=220.0,
    width=50.0,
    aperture_center=200.0,
    aperture_width=48.0,
    outer_diameter=50.0,
    focus_voltage=-7000
)
potential = system.solve_fields()

trajectories = system.simulate_beam(
    energy_eV= 10,  
    start_z=0.025,
    r_range=(0.1999925, 0.2000075),
    angle_range=(0, 0),
    num_particles=100,
    simulation_time=2e-8
)

figure = system.visualize_system(
    trajectories=trajectories)

plt.show()
```

The visualization is beautiful, and shows cross-over based demagnification of spherical aberrations, like in real-world electrostatic lenses. In other words, the 'thickness' of the focal point reduces, until the last focal point, which is the thinnest. However, rogue electrons do increase in every crossover, which is also indicative of real-life systems. Apertures are used to mitigate this. 

![FullElectronOptics](https://github.com/user-attachments/assets/22f984b8-569f-4406-89ab-941ae67f7ed5)

The main reason spherical aberrations increase after the objective lens is because you need the final crossover to happen after the last electrode of the einzel lens, and the more you extend this, the less clean the crossover is, and so the more spherical aberrations arise. This is why you often position the sample right below the opening to the electron column- the focal length is often already minimized to reduce spherical aberration.

You can also specify ions by, prior to computing the trajectories, where the below syntax is for an Na+ ion:

```python
system.tracer.set_ion('Na', charge_state=1)
```

You can use the chemical symbol of any element, and use negative charge_state values to represent ions with a negative charge. If you don't include this, by default, it assumes it's an electron.
