Rad Lab is a Monte-Carlo simulation toolkit for modeling the performance of Geiger–Müller tubes. Built on top of Calzone/Geant4, it provides an easy-to-use, reproducible, and extensible environment for detector simulation and design.

With Rad Lab, you can:

• Compute detector efficiency (detected particles per incident particle).
• Determine dose sensitivity (cpm per µSv/h) using ICRP 74.
• Explore the directional response of detectors.
• Obtain correct sensitivities for various radiation sources.
• Prototype and evaluate measurement geometries.

Explore the included notebooks:

• Simulated gamma spectra
• J305 Geiger tube
• M4011 Geiger tube
• HH614 Geiger tube
• СБМ20 (SBM20) Geiger tube
• СИЗБГ (SI3BG) Geiger tube
• LND 7317 Geiger tube

1. Install the latest Geant4 binary release: https://geant4.web.cern.ch/download/

2. Install Python: https://www.python.org/

3. Install PIP: https://pip.pypa.io/en/stable/

4. Install Python dependencies:

   pip install -r requirements.txt
   

5. Install VSCode: https://code.visualstudio.com/

6. In VSCode, install the Jupyter extension (left toolbar → Extensions → search for "Jupyter").

1. Start from an existing example notebook to create or modify a detector.
2. Edit the geometry file data/geometry.toml. (See Calzone Geometry docs: https://calzone.readthedocs.io/en/latest/geometry.html)
3. Open the corresponding notebook in VS Code and run the simulation.

Rad Lab uses a right-handed coordinate system:

• x-axis: along the detector’s length
• y-axis: direction of incoming radiation
• z-axis: upward

To display a geometry:

calzone display [geometry.toml]

For navigation instructions, see the Calzone Interactive Display docs: https://calzone.readthedocs.io/en/latest/display.html

Rad Lab performs the following steps:

1. Loads geometry

   A geometry.toml file specifies:

   • a Source box emitting parallel particles toward the detector at the coordinate origin. The source area equals the width × height of this box.
   • an EffectiveVolume, inside which freed electrons are counted.

2. Runs Monte-Carlo transport

   Particle transport is simulated using Calzone/Geant4.

3. Counts ionization electrons

   Electrons entering or produced in the EffectiveVolume are counted.

4. Computes detector efficiency

   Efficiency = detected electrons / incident particles.

5. Computes dose sensitivity

   • Ambient dose equivalent: using ICRP 74.

6. Generates emission spectra

   • Isotopes: spectra from paceENSDF (IAEA ENSDF data).
   • X-ray tubes: spectra from SpekPy.
   • Natural background: modeled as a simple decaying exponential.

7. Computes equivalent effective dose for each source.

To generate or update gamma spectra, run the notebook: build-spectra.ipynb

You will need:

• paceENSDF
• spekPy

• Special thanks to BikingBoffin from /r/radiation for inspiring this project.