1
Setup
Target mass, candidate nuclei and the expected number of events are computed from the parameters you choose.
Watch a theoretical transmutation, step by step
An educational console that draws a uniform random number for each virtual collision and compares it with a model probability. It does not represent real accelerator physics and it does not produce real nuclei.
How the console walks through the model
2
Collisions
Each trial draws u ~ Uniform(0, 1) and records a didactic transmutation when u is below p_model.
3
Results
Simulated events are compared with the expected value, together with the equivalent product mass.
Model
The target is treated as a mixture that includes a configurable source nuclide. A far jump in proton or nucleon number lowers the model probability p_model, so different elements do not behave the same.
N(source) = m(source) / M(source) × N_A p_model = p × 6 / max(6, |ΔZ| + |ΔA|) expected events = collisions × p_model m(product) = N(product) × M(product) / N_A
Run it locally
Python 3.9+ and a browser are enough. No extra packages. The standard library serves the graphical console.
python3 src/transmutation.py