Simulation

These tutorials cover how pyGSTi simulates circuits — computing the outcome probabilities a model predicts. Simulation underlies model fitting, but you can also use it standalone for forward simulation. Start with circuit simulation, then see how to pick a forward-simulation method and generate synthetic data.

• Circuit simulation — compute outcome probabilities for a circuit from a model, including stabilizer/CHP and explicit- vs. implicit-model variants.

• Data simulation — turn model predictions into simulated experimental datasets (finite-shot samples).

• Error generator propagation — propagate error generators through the layers of a circuit to get numerical quantities of interest.

• Error generator polynomials — propagate error generators through the layers of a circuit to get symbolic representations of quantities of interest, like end-of-circuit error generators.

• Forward simulation types — the available forward simulators (matrix, map, term, …) and when to use each.