Features
The simulator's capabilities — initialisation, cutoffs, evaluation, and parallelism.
This section summarises the capabilities of monoprop and explains how to use each one. For the ideas behind them see Concepts; for the full constructors and arguments see Python API.
The pages below group the features by stage of a workflow:
- Initialisation and updates — constructing a simulator (
MajoranaPropagatororPauliPropagator), choosing the Heisenberg or Schrödinger picture, and updating the Hamiltonian in place. - Truncation and cutoffs — controlling operator growth: the structural cutoff strategies and coefficient-tolerance filtering.
- Expectation values and gradients — replaying the propagated graph to evaluate expectation values and gradients, including paring.
- Parallelism and distribution — scaling across MPI ranks and shared-memory threads.