Config#

class Config(*, cutoff: int = 4, normalize: bool = True, dtype: type = <class 'numpy.float64'>, measurement_cutoff: int = 5, hbar: float = 2.0, seed_sequence: ~typing.Any | None = None, use_torontonian: bool = False, cache_size: int = 32)#

The configuration for the simulation.

Variables:

  • cutoff – The Fock space cutoff. Defaults to 4.

  • normalize – If True, the state is normalized for active gates in Fock-space based simulations. Defaults to True.

  • dtype – The underlying datatype of the simulation. Possible values: np.float32 and np.float64. Defaults to np.float64.

  • measurement_cutoff – The maximum number of particles to be allowed for ParticleNumberMeasurement using GaussianSimulator. Defaults to 5.

  • hbar – The value of the Planck constant. Defaults to 2.0.

  • seed_sequence – The seed for reproducability of sampling algorithms.

  • use_torontonian – Uses torontonian for ThresholdMeasurement. Defaults to False.

  • cache_size – The maximum size of the cache for certain algorithms. Defaults to 2.0.

property seed_sequence#

The seed sequence used to generate random numbers during the simulation.

property complex_dtype#

Returns the complex precision depending on the dtype of the Config class

copy() → Config#

Returns an exact copy of this config object.

Returns:

An exact copy of this config object.

Return type:

Config