mm.lab.State¶

class mrmustard.lab.State(cov=None, means=None, eigenvalues=None, symplectic=None, ket=None, dm=None, modes=None, cutoffs=None, _norm=1.0)[source]¶

Bases: object

Base class for quantum states.

Attributes

`cov`	Returns the covariance matrix of the state.
`cutoffs`	Returns the Hilbert space dimension of each mode.
`fock`	Returns the Fock representation of the state.
`is_mixed`	Returns whether the state is mixed.
`is_pure`	Returns `True` if the state is pure and `False` otherwise.
`means`	Returns the means vector of the state.
`modes`	Returns the modes of the state.
`norm`	Returns the norm of the state.
`number_cov`	Returns the complete photon number covariance matrix.
`number_means`	Returns the mean photon number for each mode.
`number_stdev`	Returns the square root of the photon number variances (standard deviation) in each mode.
`parameter_set`	The set of parameters for this state.
`probability`	Returns the probability of the state.
`purity`	Returns the purity of the state.
`shape`	Returns the shape of the state, accounting for ket/dm representation.

cov¶: Returns the covariance matrix of the state.

cutoffs¶: Returns the Hilbert space dimension of each mode.

fock¶: Returns the Fock representation of the state.

is_mixed¶: Returns whether the state is mixed.

is_pure¶: Returns True if the state is pure and False otherwise.

means¶: Returns the means vector of the state.

modes¶: Returns the modes of the state.

norm¶: Returns the norm of the state.

number_cov¶: Returns the complete photon number covariance matrix.

number_means¶: Returns the mean photon number for each mode.

number_stdev¶: Returns the square root of the photon number variances (standard deviation) in each mode.

parameter_set¶: The set of parameters for this state.

probability¶: Returns the probability of the state.

purity¶: Returns the purity of the state.

shape¶

Returns the shape of the state, accounting for ket/dm representation.

If the state is in Gaussian representation, the shape is inferred from the first two moments of the number operator.

Methods

`bargmann`([numpy])	Returns the Bargmann representation of the state.
`dm`([cutoffs])	Returns the density matrix of the state in Fock representation.
`fock_probabilities`(cutoffs)	Returns the probabilities in Fock representation.
`get_modes`(item)	Returns the state on the given modes.
`indices`(modes)	Returns the indices of the given modes.
`ket`([cutoffs, max_prob, max_photons])	Returns the ket of the state in Fock representation or `None` if the state is mixed.
`primal`(other)	Returns the post-measurement state after `other` is projected onto `self`.

bargmann(numpy=False)[source]¶

Returns the Bargmann representation of the state. If numpy=True, returns the numpy arrays instead of the backend arrays.

Return type:: Optional[tuple[ndarray[Tuple[int, int], TypeVar(C, complex64, complex128)], ndarray[Tuple[int], TypeVar(C, complex64, complex128)], complex]]

dm(cutoffs=None)[source]¶

Returns the density matrix of the state in Fock representation.

Parameters:: List[int] (cutoffs) – The cutoff dimensions for each mode. If a mode cutoff is None, it’s automatically computed.
Returns:: the density matrix
Return type:: Tensor

fock_probabilities(cutoffs)[source]¶

Returns the probabilities in Fock representation.

If the state is pure, they are the absolute value squared of the ket amplitudes. If the state is mixed they are the multi-dimensional diagonals of the density matrix.

Parameters:: List[int] (cutoffs) – the cutoff dimensions for each mode
Returns:: the probabilities
Return type:: Tensor

get_modes(item)[source]¶

Returns the state on the given modes.

Return type:: State

indices(modes)[source]¶

Returns the indices of the given modes.

Parameters:: modes (Sequence[int] or int) – the modes or mode
Returns:: a tuple of indices of the given modes or the single index of a single mode
Return type:: Tuple[int] or int

ket(cutoffs=None, max_prob=1.0, max_photons=None)[source]¶

Returns the ket of the state in Fock representation or None if the state is mixed.

Parameters:

None] (cutoffs List[int or) – The cutoff dimensions for each mode. If a mode cutoff is None, it’s guessed automatically.
max_prob (float) – The maximum probability of the state. Defaults to 1.0. (used to stop the calculation of the amplitudes early)
max_photons (int) – The maximum number of photons in the state, summing over all modes (used to stop the calculation of the amplitudes early)

Returns:

the ket

Return type:

Tensor

primal(other)[source]¶

Returns the post-measurement state after other is projected onto self.

other << self is other projected onto self.

If other is a Transformation, it returns the dual of the transformation applied to self: other << self is like self >> other^dual.

Note that the returned state is not normalized. To normalize a state you can use mrmustard.physics.normalize.

mm.lab.State¶

Attributes

Methods

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