entanglement distillation

Accessible in both numqi.entangle (recommended) and numqi.entangle.distillation

numqi.entangle.get_binegativity(rho, dimA, dimB)

calculate bi-negativity

reference: Entanglement Cost under Positive-Partial-Transpose-Preserving Operations doi-link

Parameters:

Name	Type	Description	Default
rho	(ndarray, Tensor)	density matrix, shape=(dimAdimB,dimAdimB)	required
dimA	int	dimension of A	required
dimB	int	dimension of B	required

Returns:

Name	Type	Description
ret	ndarray	bi-negativity, shape=(dimAdimB,dimAdimB)

numqi.entangle.get_PPT_entanglement_cost_bound(rho, dimA, dimB)

calculate the lower and upper bound of PPT entanglement cost

reference: Entanglement Cost under Positive-Partial-Transpose-Preserving Operations doi-link

Parameters:

Name	Type	Description	Default
rho	ndarray	density matrix, shape=(dimAdimB,dimAdimB)	required
dimA	int	dimension of A	required
dimB	int	dimension of B	required

Returns:

Name	Type	Description
lower_bound	float	lower bound of PPT entanglement cost
upper_bound	float	upper bound of PPT entanglement cost

numqi.entangle.SearchMinimumBinegativityModel

Bases: Module

__init__(dimA, dimB)

search the minimum of binegativity

see also: get_binegativity

Parameters:

Name	Type	Description	Default
dimA	int	dimension of A	required
dimB	int	dimension of B	required