disentangler

• full name: tenpy.algorithms.disentangler

• parent module: tenpy.algorithms

• type: module

Classes

BackwardDisentangler(parent)	Disentangle with backward time evolution.
CompositeDisentangler(disentanglers)	Concatenate multiple disentanglers.
DiagonalizeDisentangler(parent)	Disentangle by diagonalizing the two-site density matrix in the auxiliary space.
Disentangler(parent)	Prototype for a disentangler.
GradientDescentDisentangler(parent)	Gradient-descent optimization, similar to RenyiDisentangler.
LastDisentangler(parent)	Use the last total 'U' used in disentangle() for the same _update_index as guess.
MinDisentangler(disentanglers, parent)	Chose the disentangler giving the smallest entropy.
NoiseDisentangler(parent)	Apply a little bit of random noise.
NormDisentangler(parent)	Find optimal U for which the truncation of U|theta> has maximal overlap with U|theta>.
RenyiDisentangler(parent)	Iterative find U which minimized the second Renyi entropy.

Functions

get_disentangler(method, parent)

Parse the parameter method and construct a Disentangler instance.

Module description

Disentanglers.

The Disentanglers can be used to obtain a unitary reducing the entanglement between left and right while only acting on a subspace of the left and right Hilbert space.

For now, this is written for disentangling purifications; could be generalized to allow more legs.

tenpy.algorithms.disentangler.disentanglers_atom_parse_dict = {'None': <class 'tenpy.algorithms.disentangler.Disentangler'>, 'backwards': <class 'tenpy.algorithms.disentangler.BackwardDisentangler'>, 'diag': <class 'tenpy.algorithms.disentangler.DiagonalizeDisentangler'>, 'graddesc': <class 'tenpy.algorithms.disentangler.GradientDescentDisentangler'>, 'last': <class 'tenpy.algorithms.disentangler.LastDisentangler'>, 'noise': <class 'tenpy.algorithms.disentangler.NoiseDisentangler'>, 'norm': <class 'tenpy.algorithms.disentangler.NormDisentangler'>, 'renyi': <class 'tenpy.algorithms.disentangler.RenyiDisentangler'>}

Dictionary to translate the ‘disentangle’ TEBD parameter into a Disentangler.

If you define your own disentanglers, you can dynamically append them to this dictionary. CompositeDisentangler and MinDisentangler separate: they have non-default constructor and special syntax.