purification_tebd

  • full name: tenpy.algorithms.purification_tebd

  • parent module: tenpy.algorithms

  • type: module

Classes

Inheritance diagram of tenpy.algorithms.purification_tebd

BackwardDisentangler(parent)

Disentangle with backward time evolution.

CompositeDisentangler(disentanglers)

Concatenate multiple disentanglers.

DiagonalizeDisentangler(parent)

Disentangle by diagonalizing the two-site density matrix in the auxiliar 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>.

PurificationTEBD(psi, model, TEBD_params)

Time evolving block decimation (TEBD) for purification MPS.

PurificationTEBD2(psi, model, TEBD_params)

Similar as PurificationTEBD, but perform sweeps instead of brickwall.

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

Time evolving block decimation (TEBD) for MPS of purification.

See introduction in purification_mps. Time evolution for finite-temperature ensembles. This can be used to obtain correlation functions in time.

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