4.6. tnpy.tsdrg.ShiftInvertTreeTensorNetworkSDRG

class tnpy.tsdrg.ShiftInvertTreeTensorNetworkSDRG(mpo, chi, offset)

Bases: tnpy.tsdrg.TreeTensorNetworkSDRG

The tree tensor network version of strong disorder renormalization group algorithm.

Parameters

• mpo (MatrixProductOperator) – The matrix product operator.

• chi (int) – The truncation dimensions.

• offset (float) –

Examples

The tSDRG algorithm can be launched by calling run() method.

>>> tsdrg = TreeTensorNetworkSDRG(mpo, chi=32)
>>> tsdrg.run()

After executing run(), one can access the binary tensor tree TensorTree through the attribute tree. For measurements, please refer to measurements or TreeTensorNetworkMeasurements.

__init__(mpo, chi, offset)

The tree tensor network version of strong disorder renormalization group algorithm.

Parameters

• mpo (tnpy.operators.MatrixProductOperator) – The matrix product operator.

• chi (int) – The truncation dimensions.

• offset (float) –

Examples

The tSDRG algorithm can be launched by calling run() method.

>>> tsdrg = TreeTensorNetworkSDRG(mpo, chi=32)
>>> tsdrg.run()

After executing run(), one can access the binary tensor tree TensorTree through the attribute tree. For measurements, please refer to measurements or TreeTensorNetworkMeasurements.

Methods

__init__(mpo, chi, offset)	The tree tensor network version of strong disorder renormalization group algorithm.
block_eigen_solver(locus)	Solve the 2-site Hamiltonian with chi lowest eigen-pairs.
block_hamiltonian(locus)	Construct the 2-site Hamiltonian from coarse-graining MPO.
run()	Start the algorithm.
spectrum_projector(locus, evecs)	Coarse-grain the MPO with given evecs which is used to form a projector.
truncation_gap(evals)	Return the gap upon chi eigenvalues kept.

Attributes

chi	The input bond dimensions.
evals	The renormalized eigenvalues, with length chi.
measurements	Call available measurements in TreeTensorNetworkMeasurements.
mpo	The input matrix product operator.
n_sites	Number of sites, i.e. the system size.
offset
tree	The tree.

__init__(mpo, chi, offset)

The tree tensor network version of strong disorder renormalization group algorithm.

Parameters

• mpo (tnpy.operators.MatrixProductOperator) – The matrix product operator.

• chi (int) – The truncation dimensions.

• offset (float) –

Examples

The tSDRG algorithm can be launched by calling run() method.

>>> tsdrg = TreeTensorNetworkSDRG(mpo, chi=32)
>>> tsdrg.run()

After executing run(), one can access the binary tensor tree TensorTree through the attribute tree. For measurements, please refer to measurements or TreeTensorNetworkMeasurements.

property offset: float

block_eigen_solver(locus)

Solve the 2-site Hamiltonian with chi lowest eigen-pairs.

Parameters

locus (int) – The site in coarse-grained system during the RG process.

Returns

A tuple (evals, evecs), where evals are the lowest chi eigenvalues, and evecs are the corresponding eigenvectors.

Return type

Tuple[numpy.ndarray, numpy.ndarray]