Engine¶

full name: tenpy.algorithms.tdvp.Engine
parent module: tenpy.algorithms.tdvp
type: class

Inheritance Diagram

Methods

`Engine.__init__`(psi, model, options[, …])	Initialize self.
`Engine.run_one_site`([N_steps])	Run the TDVP algorithm with the one site algorithm.
`Engine.run_two_sites`([N_steps])	Run the TDVP algorithm with two sites update.
`Engine.set_anonymous_svd`(U, new_label)	Relabel the svd.
`Engine.sweep_left_right`()	Performs the sweep left->right of the second order TDVP scheme with one site update.
`Engine.sweep_left_right_two`()	Performs the sweep left->right of the second order TDVP scheme with two sites update.
`Engine.sweep_right_left`()	Performs the sweep right->left of the second order TDVP scheme with one site update.
`Engine.sweep_right_left_two`()	Performs the sweep left->right of the second order TDVP scheme with two sites update.
`Engine.theta_svd_left_right`(theta)	Performs the SVD from left to right.
`Engine.theta_svd_right_left`(theta)	Performs the SVD from right to left.
`Engine.update_s_h0`(s, H, dt)	Update with the zero site Hamiltonian (update of the singular value)
`Engine.update_theta_h1`(Lp, Rp, theta, W, dt)	Update with the one site Hamiltonian.
`Engine.update_theta_h2`(Lp, Rp, theta, W0, W1, dt)	Update with the two sites Hamiltonian.

Class Attributes and Properties

Engine.TDVP_params

class tenpy.algorithms.tdvp.Engine(psi, model, options, environment=None)[source]¶

Bases: object

Time dependent variational principle ‘Engine’.

You can call run_one_site() for single-site TDVP, or run_two_sites() for two-site TDVP.

Deprecated since version 0.6.0: Renamed parameter/attribute TDVP_params to options.

Parameters

psi (MPS) – Initial state to be time evolved. Modified in place.
model (MPOModel) – The model representing the Hamiltonian for which we want to find the ground state.
options (dict) – Further optional parameters as described in the following table. Use verbose>0 to print the used parameters during runtime.
environment (:class:'~tenpy.networks.mpo.MPOEnvironment` | None) – Initial environment. If None (default), it will be calculated at the beginning.

Options

config TDVP¶

option	summary
dt	Time step of the Trotter error
Lanczos	Lanczos options as described in :cfg:config:`Lanczos`.
start_time	Initial value for :attr:`evolved_time`
trunc_params	Truncation parameters as described in :func:`~tenpy.algorithms.truncation.t [...]
verbose (from Config) in Config	How much to print what's being done; higher means print more. [...]

option start_time: float¶: Initial value for evolved_time

option dt: float¶: Time step of the Trotter error

option trunc_params: dict¶: Truncation parameters as described in truncate()

option Lanczos: dict¶: Lanczos options as described in Lanczos.

options¶

Optional parameters.

Type: dict

verbose¶

Level of verbosity (i.e. how much status information to print); higher=more output.

Type: int

evolved_time¶

Indicating how long psi has been evolved, psi = exp(-i * evolved_time * H) psi(t=0).

Type: float | complex

psi¶

The MPS, time evolved in-place.

Type: MPS

environment¶

The environment, storing the LP and RP to avoid recalculations.

Type: MPOEnvironment

lanczos_options¶

Options passed on to LanczosEvolution.

Type: Config

run_one_site(N_steps=None)[source]¶

Run the TDVP algorithm with the one site algorithm.

Warning

Be aware that the bond dimension will not increase!

Parameters: N_steps (integer. Number of steps) –

run_two_sites(N_steps=None)[source]¶

Run the TDVP algorithm with two sites update.

The bond dimension will increase. Truncation happens at every step of the sweep, according to the parameters set in trunc_params.

Parameters: N_steps (integer. Number of steps) –

sweep_left_right()[source]¶

Performs the sweep left->right of the second order TDVP scheme with one site update.

Evolve from 0.5*dt.

sweep_left_right_two()[source]¶

Performs the sweep left->right of the second order TDVP scheme with two sites update.

Evolve from 0.5*dt

sweep_right_left()[source]¶

Performs the sweep right->left of the second order TDVP scheme with one site update.

Evolve from 0.5*dt

sweep_right_left_two()[source]¶

Performs the sweep left->right of the second order TDVP scheme with two sites update.

Evolve from 0.5*dt

update_theta_h1(Lp, Rp, theta, W, dt)[source]¶

Update with the one site Hamiltonian.

Parameters

Lp (Array) – tensor representing the left environment
Rp (Array) – tensor representing the right environment
theta (Array) – the theta tensor which needs to be updated
W (Array) – MPO which is applied to the ‘p’ leg of theta

update_theta_h2(Lp, Rp, theta, W0, W1, dt)[source]¶

Update with the two sites Hamiltonian.

Parameters

Lp (tenpy.linalg.np_conserved.Array) – tensor representing the left environment
Rp (tenpy.linalg.np_conserved.Array) – tensor representing the right environment
theta (tenpy.linalg.np_conserved.Array) – the theta tensor which needs to be updated
W (tenpy.linalg.np_conserved.Array) – MPO which is applied to the ‘p0’ leg of theta
W1 (tenpy.linalg.np_conserved.Array) – MPO which is applied to the ‘p1’ leg of theta

theta_svd_left_right(theta)[source]¶

Performs the SVD from left to right.

Parameters: theta (tenpy.linalg.np_conserved.Array) – the theta tensor on which the SVD is applied

set_anonymous_svd(U, new_label)[source]¶

Relabel the svd.

Parameters: U (tenpy.linalg.np_conserved.Array) – the tensor which lacks a leg_label

theta_svd_right_left(theta)[source]¶

Performs the SVD from right to left.

Parameters: theta (tenpy.linalg.np_conserved.Array,) – The theta tensor on which the SVD is applied

update_s_h0(s, H, dt)[source]¶

Update with the zero site Hamiltonian (update of the singular value)

Parameters

s (tenpy.linalg.np_conserved.Array) – representing the singular value matrix which is updated
H (H0_mixed) – zero site Hamiltonian that we need to apply on the singular value matrix
dt (complex number) – time step of the evolution