RenyiDisentangler¶
full name: tenpy.algorithms.purification_tebd.RenyiDisentangler
parent module:
tenpy.algorithms.purification_tebd
type: class
-
class
tenpy.algorithms.purification_tebd.
RenyiDisentangler
(parent)[source]¶ Bases:
tenpy.algorithms.purification_tebd.Disentangler
Iterative find U which minimized the second Renyi entropy.
See [Hauschild2018]
Reads of the following TEBD_params as break criteria for the iteration:
key
type
description
disent_eps
float
Break, if the change in the Renyi entropy
S(n=2)
per iteration is smaller than this value.disent_max_iter
float
Maximum number of iterations to perform.
Arguments and return values are the same as for
disentangle()
.Methods
__call__
(self, theta)Find optimal U which minimizes the second Renyi entropy.
iter
(self, theta, U)Given theta and U, find another U which reduces the 2nd Renyi entropy.
-
iter
(self, theta, U)[source]¶ Given theta and U, find another U which reduces the 2nd Renyi entropy.
Temporarily view the different U as independt and mimizied one of them - this corresponds to a linearization of the cost function. Defining Utheta as the application of U to theata, and combining the p legs of theta with
'vL', 'vR'
, this function contracts:| .----theta----. | | | | | | | q0 q1 | | | | | | q1* | | | | | | | .-Utheta*-. | | | | | | .-Utheta--. | | | | | | q0* | | | | | | | | .----Utheta*-.
The trace yields the second Renyi entropy S2. Further, we calculate the unitary U with maximum overlap with this network.
- Parameters
- Returns
- S2float
Renyi entopy (n=2), \(S2 = \frac{1}{1-2} \log tr(\rho_L^2)\) of U theta.
- new_U
Array
Unitary with legs
'q0', 'q1', 'q0*', 'q1*'
, which should disentangle theta.
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