| from functools import partial |
|
|
| import jax.numpy as jnp |
| from jax import jit |
|
|
| from varipeps.peps import PEPS_Tensor |
| from varipeps.contractions import apply_contraction_jitted |
|
|
| from typing import Sequence, List, Tuple, Literal |
|
|
| Corner_Literal = Literal["top-left", "top-right", "bottom-left", "bottom-right"] |
|
|
|
|
| @partial(jit, static_argnums=(5,)) |
| def _four_sites_quadrat_workhorse( |
| top_left: jnp.ndarray, |
| top_right: jnp.ndarray, |
| bottom_left: jnp.ndarray, |
| bottom_right: jnp.ndarray, |
| gates: Tuple[jnp.ndarray, ...], |
| real_result: bool = False, |
| ) -> List[jnp.ndarray]: |
| density_matrix = jnp.tensordot(top_left, top_right, ((5, 6, 7), (2, 3, 4))) |
| density_matrix = jnp.tensordot(density_matrix, bottom_left, ((2, 3, 4), (5, 6, 7))) |
| density_matrix = jnp.tensordot( |
| density_matrix, bottom_right, ((4, 5, 6, 9, 10, 11), (2, 3, 4, 5, 6, 7)) |
| ) |
|
|
| density_matrix = density_matrix.transpose(0, 2, 4, 6, 1, 3, 5, 7) |
| density_matrix = density_matrix.reshape( |
| density_matrix.shape[0] |
| * density_matrix.shape[1] |
| * density_matrix.shape[2] |
| * density_matrix.shape[3], |
| density_matrix.shape[4] |
| * density_matrix.shape[5] |
| * density_matrix.shape[6] |
| * density_matrix.shape[7], |
| ) |
|
|
| norm = jnp.trace(density_matrix) |
|
|
| if real_result: |
| return [ |
| jnp.real(jnp.tensordot(density_matrix, g, ((0, 1), (0, 1))) / norm) |
| for g in gates |
| ] |
| else: |
| return [ |
| jnp.tensordot(density_matrix, g, ((0, 1), (0, 1))) / norm for g in gates |
| ] |
|
|
|
|
| def calc_four_sites_quadrat_multiple_gates( |
| peps_tensors: Sequence[jnp.ndarray], |
| peps_tensor_objs: Sequence[PEPS_Tensor], |
| gates: Sequence[jnp.ndarray], |
| ) -> List[jnp.ndarray]: |
| """ |
| Calculate the four site expectation values for three as quadrat ordered |
| PEPS tensor and their environment. |
| |
| The order of the PEPS sequence have to be |
| [top-left, top-right, bottom-left, bottom-right]. |
| |
| The gate is applied in the order [top-left, top-right, bottom-left, bottom-right]. |
| |
| Args: |
| peps_tensors (:term:`sequence` of :obj:`jax.numpy.ndarray`): |
| The PEPS tensor arrays. Have to be the same objects as the tensor |
| attribute of the `peps_tensor_obj` argument. |
| peps_tensor_objs (:term:`sequence` of :obj:`~varipeps.peps.PEPS_Tensor`): |
| PEPS tensor objects. |
| gates (:term:`sequence` of :obj:`jax.numpy.ndarray`): |
| Sequence with the gates which should be applied to the PEPS tensors. |
| Gates are expected to be a matrix with first axis corresponding to |
| the Hilbert space and the second axis corresponding to the dual room. |
| Returns: |
| :obj:`list` of :obj:`jax.numpy.ndarray`: |
| List with the calculated expectation values of each gate. |
| """ |
| density_matrix_top_left = apply_contraction_jitted( |
| "density_matrix_four_sites_top_left", |
| [peps_tensors[0]], |
| [peps_tensor_objs[0]], |
| [], |
| ) |
|
|
| density_matrix_top_right = apply_contraction_jitted( |
| "density_matrix_four_sites_top_right", |
| [peps_tensors[1]], |
| [peps_tensor_objs[1]], |
| [], |
| ) |
|
|
| density_matrix_bottom_left = apply_contraction_jitted( |
| "density_matrix_four_sites_bottom_left", |
| [peps_tensors[2]], |
| [peps_tensor_objs[2]], |
| [], |
| ) |
|
|
| density_matrix_bottom_right = apply_contraction_jitted( |
| "density_matrix_four_sites_bottom_right", |
| [peps_tensors[3]], |
| [peps_tensor_objs[3]], |
| [], |
| ) |
|
|
| real_result = all(jnp.allclose(g, g.T.conj()) for g in gates) |
|
|
| return _four_sites_quadrat_workhorse( |
| density_matrix_top_left, |
| density_matrix_top_right, |
| density_matrix_bottom_left, |
| density_matrix_bottom_right, |
| tuple(gates), |
| real_result, |
| ) |
|
|
