entanglish.MaxEntangState module¶
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class
entanglish.MaxEntangState.
MaxEntangState
(num_rows, row_shape, x_axes, y_axes)[source]¶ Bases:
object
This class is designed to perform tasks related to a maximally entangled pure state with parts x_axes, y_axes. x_axes, y_axes give a bi-partition of range( len(row_shape)).
See Ref.1 for an explicit definition of the maximally entangled states that we use. The basic requirement for a density matrix Dxy to be maximally entangled is for its partial trace Dx to be a diagonal matrix with all terms in the diagonal equal to the same constant. The sum of the diagonal elements must of course be one. For example, Dx=diag(0.25, 0.25,0.25,0.25) (If num_vals_x != num_vals_y, this assumes that num_vals_x is the smaller of the two.)
References
1. R.R. Tucci, “A New Algorithm for Calculating Squashed Entanglement and a Python Implementation Thereof”
Variables: - num_rows (int) – equals product(row_shape)
- num_vals_min (int) – equals min( num_vals_x, num_vals_y)
- num_vals_x (int) – equals product(row_shape_x)
- num_vals_y (int) – equals product(row_shape_y)
- row_shape (tuple[int]) –
- row_shape_x (tuple[int]) – subset of row_shape, only items indexed by x_axes
- row_shape_y (tuple[int]) – subset of row_shape, only items indexed by y_axes
- x_axes (list{int]) –
- y_axes (list{int]) –
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__init__
(num_rows, row_shape, x_axes, y_axes)[source]¶ Constructor
Parameters: - num_rows (int) –
- row_shape (tuple[int]) –
- x_axes (list{int]) –
- y_axes (list{int]) –