Revision 587e0e5356a245645f37a6185306f8126fa0d222 authored by Jean Kossaifi on 08 November 2021, 11:54:34 UTC, committed by Jean Kossaifi on 08 November 2021, 11:54:34 UTC
1 parent 9aaaac1
entropy.py
import math
import tensorly as tl
from .. import backend as T
from ..cp_tensor import cp_normalize
from ..tt_tensor import tt_to_tensor
from ..utils import prod
# Authors: Taylor Lee Patti <taylorpatti@g.harvard.edu>
# Jean Kossaifi
def vonneumann_entropy(tensor):
"""Returns the von Neumann entropy of a density matrix (2-mode, square) tensor (matrix).
Parameters
----------
tensor : Non-decomposed tensor with indices whose shapes are all a factor of two (represent one or more qubits)
Returns
-------
von_neumann_entropy : order-0 tensor
Notes
-----
The von Neumann entropy is :math:`- \\sum_i p_i ln(p_i)`,
where p_i are the probabilities that each state is occupied
(the eigenvalues of the density matrix).
"""
square_dim = int(math.sqrt(prod(tensor.shape)))
tensor = tl.reshape(tensor, (square_dim, square_dim))
try:
eig_vals = T.eigh(tensor)[0]
except:
#All density matrices are Hermitian, here real. Hermitianize matrix if rounding/transformation
#errors have occured.
tensor = (tensor + tl.transpose(tensor))/2
eig_vals = T.eigh(tensor)[0]
eps = tl.eps(eig_vals.dtype)
eig_vals = eig_vals[eig_vals > eps]
return -T.sum(T.log2(eig_vals) * eig_vals)
def tt_vonneumann_entropy(tensor):
"""Returns the von Neumann entropy of a density matrix (square matrix) in TT tensor form.
Parameters
----------
tensor : (TT tensor)
Data structure
Returns
-------
tt_von_neumann_entropy : order-0 tensor
"""
return vonneumann_entropy(tt_to_tensor(tensor))
def cp_vonneumann_entropy(tensor):
"""Returns the von Neumann entropy of a density matrix (square matrix) in CP tensor.
Parameters
----------
tensor : (CP tensor)
Data structure
Returns
-------
cp_von_neumann_entropy : order-0 tensor
"""
eig_vals = cp_normalize(tensor).weights
eps = tl.eps(eig_vals.dtype)
eig_vals = eig_vals[eig_vals > eps]
return -T.sum(T.log2(eig_vals) * eig_vals)
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