IsProductOperator
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| IsProductOperator | |
| Determines if an operator is an elementary tensor | |
| Other toolboxes required | none |
|---|---|
| Related functions | IsProductVector OperatorSchmidtDecomposition OperatorSchmidtRank |
| Function category | Entanglement and separability |
IsProductOperator is a function that determines if a bipartite or multipartite operator is an elementary tensor or not. If it is an elementary tensor, its tensor decomposition can be provided.
Syntax
- IPO = IsProductOperator(X)
- IPO = IsProductOperator(X,DIM)
- [IPO,DEC] = IsProductOperator(X,DIM)
Argument descriptions
Input arguments
- X: An operator that acts on a bipartite or multipartite Hilbert space.
- DIM (optional, by default has all subsystems of equal dimension): A specification of the dimensions of the subsystems that X lives on. DIM can be provided in one of three ways:
- If DIM is a scalar, it is assumed that X lives on the tensor product of two spaces, the first of which has dimension DIM and the second of which has dimension length(X)/DIM.
- If $X \in M_{n_1} \otimes \cdots \otimes M_{n_p}$ then DIM should be a row vector containing the dimensions (i.e., DIM = [n_1, ..., n_p]).
- If the subsystems aren't square (i.e., $X \in M_{m_1, n_1} \otimes \cdots \otimes M_{m_p, n_p}$) then DIM should be a matrix with two rows. The first row of DIM should contain the row dimensions of the subsystems (i.e., the mi's) and its second row should contain the column dimensions (i.e., the ni's). In other words, you should set DIM = [m_1, ..., m_p; n_1, ..., n_p].
Output arguments
- IPO: Either 1 or 0, indicating that X is or is not an elementary tensor.
- DEC (optional): If IPO = 1 (i.e., X is an elementary tensor), then DEC is a cell containing two or more operators, the tensor product of which is X. If IPO = 0 then DEC is meaningless.
Examples
The following code verifies that the 8-by-8 identity operator (interpreted as living in 3-qubit space) is indeed a product operator:
>> [ipo,dec] = IsProductOperator(eye(8),[2,2,2])
ipo =
1
dec =
[2x2 double] [2x2 double] [2x2 double]
>> celldisp(dec)
dec{1} =
0.9170 0
0 0.9170
dec{2} =
-0.9170 0
0 -0.9170
dec{3} =
-1.1892 0
0 -1.1892As we can see, the tensor decomposition that is returned is not always the "cleanest" one that exists. However, we can verify that it is indeed a valid tensor decomposition of the identity operator:
>> Tensor(dec)
ans =
1.0000 0 0 0 0 0 0 0
0 1.0000 0 0 0 0 0 0
0 0 1.0000 0 0 0 0 0
0 0 0 1.0000 0 0 0 0
0 0 0 0 1.0000 0 0 0
0 0 0 0 0 1.0000 0 0
0 0 0 0 0 0 1.0000 0
0 0 0 0 0 0 0 1.0000Source code
Click here to view this function's source code on github.