SymmetricProjection

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SymmetricProjection
Produces the projection onto the symmetric subspace

Other toolboxes required opt_args
PermutationOperator
PermuteSystems
sporth

SymmetricProjection is a function that computes the orthogonal projection onto the symmetric subspace of two or more subsystems. The output of this function is always a sparse matrix.

Syntax

  • PS = SymmetricProjection(DIM)
  • PS = SymmetricProjection(DIM,P)
  • PS = SymmetricProjection(DIM,P,PARTIAL)
  • PS = SymmetricProjection(DIM,P,PARTIAL,MODE)

Argument descriptions

  • DIM: The dimension of each of the subsystems.
  • P (optional, default 2): The number of subsystems.
  • PARTIAL (optional, default 0): If PARTIAL = 1 then PS isn't the orthogonal projection itself, but rather a matrix whose columns form an orthonormal basis for the symmetric subspace (and hence PS*PS' is the orthogonal projection onto the symmetric subspace).
  • MODE (optional, default -1): A flag that determines which of two algorithms is used to compute the symmetric projection. If MODE = -1 then this script chooses which algorithm it thinks will be faster based on the values of DIM and P. If you wish to force the script to use a specific one of the algorithms (not recommended!), they are as follows:
    • MODE = 0: Computes the symmetric projection by explicitly constructing an orthonormal basis of the symmetric subspace. The details of how to construct such a basis can be found in [1]. This method is typically fast when DIM is small compared to P.
    • MODE = 1: Computes the symmetric projection by averaging all P! permutation operators (in the sense of the PermutationOperator function). Because P! grows very quickly, this method is only practical when P is small.

Examples

Two subsystems

To compute the symmetric projection on two-qubit space, the following code suffices:

>> SymmetricProjection(2)

ans =

   (1,1)       1.0000
   (2,2)       0.5000
   (3,2)       0.5000
   (2,3)       0.5000
   (3,3)       0.5000
   (4,4)       1.0000

Note that the output of this function is always sparse. If you want a full matrix (not recommended for even moderately large DIM or P), you must explicitly convert it, as in the following example).

Two subsystems

To compute a matrix whose columns form an orthonormal basis for the symmetric subspace of three-qubit space, set PARTIAL = 1:

>> PS = full(SymmetricProjection(2,3,1))

PS =

    1.0000         0         0         0
         0         0   -0.5774         0
         0         0   -0.5774         0
         0         0         0   -0.5774
         0         0   -0.5774         0
         0         0         0   -0.5774
         0         0         0   -0.5774
         0    1.0000         0         0

Note that PS is an isometry from the symmetric subspace to the full three-qubit space. In other words, PS'*PS is the identity matrix and PS*PS' is the orthogonal projection onto the symmetric subspace, which we can verify as follows:

>> PS'*PS

ans =

     1     0     0     0
     0     1     0     0
     0     0     1     0
     0     0     0     1

>> PS*PS'

ans =

    1.0000         0         0         0         0         0         0         0
         0    0.3333    0.3333         0    0.3333         0         0         0
         0    0.3333    0.3333         0    0.3333         0         0         0
         0         0         0    0.3333         0    0.3333    0.3333         0
         0    0.3333    0.3333         0    0.3333         0         0         0
         0         0         0    0.3333         0    0.3333    0.3333         0
         0         0         0    0.3333         0    0.3333    0.3333         0
         0         0         0         0         0         0         0    1.0000

References

  1. John Watrous. Lecture 21: The quantum de Finetti theorem, Theory of Quantum Information Lecture Notes, 2008.