# Difference between revisions of "IsPPT"

 Other toolboxes required IsPPT Determines whether or not a matrix has positive partial transpose none IsPSDPartialTranspose Entanglement and separability

IsPPT is a function that determines whether or not a given matrix has positive partial transpose (PPT), which is a quick and easy separability criterion. This function works on both full and sparse matrices, and if desired a witness can be provided that verifies that the input matrix is not PPT.

## Syntax

• PPT = IsPPT(X)
• PPT = IsPPT(X,SYS)
• PPT = IsPPT(X,SYS,DIM)
• PPT = IsPPT(X,SYS,DIM,TOL)
• [PPT,WIT] = IsPPT(X,SYS,DIM,TOL)

## Argument descriptions

### Input arguments

• X: A square matrix.
• SYS (optional, default 2): A scalar or vector indicating which subsystem(s) the transpose should be applied on.
• DIM (optional, default has X living on two subsystems of equal size): A vector containing the dimensions of the (possibly more than 2) subsystems on which X lives.
• TOL (optional, default sqrt(eps)): The numerical tolerance used when determining positive semidefiniteness. The matrix will be determined to have positive partial transpose if its partial transpose's minimal eigenvalue is computed to be at least -TOL.

### Output arguments

• PPT: A flag (either 1 or 0) indicating that X does or does not have positive partial transpose.
• WIT (optional): An eigenvector corresponding to the minimal eigenvalue of PartialTranspose(X). When PPT = 0, this serves as a witness that verifies that X does not have positive partial transpose, since WIT'*PartialTranspose(X)*WIT < 0.

## Examples

The following code verifies that the 9-by-9 identity operator (thought of as an operator in $M_3 \otimes M_3$) has positive partial transpose:

>> IsPPT(eye(9))

ans =

1

## Notes

Do not request the WIT output argument unless you need it. If WIT is not requested, positive semidefiniteness is determined by attempting a Cholesky decomposition of X, which is both faster and more accurate than computing its minimum eigenvalue/eigenvector pair.

## Source code

Click on "expand" to the right to view the MATLAB source code for this function.

1. %%  ISPPT    Determines whether or not a matrix has positive partial transpose
2. %   This function has one required argument:
3. %     X: a square matrix
4. %
5. %   PPT = IsPPT(X) is either 1 or 0, indicating that X does or does not
6. %   have positive partial transpose (within numerical error). X is assumed
7. %   to act on bipartite space.
8. %
9. %   This function has three optional input arguments:
10. %     SYS (default 2)
11. %     DIM (default sqrt(length(X)))
12. %     TOL (default sqrt(eps))
13. %
14. %   [PPT,WIT] = IsPPT(X,SYS,DIM,TOL) determines whether or not X has
15. %   positive partial transpose within the tolerance specified by TOL. DIM
16. %   DIM is a vector containing the dimensions of the subsystems on which X
17. %   acts, and SYS is a scalar or vector indicating which subsystems the
18. %   transpose should be applied on. WIT is the eigenvector corresponding to
19. %   the minimal eigenvalue of the partial transpose of X, and thus can
20. %   act as a witness that proves X does not have positive partial transpose
21. %   (i.e., WIT'*PartialTranspose(X,SYS,DIM)*WIT < 0).
22. %
23. %   URL: http://www.qetlab.com/IsPPT
24. 
25. %   requires: IsPSD.m, opt_args.m, PartialTranspose.m
26. %   author: Nathaniel Johnston (nathaniel@njohnston.ca)
27. %   package: QETLAB
28. %   last updated: December 12, 2014
29. 
30. function [ppt,wit] = IsPPT(X,varargin)
31. 
32. % set optional argument defaults: sys=2, dim=sqrt(length(X)), tol=sqrt(eps)
33. [sys,dim,tol] = opt_args({ 2, round(sqrt(length(X))), sqrt(eps) },varargin{:});
34. 
35. % Allow this function to be called within CVX optimization problems.
36. if(isa(X,'cvx'))
37.     cvx_begin sdp quiet
38.     subject to
39.     	PartialTranspose(X,sys,dim) >= 0;
40.     cvx_end
41.     ppt = 1-min(cvx_optval,1); % CVX-safe way to map (0,Inf) to (1,0)
42. 
43. % If the function is just being called on a non-CVX variable, just check
44. % the PPT condition normally (which is much faster).
45. else
46.     if(nargout > 1)
47.         [ppt,wit] = IsPSD(PartialTranspose(X,sys,dim),tol);
48.     else
49.         ppt = IsPSD(PartialTranspose(X,sys,dim),tol);
50.     end
51. end