Difference between revisions of "SkVectorNorm"
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− | <tt>'''SkVectorNorm'''</tt> is a [[List of functions|function]] that computes the [[s(k)-vector norm|s(k)-norm of a vector]] (i.e., the Euclidean norm of the vector of its k largest [[Schmidt coefficients]]<ref>N. Johnston and D. W. Kribs. A Family of Norms With Applications in Quantum Information Theory. ''J. Math. Phys.'', 51:082202, 2010.</ref>). | + | <tt>'''SkVectorNorm'''</tt> is a [[List of functions|function]] that computes the [[s(k)-vector norm|s(k)-norm of a vector]] (i.e., the Euclidean norm of the vector of its k largest [[Schmidt coefficients]]<ref>N. Johnston and D. W. Kribs. A Family of Norms With Applications in Quantum Information Theory. ''J. Math. Phys.'', 51:082202, 2010. E-print: [http://arxiv.org/abs/0909.3907 arXiv:0909.3907] [quant-ph]</ref>). |
==Syntax== | ==Syntax== |
Revision as of 15:34, 2 December 2012
SkVectorNorm | |
Computes the s(k)-norm of a vector | |
Other toolboxes required | opt_args SchmidtDecomposition |
---|---|
Related functions | KyFanNorm SkOperatorNorm |
SkVectorNorm is a function that computes the s(k)-norm of a vector (i.e., the Euclidean norm of the vector of its k largest Schmidt coefficients[1]).
Syntax
- SkVectorNorm(VEC)
- SkVectorNorm(VEC,K)
- SkVectorNorm(VEC,K,DIM)
Argument descriptions
- VEC: A vector living in bipartite space.
- K (optional, default 1): A positive integer.
- DIM (optional, by default has both subsystems of equal dimension): A 1-by-2 vector containing the dimensions of the subsystems that VEC lives on.
Examples
Sum of squares of eigenvalues of reduced density matrix
The square of the s(k)-vector norm is equal to the Ky Fan k-norm of the vector's reduced density matrix:
>> v = RandomStateVector(9); >> [SkVectorNorm(v,1)^2, KyFanNorm(PartialTrace(v*v'),1)] ans = 0.7754 0.7754 >> [SkVectorNorm(v,2)^2, KyFanNorm(PartialTrace(v*v'),2)] ans = 0.9333 0.9333 >> [SkVectorNorm(v,3)^2, KyFanNorm(PartialTrace(v*v'),3)] ans = 1.0000 1.0000
References
- ↑ N. Johnston and D. W. Kribs. A Family of Norms With Applications in Quantum Information Theory. J. Math. Phys., 51:082202, 2010. E-print: arXiv:0909.3907 [quant-ph]