Computing Coherence Vectors and Correlation Matrices with Application to Quantum Discord Quantification

Author

Maziero, Jonas

Source

Advances in Mathematical Physics

Issue

Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-7, 7 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2016-06-29

Country of Publication

Egypt

No. of Pages

7

Main Subjects

Physics

Abstract EN

Coherence vectors and correlation matrices are important functions frequently used in physics.

The numerical calculation of these functions directly from their definitions, which involves Kronecker products and matrix multiplications, may seem to be a reasonable option.

Notwithstanding, as we demonstrate in this paper, some algebraic manipulations before programming can reduce considerably their computational complexity.

Besides, we provide Fortran code to generate generalized Gell-Mann matrices and to compute the optimized and unoptimized versions of associated Bloch’s vectors and correlation matrix in the case of bipartite quantum systems.

As a code test and application example, we consider the calculation of Hilbert-Schmidt quantum discords.

American Psychological Association (APA)

Maziero, Jonas. 2016. Computing Coherence Vectors and Correlation Matrices with Application to Quantum Discord Quantification. Advances in Mathematical Physics،Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1095878

Modern Language Association (MLA)

Maziero, Jonas. Computing Coherence Vectors and Correlation Matrices with Application to Quantum Discord Quantification. Advances in Mathematical Physics No. 2016 (2016), pp.1-7.
https://search.emarefa.net/detail/BIM-1095878

American Medical Association (AMA)

Maziero, Jonas. Computing Coherence Vectors and Correlation Matrices with Application to Quantum Discord Quantification. Advances in Mathematical Physics. 2016. Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1095878

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1095878