Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Entanglement Monotones and Measures: An Overview

Version 1 : Received: 14 April 2017 / Approved: 17 April 2017 / Online: 17 April 2017 (11:01:38 CEST)
Version 3 : Received: 21 April 2017 / Approved: 21 April 2017 / Online: 21 April 2017 (08:47:32 CEST)

How to cite: Erol, V. Entanglement Monotones and Measures: An Overview. Preprints 2017, 2017040098. Erol, V. Entanglement Monotones and Measures: An Overview. Preprints 2017, 2017040098.


Quantum information theory and quantum computing are theoritical basis of quantum computers. Thanks to entanglement, quantum mechanical systems are provisioned to realize many information processing problems faster than classical counterparts. For example, Shor’s factorization algorithm, Grover’s search algorithm, quantum Fourrier transformation, etc. [1]. Entanglement, is the theoretical basis providing the expected speedups. It can be view in bipartite or multipartite forms. In order to quantify entanglement, some measures are defined. On the other hand, a general and accepted criterion, which can measure the amount of entanglement of multilateral systems, has not yet been found. However, since it must be used in many information processing tasks, the production and processing of multilateral quantum entangled systems is at the top of the hot topics of recent years [5-11]. Much of the work in the basic quantum technologies, such as quantum cryptography, communications, and computers, requires multi-partite entangled systems such as GHZ, W [22,30]. It can be suggested that the quantum entanglement criteria reflects the different properties of the systems. Many recent research has been done in entanglement and its related disciplines like entanglement measures and majorization, etc. [62-71]. In this work, we make an overview of recent research on the topic entanglement monotones/measures with an analitical approach.


quantum information; entanglement; entaglement measures; entanglement monotones


Computer Science and Mathematics, Computer Science

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