Segmentation of quantum generated sequences by using the Jensen–Shannon divergence

Marcelo Losada, Víctor A. Penas, Federico Holik and Pedro W. Lamberti

Physica A: Statistical Mechanics and its Applications, 2023, vol. 628, issue C

Abstract: The Jensen–Shannon divergence has been successfully applied as a segmentation tool for symbolic sequences, that is to separate the sequence into subsequences with the same symbolic content. In this work, we propose a method, based on the Jensen–Shannon divergence, for segmentation of what we call quantum generated sequences, which consist in symbolic sequences generated from measuring a quantum system. For one-qubit and two-qubit systems, we show that the proposed method is adequate for segmentation.

Keywords: Quantum information; Jensen–Shannon divergence; Sequence segmentation; Quantum generated sequence; Quantum state discrimination; Quantum map discrimination (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437123007173
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:628:y:2023:i:c:s0378437123007173

DOI: 10.1016/j.physa.2023.129162

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().