Work

Quantum hidden Markov models based on transition operation matrices

Year: 2017

Type: article

Abstract: In this work, we extend the idea of quantum Markov chains (Gudder in J Math Phys 49(7):072105 [ 3 ]) in order to propose quantum hidden Markov models (QHMMs). For that, we use the notions of transition operation matrices and vector states, which are an extension of classical stochastic matrices and probability distributions. Our main result is the Mealy QHMM formulation and proofs of algorithms needed for application of this model: Forward for general case and Vitterbi for a restricted class of QHMMs. We show the relations of the proposed model to other quantum HMM propositions and present an example of application.

Source: Quantum Information Processing

DOI: 10.1007/s11128-017-1544-8

Authors: Michał Cholewa, Piotr Gawron, Przemysław Głomb, Dariusz Kurzyk

Institutions: Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Silesian University of Technology

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,990

Funder: Narodowe Centrum Nauki