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Research Article | Open Access

Riccati equation and metric geometric means of positive semidefinite matrices involving semi-tensor products

Pattrawut ChansangiamArnon Ploymukda( )
Department of Mathematics, School of Science, King Mongkut's Institute of Technology Ladkrabang, Bangkok 10520, Thailand
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Abstract

We investigate the Riccati matrix equation X A 1 X = B in which the conventional matrix products are generalized to the semi-tensor products . When A and B are positive definite matrices satisfying the factor-dimension condition, this equation has a unique positive definite solution, which is defined to be the metric geometric mean of A and B. We show that this geometric mean is the maximum solution of the Riccati inequality. We then extend the notion of the metric geometric mean to positive semidefinite matrices by a continuity argument and investigate its algebraic properties, order properties and analytic properties. Moreover, we establish some equations and inequalities of metric geometric means for matrices involving cancellability, positive linear map and concavity. Our results generalize the conventional metric geometric means of matrices.

CLC number: 15A24, 15B48, 47A64

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AIMS Mathematics
Pages 23519-23533

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Cite this article:
Chansangiam P, Ploymukda A. Riccati equation and metric geometric means of positive semidefinite matrices involving semi-tensor products. AIMS Mathematics, 2023, 8(10): 23519-23533. https://doi.org/10.3934/math.20231195

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Received: 15 May 2023
Revised: 09 July 2023
Accepted: 17 July 2023
Published: 15 October 2023
©2023 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)