On the Kronecker Structure of linearization of Cubic Two-Parameter Eigenvalue Problems

Linearization is a classical approach to study matrix polynomial of the form P(lambda)=Sum lambdaj Aj, where A j Cnxn . It converts into a matrix pencil of the form L(lambda)=A+lambda B of high dimension, where A and B are matrices over C , and lambda is the spectral parameter. In this paper we consider Cubic two-parameter eigenvalue problems ( CTEP) and study three different linearization process of the problem. Usinglinearization techniques, CTEP is first converted into a linear two-parameter eigenvalue problem(L2EP) of coefficient matrices of different sizes. The main advantage of these linearizations lies in the fact that, after transforming them into suitable linearized forms, existing numerical techniques for linear multiparameter eigenvalue problems (LMEP) can be applied to CTEP without solving the original problem. While solving CTEP by formulating suitable linearizations, several transformations are generally used. In the current paper, it is also intended to report on these transformations, which have not been studied completely due to the complexity of their Kronecker structures.

Authors

Publication Details

Journal
Malaysian Journal of Science
Published
2025-03-28
DOI
https://doi.org/10.22452/mjs.vol44no1.9
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

On the Kronecker Structure of linearization of Cubic Two-Parameter Eigenvalue Problems

Niranjan Bora, Bharati Borgohain
Malaysian Journal of Science
Matrix Theory and Algorithms
article

On the Kronecker Structure of linearization of Cubic Two-Parameter Eigenvalue Problems

Niranjan Bora, Bharati Borgohain
article en

Abstract

Linearization is a classical approach to study matrix polynomial of the form P(lambda)=Sum lambdaj Aj, where A j Cnxn . It converts into a matrix pencil of the form L(lambda)=A+lambda B of high dimension, where A and B are matrices over C , and lambda is the spectral parameter. In this paper we consider Cubic two-parameter eigenvalue problems ( CTEP) and study three different linearization process of the problem. Usinglinearization techniques, CTEP is first converted into a linear two-parameter eigenvalue problem(L2EP) of coefficient matrices of different sizes. The main advantage of these linearizations lies in the fact that, after transforming them into suitable linearized forms, existing numerical techniques for linear multiparameter eigenvalue problems (LMEP) can be applied to CTEP without solving the original problem. While solving CTEP by formulating suitable linearizations, several transformations are generally used. In the current paper, it is also intended to report on these transformations, which have not been studied completely due to the complexity of their Kronecker structures.

Malaysian Journal of ScienceVol. 44(1)
Openalex Percentile: Top 91%
Matrix Theory and Algorithms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

On the Kronecker Structure of linearization of Cubic Two-Parameter Eigenvalue Problems — Niranjan Bora, Bharati Borgohain · Malaysian Journal of Science (2025) | TGRS Research Map | TGRS