Research article

On accurate asymptotic approximations of roots for polynomial equations containing a small, but fixed parameter

  • Received: 24 June 2024 Revised: 05 September 2024 Accepted: 18 September 2024 Published: 09 October 2024
  • MSC : 34E99, 34L15, 34L20, 65H04

  • In this paper, polynomial equations with real coefficients and in one variable were considered which contained a small, positive but specified and fixed parameter $ \varepsilon_0 \neq 0 $. By using the classical asymptotic method, roots of the polynomial equations have been constructed in the literature, which were proved to be valid for sufficiently small $ \varepsilon $-values (or equivalently for $ \varepsilon \to 0 $). In this paper, it was assumed that for some or all roots of a polynomial equation, the first few terms in a Taylor or Laurent series in a small parameter depending on $ \varepsilon $ exist and can be constructed. We also assumed that at least two approximations $ x_1(\varepsilon) $ and $ x_2(\varepsilon) $ for the real roots exist and can be constructed. For a complex root, we assumed that at least two real approximations $ a_1(\varepsilon) $ and $ a_2(\varepsilon) $ for the real part of this root, and that at least two real approximations $ b_1(\varepsilon) $ and $ b_2(\varepsilon) $ for the imaginary part of this root, exist and can be constructed. Usually it was not clear whether for $ \varepsilon = \varepsilon_0 $ the approximations were valid or not. It was shown in this paper how the classical asymptotic method in combination with the bisection method could be used to prove how accurate the constructed approximations of the roots were for a given interval in $ \varepsilon $ (usually including the specified and fixed value $ \varepsilon_0 \neq 0 $). The method was illustrated by studying a polynomial equation of degree five with a small but fixed parameter $ \varepsilon_0 = 0.1 $. It was shown how (absolute and relative) error estimates for the real and imaginary parts of the roots could be obtained for all values of the small parameter in the interval $ (0, \varepsilon_0] $.

    Citation: Fitriana Yuli Saptaningtyas, Wim T Van Horssen, Fajar Adi-Kusumo, Lina Aryati. On accurate asymptotic approximations of roots for polynomial equations containing a small, but fixed parameter[J]. AIMS Mathematics, 2024, 9(10): 28542-28559. doi: 10.3934/math.20241385

    Related Papers:

  • In this paper, polynomial equations with real coefficients and in one variable were considered which contained a small, positive but specified and fixed parameter $ \varepsilon_0 \neq 0 $. By using the classical asymptotic method, roots of the polynomial equations have been constructed in the literature, which were proved to be valid for sufficiently small $ \varepsilon $-values (or equivalently for $ \varepsilon \to 0 $). In this paper, it was assumed that for some or all roots of a polynomial equation, the first few terms in a Taylor or Laurent series in a small parameter depending on $ \varepsilon $ exist and can be constructed. We also assumed that at least two approximations $ x_1(\varepsilon) $ and $ x_2(\varepsilon) $ for the real roots exist and can be constructed. For a complex root, we assumed that at least two real approximations $ a_1(\varepsilon) $ and $ a_2(\varepsilon) $ for the real part of this root, and that at least two real approximations $ b_1(\varepsilon) $ and $ b_2(\varepsilon) $ for the imaginary part of this root, exist and can be constructed. Usually it was not clear whether for $ \varepsilon = \varepsilon_0 $ the approximations were valid or not. It was shown in this paper how the classical asymptotic method in combination with the bisection method could be used to prove how accurate the constructed approximations of the roots were for a given interval in $ \varepsilon $ (usually including the specified and fixed value $ \varepsilon_0 \neq 0 $). The method was illustrated by studying a polynomial equation of degree five with a small but fixed parameter $ \varepsilon_0 = 0.1 $. It was shown how (absolute and relative) error estimates for the real and imaginary parts of the roots could be obtained for all values of the small parameter in the interval $ (0, \varepsilon_0] $.



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    [1] J. H. Wilkinson, The Algebraic Eigenvalue Problem, Oxford:Clarendon Press, (1965).
    [2] A. Dickenstein, I. Z. Emiris, Solving Polynomial Equations: Foundations, Algorithms, and Applications: Algorithms and Computation in Mathematics, Berlin, New York: Springer, (2005).
    [3] D. A. Bini, G. Fiorentino, Design, analysis, and implementation of a multiprecision polynomial rootfinder, Numer. Algorithms, 23 (2000), 127–173. http://dx.doi.org/10.1023/A:1019199917103 doi: 10.1023/A:1019199917103
    [4] D. A. Bini, L. Robol, Solving secular and polynomial equations: A multiprecision algorithm, J. Comput. Appl. Math., 272 (2014), 276–292. https://doi.org/10.1016/j.cam.2013.04.037 doi: 10.1016/j.cam.2013.04.037
    [5] V. Y. Pan, Acceleration of subdivision root-finding for sparse polynomials, In: F. Boulier, M. England, T. M. Sadikov, E. V. Vorozhtsov, (eds.) CASC 2020, Switzerland: Springer Nature, (2020), 461–477.
    [6] V. Y. Pan, Structured Matrices and Polynomials: Unified Superfast Algorithms., Boston/New York: Birkhäuser/Springer, (2001).
    [7] M. Shams, N. Kausar, S. Araci, L. Kong, B. Carpentieri, Highly efficient family of two-step simultaneous method for all polynomial roots, AIMS Math., 9 (2024), 1755–1771. https://doi.org/10.3934/math.2024085 doi: 10.3934/math.2024085
    [8] S. Qureshi, I. K. Argyros, A. Soomro, K. Gdawiec, A. A. Shaikh, E. Hincal, new optimal root-finding iterative algorithm: local and semilocal analysis with polynomiography, Numer. Algorithms, 95 (2024), 1715–1745. https://doi.org/10.1007/s11075-023-01625-7 doi: 10.1007/s11075-023-01625-7
    [9] R. Sihwail, O. Solaiman, K. Ariffin, New robust hybrid Jarratt–Butterfly optimization algorithm for nonlinear models, J. King Saud University Comput. Inf. Sci., 34 (2022), 8207–8220. https://doi.org/10.1016/j.jksuci.2022.08.004 doi: 10.1016/j.jksuci.2022.08.004
    [10] R. Sihwail, O. Solaiman, K. Ariffin, M. Alswaitti, I. Hashim, A hybrid approach for solving systems of nonlinear equations using Harris hawks optimization and Newton's method, IEEE Access, 9 (2021), 95791–95807. https://doi.org/10.1109/ACCESS.2021.3094471 doi: 10.1109/ACCESS.2021.3094471
    [11] O. Solaiman, R. Sihwail, H. Shehadeh, I. Hashim, K. Alieyan, Hybrid Newton-Sperm swarm optimization algorithm for nonlinear systems, Mathematics, 11 (2023), 1473. https://doi.org/10.3390/math11061473 doi: 10.3390/math11061473
    [12] J. A. Murdock, Perturbations Theory and Methods: Classics in Applied Mathematics, Series Number 27, Philadelphia: SIAM, (1999).
    [13] M. H. Holmes, Introduction to Perturbation Methods, New York: Springer, (2010).
    [14] M. Pakdemirli, G. Sari, A comprehensive perturbation theorem for estimating magnitudes of roots of polynomials, LMS J. Comput. Math., 16 (2013), 1–8. https://doi.org/10.1112/S1461157012001192 doi: 10.1112/S1461157012001192
    [15] A. Luongo, M. Ferreti, Can a semi-simple eigenvalue admit fractional sensitivities?. Appl. Math. Comput., 225 (2015), 165–178. https://doi.org/10.1016/j.amc.2014.01.178 doi: 10.1016/j.amc.2014.01.178
    [16] J. Kevorkian, J. D. Cole, Multiple Scale and Singular Perturbation Methods, Applied Mathematical Sciences 114, New York: Springer, (1996).
    [17] F. Verhulst, Methods and Applications of Singular Perturbations, Texts in Applied Mathematics, New York: Springer, (2005).
    [18] R. S. Johnson, Singular Perturbation Theory, New York: Springer, (2005).
    [19] J. C. Neu, Singular Perturbation in the Physical Sciences, Graduate Studies in Mathematics Vol 167, Providence: AMS, (2015).
    [20] C. M. Bender, S. A. Orszag, Advanced Mathematical Methods for Scientists and Engineers, Asymptotic Methods and Perturbation Theory, New York Berlin: Springer, (1999).
    [21] P. D. Miller, Applied Asymptotic Analysis. Graduate Studies in Mathematics, 75, Providence: AMS, (2006).
    [22] I. V. Andrianov, L. I. Manevitch, Asymptotology, Mathematics and Its Applications, 2 Eds., New York Berlin: Springer, (2002).
    [23] R. B. White, Asymptotic Analysis of Differential Equations, London:Imperial College Press, (2005).
    [24] P. Aubry, M. M. Maza, Triangular sets for solving polynomial systems: A comparative implementation of four methods, J. Symb. Comput., 28 (1999), 125–154. https://doi.org/10.1006/jsco.1999.0270 doi: 10.1006/jsco.1999.0270
    [25] F. Y. Saptaningtyas, Spatial-Temporal Model of Interaction between the Immune System and Cancer Cells with Immunotherapy in Cervical Cancer, PhD.-Thesis (Draft), Universitas Gadjah Mada, Yogyakarta, Indonesia, (2024).
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