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June 20, 2026Mathematical Methods in the Applied Sciences0 citations

A Robust Analytical Framework for Solving Nonlinear Differential Equations Arising in Physical Sciences

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STSaurabh Tomar

Key Points

  • This research aims to develop a robust analytical framework for solving nonlinear differential equations using the quasi-linearized Picard iteration method.
  • Introduced the quasi-linearized Picard iteration method (QPIM) combining Newton's quasilinearization and Picard iteration.
  • Conducted a convergence analysis demonstrating quadratic convergence under specific conditions.
  • Provided numerical examples to showcase the applicability and accuracy of the QPIM.
  • QPIM demonstrated higher accuracy with fewer iterations compared to traditional methods.
  • Monotonic sequences of approximations were achieved, offering pointwise upper and lower bounds for solutions.
  • The quadratic rate of convergence was confirmed under suitable conditions.

Abstract

ABSTRACT In this study, we propose an effective analytical framework for solving nonlinear differential equations, termed the quasi‐linearized Picard iteration method (QPIM). This method combines Newton's quasilinearization technique, which is known for its quadratic convergence, with the Picard iteration method, which offers a straightforward iterative framework. The proposed approach converts nonlinear differential equations into a sequence of linear problems via quasilinearization, which are then solved analytically using Picard iterations. A detailed convergence analysis confirms the quadratic rate of convergence under suitable conditions. Several examples are provided to illustrate the applicability and accuracy of the QPIM. Numerical comparisons revealed that QPIM achieved higher accuracy with fewer iterations. Furthermore, the QPIM provides monotonic sequences of approximations, enabling pointwise upper and lower bounds for solutions, which is especially useful for problems with unique solutions. These advantages establish the QPIM as a reliable tool for solving a broad class of nonlinear differential equations.

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Cite This Study

Saurabh Tomar (2026) studied this question.

synapsesocial.com/papers/6a363224db0793dc1a538de8https://doi.org/10.1002/mma.70844
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