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Adomian's decomposition method for eigenvalue problems.

Yee-Mou Kao1, T F Jiang

  • 1Institute of Applied Mathematics, National Chiao-Tung University, Hsinchu, Taiwan.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|May 21, 2005
PubMed
Summary
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This study extends Adomian's decomposition method for eigenvalue problems, introducing a Hamiltonian inverse iteration method for efficient ground state and excited state solutions. A space partition method enhances convergence for complex series expansions.

Area of Science:

  • Numerical Analysis
  • Computational Physics
  • Applied Mathematics

Background:

  • Adomian's decomposition method is effective for nonlinear boundary and initial value problems.
  • General eigenvalue problems require robust numerical techniques for accurate solutions.
  • Convergence issues can arise with standard series expansion methods.

Purpose of the Study:

  • To adapt Adomian's decomposition method for general eigenvalue problems.
  • To develop an efficient numerical method for finding eigenvalues and eigenfunctions.
  • To address convergence challenges in series expansion methods.

Main Methods:

  • Extension of Adomian's decomposition method.
  • Development of the Hamiltonian inverse iteration method.

Related Experiment Videos

  • Implementation of a space partition technique.
  • Main Results:

    • The Hamiltonian inverse iteration method rapidly provides ground state eigenvalues and eigenfunctions.
    • A method for determining excited states is successfully proposed.
    • The space partition method overcomes convergence failures in series expansions.

    Conclusions:

    • The extended Adomian's decomposition method offers a powerful approach for general eigenvalue problems.
    • The Hamiltonian inverse iteration method is efficient for both ground and excited states.
    • The space partition method significantly improves the applicability of series expansion techniques.