2012
DOI: 10.1119/1.4748813
|View full text |Cite
|
Sign up to set email alerts
|

Matrix Numerov method for solving Schrödinger’s equation

Abstract: We recast the well-known Numerov method for solving Schrödinger's equation into a representation of the kinetic energy operator on a discrete lattice. With just a few lines of Mathematica code, it is simple to calculate and plot accurate eigenvalues and eigenvectors for a variety of potential problems. We illustrate the method by calculating high accuracy solutions for the |x| potential.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

1
57
0

Year Published

2014
2014
2024
2024

Publication Types

Select...
7
3

Relationship

1
9

Authors

Journals

citations
Cited by 89 publications
(58 citation statements)
references
References 8 publications
1
57
0
Order By: Relevance
“…These techniques are well established e.g., [29,30] and could be improved upon by using higher-order finite-difference elements, or using the Numerov method in matrix form.…”
Section: Finite Difference Matrix To Solve the Schrödinger Equation Fmentioning
confidence: 99%
“…These techniques are well established e.g., [29,30] and could be improved upon by using higher-order finite-difference elements, or using the Numerov method in matrix form.…”
Section: Finite Difference Matrix To Solve the Schrödinger Equation Fmentioning
confidence: 99%
“…Numerical simulations were carried out on a personal computer using Python and the scientific libraries Numpy and Scipy for matrix diagonalizations and optimization operations [24,25]. When necessary, the exact solution results in 1D were obtained by building an Hamiltonian based on a matrix Numerov method [26]. This approach was then expanded to higher dimensionality; the details are explained in Appendix C. Since this method uses a direct space basis set, all potentials are treated effectively as if they were enclosed in an infinite well.…”
Section: Simulation Detailsmentioning
confidence: 99%
“…Extending ideas of Ref. 68, we can convert this system of equations into a generalized eigenvalue problem. We introduce a matrix A having c j /a 2 on the j-th diagonal, where j > 0 refers to the upper diagonals and j < 0 refers to the lower diagonals, a diagonal matrix V = diag(V j ) representing the potential, and a matrix B having −(r!)…”
Section: (B1)mentioning
confidence: 99%