Lehmer matrix
In mathematics, particularly matrix theory, the n×ばつn Lehmer matrix (named after Derrick Henry Lehmer) is the constant symmetric matrix defined by
- {\displaystyle A_{ij}={\begin{cases}i/j,&j\geq i\\j/i,&j<i.\end{cases}}}
Alternatively, this may be written as
- {\displaystyle A_{ij}={\frac {{\mbox{min}}(i,j)}{{\mbox{max}}(i,j)}}.}
Properties
[edit ]As can be seen in the examples section, if A is an n×ばつn Lehmer matrix and B is an ×ばつm Lehmer matrix, then A is a submatrix of B whenever m>n. The values of elements diminish toward zero away from the diagonal, where all elements have value 1.
The inverse of a Lehmer matrix is a tridiagonal matrix, where the superdiagonal and subdiagonal have strictly negative entries. Consider again the n×ばつn A and ×ばつm B Lehmer matrices, where m>n. A rather peculiar property of their inverses is that A−1 is nearly a submatrix of B−1, except for the A−1n,n element, which is not equal to B−1n,n.
A Lehmer matrix of order n has trace n.
Examples
[edit ]The ×ばつ2, ×ばつ3 and ×ばつ4 Lehmer matrices and their inverses are shown below.
- {\displaystyle {\begin{array}{lllll}A_{2}={\begin{pmatrix}1&1/2\1円/2&1\end{pmatrix}};&A_{2}^{-1}={\begin{pmatrix}4/3&-2/3\\-2/3&{\color {Brown}{\mathbf {4/3} }}\end{pmatrix}};\\\\A_{3}={\begin{pmatrix}1&1/2&1/3\1円/2&1&2/3\1円/3&2/3&1\end{pmatrix}};&A_{3}^{-1}={\begin{pmatrix}4/3&-2/3&\\-2/3&32/15&-6/5\\&-6/5&{\color {Brown}{\mathbf {9/5} }}\end{pmatrix}};\\\\A_{4}={\begin{pmatrix}1&1/2&1/3&1/4\1円/2&1&2/3&1/2\1円/3&2/3&1&3/4\1円/4&1/2&3/4&1\end{pmatrix}};&A_{4}^{-1}={\begin{pmatrix}4/3&-2/3&&\\-2/3&32/15&-6/5&\\&-6/5&108/35&-12/7\\&&-12/7&{\color {Brown}{\mathbf {16/7} }}\end{pmatrix}}.\\\end{array}}}
See also
[edit ]References
[edit ]- Newman, M.; Todd, J. (1958). "The evaluation of matrix inversion programs". Journal of the Society for Industrial and Applied Mathematics. 6 (4): 466–476. doi:10.1137/0106030. JSTOR 2098717.