Math 2.0

Linear and multilinear algebra; matrix theory Definition

Tridiagonal matrix

Builds on RingSquare matrix

Definition

Let RR be a ring and let A=(aij)A = (a_{ij}) be an n×nn \times n square matrix over RR. The matrix AA is tridiagonal when aij=0a_{ij} = 0 for all i,ji, j with ∣i−j∣>1\abs{i - j} > 1.

Remarks

Example: (2−10−12−10−12)\begin{pmatrix} 2 & -1 & 0 \\ -1 & 2 & -1 \\ 0 & -1 & 2 \end{pmatrix} is tridiagonal, because the only entries with ∣i−j∣>1\abs{i - j} > 1 are a13a_{13} and a31a_{31}, and both are 00. Non-example: (101010001)\begin{pmatrix} 1 & 0 & 1 \\ 0 & 1 & 0 \\ 0 & 0 & 1 \end{pmatrix} is not tridiagonal, because a13=1a_{13} = 1 and ∣1−3∣=2\abs{1 - 3} = 2. A tridiagonal matrix is often written with diagonal a1,…,ana_1, \dots, a_n, superdiagonal b1,…,bn−1b_1, \dots, b_{n-1} and subdiagonal c1,…,cn−1c_1, \dots, c_{n-1}. Then the leading principal minors fkf_k satisfy fk=akfk−1−bk−1ck−1fk−2f_k = a_k f_{k-1} - b_{k-1} c_{k-1} f_{k-2}, with f0=1f_0 = 1 and f−1=0f_{-1} = 0. Equivalently, AA is tridiagonal when it is both upper and lower Hessenberg.

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Further reading

  1. Web https://en.wikipedia.org/wiki/Tridiagonal_matrix
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MSC15B99, 65F05
DefinesTridiagonal matrix
UsesRing, Square matrix
Changed2 November 2026

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