Given Pivoted LU decomposition , the linear system is equivalent to . Introduce the intermediate vector : first use forward substitution to solve , then back substitution to solve . With unpivoted LU decomposition, is the identity matrix, so the first right-hand side is simply .[ref]
For the factors in Computed three-by-three LU decomposition and , forward substitution gives
Then back substitution gives
Direct matrix multiplication verifies . More generally, the back substitution recurrence is
The direction matters: the last row contains only , whereas the first row generally involves every unknown. No dense matrix inverse is needed for either triangular solve.
Let . Store the tridiagonal matrix by its diagonal , lower diagonal , and upper diagonal . The linear system is
with the nonexistent endpoint terms omitted. Initialize and . For , compute the elimination multiplier, modified pivot element, and modified right-hand side:
These recurrence relations apply the elementary row operation after the preceding row has already been reduced. The transformed linear system is an upper bidiagonal matrix:
Thus back substitution is especially short:
For , only remains. Check each pivot element before its first division, including before back substitution.
Figure 1.
Tridiagonal elimination preserves the narrow band: only one row and one diagonal coefficient change per step
. Details.
Equivalently, this constructs an LU decomposition with unit lower bidiagonal matrix , whose lower diagonal is , and upper bidiagonal matrix , whose diagonal is and upper diagonal is . The sweep is forward substitution in . There is no fill-in outside these bands when no rows are interchanged. LAPACK's DGTSV source uses these same coefficient and right-hand-side updates in its branch without row interchange.[ref]
Tridiagonal solve costs 2026-10-14
For the displayed unpivoted Thomas algorithm with one right-hand side, count each scalar addition, subtraction, multiplication or division as one arithmetic operation. Forming takes five arithmetic operations per forward step. The last unknown takes one division; each remaining back substitution step takes three arithmetic operations. Thus
This is an operation-count model, excluding assignments, indexing, pivot checks and any special simplifications of the coefficients. It is not a timing benchmark. The original tridiagonal matrix needs scalar entries, and its right-hand side another . Overwriting with and with , then with , keeps storage ; the arrays, rather than the few loop temporaries, determine the total space complexity.
For repeated right-hand sides, retain the LU decomposition: computing once costs arithmetic operations, and each subsequent pair of forward substitution and back substitution sweeps costs . Hence right-hand sides cost arithmetic operations. This is the banded counterpart of Reusing LU factors for multiple right-hand sides.