torch.Tensor.Tensor.matrix_power
Tensor.matrix_power(n: number): Tensor<DynamicShape, D, Dev>Computes the matrix raised to an integer power using repeated squaring.
Efficiently computes A^n for integer n (positive, negative, or zero). For positive n, uses repeated squaring O(log n) multiplications. For negative n, computes A^(-|n|) = (A^(-1))^|n|.
Use Cases:
- Computing powers of transition matrices
- Iterative methods and convergence analysis
- Recurrence relation solving
Parameters
nnumber- Integer exponent (can be negative)
Returns
Tensor<DynamicShape, D, Dev>– Matrix power A^nExamples
// Compute A^10 efficiently
const A = torch.tensor([[1, 1], [0, 1]]);
const A10 = A.matrix_power(10); // Uses log(10) multiplications
// Compute inverse
const A_inv = A.matrix_power(-1);See Also
- PyTorch torch.matrix_power() (or tensor.matrix_power())
- matrix_exp - Matrix exponential
- lu - LU decomposition for computing inverse