TheAlgorithms/Java · error · IllegalArgumentException

Matrix A and vector x0 dimensions do not match.

Error message

Matrix A and vector x0 dimensions do not match.

What it means

Thrown by ChebyshevIteration.validateInputs when the initial guess vector x0 does not match the dimension n of matrix A (a.length). The solver clones x0 as the starting solution and updates it via x = x + alpha * p; if x0 has the wrong length, the vector add and the matrix-vector multiply would produce arrays of incompatible sizes.

Source

Thrown at src/main/java/com/thealgorithms/maths/ChebyshevIteration.java:102

        return x; // Return best guess after maxIterations
    }

    /**
     * Validates the inputs for the Chebyshev solver.
     */
    private static void validateInputs(double[][] a, double[] b, double[] x0, double minEigenvalue, double maxEigenvalue, int maxIterations, double tolerance) {
        int n = a.length;
        if (n == 0) {
            throw new IllegalArgumentException("Matrix A cannot be empty.");
        }
        if (n != a[0].length) {
            throw new IllegalArgumentException("Matrix A must be square.");
        }
        if (n != b.length) {
            throw new IllegalArgumentException("Matrix A and vector b dimensions do not match.");
        }
        if (n != x0.length) {
            throw new IllegalArgumentException("Matrix A and vector x0 dimensions do not match.");
        }
        if (minEigenvalue <= 0) {
            throw new IllegalArgumentException("Smallest eigenvalue must be positive (matrix must be positive-definite).");
        }
        if (maxEigenvalue <= minEigenvalue) {
            throw new IllegalArgumentException("Max eigenvalue must be strictly greater than min eigenvalue.");
        }
        if (maxIterations <= 0) {
            throw new IllegalArgumentException("Max iterations must be positive.");
        }
        if (tolerance <= 0) {
            throw new IllegalArgumentException("Tolerance must be positive.");
        }
    }

    // --- Vector/Matrix Helper Methods ---
    /**
     * Computes the product of a matrix A and a vector v (Av).

View on GitHub (pinned to fdfb9a395b)

Solutions

1. Ensure x0.length == a.length before calling solve. The simplest valid initial guess is new double[n] (all zeros) where n = a.length.
2. Construct x0 in the same dimensional context as A and b.
3. Add a precondition: if (x0.length != a.length) throw or resize.

Example fix

// before
ChebyshevIteration.solve(A, b, new double[2], 1, 2, 100, 1e-6); // A is 3x3
// throws 'Matrix A and vector x0 dimensions do not match.'

// after (use correctly-sized zero initial guess)
int n = A.length;
double[] x0 = new double[n]; // zero initial guess
double[] x = ChebyshevIteration.solve(A, b, x0, minEig, maxEig, maxIter, tol);

// Validate x0 dimension matches A before calling solve
int n = a.length;
if (x0 == null || x0.length != n) {
    x0 = new double[n]; // use zero initial guess as fallback
}
double[] x = ChebyshevIteration.solve(a, b, x0, minEig, maxEig, maxIter, tol);

static boolean dimensionsMatch(double[][] a, double[] x0) {
    return a != null && a.length > 0 && x0 != null && x0.length == a.length;
}

When it happens

Trigger: Calling solve with a 3x3 matrix A but x0.length != 3. For example, solve(A, b, new double[2], ...) where the initial guess has 2 elements instead of 3. Also common when x0 is initialized as new double[0] or defaults to null-derived zero-length.

Common situations: Using a zero-filled initial guess of the wrong size (e.g., new double[n-1] due to an off-by-one). Reusing x0 from a previous problem with a different dimension. Defaulting x0 to a cached vector that was computed for a different matrix size.

Related errors

• Matrix A and vector b dimensions do not match.
• Matrix A cannot be empty.
• Matrix A must be square.
• Smallest eigenvalue must be positive (matrix must be positiv
• Max eigenvalue must be strictly greater than min eigenvalue.

AI-assisted analysis of TheAlgorithms/Java@fdfb9a395b (2026-08-13). Data as JSON: /api/errors/abb9d0163c0894f6. Report an issue: GitHub.