Advanced Matrix Eigenvalues Calculator

Solve eigenvalues for 2×2, 3×3, and larger matrices. Inspect trace, determinant, and stability measures quickly. Plot spectral magnitude patterns for clear matrix interpretation today.

Matrix Eigenvalues Calculator

Use spaces, commas, or semicolons between values.
Results appear above this form after submission.

Example Data Table

Example Matrix Expected Insight
Symmetric 2×2 [2 1; 1 2] Real eigenvalues with exact closed-form verification.
Tridiagonal 3×3 [4 1 0; 1 3 1; 0 1 2] Stable real spectrum and clean QR convergence.
Dense 4×4 [6 2 1 0; 2 5 2 1; 1 2 4 2; 0 1 2 3] Useful for comparing spectral radius and trace.

Formula Used

Eigenvalues λ satisfy the characteristic equation: det(A − λI) = 0.

For a 2×2 matrix A = [a b; c d], the characteristic polynomial is λ² − (a + d)λ + (ad − bc) = 0.

This calculator uses shifted QR iteration for numerical approximation. Repeated factorization writes Aₖ = QₖRₖ and updates Aₖ₊₁ = RₖQₖ. The diagonal entries of the nearly upper triangular matrix approach the eigenvalues.

Supporting checks: trace(A) = Σλᵢ, det(A) = Πλᵢ, and spectral radius = max |λᵢ|.

How to Use This Calculator

  1. Enter a square matrix using one row per line.
  2. Separate values with spaces, commas, or semicolons.
  3. Choose display decimals, tolerance, and maximum iterations.
  4. Click Calculate Eigenvalues.
  5. Review the summary above the form.
  6. Check eigenvalues, bounds, convergence, and the graph.
  7. Use CSV or PDF export for reporting.

FAQs

1. What does this calculator compute?

It computes approximate eigenvalues of a square matrix, along with trace, determinant, Frobenius norm, spectral radius, Gershgorin bounds, and QR convergence data.

2. Does the matrix need to be square?

Yes. Eigenvalues are defined for square matrices only. Every row must contain the same number of entries as the total number of rows.

3. Are the eigenvalues exact?

For 2×2 matrices, the page also shows an exact closed-form check. Larger matrices use numerical QR iteration, so results are approximations.

4. Why compare trace and determinant?

They are fast validation checks. The sum of eigenvalues should match the trace, and the product should match the determinant within numerical tolerance.

5. What is the spectral radius?

The spectral radius is the largest absolute eigenvalue. It is useful in stability analysis, iterative methods, and dynamic systems.

6. What does QR convergence mean?

QR convergence describes how quickly off-diagonal terms shrink during iteration. Smaller final off-diagonal norms indicate a more reliable triangular approximation.

7. Can this handle complex eigenvalues?

The exact 2×2 routine reports complex conjugates when needed. For larger matrices, this implementation mainly targets real-valued approximations from QR iteration.

8. What format should I use for input?

Place one row on each line. Separate entries using spaces, commas, or semicolons. Decimal and negative values are supported.

Related Calculators

matrix determinant 4x4matrix trace calculatormatrix scalar multiplicationmatrix power calculatormatrix addition calculatoridentity matrix calculatormatrix inverse 4x4matrix cofactor calculatormatrix null space calculatormatrix vector space calculator

Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.