Adjoint (Adjugate) Matrix Calculator
Compute the classical adjoint (adjugate) matrix with cofactors, minors, sign pattern visualization, inverse connection, and verification that A·adj(A) = det(A)·I.
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Compute the classical adjoint (adjugate) matrix with cofactors, minors, sign pattern visualization, inverse connection, and verification that A·adj(A) = det(A)·I.
Find the angle between two vectors in 2D–6D using the dot product formula. Get degrees, radians, cos/sin/tan θ, perpendicularity and parallelism checks, computation steps, and a visual angle gauge.
Factor a symmetric positive definite matrix A = LLᵀ with step-by-step Cholesky algorithm, positive definiteness check, solve Ax=b, and verification display.
Solve 2×2, 3×3, and 4×4 systems of linear equations using Cramer's Rule with determinant calculations, step-by-step Dx/Dy/Dz display, solution verification, and determinant comparison visualization.
Compute the cross product of two 3D vectors, find the parallelogram area, unit normal direction, angle between vectors, and scalar triple product with step-by-step breakdowns.
Compute the dot product of two vectors in 2D–6D, find the angle between them, check orthogonality and parallelism, and visualize component contributions with an interactive calculator.
Compute eigenvalues and eigenvectors for 2×2 and 3×3 matrices with characteristic polynomial, diagonalization check, spectrum visualization, and detailed calculation steps.
Solve systems of linear equations Ax=b via augmented matrix Gauss-Jordan elimination with step-by-step row operations, back substitution display, and solution visualization.
Apply the Gram-Schmidt process to 2–4 vectors in R², R³, or R⁴. View step-by-step projections, orthonormal results, dot-product verification matrix, and norm comparison bars.
Calculate the Hadamard (element-wise) product of two matrices. Compare with standard multiplication, view properties, and explore visual breakdowns.
Factor a square matrix into lower and upper triangular matrices A=LU with step-by-step Doolittle method, solve Ax=b via forward/back substitution, and verification display.
Add or subtract matrices up to 5×5 with element-wise breakdown, scalar combination mode, Frobenius norms, comparison heat map, and detailed result tables.
Perform matrix operations including addition, subtraction, multiplication, transpose, determinant, inverse, and scalar multiplication for matrices up to 5×5.
Compute the determinant for 2×2 through 5×5 matrices with cofactor expansion steps, minor matrix display, term contribution bars, and comprehensive properties table.
Find the inverse of a matrix up to 5×5 using the cofactor/adjugate method, with step-by-step cofactor table, verification A×A⁻¹=I, condition number analysis, and singular detection.
Multiply matrices up to 5×5 with dimension compatibility check, partial products breakdown, Strassen complexity comparison, and result magnitude visualization.
Compute Frobenius, spectral, 1-norm, infinity-norm, and max-norm of a matrix with comparison bars, relationship verification, and breakdown tables.
Compute the rank of a matrix up to 5×5 via row echelon form with nullity, rank-nullity theorem verification, pivot visualization, and step-by-step row reduction.
Multiply a matrix by a scalar with element-wise display, property verification, chain operations, determinant/trace scaling, and before/after visualization.
Compute the trace of a square matrix with property verification, eigenvalue connection, diagonal contribution bars, and two-matrix mode for cyclic property testing.
Transpose a matrix up to 5×5 with symmetry checks, skew-symmetric detection, double transpose verification, before/after display, and properties table.
Find the null space of a matrix via RREF with basis vectors, dimension, solution verification, step-by-step reduction, and component visualization.
Determine the order of magnitude of any number, convert to scientific notation, compare magnitudes, see the SI prefix region, and explore a logarithmic scale with real-world examples.
Decompose a matrix A = UP into a unitary factor U and positive semi-definite factor P. View singular values, condition number, and geometric interpretation.
Compute the Moore-Penrose pseudoinverse of rectangular or singular matrices via SVD. Verify all four Moore-Penrose conditions with step-by-step details.
Compute QR decomposition via Gram-Schmidt. View orthogonal Q and upper triangular R with step-by-step process, verification, and application reference.
Transform any matrix to Row Echelon Form and Reduced Row Echelon Form with step-by-step row operations, pivot identification, rank determination, and visual pivot highlighting.
Compute the Singular Value Decomposition A = UΣVᵀ. View singular values, rank, condition number, matrix norms, energy distribution, and low-rank approximation.
Compute the unit vector (normalization) of any vector from 2D to 6D. Verify ‖û‖ = 1, see direction angles, component contributions, scaling, and compare original vs unit vector visually.
Add or subtract 2–5 vectors in 2D or 3D. View resultant magnitude, direction, component-wise breakdown table, magnitude comparison bars, and component contribution visuals.
Compute vector magnitude, unit vector, scalar multiplication, direction angles, and negation for 2D and 3D vectors with component visualization bars and properties table.
Compute direction angles α, β, γ from a 2D or 3D vector, direction cosines, azimuth/elevation, compass visualization, angle bars, and direction cosine identity verification.
Compute vector magnitude for 2D to 6D vectors using L1 (Manhattan), L2 (Euclidean), L∞ (Chebyshev), and custom Lp norms with unit vector, component contribution bars, and norm comparison.
Project vector a onto vector b: scalar projection, vector projection, rejection, angle between vectors, decomposition table, visual breakdown, and orthogonality verification.