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List of named matrices - Wikipedia

This article lists some important classes of matrices used in mathematics, science and engineering. A matrix (plural matrices, or less commonly matrixes) is a rectangular array of numbers called entries. Matrices have a long history of both study and application, leading to diverse ways of classifying matrices. A first group is matrices satisfying concrete conditions of the entries, including constant matrices. Important examples include the identity matrix given by

Further ways of classifying matrices are according to their eigenvalues, or by imposing conditions on the product of the matrix with other matrices. Finally, many domains, both in mathematics and other sciences including physics and chemistry, have particular matrices that are applied chiefly in these areas.

The list below comprises matrices whose elements are constant for any given dimension (size) of matrix. The matrix entries will be denoted a_ij. The table below uses the Kronecker delta δ_ij for two integers i and j which is 1 if i = j and 0 else.

Name Explanation Symbolic description of the entries Notes Commutation matrix The matrix of the linear map that maps a matrix to its transpose See Vectorization Duplication matrix The matrix of the linear map mapping the vector of the distinct entries of a symmetric matrix to the vector of all entries of the matrix See Vectorization Elimination matrix The matrix of the linear map mapping the vector of the entries of a matrix to the vector of a part of the entries (for example the vector of the entries that are not below the main diagonal) See vectorization Exchange matrix The binary matrix with ones on the anti-diagonal, and zeroes everywhere else. a_ij = δ_n+1−i,j A permutation matrix. Hilbert matrix A structured grid of rational values formed by the sum of polynominal denominators, modulated symmetrically and positively as approximation behavior a_ij = (i + j − 1)⁻¹. A Hankel matrix. Identity matrix A square diagonal matrix, with all entries on the main diagonal equal to 1, and the rest 0. a_ij = δ_ij Lehmer matrix a_ij = min(i, j) ÷ max(i, j). A positive symmetric matrix. Matrix of ones A matrix with all entries equal to one. a_ij = 1. Pascal matrix A matrix containing the entries of Pascal's triangle. Pauli matrices A set of three 2 × 2 complex Hermitian and unitary matrices. When combined with the I₂ identity matrix, they form an orthogonal basis for the 2 × 2 complex Hermitian matrices. Redheffer matrix Encodes a Dirichlet convolution. Matrix entries are given by the divisor function; entires of the inverse are given by the Möbius function. a_ij are 1 if i divides j or if j = 1; otherwise, a_ij = 0. A (0, 1)-matrix. Shift matrix A matrix with ones on the superdiagonal or subdiagonal and zeroes elsewhere. a_ij = δ_i+1,j or a_ij = δ_i−1,j Multiplication by it shifts matrix elements by one position. Zero matrix A matrix with all entries equal to zero. a_ij = 0.

The following lists matrices whose entries are subject to certain conditions. Many of them apply to square matrices only, that is matrices with the same number of columns and rows. The main diagonal of a square matrix is the diagonal joining the upper left corner and the lower right one or equivalently the entries a_i,i. The other diagonal is called anti-diagonal (or counter-diagonal).

Name Explanation Notes, references (0,1)-matrix A matrix with all elements either 0 or 1. Synonym for binary matrix or logical matrix. Alternant matrix A matrix in which successive columns have a particular function applied to their entries. Alternating sign matrix A square matrix with entries 0, 1 and −1 such that the sum of each row and column is 1 and the nonzero entries in each row and column alternate in sign. Anti-diagonal matrix A square matrix with all entries off the anti-diagonal equal to zero. Anti-Hermitian matrix Synonym for skew-Hermitian matrix. Anti-symmetric matrix Synonym for skew-symmetric matrix. Arrowhead matrix A square matrix containing zeros in all entries except for the first row, first column, and main diagonal. Band matrix A square matrix whose non-zero entries are confined to a diagonal band. Bidiagonal matrix A matrix with elements only on the main diagonal and either the superdiagonal or subdiagonal. Sometimes defined differently, see article. Binary matrix A matrix whose entries are all either 0 or 1. Synonym for (0,1)-matrix or logical matrix.^[1] Bisymmetric matrix A square matrix that is symmetric with respect to its main diagonal and its main cross-diagonal. Block-diagonal matrix A block matrix with entries only on the diagonal. Block matrix A matrix partitioned in sub-matrices called blocks. Block tridiagonal matrix A block matrix which is essentially a tridiagonal matrix but with submatrices in place of scalar elements. Boolean matrix A matrix whose entries are taken from a Boolean algebra. Cauchy matrix A matrix whose elements are of the form 1/(x_i + y_j) for (x_i), (y_j) injective sequences (i.e., taking every value only once). Centrosymmetric matrix A matrix symmetric about its center; i.e., a_ij = a_{n−i+1,n−j+1}. Circulant matrix A matrix where each row is a circular shift of its predecessor. Conference matrix A square matrix with zero diagonal and +1 and −1 off the diagonal, such that C^TC is a multiple of the identity matrix. Complex Hadamard matrix A matrix with all rows and columns mutually orthogonal, whose entries are unimodular. Compound matrix A matrix whose entries are generated by the determinants of all minors of a matrix. Copositive matrix A square matrix A with real coefficients, such that f ( x ) = x T A x {\displaystyle f(x)=x^{T}Ax} is nonnegative for every nonnegative vector x Diagonally dominant matrix A matrix whose entries satisfy | a i i | > ∑ j ≠ i | a i j | {\displaystyle |a_{ii}|>\sum _{j\neq i}|a_{ij}|} . Diagonal matrix A square matrix with all entries outside the main diagonal equal to zero. Discrete Fourier-transform matrix Multiplying by a vector gives the DFT of the vector as result. Elementary matrix A square matrix derived by applying an elementary row operation to the identity matrix. Equivalent matrix A matrix that can be derived from another matrix through a sequence of elementary row or column operations. Frobenius matrix A square matrix in the form of an identity matrix but with arbitrary entries in one column below the main diagonal. GCD matrix The n × n {\displaystyle n\times n} matrix ( S ) {\displaystyle (S)} having the greatest common divisor ( x i , x j ) {\displaystyle (x_{i},x_{j})} as its i j {\displaystyle ij} entry, where x i , x j ∈ S {\displaystyle x_{i},x_{j}\in S} . Generalized permutation matrix A square matrix with precisely one nonzero element in each row and column. Hadamard matrix A square matrix with entries +1, −1 whose rows are mutually orthogonal. Hankel matrix A matrix with constant skew-diagonals; also an upside down Toeplitz matrix. A square Hankel matrix is symmetric. Hermitian matrix A square matrix which is equal to its conjugate transpose, A = A^*. Hessenberg matrix An "almost" triangular matrix, for example, an upper Hessenberg matrix has zero entries below the first subdiagonal. Hollow matrix A square matrix whose main diagonal comprises only zero elements. Integer matrix A matrix whose entries are all integers. Logical matrix A matrix with all entries either 0 or 1. Synonym for (0,1)-matrix, binary matrix or Boolean matrix. Can be used to represent a k-adic relation. Markov matrix A matrix of non-negative real numbers, such that the entries in each row sum to 1. Metzler matrix A matrix whose off-diagonal entries are non-negative. Monomial matrix A square matrix with exactly one non-zero entry in each row and column. Synonym for generalized permutation matrix. Moore matrix A row consists of a, a^q, a^q², etc., and each row uses a different variable. Nonnegative matrix A matrix with all nonnegative entries. Null-symmetric matrix A square matrix whose null space (or kernel) is equal to its transpose, N(A) = N(A^T) or ker(A) = ker(A^T). Synonym for kernel-symmetric matrices. Examples include (but not limited to) symmetric, skew-symmetric, and normal matrices. Null-Hermitian matrix A square matrix whose null space (or kernel) is equal to its conjugate transpose, N(A)=N(A^*) or ker(A)=ker(A^*). Synonym for kernel-Hermitian matrices. Examples include (but not limited) to Hermitian, skew-Hermitian matrices, and normal matrices. Partitioned matrix A matrix partitioned into sub-matrices, or equivalently, a matrix whose entries are themselves matrices rather than scalars. Synonym for block matrix. Parisi matrix A block-hierarchical matrix. It consist of growing blocks placed along the diagonal, each block is itself a Parisi matrix of a smaller size. In theory of spin-glasses is also known as a replica matrix. Pentadiagonal matrix A matrix with the only nonzero entries on the main diagonal and the two diagonals just above and below the main one. Permutation matrix A matrix representation of a permutation, a square matrix with exactly one 1 in each row and column, and all other elements 0. Persymmetric matrix A matrix that is symmetric about its northeast–southwest diagonal, i.e., a_ij = a_{n−j+1,n−i+1}. Polynomial matrix A matrix whose entries are polynomials. Positive matrix A matrix with all positive entries. Quaternionic matrix A matrix whose entries are quaternions. Random matrix A matrix whose entries are random variables Sign matrix A matrix whose entries are either +1, 0, or −1. Signature matrix A diagonal matrix where the diagonal elements are either +1 or −1. Single-entry matrix A matrix where a single element is one and the rest of the elements are zero. Skew-Hermitian matrix A square matrix which is equal to the negative of its conjugate transpose, A^* = −A. Skew-symmetric matrix A matrix which is equal to the negative of its transpose, A^T = −A. Skyline matrix A rearrangement of the entries of a banded matrix which requires less space. Sparse matrix A matrix with relatively few non-zero elements. Sparse matrix algorithms can tackle huge sparse matrices that are utterly impractical for dense matrix algorithms. Symmetric matrix A square matrix which is equal to its transpose, A = A^T (a_i,j = a_j,i). Toeplitz matrix A matrix with constant diagonals. Totally positive matrix A matrix with determinants of all its square submatrices positive. Triangular matrix A matrix with all entries above the main diagonal equal to zero (lower triangular) or with all entries below the main diagonal equal to zero (upper triangular). Tridiagonal matrix A matrix with the only nonzero entries on the main diagonal and the diagonals just above and below the main one. X–Y–Z matrix A generalization to three dimensions of the concept of two-dimensional array Vandermonde matrix A row consists of 1, a, a², a³, etc., and each row uses a different variable. Walsh matrix A square matrix, with dimensions a power of 2, the entries of which are +1 or −1, and the property that the dot product of any two distinct rows (or columns) is zero. Z-matrix A matrix with all off-diagonal entries less than zero.

A number of matrix-related notions is about properties of products or inverses of the given matrix. The matrix product of a m-by-n matrix A and a n-by-k matrix B is the m-by-k matrix C given by

This matrix product is denoted AB. Unlike the product of numbers, matrix products are not commutative, that is to say AB need not be equal to BA.^[2] A number of notions are concerned with the failure of this commutativity. An inverse of square matrix A is a matrix B (necessarily of the same dimension as A) such that AB = I. Equivalently, BA = I. An inverse need not exist. If it exists, B is uniquely determined, and is also called the inverse of A, denoted A⁻¹.

Name Explanation Notes Circular matrix or Coninvolutory matrix A matrix whose inverse is equal to its entrywise complex conjugate: A⁻¹ = A. Compare with unitary matrices. Congruent matrix Two matrices A and B are congruent if there exists an invertible matrix P such that P^T A P = B. Compare with similar matrices. EP matrix or Range-Hermitian matrix A square matrix that commutes with its Moore–Penrose inverse: AA⁺ = A⁺A. Idempotent matrix or
Projection Matrix A matrix that has the property A² = AA = A. The name projection matrix inspires from the observation of projection of a point multiple
times onto a subspace(plane or a line) giving the same result as one projection. Invertible matrix A square matrix having a multiplicative inverse, that is, a matrix B such that AB = BA = I. Invertible matrices form the general linear group. Involutory matrix A square matrix which is its own inverse, i.e., AA = I. Signature matrices, Householder matrices (Also known as 'reflection matrices'
to reflect a point about a plane or line) have this property. Isometric matrix A matrix that preserves distances, i.e., a matrix that satisfies A^*A = I where A^* denotes the conjugate transpose of A. Nilpotent matrix A square matrix satisfying A^q = 0 for some positive integer q. Equivalently, the only eigenvalue of A is 0. Normal matrix A square matrix that commutes with its conjugate transpose: AA^∗ = A^∗A They are the matrices to which the spectral theorem applies. Orthogonal matrix A matrix whose inverse is equal to its transpose, A⁻¹ = A^T. They form the orthogonal group. Orthonormal matrix A matrix whose columns are orthonormal vectors. Partially Isometric matrix A matrix that is an isometry on the orthogonal complement of its kernel. Equivalently, a matrix that satisfies AA^*A = A. Equivalently, a matrix with singular values that are either 0 or 1. Singular matrix A square matrix that is not invertible. Unimodular matrix An invertible matrix with entries in the integers (integer matrix) Necessarily the determinant is +1 or −1. Unipotent matrix A square matrix with all eigenvalues equal to 1. Equivalently, A − I is nilpotent. See also unipotent group. Unitary matrix A square matrix whose inverse is equal to its conjugate transpose, A⁻¹ = A^*. Totally unimodular matrix A matrix for which every non-singular square submatrix is unimodular. This has some implications in the linear programming relaxation of an integer program. Weighing matrix A square matrix the entries of which are in {0, 1, −1}, such that AA^T = wI for some positive integer w.

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