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  2. Orthonormality - Wikipedia

    en.wikipedia.org/wiki/Orthonormality

    This is possibly the most significant use of orthonormality, as this fact permits operators on inner-product spaces to be discussed in terms of their action on the space's orthonormal basis vectors. What results is a deep relationship between the diagonalizability of an operator and how it acts on the orthonormal basis vectors.

  3. Orthonormal basis - Wikipedia

    en.wikipedia.org/wiki/Orthonormal_basis

    In mathematics, particularly linear algebra, an orthonormal basis for an inner product space with finite dimension is a basis for whose vectors are orthonormal, that is, they are all unit vectors and orthogonal to each other.

  4. Orthogonality (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Orthogonality_(mathematics)

    In Euclidean space, two vectors are orthogonal if and only if their dot product is zero, i.e. they make an angle of 90° (radians), or one of the vectors is zero. [4] Hence orthogonality of vectors is an extension of the concept of perpendicular vectors to spaces of any dimension.

  5. Orthogonality - Wikipedia

    en.wikipedia.org/wiki/Orthogonality

    The line segments AB and CD are orthogonal to each other. In mathematics, orthogonality is the generalization of the geometric notion of perpendicularity.Whereas perpendicular is typically followed by to when relating two lines to one another (e.g., "line A is perpendicular to line B"), [1] orthogonal is commonly used without to (e.g., "orthogonal lines A and B").

  6. Stiefel manifold - Wikipedia

    en.wikipedia.org/wiki/Stiefel_manifold

    Let stand for ,, or . The Stiefel manifold () can be thought of as a set of n × k matrices by writing a k-frame as a matrix of k column vectors in . The orthonormality condition is expressed by A*A = where A* denotes the conjugate transpose of A and denotes the k × k identity matrix.

  7. Orthogonal functions - Wikipedia

    en.wikipedia.org/wiki/Orthogonal_functions

    In mathematics, orthogonal functions belong to a function space that is a vector space equipped with a bilinear form.When the function space has an interval as the domain, the bilinear form may be the integral of the product of functions over the interval:

  8. Orthogonal matrix - Wikipedia

    en.wikipedia.org/wiki/Orthogonal_matrix

    In linear algebra, an orthogonal matrix, or orthonormal matrix, is a real square matrix whose columns and rows are orthonormal vectors.. One way to express this is = =, where Q T is the transpose of Q and I is the identity matrix.

  9. Gell-Mann matrices - Wikipedia

    en.wikipedia.org/wiki/Gell-Mann_matrices

    These matrices are traceless, Hermitian, and obey the extra trace orthonormality relation, so they can generate unitary matrix group elements of SU(3) through exponentiation. [1] These properties were chosen by Gell-Mann because they then naturally generalize the Pauli matrices for SU(2) to SU(3), which formed the basis for Gell-Mann's quark ...