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Bra–ket notation and Projection (linear algebra)

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between Bra–ket notation and Projection (linear algebra)

Bra–ket notation vs. Projection (linear algebra)

In quantum mechanics, bra–ket notation is a standard notation for describing quantum states. In linear algebra and functional analysis, a projection is a linear transformation P from a vector space to itself such that.

Similarities between Bra–ket notation and Projection (linear algebra)

Bra–ket notation and Projection (linear algebra) have 15 things in common (in Unionpedia): Banach space, Complete metric space, Conjugate transpose, Dot product, Functional analysis, Hilbert space, Inner product space, Linear algebra, Linear map, Linear subspace, Matrix multiplication, Orthonormal basis, Outer product, Self-adjoint operator, Vector space.

Banach space

In mathematics, more specifically in functional analysis, a Banach space (pronounced) is a complete normed vector space.

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Complete metric space

In mathematical analysis, a metric space M is called complete (or a Cauchy space) if every Cauchy sequence of points in M has a limit that is also in M or, alternatively, if every Cauchy sequence in M converges in M. Intuitively, a space is complete if there are no "points missing" from it (inside or at the boundary).

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Conjugate transpose

In mathematics, the conjugate transpose or Hermitian transpose of an m-by-n matrix A with complex entries is the n-by-m matrix A∗ obtained from A by taking the transpose and then taking the complex conjugate of each entry.

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Dot product

In mathematics, the dot product or scalar productThe term scalar product is often also used more generally to mean a symmetric bilinear form, for example for a pseudo-Euclidean space.

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Functional analysis

Functional analysis is a branch of mathematical analysis, the core of which is formed by the study of vector spaces endowed with some kind of limit-related structure (e.g. inner product, norm, topology, etc.) and the linear functions defined on these spaces and respecting these structures in a suitable sense.

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Hilbert space

The mathematical concept of a Hilbert space, named after David Hilbert, generalizes the notion of Euclidean space.

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Inner product space

In linear algebra, an inner product space is a vector space with an additional structure called an inner product.

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Linear algebra

Linear algebra is the branch of mathematics concerning linear equations such as linear functions such as and their representations through matrices and vector spaces.

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Linear map

In mathematics, a linear map (also called a linear mapping, linear transformation or, in some contexts, linear function) is a mapping between two modules (including vector spaces) that preserves (in the sense defined below) the operations of addition and scalar multiplication.

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Linear subspace

In linear algebra and related fields of mathematics, a linear subspace, also known as a vector subspace, or, in the older literature, a linear manifold, is a vector space that is a subset of some other (higher-dimension) vector space.

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Matrix multiplication

In mathematics, matrix multiplication or matrix product is a binary operation that produces a matrix from two matrices with entries in a field, or, more generally, in a ring or even a semiring.

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Orthonormal basis

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

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Outer product

In linear algebra, an outer product is the tensor product of two coordinate vectors, a special case of the Kronecker product of matrices.

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Self-adjoint operator

In mathematics, a self-adjoint operator on a finite-dimensional complex vector space V with inner product \langle\cdot,\cdot\rangle is a linear map A (from V to itself) that is its own adjoint: \langle Av,w\rangle.

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Vector space

A vector space (also called a linear space) is a collection of objects called vectors, which may be added together and multiplied ("scaled") by numbers, called scalars.

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The list above answers the following questions

Bra–ket notation and Projection (linear algebra) Comparison

Bra–ket notation has 80 relations, while Projection (linear algebra) has 66. As they have in common 15, the Jaccard index is 10.27% = 15 / (80 + 66).

References

This article shows the relationship between Bra–ket notation and Projection (linear algebra). To access each article from which the information was extracted, please visit:

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