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This is a **glossary of tensor theory**. For expositions of tensor theory from different points of view, see:

For some history of the abstract theory see also Multilinear algebra.

The earliest foundation of tensor theory – tensor index notation.^{[1]}

The components of a tensor with respect to a basis is an indexed array. The *order* of a tensor is the number of indices needed. Some texts may refer to the tensor order using the term *degree* or *rank*.

The rank of a tensor is the minimum number of rank-one tensor that must be summed to obtain the tensor. A rank-one tensor may be defined as expressible as the outer product of the number of nonzero vectors needed to obtain the correct order.

A *dyadic* tensor is a tensor of order two, and may be represented as a square matrix. In contrast, a *dyad* is specifically a dyadic tensor of rank one.

This notation is based on the understanding that whenever a multidimensional array contains a repeated index letter, the default interpretation is that the product is summed over all permitted values of the index. For example, if *a _{ij}* is a matrix, then under this convention

- Covariant tensor

- Contravariant tensor

The classical interpretation is by components. For example, in the differential form *a _{i}dx^{i}* the

This refers to any tensor that has both lower and upper indices.

**Cartesian tensor**

Cartesian tensors are widely used in various branches of continuum mechanics, such as fluid mechanics and elasticity. In classical continuum mechanics, the space of interest is usually 3-dimensional Euclidean space, as is the tangent space at each point. If we restrict the local coordinates to be Cartesian coordinates with the same scale centered at the point of interest, the metric tensor is the Kronecker delta. This means that there is no need to distinguish covariant and contravariant components, and furthermore there is no need to distinguish tensors and tensor densities. All Cartesian-tensor indices are written as subscripts. Cartesian tensors achieve considerable computational simplification at the cost of generality and of some theoretical insight.

This avoids the initial use of components, and is distinguished by the explicit use of the tensor product symbol.

If *v* and *w* are vectors in vector spaces *V* and *W* respectively, then

is a tensor in

That is, the ⊗ operation is a binary operation, but it takes values into a fresh space (it is in a strong sense *external*). The ⊗ operation is a bilinear map; but no other conditions are applied to it.

A pure tensor of *V* ⊗ *W* is one that is of the form *v* ⊗ *w*

It could be written dyadically *a ^{i}b^{j}*, or more accurately

In the tensor algebra *T*(*V*) of a vector space *V*, the operation becomes a normal (internal) binary operation. A consequence is that *T*(*V*) has infinite dimension unless *V* has dimension 0. The free algebra on a set *X* is for practical purposes the same as the tensor algebra on the vector space with *X* as basis.

The wedge product is the anti-symmetric form of the ⊗ operation. The quotient space of *T*(*V*) on which it becomes an internal operation is the *exterior algebra* of *V*; it is a graded algebra, with the graded piece of weight *k* being called the *k*-th **exterior power** of *V*.

This is the invariant way of constructing polynomial algebras.

This is an operation on fields, that does not always produce a field.

A representation of a Clifford algebra which gives a realisation of a Clifford algebra as a matrix algebra.

These are the derived functors of the tensor product, and feature strongly in homological algebra. The name comes from the torsion subgroup in abelian group theory.

These are *highly* abstract approaches used in some parts of geometry.

See:

**^**Ricci, Gregorio; Levi-Civita, Tullio (March 1900), "Méthodes de calcul différentiel absolu et leurs applications" [Absolute differential calculation methods & their applications],*Mathematische Annalen*(in French), Springer,**54**(1–2): 125–201, doi:10.1007/BF01454201, S2CID 120009332

- Bishop, R.L.; Goldberg, S.I. (1968),
*Tensor Analysis on Manifolds*(First Dover 1980 ed.), The Macmillan Company, ISBN 0-486-64039-6 - Danielson, Donald A. (2003).
*Vectors and Tensors in Engineering and Physics*(2/e ed.). Westview (Perseus). ISBN 978-0-8133-4080-7. - Dimitrienko, Yuriy (2002).
*Tensor Analysis and Nonlinear Tensor Functions*. Kluwer Academic Publishers (Springer). ISBN 1-4020-1015-X. - Lovelock, David; Hanno Rund (1989) [1975].
*Tensors, Differential Forms, and Variational Principles*. Dover. ISBN 978-0-486-65840-7. - Synge, John L; Schild, Alfred (1949).
*Tensor Calculus*. Dover Publications 1978 edition. ISBN 978-0-486-63612-2.