# Einstein notation

In mathematics, especially in applications of linear algebra to physics, **Einstein notation** (also known as the **Einstein summation convention** or **Einstein summation notation**) is a notational convention that implies summation over a set of indexed terms in a formula, thus achieving brevity. As part of mathematics it is a notational subset of Ricci calculus; however, it is often used in physics applications that do not distinguish between tangent and cotangent spaces. It was introduced to physics by Albert Einstein in 1916.^{[1]}

The upper indices are not exponents but are indices of coordinates, coefficients or basis vectors. That is, in this context *x*^{2} should be understood as the second component of *x* rather than the square of *x* (this can occasionally lead to ambiguity). The upper index position in *x*^{i} is because, typically, an index occurs once in an upper (superscript) and once in a lower (subscript) position in a term (see *§ Application* below). Typically, (*x*^{1} *x*^{2} *x*^{3}) would be equivalent to the traditional (*x* *y* *z*).

In general, indices can range over any indexing set, including an infinite set. This should not be confused with a typographically similar convention used to distinguish between tensor index notation and the closely related but distinct basis-independent abstract index notation.

An index that is summed over is a *summation index*, in this case "*i*". It is also called a dummy index since any symbol can replace "*i*" without changing the meaning of the expression provided that it does not collide with index symbols in the same term.

Einstein notation can be applied in slightly different ways. Typically, each index occurs once in an upper (superscript) and once in a lower (subscript) position in a term; however, the convention can be applied more generally to any repeated indices within a term.^{[2]} When dealing with covariant and contravariant vectors, where the position of an index also indicates the type of vector, the first case usually applies; a covariant vector can only be contracted with a contravariant vector, corresponding to summation of the products of coefficients. On the other hand, when there is a fixed coordinate basis (or when not considering coordinate vectors), one may choose to use only subscripts; see below.

They transform contravariantly or covariantly, respectively, with respect to change of basis.

In recognition of this fact, the following notation uses the same symbol both for a vector or covector and its *components*, as in:

In the presence of a non-degenerate form (an isomorphism *V* → *V*^{∗}, for instance a Riemannian metric or Minkowski metric), one can raise and lower indices.

A basis gives such a form (via the dual basis), hence when working on **R**^{n} with a Euclidean metric and a fixed orthonormal basis, one has the option to work with only subscripts.

However, if one changes coordinates, the way that coefficients change depends on the variance of the object, and one cannot ignore the distinction; see covariance and contravariance of vectors.

In the above example, vectors are represented as *n* × 1 matrices (column vectors), while covectors are represented as 1 × *n* matrices (row covectors).

The virtue of Einstein notation is that it represents the invariant quantities with a simple notation.

In physics, a scalar is invariant under transformations of basis. In particular, a Lorentz scalar is invariant under a Lorentz transformation. The individual terms in the sum are not. When the basis is changed, the *components* of a vector change by a linear transformation described by a matrix. This led Einstein to propose the convention that repeated indices imply the summation is to be done.

As for covectors, they change by the inverse matrix. This is designed to guarantee that the linear function associated with the covector, the sum above, is the same no matter what the basis is.

The value of the Einstein convention is that it applies to other vector spaces built from *V* using the tensor product and duality. For example, *V* ⊗ *V*, the tensor product of *V* with itself, has a basis consisting of tensors of the form **e**_{ij} = **e**_{i} ⊗ **e**_{j}. Any tensor **T** in *V* ⊗ *V* can be written as:

the row/column coordinates on a matrix correspond to the upper/lower indices on the tensor product.

Using an orthogonal basis, the inner product is the sum of corresponding components multiplied together:

This can also be calculated by multiplying the covector on the vector.

Again using an orthogonal basis (in 3 dimensions) the cross product intrinsically involves summations over permutations of components:

*ε _{ijk}* is the Levi-Civita symbol, and

*δ*is the generalized Kronecker delta. Based on this definition of

^{il}*ε*, there is no difference between

*ε*and

^{i}_{jk}*ε*but the position of indices.

_{ijk}For a square matrix *A ^{i}_{j}*, the trace is the sum of the diagonal elements, hence the sum over a common index

*A*.

^{i}_{i}The outer product of the column vector *u ^{i}* by the row vector

*v*yields an

_{j}*m*×

*n*matrix

**A**:

Since *i* and *j* represent two *different* indices, there is no summation and the indices are not eliminated by the multiplication.

Given a tensor, one can raise an index or lower an index by contracting the tensor with the metric tensor, *g _{μν}*. For example, take the tensor

*T*, one can raise an index:

^{α}_{β}