What is the tensor in physics?

A tensor is a concept from mathematical physics that can be thought of as a generalization of a vector. While tensors can be defined in a purely mathematical sense, they are most useful in connection with vectors in physics. In this article, all vector spaces are real and finite-dimensional.

What is tensor and example?

Tensor is the quantity which has magnitude, direction and plane in which it acts or defined with respect to its coordinate system A tensor field has a tensor corresponding to each point space. Example of tensor quantities are: Stress, Strain, Moment of Inertia, Conductivity, Electromagnetism.

What is vector and tensor?

vector are invariant physical properties that are independent of the frame of reference. Tensors. are physical quantities such as stress and strain that have magnitude and two or more directions.

How does a tensor transform?

Tensors are defined by their transformation properties under coordinate change. One distinguishes covariant and contravariant indexes. Number of indexes is tensor’s rank, scalar and vector quantities are particular case of tensors of rank zero and one. In general, the position of the indexes matters.

What is the defining characteristic of tensor quantities?

a tensor quantity is a physical quantity which has no specified direction but different values in different directions.

What is tensor Qty?

A tensor quantity is a physical quantity that is neither vector or scalar. Each point space in a tensor field has its own tensor. A stress on a material, such as a bridge building beam, is an example. The quantity of stress is a tensor quantity.

What is the difference between tensors and tensors?

While tensors are defined independent of any basis, the literature on physics often refers to them by their components in a basis related to a particular coordinate system. An elementary example of mapping, describable as a tensor, is the dot product, which maps two vectors to a scalar.

Can a tensor be represented as a multidimensional array?

A tensor may be represented as a (potentially multidimensional) array. Just as a vector in an n – dimensional space is represented by a one-dimensional array with n components with respect to a given basis, any tensor with respect to a basis is represented by a multidimensional array.

What do the numbers n and m mean in a tensor?

The numbers of, respectively, vectors: n (contravariant indices) and dual vectors: m (covariant indices) in the input and output of a tensor determine the type (or valence) of the tensor, a pair of natural numbers (n, m), which determine the precise form of the transformation law.

How do tensors respond to a change of basis?

Each type of tensor comes equipped with a transformation law that details how the components of the tensor respond to a change of basis. The components of a vector can respond in two distinct ways to a change of basis (see covariance and contravariance of vectors ), where the new basis vectors