**Tensors:****Tensors**are**ordered or organised collection of items**. Each item in the collection is known as an**Element**. The elements are organised in**zero or more Dimensions**.**Tensors**are used to represent**physical quantities**or**transformations to physical quantities**.**Dimension:**When we have more than one element, they need to be ordered or organized in a certain manner to determine their position/location/ priority etc. A**Dimension**is a**set of indexed locations**that**hold elements of a tensor**.

Adding the**first dimension**to a Tensor involves adding at least 2 or more indexed locations.

Adding the**second dimension**to a Tensor involves adding a integer multiple (> than 0) of as many index locations as there are present in the**first dimension**.

Adding the**third dimension**to a Tensor involves adding a multiple (> than 0) of as many index locations as there are present in the product of number of indices in**first dimension**and**second dimension**.

Adding the**fourth dimension**to a Tensor involves adding a multiple (> than 0) of as many index locations as there are present in the product of number of indices in**first dimension**,**second dimension**and**third dimension**.

Adding the**N**to a Tensor involves adding a multiple (> than 0) of as many index locations as there are present in the product of number of indices in^{th}dimension**N-1,N-2,N-3,... and first dimensions**.

The number of locations/elements**K**in a tensor can be calculated as follows:

**K**=**(No. of indices per dimension)**(If all dimensions are have same no. of indices)^{No. of Dimensions}

**K**=**N**(If all dimensions are have different no. of indices)_{1}x N_{2}x N_{3}x ... N_{n}

Where N_{1}x N_{2}x N_{3}x ... N_{n}are the no of indices present in dimensions 1,2,3,...,n respectively.

The no. of Dimensions present in a Tensor is also known as**Rank of the Tensor**.**Scalar:**A Tensor with a**single element**is known as a**Scalar**. A single element or**Scalar**does not need any ordering or organisation. Hence**Scalars**are also known as a**Tensors with Rank 0 (Zero Dimension)**.**Vector:**A Tensor having**2 or more elements**organised in a single row or a single column is known as a**Vector**. Hence**Vectors**are also known as a**Tensors with Rank 1 (1 Dimension)****Matrix:**A Tensor having**elements organised across a table of rows and columns**is known as a**Matrix**. Hence**Matrices**are also known as a**Tensors with Rank 2 (2 Dimensions)****Cube/Cuboid:**A Tensor having**elements organised accross more than 1 table of rows and columns**is known as a**Cube/Cuboid**. Hence**Cubes/Cuboids**are also known as a**Tensors with Rank 3 (3 Dimensions)**