If A is m by n and B is p by q, why is the size of equal to m p by n q?
Conditions
- is an matrix.
- is a matrix.
- is an element of .
Reasoning, step by step
- Identify the dimensions of () and ().
- Understand that is formed by replacing each element of with the block .
- Count the number of row blocks () and column blocks ().
- Multiply the number of row blocks by the height of each block () to get the total rows ().
- Multiply the number of column blocks by the width of each block () to get the total columns ().
Example
The video states: 'Let A be an matrix and matrix. Then the Kronecker product of A and B (denoted ) is a tensor product: it is an mp nq block matrix.'
Common misconceptions
- Assuming the size is instead of .
- Forgetting that each element of expands into a full matrix scaled by that element.
Watch the explanation
Connected concepts
Explore next
Related questions
The tensor product is unique up to isomorphism because if and are two tensor products of and , there exists a unique linear space isomorphism such that the diagram commutes, meaning and . This shows that any two realizations differ only by a unique isomorphism.
Conditions: and are linear spaces over the number field .; is a tensor product of and .; is another tensor product of and .
The isomorphism reflects the adjoint/duality relationship between Hom and tensor product. A linear map from to the space of linear maps from to corresponds to a bilinear map from to , which in turn corresponds to a linear map from the tensor product space to .
Conditions: are linear spaces over the number field .; denotes the vector space of all linear maps from to .
The notation denotes the entire tensor product space, which is uniquely determined up to isomorphism. In contrast, denotes a basic tensor element within that space, generated by applying the bilinear map to vectors and .
Conditions: and are linear spaces over the number field .; is in and is in .; is the bilinear map in the tensor product construction.
The universal property of the tensor product states that for linear spaces over a field , if there exists a bilinear map such that for any bilinear map (where is an arbitrary linear space over ), there exists a unique linear map making the diagram commute (i.e., ), then the pair is called a tensor product of and .
Conditions: are linear spaces over the field .; is a bilinear map from to .; is a bilinear map from to an arbitrary linear space over .; is the unique linear map from to .
The tensor product notation satisfies distributive laws and scalar mobility rules because it is constructed via a bilinear map . Bilinearity implies linearity in each variable separately, leading to , , and .
Conditions: belong to .; belong to .; are scalars in the field .
Answers are generated from source material and independently checked. Consult the original video or creator if something is unclear.