In mathematics, a dyadic product of two vectors is a third vector product next to dot product and cross product. The dyadic product is a square matrix that represents a tensor with respect to the same system of axes as to which the components of the vectors are defined that constitute the dyadic product. Thus, if
![{\displaystyle \mathbf {a} ={\begin{pmatrix}a_{x}\\a_{y}\\a_{z}\end{pmatrix}}\quad {\hbox{and}}\quad \mathbf {b} ={\begin{pmatrix}b_{x}\\b_{y}\\b_{z}\end{pmatrix}},}](https://wikimedia.org/api/rest_v1/media/math/render/svg/a05476b0bbdd85064e365c587e11f30787bfc4d5)
then the dyadic product is
![{\displaystyle \mathbf {a} \otimes \mathbf {b} \;{\stackrel {\mathrm {def} }{=}}\;{\begin{pmatrix}a_{x}b_{x}&a_{x}b_{y}&a_{x}b_{z}\\a_{y}b_{x}&a_{y}b_{y}&a_{y}b_{z}\\a_{z}b_{x}&a_{z}b_{y}&a_{z}b_{z}\\\end{pmatrix}}.}](https://wikimedia.org/api/rest_v1/media/math/render/svg/9082d973a1170df6aa26faed1fecc94ed38c72fa)
Sometimes it is useful to write a dyadic product as matrix product of two matrices, the first being a column matrix and the second a row matrix,
![{\displaystyle \mathbf {a} \otimes \mathbf {b} ={\begin{pmatrix}a_{x}\\a_{y}\\a_{z}\end{pmatrix}}\left(b_{x},\;b_{y},\;b_{z}\right)}](https://wikimedia.org/api/rest_v1/media/math/render/svg/8cf0a5fb91d5fa3986b16ebce256b753ee1d2d43)
Example
![{\displaystyle \mathbf {a} ={\begin{pmatrix}-1\\3\\2\end{pmatrix}}\quad {\hbox{and}}\quad \mathbf {b} ={\begin{pmatrix}5\\-3\\4\end{pmatrix}}\Longrightarrow \mathbf {a} \otimes \mathbf {b} ={\begin{pmatrix}-5&3&-4\\15&-9&12\\10&-6&8\\\end{pmatrix}}}](https://wikimedia.org/api/rest_v1/media/math/render/svg/b9d5ac68e884739ea10b55201fae007c2408c359)
Use
An important use of a dyadic product is the reformulation of a vector expression as a matrix-vector expression, for instance,
![{\displaystyle \mathbf {a} \,(\mathbf {b} \cdot \mathbf {c} )=(\mathbf {a} \otimes \mathbf {b} )\,\mathbf {c} .}](https://wikimedia.org/api/rest_v1/media/math/render/svg/1d495d350c35cb1cd175de68056eac2771748551)
Indeed, take the ith component,
![{\displaystyle a_{i}(\mathbf {b} \cdot \mathbf {c} )=a_{i}\sum _{j=x,y,z}b_{j}c_{j}=\sum _{j=x,y,z}a_{i}b_{j}c_{j}=\sum _{j=x,y,z}(\mathbf {a} \otimes \mathbf {b} )_{ij}\,c_{j}\quad {\hbox{for}}\quad i=x,y,z.}](https://wikimedia.org/api/rest_v1/media/math/render/svg/08c7809896e2e9963ebaa5ce221776d8c40b376f)
Or, equivalently, by use of the associative law valid for matrix multiplication,
![{\displaystyle (\mathbf {a} \otimes \mathbf {b} )\,\mathbf {c} ={\begin{pmatrix}a_{x}\\a_{y}\\a_{z}\end{pmatrix}}\left(b_{x},\;b_{y},\;b_{z}\right){\begin{pmatrix}c_{x}\\c_{y}\\c_{z}\end{pmatrix}}=\mathbf {a} (\mathbf {b} \cdot \mathbf {c} )}](https://wikimedia.org/api/rest_v1/media/math/render/svg/7b4d24ce873fa315db685015f5e2d854950871f5)
Multiplication
The matrix multiplication of two dyadic products is given by,
![{\displaystyle (\mathbf {a} \otimes \mathbf {b} )\,(\mathbf {c} \otimes \mathbf {d} )={\begin{pmatrix}a_{x}\\a_{y}\\a_{z}\end{pmatrix}}\left(b_{x},\;b_{y},\;b_{z}\right){\begin{pmatrix}c_{x}\\c_{y}\\c_{z}\end{pmatrix}}\left(d_{x},\;d_{y},\;d_{z}\right)=(\mathbf {a} \otimes \mathbf {d} )\,(\mathbf {b} \cdot \mathbf {c} ).}](https://wikimedia.org/api/rest_v1/media/math/render/svg/e9c5a36310725f27f3e089c02bebbd79be3e3342)
Generalization
In more general terms, a dyadic product is the representation of a simple element in (binary) tensor product space with respect to bases carrying the constituting spaces. Let U and V be linear spaces and U ⊗ V be their tensor product space
![{\displaystyle u\in U,\quad v\in V\;\Longrightarrow \;u\otimes v\in U\otimes V.}](https://wikimedia.org/api/rest_v1/media/math/render/svg/54281117fbe297e595c52b27e4db731cb60a7dad)
If {ai} and {bj} are bases of U and V, respectively, then
![{\displaystyle u=\sum _{i=1}^{m}a_{i}u_{i}=(a_{1},\;a_{2},\;\ldots ,\;a_{m}){\begin{pmatrix}u_{1}\\u_{2}\\\vdots \\u_{m}\end{pmatrix}}=(a_{1},\;a_{2},\;\ldots ,\;a_{m})\mathbf {u} ,}](https://wikimedia.org/api/rest_v1/media/math/render/svg/5beb2734b66201e4afdd6eed5a0ed825bdc889c0)
![{\displaystyle v=\sum _{j=1}^{n}b_{j}v_{j}=(b_{1},\;b_{2},\;\ldots ,\;b_{n}){\begin{pmatrix}v_{1}\\v_{2}\\\vdots \\v_{n}\end{pmatrix}}=(b_{1},\;b_{2},\;\ldots ,\;b_{n})\mathbf {v} }](https://wikimedia.org/api/rest_v1/media/math/render/svg/8b1ee9be9ccdc587f45d44b2fdbc11a751455b2f)
and
![{\displaystyle u\otimes v=\sum _{i=1}^{m}\sum _{j=1}^{n}(a_{i}b_{j})(u_{i}v_{j})=\sum _{i=1}^{m}\sum _{j=1}^{n}(a_{i}b_{j})(\mathbf {u} \otimes \mathbf {v} )_{ij}}](https://wikimedia.org/api/rest_v1/media/math/render/svg/9a5d51c0c3149fac4256efe463b69634b7953dcb)
The dyadic product u ⊗ v is an m × n matrix that represents the simple tensor u ⊗ v in U ⊗ V.