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A bilinear form $A$ on a vector space $V$ (over a field $k$ ) is called an alternating form if for all $v\in V$ , $A(v,v)=0$ .
Since for any $u,v\in V$ , $$0=A(u+v,u+v)=A(u,u)+A(u,v)+A(v,u)+A(v,v)=A(u,v)+A(v,u),$$ we see that $A(u,v)=-A(v,u)$ . So an alternating form is automatically a anti-symmetric, or skew symmetric form. The converse is true if the characteristic of $k$ is not $2$ .
Let $V$ be a two dimensional vector space over $k$ with an alternating form $A$ . Let $\lbrace e_1,e_2\rbrace$ be a basis for $V$ . The matrix associated with $A$ looks like
$ \begin{pmatrix} A(e_1,e_1) & A(e_1,e_2) \\ A(e_2,e_1) & A(e_2,e_2) \end{pmatrix}=r \begin{pmatrix} 0 & 1 \\ -1 & 0 \end{pmatrix}=rS, $
where $r=A(e_1,e_2)$ . The skew symmetric matrix $S$ has the property that its diagonal entries are all $0$ . $S$ is called the $2\times 2$ alternating or symplectic matrix.
$A$ is called non-singular or non-degenerate if there exist a vectors $u,v\in V$ such that $A(u,v)\neq 0$ . $u,v$ are necessarily non-zero. Note that the associated matrix $rS$ is non-singular iff $r\neq 0$ iff $A$ is non-singular.
In the two dimensional vector space case above, if $A$ is non-singular, we can re-scale the basis elements so that $r=1$ . This means that the matrix associated with $A$ is the alternating matrix. A two-dimensional vector space which carries a non-singular alternating form is sometimes called an alternating or symplectic hyperbolic plane. Some authors also call it simply a hyperbolic plane. But here on PlanetMath, we will reserve the shorter name for its cousin in the category of quadratic spaces. Let's denote an alternating hyperbolic plane by $\mathcal{A}$ .
Remark. In general, it can be shown that if $V$ is an $n$ -dimensional vector space equipped with a non-singular alternating form $A$ , then $V$ can be written as an orthogonal direct sum of the alternating hyperbolic planes $\mathcal{A}$ . In other words, the associated matrix for $A$ has the block form
$ \begin{pmatrix} S & \boldsymbol{0} & \cdots & \boldsymbol{0} \\ \boldsymbol{0} & S & \cdots & \boldsymbol{0} \\ \vdots & \vdots & \ddots & \vdots \\ \boldsymbol{0} & \boldsymbol{0} & \cdots & S \\ \end{pmatrix},\mbox{ where }\boldsymbol{0}= \begin{pmatrix} 0 & 0 \\ 0 & 0 \end{pmatrix}. $
Furthermore, $n$ is even. $V$ is called a symplectic vector space.
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