Bilinear Form Non-Degenerate on a Subspace.

In summary, we have a finite dimensional vector space $V$ over a field $F$ with a symmetric bilinear form $f:V\times V\to F$. We also have a subspace $W$ of $V$ where $f$ is non-degenerate. Our goal is to prove that $V$ can be decomposed into the direct sum of $W$ and its orthogonal complement $W^\perp$, where $W^\perp$ is defined as the set of all vectors in $V$ that are orthogonal to every vector in $W$ under the given bilinear form.To prove this, we consider the map $L_f:V\to V^*$ defined as $(L_fu)v=f
  • #1
caffeinemachine
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I am trying to prove the following standard result:Let $V$ be a finite dimensional vector space over a field $F$ and $f:V\times V\to F$ be a symmetric bilinear form on $V$. Let $W$ be a subspace of $V$ such that $f$ is non-degenerate on $W$.
Then
$$V=W\oplus W^\perp$$(Here $W^\perp=\{v\in V:f(w,v)=0\text{ for all } w\in W\}$).Here is what I tried:The bilinear form gives us a map $L_f:V\to V^*$ defined as
$$(L_fu)v=f(u,v),\quad\forall u,v\in V$$
Let $W^0$ denote the annihilator of $W$.
We show that
$$v\in W^\perp \text{ if and only if } L_fv\in W^0$$Let $v\in W^\perp$.
Then $(L_fv)w=f(v,w)=0$ for all $w\in W$. Therefore $L_fv\in W^0$.
Now say $L_fv\in W^0$ for some $v\in V$.
Then $(L_fv)w=0$ for all $w\in W$, giving $f(v,w)=0$ for all $w\in W$.
Therefore $v\in W^\perp$.Also, it is clear that $W\cap W^\perp=0$.Since $\dim W^0=\dim V-\dim W$, we would be done if we could show that $\dim W^\perp \geq \dim W^0$.From the observation done above, it is natural to consider the map $T:W^\perp\to W^0$ defined as $Tv=L_fv$ for all $v\in W^\perp$.
We just need to show that $T$ is surjective.
But here I am stuck.Can somebody help.Thanks.
 
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  • #2
We need not to use the concept of dual space. As $V$ is finite dimensional, if $B_W=\{e_1,\ldots,e_r\}$ is a basis of $W$ and $B=\{e_1,\ldots,e_r,\ldots,e_n\}$ a basis of $V$ then, $f(x,y)=X^TAY$ with $A=[a_{ij}]$ symmetric, $\text{rank}(A)=n$ and $X,$ $Y$ coordinates of $x,$ $y$ with respect to $B.$ Then, $$x\in W^{\perp}\Leftrightarrow \left \{ \begin{matrix} f(x.e_1)=0\\\ldots\\f(x.e_r)=0\end{matrix}\right.\Leftrightarrow \left \{ \begin{matrix} a_{11}x _1+\ldots +a_{n1}x_n=0\\\ldots\\a_{1r}x_1+\ldots +a_{nr}x_n=0\end{matrix}\right.\Leftrightarrow MX=0.$$ But $\text{rank}(M)=r$ because $A$ has maximum rank so, $\dim W^{\perp}=n-r.$ This implies $\dim W+\dim W^{\perp}=\dim V.$ As $W\cap W^{\perp}=\{0\},$ we conclude $V=W\oplus W^{\perp}.$
 
  • #3
Fernando Revilla said:
We need not to use the concept of dual space. As $V$ is finite dimensional, if $B_W=\{e_1,\ldots,e_r\}$ is a basis of $W$ and $B=\{e_1,\ldots,e_r,\ldots,e_n\}$ a basis of $V$ then, $f(x,y)=X^TAY$ with $A=[a_{ij}]$ symmetric, $\text{rank}(A)=n$ and $X,$ $Y$ coordinates of $x,$ $y$ with respect to $B.$ Then, $$x\in W^{\perp}\Leftrightarrow \left \{ \begin{matrix} f(x.e_1)=0\\\ldots\\f(x.e_r)=0\end{matrix}\right.\Leftrightarrow \left \{ \begin{matrix} a_{11}x _1+\ldots +a_{n1}x_n=0\\\ldots\\a_{1r}x_1+\ldots +a_{nr}x_n=0\end{matrix}\right.\Leftrightarrow MX=0.$$ But $\text{rank}(M)=r$ because $A$ has maximum rank so, $\dim W^{\perp}=n-r.$ This implies $\dim W+\dim W^{\perp}=\dim V.$ As $W\cap W^{\perp}=\{0\},$ we conclude $V=W\oplus W^{\perp}.$

Here we cannot assume that $\text{rank}(A)=n$ because $f$ is not necessarily degenerate on the whole of $V$. The hypothesis merely demands the non-degeneracy of $f$ on $W$.

Also, what does $M$ denote in your answer?
 
  • #4
caffeinemachine said:
Here we cannot assume that $\text{rank}(A)=n$ because $f$ is not necessarily degenerate on the whole of $V$.

Sorry, I didn't notice it, but it does not matter, if $f_{W}:W\times W\to K$ is not degenerate then, the matrix of $f_W$ with respect to $B_W=\{e_1,\ldots,e_r\}$ is $$A_W=\begin{bmatrix} a_{11} & a_{12} & \ldots & a_{1r}\\ a_{21} &a_{22} & \ldots & a_{2r} \\ \vdots&&&\vdots \\ a_{r1} & a_{r2} &\ldots & a_{rr}\end{bmatrix}\text{ with }\det( A_W)\neq 0.\qquad (*)$$

Also, what does $M$ denote in your answer?

Denotes the matrix of the cooresponding system, that is $M=\begin{bmatrix} a_{11} & a_{21} & \ldots & a_{n1}\\ \vdots&&&\vdots \\ a_{1r} & a_{2r} &\ldots & a_{nr}\end{bmatrix},$ and $\text{rank}(M)=r$ by $(*).$
 
  • #5
Fernando Revilla said:
Sorry, I didn't notice it, but it does not matter, if $f_{W}:W\times W\to K$ is not degenerate then, the matrix of $f_W$ with respect to $B_W=\{e_1,\ldots,e_r\}$ is $$A_W=\begin{bmatrix} a_{11} & a_{12} & \ldots & a_{1r}\\ a_{21} &a_{22} & \ldots & a_{2r} \\ \vdots&&&\vdots \\ a_{r1} & a_{r2} &\ldots & a_{rr}\end{bmatrix}\text{ with }\det( A_W)\neq 0.\qquad (*)$$
Denotes the matrix of the cooresponding system, that is $M=\begin{bmatrix} a_{11} & a_{21} & \ldots & a_{n1}\\ \vdots&&&\vdots \\ a_{1r} & a_{2r} &\ldots & a_{nr}\end{bmatrix},$ and $\text{rank}(M)=r$ by $(*).$
This solves the problem I was originally trying to solve. Thanks.

But can you say for sure that $T$, defined in the last paragraph of my first post, is necessarily surjective?
 
  • #6
caffeinemachine said:
But can you say for sure that $T$, defined in the last paragraph of my first post, is necessarily surjective?

Yes, $T: W^{\perp}\to W^{0}$ is a linear map, injective and $\dim W^{\perp}=\dim W^{0}$ so, $T$ is surjective.
 
Last edited:

1. What is a bilinear form?

A bilinear form is a mathematical function that takes in two vectors and outputs a scalar value. It is linear in each of its arguments, meaning that it satisfies the properties of additivity and homogeneity.

2. What does it mean for a bilinear form to be non-degenerate?

A bilinear form is non-degenerate if it is never equal to zero for all non-zero inputs. In other words, there are no vectors that can be multiplied by another vector to result in a zero scalar value.

3. How is a bilinear form defined on a subspace?

A bilinear form is defined on a subspace by restricting its inputs to only vectors within the subspace. This means that the bilinear form will only take in vectors that are elements of the subspace and output a scalar value based on those vectors.

4. What is the significance of a bilinear form being non-degenerate on a subspace?

If a bilinear form is non-degenerate on a subspace, it means that every non-zero vector in the subspace has a unique "dual" vector that can be multiplied with it to produce a non-zero scalar value. This can be useful in various mathematical applications, such as optimization problems and matrix analysis.

5. How can you determine if a bilinear form is non-degenerate on a subspace?

To determine if a bilinear form is non-degenerate on a subspace, you can check if its matrix representation is non-singular. If the determinant of the matrix is non-zero, then the bilinear form is non-degenerate. Additionally, you can also check if the null space of the matrix is empty, as this would indicate that there are no vectors that can produce a zero scalar value when multiplied with another vector in the subspace.

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