Hyperplanes of ##M_n(\mathbb{C})##

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In summary, the conversation discussed how to prove that any hyperplane of ##M_n(\mathbb{C})## contains at least one invertible matrix. The conversation first explored the possibility of using contradiction to prove this statement, but encountered difficulty in showing that a certain function was linear. Another approach was suggested, involving the use of linear forms and non-zero functionals, but it was not immediately clear how to apply this to the problem. Finally, it was suggested to use the fact that the set of invertible matrices ##GL_n(\mathbb{C})## is a dense subset of ##M_n(\mathbb{C})##, leading to the solution of choosing a
  • #1
geoffrey159
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Homework Statement


Show that any hyperplane of ##M_n(\mathbb{C})## contains at least an invertible matrix

Homework Equations


Let ##H## be an hyperplane of ##M_n(\mathbb{C})##.

The Attempt at a Solution



By contradiction, assume that for any matrix ##A\in H##, ##A## is not invertible.
Therefore 0 is an eigenvalue of A, and there exists a basis of ##M_{n,1}(\mathbb{C})## in which at least the first column of ##A## is 0.
This can be translated to : there is a surjection ##\phi## between the vector space ##U = \{ M\in M_n(\mathbb{C}) : \forall i = 1...n\ m_{i1} = 0 \} ## and hyperplane ##H##.

My problem to obtain a contradiction is that ##\phi## is not linear. If it was I would use the rank theorem and
## n^2 - 1 = \text{dim}(H) = \text{rk}(\phi) \le \text{dim}(U) = n^2 -n ##
which is a contradiction as soon as ##n\ge 2##.

How would you solve this ?
 
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  • #2
geoffrey159 said:
By contradiction, assume that for any matrix ##A\in H##, ##A## is not invertible.
Therefore 0 is an eigenvalue of A, and there exists a basis of ##M_{n,1}(\mathbb{C})## in which at least the first column of ##A## is 0
To me it is not immediately clear that there exists a basis that accomplishes this simultaneously for all ##A \in H##.
geoffrey159 said:
How would you solve this ?
I would perhaps start by noting that there exists a nonzero ##c \in \mathbb{C}^{n \times n}## such that ##H## is linearly isomorphic to
$$
\left\{a \in \mathbb{C}^{n \times n}\,:\,\sum_{j = 1}^n\sum_{i=1}^nc_{ij}\overline{a_{ij}} = 0 \right\}
$$
(Every hyperplane can be written as the kernel of some non-zero functional.) Since ##c## is non-zero, you could then solve for one of the entries of ##a## while keeping the freedom to choose the other ##n^2 - 1## entries at will.

Does this help?
 
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  • #3
We can write ##M_n(\mathbb{C}) = H \bigoplus \mathbb{C} M_0 ##, where ##H ## is the kernel of a linear form ##\phi : M_n(\mathbb{C}) \to \mathbb{C} ##, and ##\phi(M_0) \neq 0##

Assuming that ##H## doesn't contain any invertible matrix, the family ##(M_i)_{i\in I}## of all invertible matrices has the form : ##M_i = A_i + \lambda_i M_0##, with ##\lambda_i \neq 0 ##.

But that means that for all ##i\in I##, ##\phi(\lambda_i^{-1} M_i) = \phi(M_0) \neq 0 ##. This implies that for all ##i\in I##, ## \lambda_i^{-1} M_i \in \mathbb{C}M_0##

But the restriction of ##\phi## to ##\mathbb{C}M_0## is a bijection onto ##\mathbb{C}##. Since the ##(\phi(\lambda_i ^{-1} M_i))_{i\in I}## are all equal to ##\phi(M_0)##, that means by injectivity that all invertible matrices should be proportional 2 by 2. This is absurd.

Is it correct?
 
  • #4
geoffrey159 said:
But that means that for all ##i\in I##, ##\phi(\lambda_i^{-1} M_i) = \phi(M_0) \neq 0 ##. This implies that for all ##i\in I##, ## \lambda_i^{-1} M_i \in \mathbb{C}M_0##
It implies ## \lambda_i^{-1} M_i = \lambda_i^{-1} A_i + M_0 ∉ H##, i.e. its projection on ##\mathbb{C}M_0## equals ##1## and not that it is included in ##\mathbb{C}M_0##.
I think that you somehow need to use the fact that ##GL_n(ℂ) ⊂ M_n(ℂ)## is a dense subset, i.e. you probably need to wiggle a little bit on a point ##M## in ##H## to find an invertible point ##M+εM'## without leaving ##H##.

Edit: IMO induction on n seems to be the easiest way.
 
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  • #5
fresh_42 said:
It implies ## \lambda_i^{-1} M_i = \lambda_i^{-1} A_i + M_0 ∉ H##, i.e. its projection on ##\mathbb{C}M_0## equals ##1## and not that it is included in ##\mathbb{C}M_0##.

Doomed ! Once again :woot:
 
  • #6
Krylov said:
Since ##c## is non-zero, you could then solve for one of the entries of ##a## while keeping the freedom to choose the other ##n^2 - 1## entries at will.
(bolding mine)
Without loss of generality, you can assume ##a_{11}## is that one entry.
 
  • #7
I think I have it :

Let ##(E_i)_{i = 1...n^2-1}## be a basis of ##H##. Then the matrices ## M_\lambda = E_i + \lambda E_j ## are in ##H##.
But ##P(\lambda) = \det M_\lambda ## is a polynomial of ##\mathbb{C}_n[X]##.
Therefore it has at most ##n## zeros and there is a complex ##\lambda_0## for which ##P(\lambda_0)\neq 0##.
Meaning that ##M_{\lambda_0} \in H## is invertible.

Is it good now?
 
  • #8
geoffrey159 said:
I think I have it :

Let ##(E_i)_{i = 1...n^2-1}## be a basis of ##H##. Then the matrices ## M_\lambda = E_i + \lambda E_j ## are in ##H##.
But ##P(\lambda) = \det M_\lambda ## is a polynomial of ##\mathbb{C}_n[X]##.
Therefore it has at most ##n## zeros and there is a complex ##\lambda_0## for which ##P(\lambda_0)\neq 0##.
Meaning that ##M_{\lambda_0} \in H## is invertible.

Is it good now?
##E_1=\begin{pmatrix}
1 & 0\\
0 & 0
\end{pmatrix}
##, ##E_2=\begin{pmatrix}
0& 1\\
0 & 0
\end{pmatrix}
##
What is the polynomial ##P(\lambda)##?
 
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  • #9
Hmmm I get it, but really, I'm starting to dry up with this problem !
 
  • #10
geoffrey159 said:
Hmmm I get it, but really, I'm starting to dry up with this problem !
Look again at @Krylov 's tip and its implications.
 
  • #11
I did not understand what he said
 
  • #12
geoffrey159 said:
I did not understand what he said
Since H is a hyperplane, the n² matrix elements of matrices in H satisfy a linear equation. Solve this equation for one the elements (without loss of generality, say ##a_{11}##): that element is then a linear combination of all the others. To get a matrix in H, you then have n²-1 degrees of freedom, meaning you can chose n²-1 matrix elements freely. The last one will then be a linear combination of these freely chosen n²-1 elements.
 
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  • #13
I'm sorry, but this is above my head, I don't follow you.
If you know how to solve it I'll be glad to read your solution. But it has already taken me too much time and I need to move on.
Really sorry.

Thread closed, unless someone posts a solution
 
  • #14
Is ##A=\begin{pmatrix}
x & 0 & 0 & 0 & 1\\
0 & 0 & 0 & 1 & 0\\
0 & 0 & 1 & 0 & 0\\
0 & 1 & 0 & 0 & 0\\
1 & 0 & 0 & 0 & 0
\end{pmatrix}## invertible?
 
  • #15
geoffrey159 said:
I did not understand what he said
Don't be afraid to ask me next time. @Samy_A, thank you for clarifying.
geoffrey159 said:
I'm sorry, but this is above my head, I don't follow you.
If you know how to solve it I'll be glad to read your solution. But it has already taken me too much time and I need to move on.
Really sorry.

Thread closed, unless someone posts a solution
I hope you are willing to let it rest a bit (maybe for a few days) and then reconsider with a fresh mind. Sometimes it takes a while to solve an exercise, don't give up on it.
 

Related to Hyperplanes of ##M_n(\mathbb{C})##

1. What is a hyperplane in ##M_n(\mathbb{C})##?

A hyperplane in ##M_n(\mathbb{C})## is a subspace of dimension n-1. In other words, it is a flat subset of the space that contains n-dimensional matrices over the complex numbers. It can also be thought of as a generalization of a line or a plane in higher dimensions.

2. How are hyperplanes defined in ##M_n(\mathbb{C})##?

Hyperplanes in ##M_n(\mathbb{C})## are defined by a single equation of the form ax + by + cz + ... = d, where a, b, c, ... are complex numbers and x, y, z, ... are the entries of an n-dimensional matrix. This equation represents a linear relationship between the entries of the matrix, and the solutions to this equation form the hyperplane in ##M_n(\mathbb{C})##.

3. What is the significance of hyperplanes in ##M_n(\mathbb{C})##?

Hyperplanes in ##M_n(\mathbb{C})## are important in linear algebra and related fields because they help to understand the structure and properties of higher dimensional spaces. They also play a crucial role in solving systems of linear equations and in finding solutions to optimization problems.

4. Can hyperplanes intersect in ##M_n(\mathbb{C})##?

Yes, hyperplanes can intersect in ##M_n(\mathbb{C})##. In fact, the intersection of two hyperplanes in ##M_n(\mathbb{C})## is a subspace of dimension n-2. This can be visualized as a line or a plane in lower dimensions, and the same principles of linear algebra apply to these intersections in higher dimensions.

5. How are hyperplanes related to eigenvalues and eigenvectors in ##M_n(\mathbb{C})##?

In ##M_n(\mathbb{C})##, hyperplanes can be defined by the eigenvectors and eigenvalues of a matrix. Specifically, the eigenvectors corresponding to a certain eigenvalue span a hyperplane in ##M_n(\mathbb{C})##. This relationship is useful in understanding the geometric interpretation of eigenvalues and eigenvectors in higher dimensions.

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