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

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Homework Help Overview

The discussion revolves around the properties of hyperplanes in the space of complex matrices, specifically ##M_n(\mathbb{C})##. The original poster attempts to show that any hyperplane contains at least one invertible matrix, using contradiction and properties of eigenvalues.

Discussion Character

  • Exploratory, Assumption checking, Conceptual clarification

Approaches and Questions Raised

  • Participants explore the implications of assuming all matrices in a hyperplane are non-invertible, questioning the existence of a common basis for such matrices. They discuss the structure of hyperplanes and the relationship between linear forms and invertibility.

Discussion Status

Several participants have offered insights and alternative approaches, including the use of polynomial properties and the dimensionality of the hyperplane. There is ongoing exploration of different methods to demonstrate the presence of an invertible matrix, with no explicit consensus reached.

Contextual Notes

Some participants express confusion regarding the mathematical concepts involved, indicating varying levels of understanding. The discussion is marked by attempts to clarify definitions and assumptions related to hyperplanes and matrix properties.

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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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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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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?
 
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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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:
 
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.
 
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?
 
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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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.
 

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