Proving the Symplectic Positive Definite Matrix Theorem

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SUMMARY

The discussion centers on proving the Symplectic Positive Definite Matrix Theorem, specifically regarding the properties of symplectic vector spaces and their associated Lagrangian subspaces. The participants reference McDuff-Salamon's "Introduction to Symplectic Topology" and discuss the eigenspace decomposition of matrices, particularly focusing on the relationship between symplectic forms and eigenvectors. The conversation highlights the necessity of establishing symplectomorphisms between symplectic vector spaces of equal finite dimensions, emphasizing that a basis of a Lagrangian subspace can be extended to a symplectic basis of the entire space.

PREREQUISITES
  • Understanding of symplectic geometry and symplectic vector spaces
  • Familiarity with Lagrangian subspaces and their properties
  • Knowledge of eigenspace decomposition and matrix diagonalization
  • Proficiency in linear algebra, particularly with bilinear forms
NEXT STEPS
  • Study McDuff-Salamon's "Introduction to Symplectic Topology" for foundational concepts
  • Learn about symplectomorphisms and their applications in symplectic geometry
  • Explore the properties of Lagrangian subspaces in greater detail
  • Investigate the relationship between eigenvalues and symplectic forms in matrices
USEFUL FOR

Mathematicians, particularly those specializing in symplectic geometry, linear algebra researchers, and graduate students studying advanced topics in topology and matrix theory.

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You can self-administer yourself hints by looking at p.45 of McDuff-Salamon's intro to sympolectic topology.
 
I appreciate your help, but it doesn't help.
 
I think I can see how to prove that this is valid for $\alpha =n$ where n is an integers. Because the eigenspace decomposition of $\mathbb{R}^{2n}$ in $P$ is the same as its decomposition by $P^{-1}$.

To extend this to rationals and then to real, is just taking common factors and reducing the rational case to integers. And for the real exponent to take the limit of rational sequence.

Am I right in this hand waving method? :-D
 
Provided you get the details right, I don't see why it wouldn't work.

How is ##A^\alpha## defined? Do you just write ##A=Q^T \text{diag}\{\lambda_1, \ldots, \lambda_{2n}\} Q## (possible because A is symmetric) and then let ##A^\alpha=Q^T \text{diag}\{\lambda_1^\alpha, \ldots, \lambda_{2n}^\alpha\} Q## (not problematic because each ##\lambda_i## is positive). It seems pretty clear then that ##A^\alpha## will preserve whatever symplectic form ##A## preserves (it's enough to check at eigenvectors, and for eigenvectors this isn't so bad).
 
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Yes, I thought along these lines too.

Thanks.
 
I've got another question.

I want to show that for any two symplectic vector spaces of equal finite dimensions, W_i, and L_i are lagrange subspaces of W_i (i=1,2), we have a symplectomorphism A:W_1\rightarrow W_2 s.t

A(L_1)=L_2.

I was thinking along the next lines, the dimensions of L_1 and L_2 are the same cause:
dim L_1+ dim L^{\omega}_1 = dim L_1 + dim L_1 =dim V_1=dim V_2= dim L_2+dim L^{\omega}_2 = 2dim L_2 so we must have an isomorphism between L_1 and L_2, I don't see how to extend it to W_1 and W_2.
 
A linear map btw symplectic vector spaces is a symplectomorphism iff it sends a symplectic basis to a symplectic basis. (A symplectic basis for a symplectic bilinear map B is a basis (v_i) s.t. B(v_i,v_j) = the standard symplectic matrix -J.)

Observe then, that it suffices for you to prove that a basis of a lagrangian subspace L can always be completed to a symplectic basis of the whole space.

Note that lagrangian spaces are always of dimension half the dimension of the ambient space. So of course if W_1, W_2 are of equal dimension, say 2n, then L_1, L_2 are of equal dimension equal to n.
 
OK, thanks. I see it's proved in the textbook you mentioned.

Cheers!
:-)
 

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