Poincaré separation theorem

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In mathematics, the Poincaré separation theorem, also known as the Cauchy interlacing theorem,[1] gives some upper and lower bounds of eigenvalues of a real symmetric matrix B'AB that can be considered as the orthogonal projection of a larger real symmetric matrix A onto a linear subspace spanned by the columns of B. The theorem is named after Henri Poincaré. More specifically, let A be an n × n real symmetric matrix and B an n × r semi-orthogonal matrix such that B'B = Ir. Denote by [math]\displaystyle{ \lambda_i }[/math], i = 1, 2, ..., n and [math]\displaystyle{ \mu_i }[/math], i = 1, 2, ..., r the eigenvalues of A and B'AB, respectively (in descending order). We have

[math]\displaystyle{ \lambda_i \geq \mu_i \geq \lambda_{n-r+i}, }[/math]

Proof

An algebraic proof, based on the variational interpretation of eigenvalues, has been published in Magnus' Matrix Differential Calculus with Applications in Statistics and Econometrics.[2] From the geometric point of view, B'AB can be considered as the orthogonal projection of A onto the linear subspace spanned by B, so the above results follow immediately.[3]

References

  1. Min-max theorem
  2. Magnus, Jan R.; Neudecker, Heinz (1988). Matrix Differential Calculus with Applications in Statistics and Econometrics. John Wiley & Sons. pp. 209.. ISBN 0-471-91516-5. 
  3. Richard Bellman (1 December 1997). Introduction to Matrix Analysis: Second Edition. SIAM. pp. 118–. ISBN 978-0-89871-399-2. https://books.google.com/books?id=sP8J4oqwlLkC&pg=PA118.