Local spectral theory for normal operators in Krein spaces

Mathematics – Spectral Theory

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

22 pages

Scientific paper

Sign type spectra are an important tool in the investigation of spectral properties of selfadjoint operators in Krein spaces. It is our aim to show that also sign type spectra for normal operators in Krein spaces provide insight in the spectral nature of the operator: If the real part and the imaginary part of a normal operator in a Krein space have real spectra only and if the growth of the resolvent of the imaginary part (close to the real axis) is of finite order, then the normal operator possesses a local spectral function defined for Borel subsets of the spectrum which belong to positive (negative) type spectrum. Moreover, the restriction of the normal operator to the spectral subspace corresponding to such a Borel subset is a normal operator in some Hilbert space. In particular, if the spectrum consists entirely out of positive and negative type spectrum, then the operator is similar to a normal operator in some Hilbert space. We use this result to show the existence of operator roots of a class of quadratic operator polynomials with normal coefficients.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Local spectral theory for normal operators in Krein spaces does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Local spectral theory for normal operators in Krein spaces, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Local spectral theory for normal operators in Krein spaces will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-184707

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.