Reconstruction of Baxter Q-operator from Sklyanin SOV for cyclic representations of integrable quantum models

Physics – High Energy Physics – High Energy Physics - Theory

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

25 pages, Version published on Nucl.Phys. B; no formula changed, some references added together with Appendix B.

Scientific paper

10.1016/j.nuclphysb.2010.03.009

In [1], the spectrum (eigenvalues and eigenstates) of a lattice regularizations of the Sine-Gordon model has been completely characterized in terms of polynomial solutions with certain properties of the Baxter equation. This characterization for cyclic representations has been derived by the use of the Separation of Variables (SOV) method of Sklyanin and by the direct construction of the Baxter Q-operator family. Here, we reconstruct the Baxter Q-operator and the same characterization of the spectrum by only using the SOV method. This analysis allows us to deduce the main features required for the extension to cyclic representations of other integrable quantum models of this kind of spectrum characterization.

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

Reconstruction of Baxter Q-operator from Sklyanin SOV for cyclic representations of integrable quantum models 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 Reconstruction of Baxter Q-operator from Sklyanin SOV for cyclic representations of integrable quantum models, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Reconstruction of Baxter Q-operator from Sklyanin SOV for cyclic representations of integrable quantum models will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-103815

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