Chiral Parametrization of QCD Vector Field in SU(3)

The chiral parametrization of gluons in SU(3) QCD is proposed extending an approach developed earlier for SU(2) case. A color chiral field is introduced, gluons are chirally rotated, and vector component of rotated gluons is defined on condition that no new color variables appeared with the chiral field. This condition associates such a vector component with SU(3)/U(2) coset plus an U(2) field. The topological action in SU(3) QCD is derived. It is expressed in terms of axial vector component of rotated gluons. The vector field in CP^2 sector is studied in new variables of chiral parametrization.Comment: 17 page

Color Bosonization, Chiral Parametrization of Gluonic Field and QCD Effective Action

We develop a color bosonization approach to treatment of QCD gauge field (''gluons'') at low energies in order to derive an effective color action of QCD taking into account the quark chiral anomaly in the case of SU(2) color.. We have found that there exists such a region in the chiral sector of color space, where a gauge field coincides with of chirally rotated vector field, while an induced axial vector field disappears. In this region, the unit color vector of chiral field plays a defining role, and a gauge field is parametrized in terms of chiral parameters, so that no additional degrees of freedom are introduced by the chiral field. A QCD gauge field decomposition in color bosonization is a sum of a chirally rotated gauge field and an induced axial-vector field expressed in terms of gluonic variables. An induced axial-vector field defines the chiral color anomaly and an effective color action of QCD. This action admits existence of a gauge invariant d=2 condensate of induced axial-vector field and mass.Comment: 13 pages, LaTe

Adaptive Fitness Landscape for Replicator Systems: To Maximize or not to Maximize

Sewall Wright's adaptive landscape metaphor penetrates a significant part of evolutionary thinking. Supplemented with Fisher's fundamental theorem of natural selection and Kimura's maximum principle, it provides a unifying and intuitive representation of the evolutionary process under the influence of natural selection as the hill climbing on the surface of mean population fitness. On the other hand, it is also well known that for many more or less realistic mathematical models this picture is a sever misrepresentation of what actually occurs. Therefore, we are faced with two questions. First, it is important to identify the cases in which adaptive landscape metaphor actually holds exactly in the models, that is, to identify the conditions under which system's dynamics coincides with the process of searching for a (local) fitness maximum. Second, even if the mean fitness is not maximized in the process of evolution, it is still important to understand the structure of the mean fitness manifold and see the implications of this structure on the system's dynamics. Using as a basic model the classical replicator equation, in this note we attempt to answer these two questions and illustrate our results with simple well studied systems.Comment: 13 pages, 4 figure