We introduce the constraint equations for the Einstein-scalar field system on compact manifolds. Using the conformal method we reformulate these equations as a determined system of nonlinear partial differential equations. By introducing a new conformal invariant, which is sensitive to the presence of the initial data for the scalar field, we are able to divide the set of free conformal data into subclasses depending on the possible signs for the coefficients of terms in the resulting Einstein-scalar field Lichnerowicz equation. For most of these subclasses we determine whether or not a solution exists. In contrast to other well studied field theories, there are certain cases, depending on the mean curvature and the potential of the scalar field, for which we are unable to resolve the question of existence of a solution. We consider this system in such generality so as to include the vacuum constraint equations with an arbitrary cosmological constant, the Yamabe equation and even (all cases of) the prescribed scalar curvature problem as special cases.
This is joint work with Yvonne Choquet-Bruhat and Jim Isenberg.
We are going to consider the general problem whether the sum of
two closed operators on a Banach space is closed on the
intersection of their domains. We introduce absolute functional
calculus for sectorial operators, which is stronger than
$H^\infty$-calculus. Using this technique, we prove a theorem of
Dore-Venni type for sums of closed operators. There, we are able
to remove any assumptions such as R-boundedness or BIP on one of
the operators given that the second operator has absolute
calculus. Moreover, we show that any sectorial operator has
absolute calculus on the real interpolation spaces between its
domain and the space itself.
In many areas of applied sciences, engineering and technology there are three problems dealing with data and signals: (i) data compression; (ii) signal representations; and (iii) recovery of signals from partial or indirect information about the signals, often contaminated by noise. Major advances in these problems have been achieved in recent years where wavelets, multiresolution analysis, and kernel methods have played key roles. We consider problem (iii) and give an overview of specific contributions to inverse and ill-posed problems where reproducing kernel Hilbert spaces provide a natural setting.