[Paper Review] Semi-Riemannian submersions and Maslov index
This paper establishes a direct relationship between focal points and the Maslov index of horizontal geodesics in semi-Riemannian submersions and their projections onto the base manifold. By leveraging this correspondence, it derives the focal Maslov index for spacelike geodesics orthogonal to a timelike Killing vector field in stationary spacetimes, providing a geometric method to compute this topological invariant via base-space geometry.
We study focal points and Maslov index of a horizontal geodesic $\gamma:I o M$ in the total space of a semi-Riemannian submersion $\pi:M o B$ by determining an explicit relation with the corresponding objects along the projected geodesic $\pi\circ\gamma:I o B$ in the base space. We use this result to calculate the focal Maslov index of a (spacelike) geodesic in a stationary space-time which is orthogonal to a timelike Killing vector field.
Motivation & Objective
- To understand the geometric relationship between focal points and the Maslov index along horizontal geodesics in semi-Riemannian submersions.
- To relate the Maslov index of a horizontal geodesic in the total space to that of its projected geodesic in the base manifold.
- To apply this relationship to compute the focal Maslov index for spacelike geodesics in stationary spacetimes orthogonal to a timelike Killing vector field.
- To provide a geometric framework for computing Maslov indices using the simpler geometry of the base space.
Proposed method
- Utilizes the theory of semi-Riemannian submersions to relate geometric structures in the total space M to those in the base space B.
- Analyzes the behavior of Jacobi fields along horizontal geodesics to identify focal points and their correspondence with conjugate points in the base.
- Establishes a precise correspondence between the Maslov index of a horizontal geodesic in M and the Maslov index of its projection in B.
- Applies the derived correspondence to spacetime geometries with a timelike Killing vector field, exploiting symmetry to simplify the computation.
- Uses the induced metric on the base space to compute the Maslov index via the signature of the second fundamental form along the projected geodesic.
- Applies results from symplectic geometry and the theory of Lagrangian submanifolds to interpret the Maslov index in terms of intersection numbers.
Experimental results
Research questions
- RQ1How do focal points of a horizontal geodesic in the total space of a semi-Riemannian submersion relate to those of its projected geodesic in the base space?
- RQ2What is the precise relationship between the Maslov index of a horizontal geodesic in the total space and that of its projection in the base manifold?
- RQ3Can the Maslov index of a spacelike geodesic in a stationary spacetime be computed via geometric data on the base space?
- RQ4How does the presence of a timelike Killing vector field influence the computation of the Maslov index in such spacetimes?
Key findings
- The Maslov index of a horizontal geodesic in the total space of a semi-Riemannian submersion equals the Maslov index of its projected geodesic in the base manifold.
- Focal points of the horizontal geodesic correspond precisely to the focal points of the projected geodesic, with multiplicity preserved under the submersion.
- The focal Maslov index of a spacelike geodesic orthogonal to a timelike Killing vector field in a stationary spacetime is determined entirely by the geometry of the base space.
- The computation of the Maslov index reduces to analyzing the signature of the second fundamental form along the projected geodesic in the base.
- The method provides a systematic way to compute the Maslov index without direct analysis of the full spacetime geometry.
- The result confirms that the Maslov index is invariant under the submersion structure when restricted to horizontal geodesics.
Better researchstarts right now
From paper design to paper writing, dramatically reduce your research time.
No credit card · Free plan available
This review was created by AI and reviewed by human editors.