Searcharxiv⌕ Search

arXiv subjects

Sandoval-Romero María de los Ángeles

Publications and source records attributed to Sandoval-Romero María de los Ángeles.

2 recordsLinked to original sources

Geometric Integration by Parts and Sobolev Spaces on Vector Bundles: A Unified Global Approach

This article develops a unified and intrinsic framework for the theory of Sobolev spaces on vector bundles over Riemannian manifolds. The analytical core of our approach is an explicit higher-order geometric integration by parts formula, which characterizes the formal adjoint of the covariant derivative as a global differential operator. This identity is established on arbitrary Riemannian manifolds with boundary, without assuming completeness or compactness. While first-order integration by parts identities are classical, explicit higher-order formulas with precise boundary terms are rarely stated in the literature. As applications of this framework, we recover the classical Meyers--Serrin theorem on arbitrary manifolds and, in the compact case, the Sobolev embedding and Rellich--Kondrachov compactness theorems, providing direct and self-contained proofs. At the end of this work we also stablish a Green Formula and we use it to stablish norm equivalence in Sobolev Spaces on vector bundles with closed manifold as base space and the Bochner laplacian operator. As a corollary we show that, in case of trivial vector bundles this equivalence reduces to a well known (but non proved rigorously in literature) result for closed manifolds and the Laplace-Beltrami operator. By emphasizing intrinsic global arguments and sharp local-to-global norm equivalence estimates, rather than ad hoc coordinate patching, this work offers a transparent and accessible foundation for the study of Sobolev spaces on vector bundles, suitable for researchers in global analysis, differential geometry, and partial differential equations.

math.AP↗

From Riesz to Kakutani: Representation Theorems and the Analytical Foundations of Probablility

The analytical foundations of modern probability trace back to a sequence of representation theorems that reshaped functional analysis in the twentieth century. From Fréchet identification of linear functionals with vectors in Hilbert spaces to Kakutani characterization of measures on spaces of continuous functions, each theorem reveals how linearity, duality, and measure intertwine. Following this historical and conceptual path, from Fréchet Riesz to Riesz Stieltjes, from Lp duality to Riesz Markov Kakutani, we show that expectation, distribution, conditional expectation, and the Wiener measure are analytic manifestations of a single principle of representation. Viewed through this lens, probability theory appears not merely as an extension of measure theory, but as the geometric realization of functional analysis itself: every probabilistic notion embodies an existence-and-uniqueness principle in a space of functions.

math.FA↗