Study shows solutions to certain equations form smooth manifolds.
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Non-linear Hopf manifolds can be embedded into linear ones and admit LCK metrics.
Paper solves complex equations on noncompact manifolds.
Paper establishes estimates for solutions on compact manifolds.
Solves Dirichlet problem for elliptic equations on Hermitian manifolds.
We show how the tangent functor extends from ordinary smooth maps to "microformal morphisms" (also called "thick morphisms") of supermanifolds. Microformal morphisms generalize ordinary maps and correspond to formal canonical relations between the cotangent bundles specified by generating functions depending on positio…
Paper generalizes sub-slope definition and solves complex equations on compact manifolds.
Develops an efficient method for real-time data analysis and visualization.
Study shows long-term solutions for complex equations on curved spaces.
The paper establishes boundary estimates for solutions to elliptic equations on Hermitian manifolds.
Sharp L∞ estimates for fully non-linear elliptic equations on compact complex manifolds.
Extends parabolic study to flat hyperkähler manifolds.
New complex-valued maps found on complex geometries.
We derive a priori estimates for solutions of a general class of fully non-linear equations on compact Hermitian manifolds. Our method is based on ideas that have been used for different specific equations, such as the complex Monge-Ampère, Hessian and inverse Hessian equations. As an application we solve a class of He…
Finite time for subsolutions on Riemannian manifolds proved.
Develops a Riemannian archetypal analysis for interpretable non-linear data.
Matrix completion works well for smooth non-linear structures, even without low-rank assumptions.
Derives estimates for geometric elliptic equations on complex manifolds.
This work develops methods to analyze data on curved spaces using deep learning.
Diffusion Maps improves on Functional PCA for non-linear functional data.
In the neighborhood of a regular point, generalized Kahler geometry admits a description in terms of a single real function, the generalized Kahler potential. We study the local conditions for a generalized Kahler manifold to be a generalized Calabi-Yau manifold and we derive a non-linear PDE that the generalized Kahle…
Using the Perron method, we prove the existence of hypersurfaces of prescribed special Lagrangian curvature with prescribed boundary inside complete Riemannian manifolds of non-positive curvature.
In this article, we study a generalisation of the Seiberg-Witten equations, replacing the spinor representation with a hyperKahler manifold equipped with certain symmetries. Central to this is the construction of a (non-linear) Dirac operator acting on the sections of the non-linear fibre-bundle. For hyperKahler manifo…
Non linear sigma models are quantum field theories describing, in the large deviations sense, random fluctuations of harmonic maps between a Riemann surface and a Riemannian manifold. Via their formal renormalization group analysis, they provide a framework for possible generalizations of the Hamilton-Perelman Ricci fl…
We survey recent results on inverse problems for geodesic X-ray transforms and other linear and non-linear geometric inverse problems for Riemannian metrics, connections and Higgs fields defined on manifolds with boundary.
New proof of Riemannian Penrose Inequality for manifolds with corners
We succeed in writing 2-dimensional conformally invariant non-linear elliptic PDE (harmonic map equation, prescribed mean curvature equations...etc) in divergence form. This divergence free quantities generalize to target manifolds without symmetries the well known conservation laws for harmonic maps into homogeneous s…
We study two inverse problems on a globally hyperbolic Lorentzian manifold . The problems are: 1. Passive observations in spacetime: Consider observations in a neighborhood of a time-like geodesic . Under natural causality conditions, we reconstruct the conformal type of the unknown open, relativ…
Essential curves in certain graph manifolds imply non-linear groups.
ML reduces high-dimensional data to reveal its underlying structure.
Study non-linear Dirichlet-to-Neumann map for Poincaré-Einstein fillings.
We consider the boundary rigidity problem for asymptotically hyperbolic manifolds. We show injectivity of the X-ray transform in several cases and consider the non-linear inverse problem which consists of recovering a metric from boundary measurements for the geodesic flow.
Proves solutions to elliptic equations on Hermitian manifolds with optimal conditions.
Sharp estimates for non-Kähler manifolds' PDEs are derived.
The construction (by Kapranov) of the space of infinitesimal paths on a manifold is extended to include higher dimensional infinitesimal objects, encoding contractions of infinitesimal loops. This full infinitesimal groupoid is shown to have the algebra of polyvector fields as its non-linear cohomology.
Generalizing the canonical symplectization of contact manifolds, we construct an infinite dimensional non-linear Stiefel manifold of weighted embeddings into a contact manifold. This space carries a symplectic structure such that the contact group and the group of reparametrizations act in a Hamiltonian fashion with eq…
We give an exposition of graded and microformal geometry, and the language of -manifolds. -manifolds are supermanifolds endowed with an odd vector field of square zero. They can be seen as a non-linear analogue of Lie algebras (in parallel with even and odd Poisson manifolds), a basis of "non-linear homological a…
We present a general existence proof for a wide class of non-linear elliptic equations which can be applied to problems with barrier conditions without specifying any assumptions guaranteeing the uniqueness or local uniqueness of particular solutions. As an application we prove the existence of closed hypersurfaces wit…
Uniform bounds for Green's function on Kähler manifolds derived from complex Monge-Ampère equations.
For a given manifold we consider the non-linear Grassmann manifold of -dimensional submanifolds in . A closed -form on gives rise to a closed 2-form on . If the original form was integral, the 2-form will be the curvature of a principal -bundle over . Using this $S^…
Bayesian neural networks improve uncertainty quantification in non-linear dimensionality reduction.
We give a characterization of the boundaries of holomorphic chains in complex projective space in terms of certain non-linear moment conditions. This extends previous work of the authors and complements results of Dolbeault and Henkin.
We develop a general theory for the goodness-of-fit test to non-linear models. In particular, we assume that the observations are noisy samples of a submanifold defined by a \yao{sufficiently smooth non-linear map}. The observation noise is additive Gaussian. Our main result shows that the "residual" of the model fit, …
In this paper we investigate the properties of a semi-linear problem on a spin manifold involving the Dirac operator, through the construction of Rabinowitz-Floer homology groups. We give several existence results for sub-critical and critical non-linearities as application of the computation of the different homologie…
We study the existence of solutions of the non-linear differential equations on the compact Riemannian manifolds , Δ_p u + a(x)u^{p-1} = λf(u,x), (E2) where is the laplacian, with . The equation (E2) generalizes a equation considered by Aubin, where he has considered, a compact Rieman…
In this contribution we review results on the kinematics of a quantum system localized on a connected configuration manifold and compatible dynamics for the quantum system including external fields and leading to non-linear Schrödinger equations for pure states.
We give conditions on the Lee vector field of an almost Hermitian manifold such that any holomorphic map from this manifold into a (1,2)-symplectic manifold must satisfy the fourth-order condition of being biharmonic, hence generalizing the Lichnerowicz theorem on harmonic maps. These third-order non-linear conditions …
Scientific and engineering processes deliver massive high-dimensional data sets that are generated as non-linear transformations of an initial state and few process parameters. Mapping such data to a low-dimensional manifold facilitates better understanding of the underlying processes, and enables their optimization. I…