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We show that on simple surfaces the geodesic ray transform acting on solenoidal symmetric tensor fields of arbitrary order is injective. This solves a long standing inverse problem in the two-dimensional case.

Differential Geometry · Mathematics 2012-11-13 Gabriel P. Paternain , Mikko Salo , Gunther Uhlmann

In this short paper we introduce a variant of the approach to inverting the X-ray transform that originated in the author's work with Uhlmann. The new method is based on semiclassical analysis and eliminates the need for using sufficiently…

Differential Geometry · Mathematics 2020-12-29 András Vasy

We consider the problem of developing a method to reconstruct a potential $q$ from the partial data Dirichlet-to-Neumann map for the Schr\"odinger equation $(-\Delta_g+q)u=0$ on a fixed admissible manifold $(M,g)$. If the part of the…

Analysis of PDEs · Mathematics 2015-11-11 Yernat M Assylbekov

We give reconstruction formulas inverting the geodesic X-ray transform over functions (call it $I_0$) and solenoidal vector fields on surfaces with negative curvature and strictly convex boundary. These formulas generalize the…

Differential Geometry · Mathematics 2015-11-18 Colin Guillarmou , François Monard

Consider a compact Riemannian manifold in dimension $n$ with strictly convex boundary. We show the local invertibility near a boundary point of the transverse ray transform of $2$ tensors for $n\geq 3$ and the mixed ray transform of $2+2$…

Differential Geometry · Mathematics 2024-02-21 Gunther Uhlmann , Jian Zhai

We consider the inverse problem of the broken ray transform (sometimes also referred to as the V-line transform). Explicit image reconstruction formulas are derived and tested numerically. The obtained formulas are generalizations of the…

Mathematical Physics · Physics 2011-01-07 Lucia Florescu , Vadim A. Markel , John C. Schotland

This paper addresses the solution of inverse problems in imaging given an additional reference image. We combine a modification of the discrete geodesic path model for image metamorphosis with a variational model,actually the $L^2$-$TV$…

Numerical Analysis · Mathematics 2019-05-22 Sebastian Neumayer , Johannes Persch , Gabriele Steidl

Given a Lorentzian manifold, the light ray transform of a function is its integrals along null geodesics. This paper is concerned with the injectivity of the light ray transform on functions and tensors, up to the natural gauge for the…

Analysis of PDEs · Mathematics 2023-05-10 Ali Feizmohammadi , Joonas Ilmavirta , Lauri Oksanen

This paper presents a unified geometric framework for the statistical analysis of a general ill-posed linear inverse model which includes as special cases noisy compressed sensing, sign vector recovery, trace regression, orthogonal matrix…

Statistics Theory · Mathematics 2020-07-27 T. Tony Cai , Tengyuan Liang , Alexander Rakhlin

In this paper, we consider the inverse problem of determining an unknown function defined in three space dimensions from its geodesic X-ray transform. The standard X-ray transform is defined on the Euclidean metric and is given by the…

Numerical Analysis · Mathematics 2018-04-27 Tak Shing Au Yeung , Eric T. Chung , Gunther Uhlmann

This work gives an expository account of certain applications of microlocal analysis in three geometric inverse problems. We will discuss the geodesic X-ray transform inverse problem, the Gelfand problem for the wave equation on a…

Analysis of PDEs · Mathematics 2023-12-14 Mikko Salo

In this article we introduce an approach for studying the geodesic X-ray transform and related geometric inverse problems by using Carleman estimates. The main result states that on compact negatively curved manifolds (resp. nonpositively…

Analysis of PDEs · Mathematics 2021-11-29 Gabriel P. Paternain , Mikko Salo

The X-ray transform on a compact symmetric space M is here inverted by means of an explicit inversion formula. The proof uses the conjugacy of the minimal closed geodesics in M and of the maximally curved totally geodesic spheres in M,…

Representation Theory · Mathematics 2007-05-23 Sigurdur Helgason

In this paper we show the invertibility of the geodesic X-ray transform on one forms and 2-tensors on asymptotically conic manifolds, up to the natural obstruction, allowing existence of certain kinds of conjugate points. We use the 1-cusp…

Differential Geometry · Mathematics 2022-12-06 Qiuye Jia , András Vasy

We consider the nonlinear problem of determining a connection and a Higgs field from the corresponding parallel transport along geodesics on a Riemannian manifold with boundary, in any dimension. The problem can be reduced to an integral…

Analysis of PDEs · Mathematics 2016-10-18 Hanming Zhou

A solution to the inversion problem of scattering would offer aberration-free diffraction-limited 3D images without the resolution and depth-of-field limitations of lens-based tomographic systems. Powerful algorithms are increasingly being…

This PhD dissertation is concerned with integral geometric inverse problems. The geodesic ray transform is an operator that encodes the line integrals of a function along geodesics. The dissertation establishes many conditions when such…

Differential Geometry · Mathematics 2020-10-23 Jesse Railo

We consider Calderon's inverse problem with partial data in dimensions $n \geq 3$. If the inaccessible part of the boundary satisfies a (conformal) flatness condition in one direction, we show that this problem reduces to the invertibility…

Analysis of PDEs · Mathematics 2016-01-20 Carlos E. Kenig , Mikko Salo

We reduce the broken ray transform on some Riemannian manifolds (with corners) to the geodesic ray transform on another manifold, which is obtained from the original one by reflection. We give examples of this idea and present injectivity…

Differential Geometry · Mathematics 2016-06-21 Joonas Ilmavirta

The paper uses a frame-theoretic setting to study the injectivity of a ReLU-layer on the closed ball of $\mathbb{R}^n$ and its non-negative part. In particular, the interplay between the radius of the ball and the bias vector is emphasized.…

Machine Learning · Computer Science 2023-10-24 Daniel Haider , Martin Ehler , Peter Balazs