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Efficient and high-fidelity prior sampling and inversion for complex geological media is still a largely unsolved challenge. Here, we use a deep neural network of the variational autoencoder type to construct a parametric low-dimensional…

Machine Learning · Statistics 2017-10-26 Eric Laloy , Romain Hérault , John Lee , Diederik Jacques , Niklas Linde

Combination of a construction of unambiguous quantum conditions out of the conventional one and a simultaneous quantization of the positions, momenta, angular momenta and Hamiltonian leads to the geometric potential given by the so-called…

Quantum Physics · Physics 2017-02-15 D. K. Lian , L. D. Hu , Q. H. Liu

A survey on recent developments in (algebraic) integral geometry is given. The main focus lies on algebraic structures on the space of translation invariant valuations and applications in integral geometry.

Differential Geometry · Mathematics 2013-04-04 Andreas Bernig

An out of the box intellectual path exploring the foundations of quantum mechanics is discussed in some detail, in order to clarify why a possibly different way to look at the relevant fundamental questions can be identified and can support…

General Physics · Physics 2012-11-06 Alberto Ottolenghi

Electrical Impedance Tomography (EIT) is a powerful imaging technique with diverse applications, e.g., medical diagnosis, industrial monitoring, and environmental studies. The EIT inverse problem is about inferring the internal conductivity…

Machine Learning · Computer Science 2023-10-31 Derick Nganyu Tanyu , Jianfeng Ning , Andreas Hauptmann , Bangti Jin , Peter Maass

We introduce a `double-difference' method for the inversion for seismic wavespeed structure based on adjoint tomography. Differences between seismic observations and model predictions at individual stations may arise from factors other than…

Geophysics · Physics 2016-07-08 Yanhua O. Yuan , Frederik J. Simons , Jeroen Tromp

Computed tomography is a method for synthesizing volumetric or cross-sectional images of an object from a collection of projections. Popular reconstruction methods for computed tomography are based on idealized models and assumptions that…

Numerical Analysis · Mathematics 2022-03-03 Frederik H. Pedersen , Jakob S. Jørgensen , Martin S. Andersen

The probability representation for quantum states of the universe in which the states are described by a fair probability distribution instead of wave function (or density matrix) is developed to consider cosmological dynamics. The…

General Relativity and Quantum Cosmology · Physics 2015-06-25 V. I. Man'ko , G. Marmo , C. Stornaiolo

We apply tomography, a general method for reconstructing 3-D distributions from multiple projections, to reconstruct the momentum distribution of electrons produced via strong field photoionization. The projections are obtained by rotating…

Atomic Physics · Physics 2009-09-28 C Smeenk , L Arissian , A Staudte , D M Villeneuve , P B Corkum

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

This article provides an overview of the current state of digital rock technology, with emphasis on industrial applications. We show how imaging and image analysis can be applied for rock typing and modeling of end-point saturations.…

Geophysics · Physics 2020-05-07 Carl Fredrik Berg , Olivier Lopez , Håvard Berland

An optical waveplate rotating light polarization can be modeled as a single-qubit unitary operator, whose action can be experimentally determined via quantum process tomography. Standard approaches to tomographic problems rely on the…

This paper proposes a novel approach to reconstruct changes in a target conductivity from electrical impedance tomography measurements. As in the conventional difference imaging, the reconstruction of the conductivity change is based on…

Computational Physics · Physics 2014-03-27 Dong Liu , Ville Kolehmainen , Samuli Siltanen , Anne maria Laukkanen , Aku Seppanen

Based on a geometric picture, the example of free particle motion for both classical and quantum domains is considered in the tomographic probability representation. Wave functions and density operators as well as optical and symplectic…

Quantum Physics · Physics 2011-12-01 Vladimir I. Man'ko , Franco Ventriglia

In this chapter, we identify fundamental geometric structures that underlie the problems of sampling, optimisation, inference and adaptive decision-making. Based on this identification, we derive algorithms that exploit these geometric…

When the dynamics of a quantum system of interest is known, an informationally-complete set of observables is not needed for state reconstruction via tomographic techniques: letting the system evolve before performing the measurement allows…

Quantum Physics · Physics 2026-02-17 Marco Peruzzo , Tommaso Grigoletto , Francesco Ticozzi

Using techniques of projective geometry, we give elementary proofs of two theorems concerning Hagge configurations.

History and Overview · Mathematics 2023-11-28 Zoltán Szilasi

The probability representation of quantum and classical statistical mechanics is discussed. Symplectic tomography, center-of-mass tomography, and spin tomography are studied. The connection of tomographic probabilities with dynamic…

Quantum Physics · Physics 2015-05-27 Margarita A. Man'ko , Vladimir I. Man'ko

We construct algorithms and topological invariants that allow us to distinguish the topological type of a surface, as well as functions and vector fields for their topological equivalence. In the first part (arXiv:2501.15657), we discused…

Geometric Topology · Mathematics 2025-02-17 Alexandr Prishlyak

The field of topological photonics emerged as one of the most promising areas for applications in transformative technologies: possible applications are in topological lasers or quantum optics interfaces. Nevertheless, efficient and simple…