Search results for "inverse problems"

showing 10 items of 39 documents

Inverse problems for $p$-Laplace type equations under monotonicity assumptions

2016

We consider inverse problems for $p$-Laplace type equations under monotonicity assumptions. In two dimensions, we show that any two conductivities satisfying $\sigma_1 \geq \sigma_2$ and having the same nonlinear Dirichlet-to-Neumann map must be identical. The proof is based on a monotonicity inequality and the unique continuation principle for $p$-Laplace type equations. In higher dimensions, where unique continuation is not known, we obtain a similar result for conductivities close to constant.

010101 applied mathematicsunique continuation principleMathematics - Analysis of PDEsinverse problems010102 general mathematicsFOS: MathematicsDirichlet-to-Neumann map35J92 35R300101 mathematics01 natural sciencesp-Laplace equationinversio-ongelmatAnalysis of PDEs (math.AP)
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Jacobian of solutions to the conductivity equation in limited view

2022

Abstract The aim of hybrid inverse problems such as Acousto-Electric Tomography or Current Density Imaging is the reconstruction of the electrical conductivity in a domain that can only be accessed from its exterior. In the inversion procedure, the solutions to the conductivity equation play a central role. In particular, it is important that the Jacobian of the solutions is non-vanishing. In the present paper we address a two-dimensional limited view setting, where only a part of the boundary of the domain can be controlled by a non-zero Dirichlet condition, while on the remaining boundary there is a zero Dirichlet condition. For this setting, we propose sufficient conditions on the bounda…

Applied Mathematicscurrent density imagingconductivity equationacousto-electric tomographyinversio-ongelmatComputer Science ApplicationsTheoretical Computer ScienceFunctional Analysis (math.FA)Mathematics - Functional Analysisnon-vanishing Jacobianhybrid inverse problemsSignal Processingcoupled physics imagingFOS: MathematicsMathematical Physics
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A Review of Mathematical and Computational Methods in Cancer Dynamics.

2022

Cancers are complex adaptive diseases regulated by the nonlinear feedback systems between genetic instabilities, environmental signals, cellular protein flows, and gene regulatory networks. Understanding the cybernetics of cancer requires the integration of information dynamics across multidimensional spatiotemporal scales, including genetic, transcriptional, metabolic, proteomic, epigenetic, and multi-cellular networks. However, the time-series analysis of these complex networks remains vastly absent in cancer research. With longitudinal screening and time-series analysis of cellular dynamics, universally observed causal patterns pertaining to dynamical systems, may self-organize in the si…

Cancer Researchinverse problemssystems oncologyFOS: Physical sciencescomplex networksdynamical systemsOther Quantitative Biology (q-bio.OT)Nonlinear Sciences - Chaotic DynamicsalgorithmsQuantitative Biology - Other Quantitative BiologyOncologyFOS: Biological sciencescancerChaotic Dynamics (nlin.CD)complexity scienceinformation theory
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CLEAR: Covariant LEAst-Square Refitting with Applications to Image Restoration

2017

International audience; In this paper, we propose a new framework to remove parts of the systematic errors affecting popular restoration algorithms, with a special focus for image processing tasks. Generalizing ideas that emerged for $\ell_1$ regularization, we develop an approach re-fitting the results of standard methods towards the input data. Total variation regularizations and non-local means are special cases of interest. We identify important covariant information that should be preserved by the re-fitting method, and emphasize the importance of preserving the Jacobian (w.r.t. the observed signal) of the original estimator. Then, we provide an approach that has a ``twicing'' flavor a…

FOS: Computer and information sciencesInverse problemsMathematical optimization[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingComputer Vision and Pattern Recognition (cs.CV)General MathematicsComputer Science - Computer Vision and Pattern RecognitionMachine Learning (stat.ML)Mathematics - Statistics TheoryImage processingStatistics Theory (math.ST)02 engineering and technologyDebiasing[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]01 natural sciencesRegularization (mathematics)Boosting010104 statistics & probabilitysymbols.namesake[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[STAT.ML]Statistics [stat]/Machine Learning [stat.ML]Variational methods[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]Statistics - Machine LearningRefittingMSC: 49N45 65K10 68U10[ INFO.INFO-TI ] Computer Science [cs]/Image ProcessingFOS: Mathematics0202 electrical engineering electronic engineering information engineeringCovariant transformation[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]0101 mathematicsImage restoration[ STAT.ML ] Statistics [stat]/Machine Learning [stat.ML]MathematicsApplied Mathematics[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]EstimatorInverse problem[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Jacobian matrix and determinantsymbolsTwicing020201 artificial intelligence & image processingAffine transformationAlgorithm
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Coherent Quantum Tomography

2016

We discuss a quantum mechanical indirect measurement method to recover a position dependent Hamilton matrix from time evolution of coherent quantum mechanical states through an object. A mathematical formulation of this inverse problem leads to weighted X-ray transforms where the weight is a matrix. We show that such X-ray transforms are injective with very rough weights. Consequently, we can solve our quantum mechanical inverse problem in several settings, but many physically relevant problems we pose also remain open. We discuss the physical background of the proposed imaging method in detail. We give a rigorous mathematical treatment of a neutrino tomography method that has been previous…

FOS: Physical sciences01 natural sciencesMatrix (mathematics)neutrino physics0103 physical sciencesClassical Analysis and ODEs (math.CA)FOS: MathematicsStatistical physics0101 mathematics010306 general physicsQuantumMathematical PhysicsMathematicsQuantum Physicsinverse problemsgeophysicsApplied Mathematicsta111quantum mechanics010102 general mathematicsMathematical analysisTime evolutionweighted ray transformsMathematical Physics (math-ph)81Q99 81V99 86A22 44A12Inverse problemQuantum tomographyInjective functionComputational MathematicsMathematics - Classical Analysis and ODEsTomographyNeutrinoQuantum Physics (quant-ph)AnalysisSIAM Journal on Mathematical Analysis
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Recovery of time-dependent coefficients from boundary data for hyperbolic equations

2019

We study uniqueness of the recovery of a time-dependent magnetic vector-valued potential and an electric scalar-valued potential on a Riemannian manifold from the knowledge of the Dirichlet to Neumann map of a hyperbolic equation. The Cauchy data is observed on time-like parts of the space-time boundary and uniqueness is proved up to the natural gauge for the problem. The proof is based on Gaussian beams and inversion of the light ray transform on Lorentzian manifolds under the assumptions that the Lorentzian manifold is a product of a Riemannian manifold with a time interval and that the geodesic ray transform is invertible on the Riemannian manifold.

GeodesicDirichlet-to-Neumann maplight ray transformmagnetic potentialBoundary (topology)CALDERON PROBLEM01 natural sciencesGaussian beamMathematics - Analysis of PDEsFOS: Mathematics111 Mathematics[MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP]Uniqueness0101 mathematicsMathematics::Symplectic GeometryMathematical PhysicsMathematicsX-ray transformSTABILITYinverse problemsMathematical analysisStatistical and Nonlinear PhysicsRiemannian manifoldX-RAY TRANSFORMWave equationMathematics::Geometric TopologyManifoldTENSOR-FIELDS010101 applied mathematicsUNIQUE CONTINUATIONGeometry and TopologyMathematics::Differential GeometryWAVE-EQUATIONSHyperbolic partial differential equationAnalysis of PDEs (math.AP)
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Tensor tomography in periodic slabs

2018

Abstract The X-ray transform on the periodic slab [ 0 , 1 ] × T n , n ≥ 0 , has a non-trivial kernel due to the symmetry of the manifold and presence of trapped geodesics. For tensor fields gauge freedom increases the kernel further, and the X-ray transform is not solenoidally injective unless n = 0 . We characterize the kernel of the geodesic X-ray transform for L 2 -regular m -tensors for any m ≥ 0 . The characterization extends to more general manifolds, twisted slabs, including the Mobius strip as the simplest example.

Geodesicx-ray examinationslab geometrytomography01 natural sciencesinversio-ongelmatTensor fieldsymbols.namesaketomografiaMöbius stripTensor0101 mathematicsMathematical physicsMathematicsinverse problems010102 general mathematicsta111röntgentutkimusSymmetry (physics)Injective functionManifold010101 applied mathematicsKernel (algebra)symbolstensor tomographyX-ray tomographyAnalysisJournal of Functional Analysis
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Dimension bounds in monotonicity methods for the Helmholtz equation

2019

The article [B. Harrach, V. Pohjola, and M. Salo, Anal. PDE] established a monotonicity inequality for the Helmholtz equation and presented applications to shape detection and local uniqueness in inverse boundary problems. The monotonicity inequality states that if two scattering coefficients satisfy $q_1 \leq q_2$, then the corresponding Neumann-to-Dirichlet operators satisfy $\Lambda(q_1) \leq \Lambda(q_2)$ up to a finite-dimensional subspace. Here we improve the bounds for the dimension of this space. In particular, if $q_1$ and $q_2$ have the same number of positive Neumann eigenvalues, then the finite-dimensional space is trivial. peerReviewed

Helmholtz equationMathematics::Number Theorymontonicity methodMonotonic function01 natural sciencesinversio-ongelmatMathematics::Numerical AnalysisMathematics - Spectral TheoryMathematics - Analysis of PDEsDimension (vector space)FOS: MathematicsHelmholtz equationUniqueness0101 mathematicsSpectral Theory (math.SP)Mathematicsinverse problemsApplied Mathematics010102 general mathematicsMathematical analysisInverse problemMathematics::Spectral Theory010101 applied mathematicsComputational MathematicsNonlinear Sciences::Exactly Solvable and Integrable Systems35R30AnalysisAnalysis of PDEs (math.AP)
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A New Procedure for the Evaluation of Non-Uniform Residual Stresses by the Hole Drilling Method Based on the Newton-Raphson Technique

2010

The hole drilling method is one of the most used semi-destructive techniques for the analysis of residual stresses in mechanical components. The non-uniform stresses are evaluated by solving an integral equation in which the strains relieved by drilling a hole are introduced. In this paper a new calculation procedure, based on the Newton-Raphson method for the determination of zeroes of functions, is presented. This technique allows the user to introduce complex and effective forms of stress functions for the solution of the problem. All the relationships needed for the evaluation of the stresses are obtained in explicit form, eliminating the need to use additional mathematical tools. The t…

Hole drilling methodEngineeringbusiness.industryMechanical EngineeringAerospace EngineeringMechanical engineeringDrillingStructural engineeringStress functionsInverse problemIntegral equationResidual stresses Hole drilling method Inverse problems Newton Raphson technique Experimental stress analysissymbols.namesakeSettore ING-IND/14 - Progettazione Meccanica E Costruzione Di MacchineMechanics of MaterialsResidual stressSolid mechanicssymbolsbusinessNewton's method
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Partial data inverse problems for Maxwell equations via Carleman estimates

2015

In this article we consider an inverse boundary value problem for the time-harmonic Maxwell equations. We show that the electromagnetic material parameters are determined by boundary measurements where part of the boundary data is measured on a possibly very small set. This is an extension of earlier scalar results of Bukhgeim-Uhlmann and Kenig-Sj\"ostrand-Uhlmann to the Maxwell system. The main contribution is to show that the Carleman estimate approach to scalar partial data inverse problems introduced in those works can be carried over to the Maxwell system.

Inverse problemsELECTRODYNAMICSINFORMATIONadmissible manifoldsWEIGHTSMathematics::Analysis of PDEsBoundary (topology)InverseBOUNDARY-VALUE PROBLEMCALDERON PROBLEMpartial data01 natural sciencesMATERIAL PARAMETERSinversio-ongelmatsymbols.namesakeMathematics - Analysis of PDEsFOS: Mathematics35R30 35Q61111 MathematicsMaxwellin yhtälötBoundary value problemUniqueness0101 mathematicsPartial dataMathematical PhysicsMathematicsAdmissible manifoldsApplied Mathematicsta111010102 general mathematicsMathematical analysisScalar (physics)Inverse problemCarleman estimatesSmall set010101 applied mathematicsUNIQUENESSMaxwell's equationsMaxwell equationsLOCAL DATAsymbolsAnalysisAnalysis of PDEs (math.AP)
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