arXiv subjects

William Rundell

Publications and source records attributed to William Rundell.

At least 19 recordsLinked to original sources

arXiv2026

Identification of space-dependent coefficients in two competing terms of a nonlinear subdiffusion equation

We consider a (sub)diffusion equation with a nonlinearity of the form $pf(u)-qu$, where $p$ and $q$ are space dependent functions. Prominent examples are the Fisher-KPP, the Frank-Kamenetskii-Zeldovich and the Allen-Cahn equations. We devise a fixed point scheme for reconstructing the spatially varying coefficients from interior observations a) at final time under two different excitations b) at two different time instances under a single excitation. Convergence of the scheme as well as local uniqueness of these coefficients is proven. Numerical experiments illustrate the performance of the reconstruction scheme.

math.NA↗

arXiv2025

Reconstruction of space-dependence and nonlinearity of a reaction term in a subdiffusion equation

In this paper we study the simultaneous reconstruction of two coefficients in a reaction-subdiffusion equation, namely a nonlinearity and a space dependent factor. The fact that these are coupled in a multiplicative matter makes the reconstruction particularly challenging. Several situations of overposed data are considered: boundary observations over a time interval, interior observations at final time, as well as a combination thereof. We devise fixed point schemes and also describe application of a frozen Newton method. In the final time data case we prove convergence of the fixed point scheme as well as uniqueness of both coefficients. Numerical experiments illustrate performance of the reconstruction methods, in particular dependence on the differentiation order in the subdiffusion equation.

math.NA↗

arXiv2023

On the simultanenous identification of the nonlinearity coefficient and the sound speed in the Westervelt equation

This paper considers the Westervelt equation, one of the most widely used models in nonlinear acoustics, and seeks to recover two spatially-dependent parameters of physical importance from time-trace boundary measurements. Specifically, these are the nonlinearity parameter $κ(x)$ often referred to as $B/A$ in the acoustics literature and the wave speed $c_0(x)$. The determination of the spatial change in these quantities can be used as a means of imaging. We consider identifiability from one or two boundary measurements as relevant in these applications. For a reformulation of the problem in terms of the squared slowness $\mathfrak{s}=1/c_0^2$ and the combined coefficient $η=\frac{B/A+2}{\varrho_0 c_0^4}$ we devise a frozen Newton method and prove its convergence. The effectiveness (and limitations) of this iterative scheme are demonstrated by numerical examples.

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arXiv2023

Nonlinearity parameter imaging in the frequency domain

Nonlinearity parameter tomography leads to the problem of identifying a coefficient in a nonlinear wave equation (such as the Westervelt equation) modeling ultrasound propagation. In this paper we transfer this into frequency domain, where the Westervelt equation gets replaced by a coupled system of Helmholtz equations with quadratic nonlinearities. For the case of the to-be-determined nonlinearity coefficient being a characteristic function of an unknown, not necessarily connected domain $D$, we devise and test a reconstruction algorithm based on weighted point source approximations combined with Newton's method. In a more abstract setting, convergence of a regularised Newton type method for this inverse problem is proven by verifying a range invariance condition of the forward operator and establishing injectivity of its linearisation.

math.NA↗

arXiv2022

Determining damping terms in fractional wave equations

This paper deals with the inverse problem of recovering an arbitrary number of fractional damping terms in a wave equation. We develop several approaches on uniqueness and reconstruction, some of them relying on Tauberian theorems on the relation between the asymptotics of solutions in time and Laplace domain. Also the possibility of additionally recovering space dependent coefficients or initial data is discussed. The resulting methods for reconstructing coefficients and fractional orders in these terms are tested numerically. Additionally, we provide an analysis of the forward problem, a multiterm fractional wave equation.

math.AP↗

arXiv2021

Determining the nonlinearity in an acoustic wave equation

We consider an undetermined coefficient inverse problem for a nonlinear partial differential equation describing high intensity ultrasound propagation as widely used in medical imaging and therapy. The usual nonlinear term in the standard model using the Westervelt equation in pressure formulation is of the form $p p_t$. However, this should be considered as a low order approximation to a more complex physical model where higher order terms will be required. Here we assume a more general case where the form taken is $f(p)\,p_t$ and $f$ is unknown and must be recovered from data measurements. Corresponding to the typical measurement setup, the overposed data consists of time trace observations of the acoustic pressure at a single point or on a one dimensional set $Σ$ representing the receiving transducer array at a fixed time. Additionally to an analysis of well-posedness of the resulting {\sc pde}, we show injectivity of the linearized forward map from $f$ to the overposed data and use this as motivation for several iterative schemes to recover $f$. Numerical simulations will also be shown to illustrate the efficiency of the methods.

math.NA↗

arXiv2021

On an inverse problem of nonlinear imaging with fractional damping

This paper considers the attenuated Westervelt equation in pressure formulation. The attenuation is by various models proposed in the literature and characterised by the inclusion of non-local operators that give power law damping as opposed to the exponential of classical models. The goal is the inverse problem of recovering a spatially dependent coefficient in the equation, the parameter of nonlinearity $κ(x)$, in what becomes a nonlinear hyperbolic equation with nonlocal terms. The overposed measured data is a time trace taken on a subset of the domain or its boundary. We shall show injectivity of the linearised map from $κ$ to the overposed data used to recover it and from this basis develop and analyse Newton-type schemes for its effective recovery.

math.AP↗

arXiv2021

On the identification of the nonlinearity parameter in the Westervelt equation from boundary measurements

We consider an undetermined coefficient inverse problem for a non-\\linear partial differential equation occurring in high intensity ultrasound propagation as used in acoustic tomography. In particular, we investigate the recovery of the nonlinearity coefficient commonly labeled as $B/A$ in the literature which is part of a space dependent coefficient $κ$ in the Westervelt equation governing nonlinear acoustics. Corresponding to the typical measurement setup, the overposed data consists of time trace measurements on some zero or one dimensional set $Σ$ representing the receiving transducer array. After an analysis of the map from $κ$ to the overposed data, we show injectivity of its linearisation and use this as motivation for several iterative schemes to recover $κ$. Numerical simulations will also be shown to illustrate the efficiency of the methods.

math.AP↗

arXiv2021

On uniqueness and reconstruction of a nonlinear diffusion term in a parabolic equation

The problem of recovering coefficients in a diffusion equation is one of the basic inverse problems. Perhaps the most important term is the one that couples the length and time scales and is often referred to as {\it the\/} diffusion coefficient $a$ in $u_t - \nabla(a\nabla u) = f$. In this paper we seek the unknown $a$ assuming that $a=a(u)$ depends only on the value of the solution at a given point. Such diffusion models are the basic of a wide range of physical phenomena such as nonlinear heat conduction, chemical mixing and population dynamics. We shall look at two types of overposed data in order to effect recovery of $a(u)$: the value of a time trace $u(x_0,t)$ for some fixed point $x_0$ on the boundary of the region $Ω$; or the value of $u$ on an interior curve $Σ$ lying within $Ω$. As examples, these might represent a temperature measurement on the boundary or a census of the population in some subset of $Ω$ taken at a fixed time $T>0$. In the latter case we shall show a uniqueness result that leads to a constructive method for recovery of $a$. Indeed, for both types of measured data we shall show reconstructions based on the iterative algorithms developed in the paper.

math.AP↗

arXiv2021

On the simultaneous recovery of the conductivity and the nonlinear reaction term in a parabolic equation

This paper considers the inverse problem of recovering both the unknown, spatially-dependent conductivity $a(x)$ and the nonlinear reaction term $f(u)$ in a reaction-diffusion equation from overposed data. These measurements can consist of: the value of two different solution measurements taken at a later time $T$; time-trace profiles from two solutions; or both final time and time-trace measurements from a single forwards solve data run. We prove both uniqueness results and the convergence of iteration schemes designed to recover these coefficients. The last section of the paper shows numerical reconstructions based on these algorithms.

math.AP↗

arXiv2020

The Inverse Problem of Reconstructing Reaction-Diffusion Systems

This paper considers the inverse problem of recovering state-dependent source terms in a reaction-diffusion system from overposed data consisting of the values of the state variables either at a fixed finite time (census-type data) or a time trace of their values at a fixed point on the boundary of the spatial domain. We show both uniqueness results and the convergence of an iteration scheme designed to recover these sources. This leads to a reconstructive method and we shall demonstrate its effectiveness by several illustrative examples.

math.NA↗

arXiv2019

Regularization of a backwards parabolic equation by fractional operators

The backwards diffusion equation is one of the classical ill-posed inverse problems, related to a wide range of applications, and has been extensively studied over the last 50 years. One of the first methods was that of {\it quasireversibility\/} whereby the parabolic operator is replaced by a differential operator for which the backwards problem in time is well posed. This is in fact the direction we will take but will do so with a nonlocal operator; an equation of fractional order in time for which the backwards problem is known to be ``almost well posed.'' We shall look at various possible options and strategies but our conclusion for the best of these will exploit the linearity of the problem to break the inversion into distinct frequency bands and to use a different fractional order for each. The fractional exponents will be chosen using the discrepancy principle under the assumption we have an estimate of the noise level in the data. An analysis of the method is provided as are some illustrative numerical examples.

math.NA↗

arXiv2019

On the identification of source term in the heat equation from sparse data

We consider the recovery of a source term $f(x,t)=p(x)q(t)$ for the nonhomogeneous heat equation in $Ω\times (0,\infty)$ where $Ω$ is a bounded domain in $\mathbb{R}^2$ with smooth boundary $\partialΩ$ from overposed lateral data on a sparse subset of $\partialΩ\times(0,\infty)$. Specifically, we shall require a small finite number $N$ of measurement points on $\partialΩ$ and prove a uniqueness result; namely the recovery of the pair $(p,q)$ within a given class, by a judicious choice of $N=2$ points. Naturally, with this paucity of overposed data, the problem is severely ill-posed. Nevertheless we shall show that provided the data noise level is low, effective numerical reconstructions may be obtained.

math.AP↗

arXiv2019

Recovery of multiple coefficients in a reaction-diffusion equation

This paper considers the inverse problem of recovering both the unknown, spatially-dependent conductivity $a(x)$ and the potential $q(x)$ in a parabolic equation from overposed data consisting of the value of solution profiles taken at a later time $T$. We show both uniqueness results and the convergence of an iteration scheme designed to recover these coefficients. We also allow a more general setting, in particular when the usual time derivative is replaced by one of fractional order and when the potential term is coupled with a known nonlinearity $f$ of the form $q(x)f(u)$.

math.NA↗

arXiv2019

On the identification of a nonlinear term in a reaction-diffusion equation

Reaction-diffusion equations are one of the most common partial differential equations used to model physical phenomenon. They arise as the combination of two physical processes: a driving force $f(u)$ that depends on the state variable $u$ and a diffusive mechanism that spreads this effect over a spatial domain. The canonical form is $u_t - \triangle u = f(u)$. Application areas include chemical processes, heat flow models and population dynamics. The direct or forwards problem for such equations is now very well-developed and understood. However, our interest lies in the inverse problem of recovering the reaction term $f(u)$ not just at the level of determining a few parameters in a known functional form, but recovering the complete functional form itself. To achieve this we set up the usual paradigm for the parabolic equation where $u$ is subject to both given initial and boundary data, then prescribe overposed data consisting of the solution at a later time $T$. For example, in the case of a population model this amounts to census data at a fixed time. Our approach will be two-fold.First we will transform the inverse problem into an equivalent nonlinear mapping from which we seek a fixed point. We will be able to prove important features of this map such as a self-mapping property and give conditions under which it is contractive. Second, we consider the direct map from $f$ through the partial differential operator to the overposed data. We will investigate Newton schemes for this case. In recent decades various anomalous processes have been used to generalize classical Brownian diffusion. Amongst the most popular is one that replaces the usual time derivative by a fractional one of order $\alpha \leq 1$. We will also include this model in our analysis. The final section of the paper shows numerical reconstructions that demonstrate the viability of the suggested approaches.

math.NA↗

arXiv2018

Recovery of a potential in a fractional diffusion equation

We consider the determination of an unknown potential $q(x)$ form a fractional diffusion equation subject to overposed lateral boundary data. We show that this data allows recovery of two spectral sequences for the associated inverse Sturm-Liouville problem and these are sufficient to apply standard uniqueness results for this case. We also look at reconstruction methods and in particular examine the issue of stability of the solution with respect to the data. The outcome shows the inverse problem to be severely ill-conditioned and we consider the differences between the cases of fractional and of classical diffusion.

math-ph↗

arXiv2017

Recovering an Unknown Source in a Fractional Diffusion Problem

A standard inverse problem is to determine a source which is supported in an unknown domain $D$ from external boundary measurements. Here we consider the case of a time-dependent situation where the source is equal to unity in an unknown subdomain $D$ of a larger given domain $\Omega$. Overposed measurements consist of time traces of the solution or its flux values on a set of discrete points on the boundary $\partial\Omega$. The case of a parabolic equation was considered in [HettlichRundell:2001]. In our situation we extend this to cover the subdiffusion case based on an anomalous diffusion model and leading to a fractional order differential operator. We will show a uniqueness result and examine a reconstruction algorithm. One of the main motives for this work is to examine the dependence of the reconstructions on the parameter $\alpha$, the exponent of the fractional operator which controls the degree of anomalous behaviour of the process. Some previous inverse problems based on fractional diffusion models have shown considerable differences between classical Brownian diffusion and the anomalous case.

math.NA↗

arXiv2016

Fraction diffusion: Recovering the distributed fractional derivative from overposed data

There has been considerable recent study in "sub-diffusion" models that replace the standard parabolic equation model by a one with a fractional derivative in the time variable. There are many ways to look at this newer approach and one such is to realize that the order of the fractional derivative is related to the time scales of the underlying diffusion process. This raises the question of what order ? of derivative should be taken and if a single value actually suffices. This has led to models that combine a finite number of these derivatives each with a different fractional exponent α_k and different weighting value c_k to better model a greater possible range of time scales. Ultimately, one wants to look at a situation that combines derivatives in a continuous way { the so-called distributional model with parameter μ(α). However all of this begs the question of how one determines this "order" of differentiation. Recovering a single fractional value has been an active part of the process from the beginning of fractional diffusion modeling and if this is the only unknown then the markers left by the fractional order derivative are relatively straightforward to determine. In the case of a finite combination of derivatives this becomes much more complex due to the more limited analytic tools available for such equations, but recent progress in this direction has been made, [9, 8]. This paper considers the full distributional model where the order is viewed as a function μ(α) on the interval (0; 1]. We show existence, uniqueness and regularity for an initial-boundary value problem including an important representation theorem in the case of a single spatial variable. This is then used in the inverse problem of recovering the distributional coefficient μ(α) from a time trace of the solution and a uniqueness result is proven.

math.AP↗