15,210 research outputs found
Review of Inverse Laplace Transform Algorithms for Laplace-Space Numerical Approaches
A boundary element method (BEM) simulation is used to compare the efficiency
of numerical inverse Laplace transform strategies, considering general
requirements of Laplace-space numerical approaches. The two-dimensional BEM
solution is used to solve the Laplace-transformed diffusion equation, producing
a time-domain solution after a numerical Laplace transform inversion. Motivated
by the needs of numerical methods posed in Laplace-transformed space, we
compare five inverse Laplace transform algorithms and discuss implementation
techniques to minimize the number of Laplace-space function evaluations. We
investigate the ability to calculate a sequence of time domain values using the
fewest Laplace-space model evaluations. We find Fourier-series based inversion
algorithms work for common time behaviors, are the most robust with respect to
free parameters, and allow for straightforward image function evaluation re-use
across at least a log cycle of time
Expectation Propagation for Poisson Data
The Poisson distribution arises naturally when dealing with data involving
counts, and it has found many applications in inverse problems and imaging. In
this work, we develop an approximate Bayesian inference technique based on
expectation propagation for approximating the posterior distribution formed
from the Poisson likelihood function and a Laplace type prior distribution,
e.g., the anisotropic total variation prior. The approach iteratively yields a
Gaussian approximation, and at each iteration, it updates the Gaussian
approximation to one factor of the posterior distribution by moment matching.
We derive explicit update formulas in terms of one-dimensional integrals, and
also discuss stable and efficient quadrature rules for evaluating these
integrals. The method is showcased on two-dimensional PET images.Comment: 25 pages, to be published at Inverse Problem
A Fast Algorithm for Parabolic PDE-based Inverse Problems Based on Laplace Transforms and Flexible Krylov Solvers
We consider the problem of estimating parameters in large-scale weakly
nonlinear inverse problems for which the underlying governing equations is a
linear, time-dependent, parabolic partial differential equation. A major
challenge in solving these inverse problems using Newton-type methods is the
computational cost associated with solving the forward problem and with
repeated construction of the Jacobian, which represents the sensitivity of the
measurements to the unknown parameters. Forming the Jacobian can be
prohibitively expensive because it requires repeated solutions of the forward
and adjoint time-dependent parabolic partial differential equations
corresponding to multiple sources and receivers. We propose an efficient method
based on a Laplace transform-based exponential time integrator combined with a
flexible Krylov subspace approach to solve the resulting shifted systems of
equations efficiently. Our proposed solver speeds up the computation of the
forward and adjoint problems, thus yielding significant speedup in total
inversion time. We consider an application from Transient Hydraulic Tomography
(THT), which is an imaging technique to estimate hydraulic parameters related
to the subsurface from pressure measurements obtained by a series of pumping
tests. The algorithms discussed are applied to a synthetic example taken from
THT to demonstrate the resulting computational gains of this proposed method
Laplace transform analysis of a multiplicative asset transfer model
We analyze a simple asset transfer model in which the transfer amount is a
fixed fraction of the giver's wealth. The model is analyzed in a new way by
Laplace transforming the master equation, solving it analytically and
numerically for the steady-state distribution, and exploring the solutions for
various values of . The Laplace transform analysis is superior to
agent-based simulations as it does not depend on the number of agents, enabling
us to study entropy and inequality in regimes that are costly to address with
simulations. We demonstrate that Boltzmann entropy is not a suitable (e.g.
non-monotonic) measure of disorder in a multiplicative asset transfer system
and suggest an asymmetric stochastic process that is equivalent to the asset
transfer model
High-order, Dispersionless "Fast-Hybrid" Wave Equation Solver. Part I: Sampling Cost via Incident-Field Windowing and Recentering
This paper proposes a frequency/time hybrid integral-equation method for the
time dependent wave equation in two and three-dimensional spatial domains.
Relying on Fourier Transformation in time, the method utilizes a fixed
(time-independent) number of frequency-domain integral-equation solutions to
evaluate, with superalgebraically-small errors, time domain solutions for
arbitrarily long times. The approach relies on two main elements, namely, 1) A
smooth time-windowing methodology that enables accurate band-limited
representations for arbitrarily-long time signals, and 2) A novel Fourier
transform approach which, in a time-parallel manner and without causing
spurious periodicity effects, delivers numerically dispersionless
spectrally-accurate solutions. A similar hybrid technique can be obtained on
the basis of Laplace transforms instead of Fourier transforms, but we do not
consider the Laplace-based method in the present contribution. The algorithm
can handle dispersive media, it can tackle complex physical structures, it
enables parallelization in time in a straightforward manner, and it allows for
time leaping---that is, solution sampling at any given time at
-bounded sampling cost, for arbitrarily large values of ,
and without requirement of evaluation of the solution at intermediate times.
The proposed frequency-time hybridization strategy, which generalizes to any
linear partial differential equation in the time domain for which
frequency-domain solutions can be obtained (including e.g. the time-domain
Maxwell equations), and which is applicable in a wide range of scientific and
engineering contexts, provides significant advantages over other available
alternatives such as volumetric discretization, time-domain integral equations,
and convolution-quadrature approaches.Comment: 33 pages, 8 figures, revised and extended manuscript (and now
including direct comparisons to existing CQ and TDIE solver implementations)
(Part I of II
Joint densities of first hitting times of a diffusion process through two time dependent boundaries
Consider a one dimensional diffusion process on the diffusion interval
originated in . Let and be two continuous functions of
, with bounded derivatives and with and , . We study the joint distribution of the two random
variables and , first hitting times of the diffusion process through
the two boundaries and , respectively. We express the joint
distribution of in terms of and
and we determine a system of integral equations verified by
these last probabilities. We propose a numerical algorithm to solve this system
and we prove its convergence properties. Examples and modeling motivation for
this study are also discussed
- …