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SUMMARY:Data-to-Born transform for multiple removal and imaging with waves
  - Alexander Mamonov (University of Houston)
DTSTART:20230524T080000Z
DTEND:20230524T084500Z
UID:TALK198886@talks.cam.ac.uk
DESCRIPTION:This work is motivated by an inverse problem for the acoustic 
 wave equation\, where an array of sensors probes an unknown medium with pu
 lses and measures the scattered waves. The goal of the inversion is to det
 ermine from these measurements the structure of the scattering medium\, mo
 deled by a spatially varying acoustic impedance function. Many inversion a
 lgorithms assume that the mapping from the unknown impedance to the scatte
 red waves is approximately linear. This linearization\, known as the Born 
 approximation\, is not accurate in strongly scattering media\, where the w
 aves undergo multiple reflections before they reach the sensors in the arr
 ay. This results in the artifacts in the reconstructions of the impedance 
 obtained via linearized approaches (e.g.\, various migration algorithms).\
 nOur main result is a novel\, linear-algebraic algorithm that uses a reduc
 ed order model (ROM) to map the multiply scattered data to those correspon
 ding to the single scattering (Born) model\, the so-called Data-to-Born tr
 ansform. The ROM is a proxy for the wave propagator operator\, that propag
 ates the wave in the unknown medium over the duration of the time sampling
  interval. Its construction is based only on the measurements at the senso
 rs in the array. &nbsp\;The output of the algorithm can be passed to any o
 ff-the-shelf inversion software that incorporates state of the art linear 
 inversion algorithms to reconstruct the unknown acoustic impedance.
LOCATION:Seminar Room 1\, Newton Institute
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