Inverse problems are the problems of finding unknown parameters or
structures by indirect measurements.
A typical inverse problem is the inverse conductivity problem.
Its practical setting is the following: Assume that you want to find the inner
structure of your torso by doing resistivity measurements at your skin.
In mathematical terms, the inverse problems usually mean the finding
of the unknown parameter functions of a partial differential equation
from the knowledge of the boundary values of the solutions. Recently
I have worked with the inverse problems in Riemannian geometry, e.g.
how to find an unknown Riemannian
manifold and an unknown elliptic operator
defined on it from 'boundary data'. This has some connections to my
thesis concerning electromagnetic inverse spectral problem (which was
in playfully terms the problem 'Can you hear the shape of a radio?')
Recently, my research has turned more towards
inverse problems
in differential geometry and stochastical inverse problems.
The inverse problems are studied all around Finland, we have
founded the
Finnish Inverse Problems Society which promotes the research
on the area.
Below is a list of
some of my collaborators and friends studying inverse problems
in Finland.
Here are some of my collaborators around the world
-
Michael Anderson, State University of New York, USA.
-
Margaret Cheney, Rensselare Polytechnic Institute, USA.
-
Allan Greenleaf, Rochester, USA.
- David Isaacson, Rensselaer, USA.
- Atsushi Katsuda, Okayama, Japan.
-
Alexander Katchalov, Steklov Institute, Russia.
-
Slava Kurylev, Loughborough, UK.
- Niculae Mandache, Loughborough, UK.
-
Jennifer Mueller,
Colorado State, USA.
- Vladimir
Sharafutdinov, Novosibirsk, Russia.
-
Michael E. Taylor, University of North Carolina, USA.
- Gunther Uhlmann,
Washington, USA.
In Finland there are also various institutes
solving inverse problems in practice.
-
Check out the 3D-movies
of reconstructed
viruses and
human chromosomes made by using X-ray tomography in the Department of Virology in
University of Helsinki and CSC-center.
-
Instrumentarium Imaging Inc. is one of worlds biggest manufacturer of
dental X-ray and mammography devices. The collaboration with Finnish
inverse problems researcher and this company has been very active.
-
Invers Ltd is producer of world fastest
stochastical inverse problem solvers as well as sonar and radar systems.
- The finnish company
Neuromag is specialized in noninvasively study the human brain by using electromagnetic
measurements.
You can look also the list of the universities with
Inverse Problems research groups .
Mathematical methods for electromagnetism
We have studied absorbing boundary conditions, particularly
so-called Perfectly Matched Layer (PML)-condition. Absorbing
boundary conditions are used in computer simulations for
scattering problems, for simulating radar or cellular phones etc.
When simulating the waves in infinite
space one faces the problem that any computer has only finite
memory. Thus the domain of simulation has to be cut finite.
The boundary of this new domain should cause as little echo as
possible. The echo-less boundary structures implemented at the boundary
are called absorbing boundary conditions. Mathematically,
the PML-structure is equivalent for interpreting the real space
Rn as a submanifold of the complex space Cn and
stretching the real space into the complex direction.
In following videos the PML absorbing boundary condition
is demonstrated: In Video1 the
is the scattered wave when a plane wave scatters to a ball.
In Video2 the a solution
is shown in the presence of absorbing boundary layer. Note
how the waves propagate into the absorbing media and fade
there without giving any echo. Thus the solution coincides
with the true solution near the ball.
ps
We have have also done some applied research of radar systems
for a Finnish company
Vaisala.
General mathematical interests
Inverse problems are an area of mathematics applying
various results from several different fields. My own fields
of interests contain the areas of
real, complex and functional analysis, particularly theory of PDE:s
and microlocal analysis, Riemannian
geometry and stochastics.