Many objects of physical interest cannot be studied directly.
Examples include, imaging the interior of the body, determining material parameters such as the conductivity of inaccessible objects and indeed of fundamental terms in the mathematical description of physical models.
When these problems are translated into mathematical terms they take the form of partial differential equations, the Lingua Franca of the mathematical sciences. However, since we have additional unknowns in the model, these introduce unknown parameters in the equations that have to be additionally resolved by means of further measurements.
These “inverse problems” are critical to much of science and technology. We are interested in when a unique determination can be made as well as designing and analyzing algorithms for the efficient numerical recovery of the unknowns.
This workshop will bring together experts covering all of the above aspects and problems based on a wide range of application areas will be represented.