At baobab soluciones we are proud to announce that Alejandro Mus, researcher and one of our talents, has participated significantly in the development and publication of an important scientific article titled “Using multiobjective optimization to reconstruct interferometric data” in collaboration with two colleagues.
Who is Alejandro Mus?
Alejandro Mus is an expert in mathematical optimization, with an outstanding career in the research and development of advanced analytics solutions. His extensive knowledge and dedication have been essential to address the challenges raised in the article, and his contributions have been key to the success of the project.
About the publication
The paper addresses a novel approach to imaging in radio astronomy, a complex inverse problem. Where traditionally, multi-criteria (or multi-objective) optimization has been used together with genetic algorithms to convert telescope data into a set of images more quickly and cheaply.
The research proposes a multi-objective optimization problem together with genetic algorithms to obtain a set of black hole images, taking into account technological limitations.
On the other hand, they have applied artificial intelligence to group the solutions into groups (clusters) and have automated the choice of the “best” photograph in an agnostic manner.
Thanks to multi-objective optimization and genetic algorithms, images can be reconstructed without losing quality and with a reduction in the computing costs necessary to obtain them. Likewise, the flexibility of genetic algorithms and multi-criteria optimization takes on special relevance when the problems are highly complex, involving numerous variables with many decisions that cannot be related to each other in a simple way, or that could even seem contradictory.
In the attached image, we can see the set of images obtained by the researchers’ algorithm and grouped into groups (clusters) of the M87 black hole.
For more details about the article, visit the link.
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