In uncertain seas, anchors of certainty

Mathematics to Decode Chaos
Date
Wednesday, 14 May, 2025 - 13:30
Location
Room JH 1.6

La Salle-URL is organizing a talk with Eva Miranda, full professor of geometry and topology at the UPC, entitled 'In uncertain seas, anchors of certainty. Mathematics to decipher chaos'. The talk is aimed at students and researchers on campus, especially those from the different areas of knowledge at the La Salle Digital School of Engineering (ETSELS). The talk will be held next Wednesday, May 14, in the room JH 1.6 of the Sant Jaume Hilari building.

Eva Miranda is a professor of geometry and topology at the UPC, recipient of two consecutive ICREA awards (2016 and 2021), and a member of the CRM and IMTECH. She was recently awarded the François Deruyts Prize, awarded by the Royal Academy of the Royal Humboldt Academy. In 2023, she was elected Hardy Lecturer by the London Mathematical Society. GEOMVAP. Recently, together with Marta Mazzocco, he promoted the creation of the SYMCREA excellence unit.

Mathematics to Decode Chaos

For months, scientists around the world have been refining calculations, improving models and simulating scenarios: the asteroid Y4R could hit Earth on Christmas Eve 2032. Everything indicates that it will not. But... can we be sure?

This question opens the door to another, deeper one: are there phenomena that, no matter how much we know the equations, we will never be able to fully predict?

Alan Turing sensed this long before he cracked Enigma. Years before Bletchley Park, he demonstrated that there are undecidable problems: questions that no algorithm can solve. This discovery gave rise to theoretical computing and set clear limits to our ability to calculate... and predict.

And what do 29,000 rubber ducks have to do with it? In 1992, a container fell into the ocean. Even today, ducks appear on beaches around the world. If we know the equations of fluid dynamics, why can't we predict where they will end up?

Between asteroids and rubber ducks we will discover that the limits of prediction are not always a technical problem: sometimes they are a law of nature.