Speaker: Jens Marklof
Affiliation: University of Bristol, UK
Title: Chance and chaos: how to predict the unpredictable
Date and Time: October 13, 2023, 17:00:00 Hours
Venue: Homi Bhabha Auditorium
Asbtract: We live in a chaotic world: from weather forecasts and natural disasters to political developments, it seems often impossible to even make the most basic predictions. In this lecture I will discuss one of the most fundamental mathematical principles behind such unpredictability: the inherent instability of systems with chaotic behaviour that leads to extreme amplification of the smallest errors in the data. In particular, I will explore with you the legendary question `Does the flap of a butterfly's wings in Brazil set off a tornado in Texas'? (Lorenz 1972) and explain how chaos theory has established the best way of kneading bread dough! By the end of this lecture, I hope to have convinced you of the power of mathematics in the understanding of chaotic systems. And although we will never be able to predict the future with complete certainty, we can forecast likelihoods: the more chaotic, the better!
Affiliation: University of Bristol, UK
Title: Chance and chaos: how to predict the unpredictable
Date and Time: October 13, 2023, 17:00:00 Hours
Venue: Homi Bhabha Auditorium
Asbtract: We live in a chaotic world: from weather forecasts and natural disasters to political developments, it seems often impossible to even make the most basic predictions. In this lecture I will discuss one of the most fundamental mathematical principles behind such unpredictability: the inherent instability of systems with chaotic behaviour that leads to extreme amplification of the smallest errors in the data. In particular, I will explore with you the legendary question `Does the flap of a butterfly's wings in Brazil set off a tornado in Texas'? (Lorenz 1972) and explain how chaos theory has established the best way of kneading bread dough! By the end of this lecture, I hope to have convinced you of the power of mathematics in the understanding of chaotic systems. And although we will never be able to predict the future with complete certainty, we can forecast likelihoods: the more chaotic, the better!