Often seen as the Nobel Prize for mathematicians, the Abel Prize rewards the work of a mathematician as a whole. Michel Talagrand is thus distinguished for his work in probability theory and stochastic processes. Since its origins, probability theory has been motivated by problems arising from games of chance or risk assessment. The common thread of Michel Talagrand’s revolutionary discoveries lies in the use and understanding of the random processes that surround us. The in-depth understanding of random phenomena has become essential in today’s world. Random algorithms are, for example, the basis of our weather forecasts and our large linguistic models.
The modern world is a constant stream of random events, and understanding this randomness has implications in far-reaching areas, from business logistics to condensed matter physics. His work thus allows us to better understand how and why many phenomena are described by the “Gaussian distribution”, often better known as the “normal distribution” or, thanks to its shape, the “bell curve”. Our entire lives are guided by the Gaussian distribution: the weight of babies at birth, how well students do in school, and the age at which athletes retire are all seemingly random events that follow the distribution perfectly. Gaussian.
Three specific areas
This award distinguishes three specific areas of Michel Talagrand’s work:
- Supremum of stochastic processes – A stochastic process produces a sequence of random values, and the “supremum” is their largest value. If the height of waves crashing on a beach is a stochastic process, knowing what the largest wave will hit the beach next year is useful.
- Concentration of measures – Paradoxically, when a process depends on a series of independent random sources, instead of complicating itself, it is possible for the different random factors to compensate for each other and produce more predictable results. This is what we call the law of large numbers, about which Michel Talagrand has formulated precise quantitative estimates.
- Spin Glass – Beyond the abstract theory of probability, a “spin glass” is a metallic alloy with randomly arranged impurities. Michel Talagrand used his knowledge of statistics and probability to rigorously analyze the behavior of spin glasses, and thus completed the proof of work by Giorgio Parisi, Nobel Prize winner (2021).
Michel Talagrand was born in 1952 in France, and he obtained his doctorate in mathematical sciences in 1977 at the University of Paris VI. He then spent a few years at Ohio State University in the United States. Recruited at the CNRS in 1974, he studied functional analysis there, then probability and their applications, until his retirement in 2017. He was assigned to a laboratory, the Jussieu Mathematics Institute – Paris Rive Gauche under the CNRS, but also to Sorbonne University and Paris Cité University. Michel Talagrand is married and father of two sons. Member of the Academy of Sciences, this former research director of the CNRS has received more than ten prizes including the Shaw Prize in 2019.
“Congratulations to Michel Talagrand, whose exceptional research has had a considerable impact on mathematics and its applications. This prize, which rewards an entire career at the CNRS, testifies to the excellence of French mathematics. It also recalls the absolute urgency of investing in this vital discipline as much for research, for education, for the major challenges of society as for the economy of our country. », underlines Antoine Petit, president and CEO of the CNRS
A video meeting with Michel Talagrand.
Rushes may be available on request from [email protected]
About the Abel Prize
- The award ceremony will take place in Oslo on May 21, 2024.
- The Abel Prize is funded by the Norwegian government and the prize amount is 7.5 million Norwegian crowns
- The prize is awarded by the Norwegian Academy of Science and Letters and presented by King Harald V.
- The choice of the Abel Laureate is based on the recommendation of the Abel Committee, which is made up of five internationally renowned mathematicians.