| Speaker : | Guodong Sun |
| Nokia Bell Labs | |
| Date: | 14/02/2024 |
| Time: | 10:30 am - 11:30 am |
| Location: | Room 4B01 |
Abstract
Have you ever wondered how mathematicians “understand”? In a 1932 lecture, Hermann Weyl identified two key modes of mathematical reasoning: topology and abstract algebra. These, he argued, can help us solve problems in a way subject to the Dirichlet principle, minimizing mindless calculations and maximizing insightful thoughts. Recently, Dr. Tai-Danae Bradley took this idea further, suggesting that information theory, using the formular of Shannon entropy, can bridge these two modes of understanding. In this lecture, I’ll explore her fascinating work, “Entropy as a Topological Operad Derivation”, and show how it offers a new way to understand entropy – not just as a measure of disorder, but also as a tool for mathematical reasoning. Join me to gain a fresh perspective on this interesting concept and its potential impact on our understanding of the world.
[1]: Weyl, Hermann. “Part I. Topology and abstract algebra as two roads of mathematical comprehension.” The American mathematical monthly 102.5 (1995): 453-460.
[2]: Weyl, Hermann. “Part II. Topology and Abstract Algebra as Two Roads of Mathematical Comprehension.” The American mathematical monthly 102.7 (1995): 646-651.
[3]: Bradley, Tai-Danae. “Entropy as a topological operad derivation.” Entropy 23.9 (2021): 1195.
[4]: A more accessible version of [3] provided by the same author https://uploads-ssl.webflow.com/649f7839d1d9d9bbdb8bc7ea/650e1fa362d02601b24d560b_bradley_spring22.pdf.