Penguin Press
Shape: The Hidden Geometry of Information, Biology, Strategy, Democracy, and Everything Else
Key Metrics
- Jordan Ellenberg
- Penguin Press
- Hardcover
- 9781984879059
- 9.25 X 6.13 X 1.13 inches
- 1.59 pounds
- Mathematics > Applied
- English
Secure TransactionBook Description
How should a democracy choose its representatives? How can you stop a pandemic from sweeping the world? How do computers learn to play chess, and why is learning chess so much easier for them than learning to read a sentence? Can ancient Greek proportions predict the stock market? (Sorry, no.) What should your kids learn in school if they really want to learn to think? All these are questions about geometry.
For real. If you're like most people, geometry is a sterile and dimly-remembered exercise you gladly left behind in the dust of 9th grade, along with your braces and active romantic interest in pop singers. If you recall any of it, it's plodding through a series of miniscule steps, only to prove some fact about triangles that was obvious to you in the first place. That's not geometry. OK, it is geometry, but only a tiny part, a border section that has as much to do with geometry in all its flush modern richness as conjugating a verb has to do with a great novel.
Shape reveals the geometry underneath some of the most important scientific, political, and philosophical problems we face. Geometry asks: where are things? Which things are near each other? How can you get from one thing to another thing? Those are important questions. The word geometry, from the Greek, has the rather grand meaning of measuring the world. If anything, that's an undersell. Geometry doesn't just measure the world - it explains it. Shape shows us how.
Author Bio
Jordan S. Ellenberg is John D. MacArthur Professor of Mathematics and Vilas Distinguished Achievement Professor of Mathematics at University of Wisconsin Madison.
I've been at Wisconsin since the fall of 2005. My field is arithmetic algebraic geometry: my specific interests include rational points on varieties, asymptotic enumeration of number fields and other arithmetic objects, incidence problems and algebraic methods in combinatorial geometry, Galois representations attached to varieties and their fundamental groups, representation stability and FI-modules, the geometry of large data sets, non-abelian Iwasawa theory, pro-p group theory, automorphic forms, stable cohomology of moduli spaces, the complex of curves, Hilbert-Blumenthal abelian varieties, Q-curves, Serre's conjecture, the ABC conjecture, and Diophantine problems related to all of the above.
My research here is partially supported by an NSF grant, a Kellett Mid-Career Award, and the Office of the Vice Chancellor for Research and Graduate Education, with funding by the Wisconsin Alumni Research Foundation. I co-organize the Wisconsin number theory seminar. I am also a Discovery Fellow at the Wisconsin Institute for Discovery, where I am part of the Machine Learning group and the Institute for Foundations of Data Science. I am a member of the Science Board of IPAM.
Source: University of Wisconsin Madison
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