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When Least Is Best: How Mathematicians Discovered Many Clever Ways to Make Things as Small (or as Large) as Possible

When Least Is Best: How Mathematicians Discovered Many Clever Ways to Make Things as Small (or as Large) as Possible

          
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About the Book

A mathematical journey through the most fascinating problems of extremes and how to solve them

What is the best way to photograph a speeding bullet? How can lost hikers find their way out of a forest? Why does light move through glass in the least amount of time possible? When Least Is Best combines the mathematical history of extrema with contemporary examples to answer these intriguing questions and more. Paul Nahin shows how life often works at the extremes--with values becoming as small (or as large) as possible--and he considers how mathematicians over the centuries, including Descartes, Fermat, and Kepler, have grappled with these problems of minima and maxima. Throughout, Nahin examines entertaining conundrums, such as how to build the shortest bridge possible between two towns, how to vary speed during a race, and how to make the perfect basketball shot. Moving from medieval writings and modern calculus to the field of optimization, the engaging and witty explorations of When Least Is Best will delight math enthusiasts everywhere.


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Product Details
  • ISBN-13: 9780691218762
  • Publisher: Princeton University Press
  • Publisher Imprint: Princeton University Press
  • Height: 211 mm
  • No of Pages: 406
  • Series Title: Princeton Science Library
  • Sub Title: How Mathematicians Discovered Many Clever Ways to Make Things as Small (or as Large) as Possible
  • Width: 140 mm
  • ISBN-10: 0691218765
  • Publisher Date: 18 May 2021
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Spine Width: 30 mm
  • Weight: 520 gr


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When Least Is Best: How Mathematicians Discovered Many Clever Ways to Make Things as Small (or as Large) as Possible
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When Least Is Best: How Mathematicians Discovered Many Clever Ways to Make Things as Small (or as Large) as Possible
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