The Calabi–Yau Landscape: From Geometry, to Physics, to Machine Learning (Lecture Notes in Mathematics, 2293)
Language: English
Published by Springer, 2021
- Softcover
- New
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Title
- The Calabi–Yau Landscape: From Geometry, to Physics, to Machine Learning (Lecture Notes in Mathematics, 2293)
- Author
- He, Yang-Hui
- Publisher
- Springer
- Publication year
- 2021
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 3030775615
- ISBN 13
- 9783030775612
- Item weight
- 474 grams
- Series
- Book 1 of 1: Lecture Notes in Mathematics
The study of Calabi–Yau manifolds lies at an exciting intersection between physics and mathematics. Recently, there has been much activity in applying machine learning to solve otherwise intractable problems, to conjecture new formulae, or to understand the underlying structure of mathematics. In this book, insights from string and quantum field theory are combined with powerful techniques from complex and algebraic geometry, then translated into algorithms with the ultimate aim of deriving new information about Calabi–Yau manifolds. While the motivation comes from mathematical physics, the techniques are purely mathematical and the theme is that of explicit calculations. The reader is guided through the theory and provided with explicit computer code in standard software such as SageMath, Python and Mathematica to gain hands-on experience in applications of artificial intelligence to geometry.
Driven by data and written in an informal style, The Calabi–Yau Landscape makes cutting-edge topics in mathematical physics, geometry and machine learning readily accessible to graduate students and beyond. The overriding ambition is to introduce some modern mathematics to the physicist, some modern physics to the mathematician, and machine learning to both.
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Ria Christie Collections
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