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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.
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.
The first monograph applying machine learning to problems of geometry
Provides a data-driven introduction to computational algebraic geometry
Delivers a quick introduction to modern data science, with code in popular software (Python, SageMath and Mathematica)
Includes background in geometry, algebra, and theoretical physics
| Erscheinungsjahr: | 2021 |
|---|---|
| Fachbereich: | Arithmetik & Algebra |
| Genre: | Mathematik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Seiten: | 224 |
| Reihe: | Lecture Notes in Mathematics |
| Inhalt: |
xvii
206 S. 10 s/w Illustr. 26 farbige Illustr. 206 p. 36 illus. 26 illus. in color. |
| ISBN-13: | 9783030775612 |
| ISBN-10: | 3030775615 |
| Sprache: | Englisch |
| Ausstattung / Beilage: | Paperback |
| Einband: | Kartoniert / Broschiert |
| Autor: | He, Yang-Hui |
| Auflage: | 1st ed. 2021 |
| Hersteller: |
Springer International Publishing
Springer International Publishing AG Lecture Notes in Mathematics |
| Maße: | 235 x 155 x 13 mm |
| Von/Mit: | Yang-Hui He |
| Erscheinungsdatum: | 02.08.2021 |
| Gewicht: | 0,347 kg |
The first monograph applying machine learning to problems of geometry
Provides a data-driven introduction to computational algebraic geometry
Delivers a quick introduction to modern data science, with code in popular software (Python, SageMath and Mathematica)
Includes background in geometry, algebra, and theoretical physics
| Erscheinungsjahr: | 2021 |
|---|---|
| Fachbereich: | Arithmetik & Algebra |
| Genre: | Mathematik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Seiten: | 224 |
| Reihe: | Lecture Notes in Mathematics |
| Inhalt: |
xvii
206 S. 10 s/w Illustr. 26 farbige Illustr. 206 p. 36 illus. 26 illus. in color. |
| ISBN-13: | 9783030775612 |
| ISBN-10: | 3030775615 |
| Sprache: | Englisch |
| Ausstattung / Beilage: | Paperback |
| Einband: | Kartoniert / Broschiert |
| Autor: | He, Yang-Hui |
| Auflage: | 1st ed. 2021 |
| Hersteller: |
Springer International Publishing
Springer International Publishing AG Lecture Notes in Mathematics |
| Maße: | 235 x 155 x 13 mm |
| Von/Mit: | Yang-Hui He |
| Erscheinungsdatum: | 02.08.2021 |
| Gewicht: | 0,347 kg |
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