توضیحاتی در مورد کتاب The Calabi–Yau Landscape: From Geometry, to Physics, to Machine Learning (Lecture Notes in Mathematics)
نام کتاب : The Calabi–Yau Landscape: From Geometry, to Physics, to Machine Learning (Lecture Notes in Mathematics)
ویرایش : 1st ed. 2021
عنوان ترجمه شده به فارسی : چشم انداز Calabi–Yau: از هندسه، فیزیک، تا یادگیری ماشین (یادداشت های سخنرانی در ریاضیات)
سری :
نویسندگان : Yang-Hui He
ناشر : Springer
سال نشر : 2021
تعداد صفحات : 214
ISBN (شابک) : 3030775615 , 9783030775612
زبان کتاب : English
فرمت کتاب : pdf
حجم کتاب : 2 مگابایت
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فهرست مطالب :
Preface
Acknowledgements
Contents
1 Prologus Terræ Sanctæ
1.1 A Geometrical Tradition
1.1.1 A Modern Breakthrough
1.1.2 Preliminary Examples: 1,2,? …
1.2 10 = 4 + 2 3: A Physical Motivation
1.2.1 Triadophilia
1.2.2 Caveat and Apology for the Title
1.3 Topological Rudiments
1.3.1 The Hodge Diamond
2 The Compact Landscape
2.1 The Quintic
2.1.1 Topological Quantities: Exact Sequences
2.1.2 Topological Quantities: Computer Algebra
2.2 CICY: Complete Intersection Calabi–Yau
2.2.1 Topological Quantities: Statistics
2.3 Other Datasets
2.3.1 Hypersurfaces in Weighted CP4
2.3.2 Elliptic Fibrations
2.4 An Explosion: The Kreuzer–Skarke Dataset
2.4.1 Reflexive Polytopes
2.4.2 CY Hypersurfaces: Gradus ad Parnassum
2.4.3 1, 16, 4319, 473800776 …
2.5 Cartography of the Compact Landscape
2.6 Epilogue: Recent Developments
2.7 Post Scriptum: Calabi–Yau Metrics
2.7.1 Numerical Metric on the Quintic
3 The Non-Compact Landscape
3.1 Another 10 = 4 + 2 3
3.1.1 Quiver Representations and a Geometer\'s AdS/CFT
3.1.2 The Archetypal Example
3.2 Orbifolds and Quotient Singularities
3.2.1 McKay Correspondence
McKay Quiver for Z/(2 Z)
3.2.2 Beyond ADE
3.3 Toric Calabi-Yau Varieties
3.3.1 Cone over P2
3.3.2 The Conifold
3.3.3 Bipartite Graphs and Brane Tilings
3.4 Cartography of the Affine Landscape
3.4.1 Gorenstein Singularities
3.4.2 The Non-Compact Landscape
4 Machine-Learning the Landscape
4.1 A Typical Problem
4.1.1 WWJD
4.2 Rudiments of Machine-Learning
4.2.1 Regression and a Single Neuron
4.2.2 MLP: Forward Feeding Neural Networks
4.2.3 Convolutional Neural Networks
4.2.4 Some Terminology
4.2.5 Other Common Supervised ML Algorithms
Support Vector Machines
Decision Trees
Naïve Bayes Classifier
Nearest Neighbours
4.2.6 Goodness of Fit
4.3 Machine-Learning Algebraic Geometry
4.3.1 Warm-up: Hypersurface in Weighted P4
ML WP4-Hypersurfaces: Python
ML WP4-Hypersurfaces: Mathematica
Non-NN ML methods
4.3.2 Learning CICYs
4.3.3 More Success Stories in Geometry
4.4 Beyond Algebraic Geometry
4.5 Epilogue
5 Postscriptum
A Some Rudiments of Complex Geometry
A.1 (Co-)Homology
A.2 From Real to Complex to Kähler
A.3 Bundles and Sequences
A.4 Chern Classes
A.5 Covariantly Constant Spinor
A.6 A Lightning Refresher on Toric Varieties
A.6.1 Digressions on Spec and All That
A.6.2 Example: The Conifold
A.6.3 From Cones to Fans
A.7 Dramatis Personae
A.8 The Kodaira Classification of Elliptic Fibrations
B Gröbner Bases: The Heart of Computational Algebraic Geometry
B.1 An Elimination Problem
B.2 Hilbert Series
C Brane Tilings
C.1 Dessins d\'Enfants
D Remembering Logistic Regression
E A Computational Compendium: Homage to SageMath
E.1 Algebraic Varieties
E.2 Combinatorics and Toric Varieties
E.3 Representation Theory
E.4 Number Theory and More
Glossary
References
Index