Differential Geometry Mikhail G. Katz∗
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A Guide to Symplectic Geometry
OSU — SYMPLECTIC GEOMETRY CRASH COURSE IVO TEREK A GUIDE TO SYMPLECTIC GEOMETRY IVO TEREK* These are lecture notes for the SYMPLECTIC GEOMETRY CRASH COURSE held at The Ohio State University during the summer term of 2021, as our first attempt for a series of mini-courses run by graduate students for graduate students. Due to time and space constraints, many things will have to be omitted, but this should serve as a quick introduction to the subject, as courses on Symplectic Geometry are not currently offered at OSU. There will be many exercises scattered throughout these notes, most of them routine ones or just really remarks, not only useful to give the reader a working knowledge about the basic definitions and results, but also to serve as a self-study guide. And as far as references go, arXiv.org links as well as links for authors’ webpages were provided whenever possible. Columbus, May 2021 *[email protected] Page i OSU — SYMPLECTIC GEOMETRY CRASH COURSE IVO TEREK Contents 1 Symplectic Linear Algebra1 1.1 Symplectic spaces and their subspaces....................1 1.2 Symplectomorphisms..............................6 1.3 Local linear forms................................ 11 2 Symplectic Manifolds 13 2.1 Definitions and examples........................... 13 2.2 Symplectomorphisms (redux)......................... 17 2.3 Hamiltonian fields............................... 21 2.4 Submanifolds and local forms......................... 30 3 Hamiltonian Actions 39 3.1 Poisson Manifolds................................ 39 3.2 Group actions on manifolds.......................... 46 3.3 Moment maps and Noether’s Theorem................... 53 3.4 Marsden-Weinstein reduction......................... 63 Where to go from here? 74 References 78 Index 82 Page ii OSU — SYMPLECTIC GEOMETRY CRASH COURSE IVO TEREK 1 Symplectic Linear Algebra 1.1 Symplectic spaces and their subspaces There is nothing more natural than starting a text on Symplecic Geometry1 with the definition of a symplectic vector space. -
Book: Lectures on Differential Geometry
Lectures on Differential geometry John W. Barrett 1 October 5, 2017 1Copyright c John W. Barrett 2006-2014 ii Contents Preface .................... vii 1 Differential forms 1 1.1 Differential forms in Rn ........... 1 1.2 Theexteriorderivative . 3 2 Integration 7 2.1 Integrationandorientation . 7 2.2 Pull-backs................... 9 2.3 Integrationonachain . 11 2.4 Changeofvariablestheorem. 11 3 Manifolds 15 3.1 Surfaces .................... 15 3.2 Topologicalmanifolds . 19 3.3 Smoothmanifolds . 22 iii iv CONTENTS 3.4 Smoothmapsofmanifolds. 23 4 Tangent vectors 27 4.1 Vectorsasderivatives . 27 4.2 Tangentvectorsonmanifolds . 30 4.3 Thetangentspace . 32 4.4 Push-forwards of tangent vectors . 33 5 Topology 37 5.1 Opensubsets ................. 37 5.2 Topologicalspaces . 40 5.3 Thedefinitionofamanifold . 42 6 Vector Fields 45 6.1 Vectorsfieldsasderivatives . 45 6.2 Velocityvectorfields . 47 6.3 Push-forwardsofvectorfields . 50 7 Examples of manifolds 55 7.1 Submanifolds . 55 7.2 Quotients ................... 59 7.2.1 Projectivespace . 62 7.3 Products.................... 65 8 Forms on manifolds 69 8.1 Thedefinition. 69 CONTENTS v 8.2 dθ ....................... 72 8.3 One-formsandtangentvectors . 73 8.4 Pairingwithvectorfields . 76 8.5 Closedandexactforms . 77 9 Lie Groups 81 9.1 Groups..................... 81 9.2 Liegroups................... 83 9.3 Homomorphisms . 86 9.4 Therotationgroup . 87 9.5 Complexmatrixgroups . 88 10 Tensors 93 10.1 Thecotangentspace . 93 10.2 Thetensorproduct. 95 10.3 Tensorfields. 97 10.3.1 Contraction . 98 10.3.2 Einstein summation convention . 100 10.3.3 Differential forms as tensor fields . 100 11 The metric 105 11.1 Thepull-backmetric . 107 11.2 Thesignature . 108 12 The Lie derivative 115 12.1 Commutator of vector fields . -
Lusternik-Schnirelmann Category and Systolic Category of Low Dimensional Manifolds
LUSTERNIK-SCHNIRELMANN CATEGORY AND SYSTOLIC CATEGORY OF LOW DIMENSIONAL MANIFOLDS1 MIKHAIL G. KATZ∗ AND YULI B. RUDYAK† Abstract. We show that the geometry of a Riemannian mani- fold (M, G) is sensitive to the apparently purely homotopy-theoretic invariant of M known as the Lusternik-Schnirelmann category, denoted catLS(M). Here we introduce a Riemannian analogue of catLS(M), called the systolic category of M. It is denoted catsys(M), and defined in terms of the existence of systolic in- equalities satisfied by every metric G, as initiated by C. Loewner and later developed by M. Gromov. We compare the two cate- gories. In all our examples, the inequality catsys M ≤ catLS M is satisfied, which typically turns out to be an equality, e.g. in dimen- sion 3. We show that a number of existing systolic inequalities can be reinterpreted as special cases of such equality, and that both categories are sensitive to Massey products. The comparison with the value of catLS(M) leads us to prove or conjecture new systolic inequalities on M. Contents Introduction 2 1. Systoles 3 2. Systolic categories 4 3. Categories agree in dimension 2 6 4. Essential manifolds and detecting elements 7 arXiv:math/0410456v2 [math.DG] 20 Dec 2004 5. Inessential manifolds and pullback metrics 8 6. Manifolds of dimension 3 9 1Communications on Pure and Applied Mathematics, to appear. Available at arXiv:math.DG/0410456 Date: August 31, 2018. 1991 Mathematics Subject Classification. Primary 53C23; Secondary 55M30, 57N65 . Key words and phrases. detecting element, essential manifolds, isoperimetric quotient, Lusternik-Schnirelmann category, Massey product, systole. -
MAT 531 Geometry/Topology II Introduction to Smooth Manifolds
MAT 531 Geometry/Topology II Introduction to Smooth Manifolds Claude LeBrun Stony Brook University April 9, 2020 1 Dual of a vector space: 2 Dual of a vector space: Let V be a real, finite-dimensional vector space. 3 Dual of a vector space: Let V be a real, finite-dimensional vector space. Then the dual vector space of V is defined to be 4 Dual of a vector space: Let V be a real, finite-dimensional vector space. Then the dual vector space of V is defined to be ∗ V := fLinear maps V ! Rg: 5 Dual of a vector space: Let V be a real, finite-dimensional vector space. Then the dual vector space of V is defined to be ∗ V := fLinear maps V ! Rg: ∗ Proposition. V is finite-dimensional vector space, too, and 6 Dual of a vector space: Let V be a real, finite-dimensional vector space. Then the dual vector space of V is defined to be ∗ V := fLinear maps V ! Rg: ∗ Proposition. V is finite-dimensional vector space, too, and ∗ dimV = dimV: 7 Dual of a vector space: Let V be a real, finite-dimensional vector space. Then the dual vector space of V is defined to be ∗ V := fLinear maps V ! Rg: ∗ Proposition. V is finite-dimensional vector space, too, and ∗ dimV = dimV: ∗ ∼ In particular, V = V as vector spaces. 8 Dual of a vector space: Let V be a real, finite-dimensional vector space. Then the dual vector space of V is defined to be ∗ V := fLinear maps V ! Rg: ∗ Proposition. V is finite-dimensional vector space, too, and ∗ dimV = dimV: ∗ ∼ In particular, V = V as vector spaces. -
INTRODUCTION to ALGEBRAIC GEOMETRY 1. Preliminary Of
INTRODUCTION TO ALGEBRAIC GEOMETRY WEI-PING LI 1. Preliminary of Calculus on Manifolds 1.1. Tangent Vectors. What are tangent vectors we encounter in Calculus? 2 0 (1) Given a parametrised curve α(t) = x(t); y(t) in R , α (t) = x0(t); y0(t) is a tangent vector of the curve. (2) Given a surface given by a parameterisation x(u; v) = x(u; v); y(u; v); z(u; v); @x @x n = × is a normal vector of the surface. Any vector @u @v perpendicular to n is a tangent vector of the surface at the corresponding point. (3) Let v = (a; b; c) be a unit tangent vector of R3 at a point p 2 R3, f(x; y; z) be a differentiable function in an open neighbourhood of p, we can have the directional derivative of f in the direction v: @f @f @f D f = a (p) + b (p) + c (p): (1.1) v @x @y @z In fact, given any tangent vector v = (a; b; c), not necessarily a unit vector, we still can define an operator on the set of functions which are differentiable in open neighbourhood of p as in (1.1) Thus we can take the viewpoint that each tangent vector of R3 at p is an operator on the set of differential functions at p, i.e. @ @ @ v = (a; b; v) ! a + b + c j ; @x @y @z p or simply @ @ @ v = (a; b; c) ! a + b + c (1.2) @x @y @z 3 with the evaluation at p understood. -
Optimization Algorithms on Matrix Manifolds
00˙AMS September 23, 2007 © Copyright, Princeton University Press. No part of this book may be distributed, posted, or reproduced in any form by digital or mechanical means without prior written permission of the publisher. Index 0x, 55 of a topology, 192 C1, 196 bijection, 193 C∞, 19 blind source separation, 13 ∇2, 109 bracket (Lie), 97 F, 33, 37 BSS, 13 GL, 23 Grass(p, n), 32 Cauchy decrease, 142 JF , 71 Cauchy point, 142 On, 27 Cayley transform, 59 PU,V , 122 chain rule, 195 Px, 47 characteristic polynomial, 6 ⊥ chart Px , 47 Rn×p, 189 around a point, 20 n×p R∗ /GLp, 31 of a manifold, 20 n×p of a set, 18 R∗ , 23 Christoffel symbols, 94 Ssym, 26 − Sn 1, 27 closed set, 192 cocktail party problem, 13 S , 42 skew column space, 6 St(p, n), 26 commutator, 189 X, 37 compact, 27, 193 X(M), 94 complete, 56, 102 ∂ , 35 i conjugate directions, 180 p-plane, 31 connected, 21 S , 58 sym+ connection S (n), 58 upp+ affine, 94 ≃, 30 canonical, 94 skew, 48, 81 Levi-Civita, 97 span, 30 Riemannian, 97 sym, 48, 81 symmetric, 97 tr, 7 continuous, 194 vec, 23 continuously differentiable, 196 convergence, 63 acceleration, 102 cubic, 70 accumulation point, 64, 192 linear, 69 adjoint, 191 order of, 70 algebraic multiplicity, 6 quadratic, 70 arithmetic operation, 59 superlinear, 70 Armijo point, 62 convergent sequence, 192 asymptotically stable point, 67 convex set, 198 atlas, 19 coordinate domain, 20 compatible, 20 coordinate neighborhood, 20 complete, 19 coordinate representation, 24 maximal, 19 coordinate slice, 25 atlas topology, 20 coordinates, 18 cotangent bundle, 108 basis, 6 cotangent space, 108 For general queries, contact [email protected] 00˙AMS September 23, 2007 © Copyright, Princeton University Press. -
SYMPLECTIC GEOMETRY and MECHANICS a Useful Reference Is
GEOMETRIC QUANTIZATION I: SYMPLECTIC GEOMETRY AND MECHANICS A useful reference is Simms and Woodhouse, Lectures on Geometric Quantiza- tion, available online. 1. Symplectic Geometry. 1.1. Linear Algebra. A pre-symplectic form ω on a (real) vector space V is a skew bilinear form ω : V ⊗ V → R. For any W ⊂ V write W ⊥ = {v ∈ V | ω(v, w) = 0 ∀w ∈ W }. (V, ω) is symplectic if ω is non-degenerate: ker ω := V ⊥ = 0. Theorem 1.2. If (V, ω) is symplectic, there is a “canonical” basis P1,...,Pn,Q1,...,Qn such that ω(Pi,Pj) = 0 = ω(Qi,Qj) and ω(Pi,Qj) = δij. Pi and Qi are said to be conjugate. The theorem shows that all symplectic vector spaces of the same (always even) dimension are isomorphic. 1.3. Geometry. A symplectic manifold is one with a non-degenerate 2-form ω; this makes each tangent space TmM into a symplectic vector space with form ωm. We should also assume that ω is closed: dω = 0. We can also consider pre-symplectic manifolds, i.e. ones with a closed 2-form ω, which may be degenerate. In this case we also assume that dim ker ωm is constant; this means that the various ker ωm fit tog ether into a sub-bundle ker ω of TM. Example 1.1. If V is a symplectic vector space, then each TmV = V . Thus the symplectic form on V (as a vector space) determines a symplectic form on V (as a manifold). This is locally the only example: Theorem 1.4. -
3. Introducing Riemannian Geometry
3. Introducing Riemannian Geometry We have yet to meet the star of the show. There is one object that we can place on a manifold whose importance dwarfs all others, at least when it comes to understanding gravity. This is the metric. The existence of a metric brings a whole host of new concepts to the table which, collectively, are called Riemannian geometry.Infact,strictlyspeakingwewillneeda slightly di↵erent kind of metric for our study of gravity, one which, like the Minkowski metric, has some strange minus signs. This is referred to as Lorentzian Geometry and a slightly better name for this section would be “Introducing Riemannian and Lorentzian Geometry”. However, for our immediate purposes the di↵erences are minor. The novelties of Lorentzian geometry will become more pronounced later in the course when we explore some of the physical consequences such as horizons. 3.1 The Metric In Section 1, we informally introduced the metric as a way to measure distances between points. It does, indeed, provide this service but it is not its initial purpose. Instead, the metric is an inner product on each vector space Tp(M). Definition:Ametric g is a (0, 2) tensor field that is: Symmetric: g(X, Y )=g(Y,X). • Non-Degenerate: If, for any p M, g(X, Y ) =0forallY T (M)thenX =0. • 2 p 2 p p With a choice of coordinates, we can write the metric as g = g (x) dxµ dx⌫ µ⌫ ⌦ The object g is often written as a line element ds2 and this expression is abbreviated as 2 µ ⌫ ds = gµ⌫(x) dx dx This is the form that we saw previously in (1.4). -
Symbol Table for Manifolds, Tensors, and Forms Paul Renteln
Symbol Table for Manifolds, Tensors, and Forms Paul Renteln Department of Physics California State University San Bernardino, CA 92407 and Department of Mathematics California Institute of Technology Pasadena, CA 91125 [email protected] August 30, 2015 1 List of Symbols 1.1 Rings, Fields, and Spaces Symbol Description Page N natural numbers 264 Z integers 265 F an arbitrary field 1 R real field or real line 1 n R (real) n space 1 n RP real projective n space 68 n H (real) upper half n-space 167 C complex plane 15 n C (complex) n space 15 1.2 Unary operations Symbol Description Page a¯ complex conjugate 14 X set complement 263 jxj absolute value 16 jXj cardinality of set 264 kxk length of vector 57 [x] equivalence class 264 2 List of Symbols f −1(y) inverse image of y under f 263 f −1 inverse map 264 (−1)σ sign of permutation σ 266 ? hodge dual 45 r (ordinary) gradient operator 73 rX covariant derivative in direction X 182 d exterior derivative 89 δ coboundary operator (on cohomology) 127 δ co-differential operator 222 ∆ Hodge-de Rham Laplacian 223 r2 Laplace-Beltrami operator 242 f ∗ pullback map 95 f∗ pushforward map 97 f∗ induced map on simplices 161 iX interior product 93 LX Lie derivative 102 ΣX suspension 119 @ partial derivative 59 @ boundary operator 143 @∗ coboundary operator (on cochains) 170 [S] simplex generated by set S 141 D vector bundle connection 182 ind(X; p) index of vector field X at p 260 I(f; p) index of f at p 250 1.3 More unary operations Symbol Description Page Ad (big) Ad 109 ad (little) ad 109 alt alternating map -
M7210 Lecture 7. Vector Spaces Part 4, Dual Spaces Wednesday September 5, 2012 Assume V Is an N-Dimensional Vector Space Over a field F
M7210 Lecture 7. Vector Spaces Part 4, Dual Spaces Wednesday September 5, 2012 Assume V is an n-dimensional vector space over a field F. Definition. The dual space of V , denoted V ′ is the set of all linear maps from V to F. Comment. F is an ambiguous object. It may be regarded: (a) as a field, (b) vector space over F, (c) as a vector space equipped with basis, {1}. It is always important to bear in mind which of the three objects we are thinking about. In the definition of V ′, we use (c). The distinctions are often pushed into the background, but let us keep them in clear view for the remainder of this paragraph. Suppose V has basis E = {e1,e2,...,en}. ′ If w ∈ V , then for each ei, there is a unique scalar ω(ei) such that w(ei) = ω(ei)1. Then w = ω(e1) ω(e2) · · · ω(en) . (1) {1}E The columns (of height 1) on the right hand side are the coefficients required to write the images of the basis elements in E in terms of the basis {1}. (The definition of the matrix of a linear map that we gave in the last lecture demands that each entry in the matrix be an element of the scalar field, not of a vector space.) The notation w(ei) = ω(ei)1 is a reminder that w(ei) is an element of the vector space F, while ω(ei) is an element of the field F. But scalar multiplication of elements of the vector space F by elements of the field F is good old fashioned multiplication ∗ : F × F → F. -
A Mathematica Package for Doing Tensor Calculations in Differential Geometry User's Manual
Ricci A Mathematica package for doing tensor calculations in differential geometry User’s Manual Version 1.32 By John M. Lee assisted by Dale Lear, John Roth, Jay Coskey, and Lee Nave 2 Ricci A Mathematica package for doing tensor calculations in differential geometry User’s Manual Version 1.32 By John M. Lee assisted by Dale Lear, John Roth, Jay Coskey, and Lee Nave Copyright c 1992–1998 John M. Lee All rights reserved Development of this software was supported in part by NSF grants DMS-9101832, DMS-9404107 Mathematica is a registered trademark of Wolfram Research, Inc. This software package and its accompanying documentation are provided as is, without guarantee of support or maintenance. The copyright holder makes no express or implied warranty of any kind with respect to this software, including implied warranties of merchantability or fitness for a particular purpose, and is not liable for any damages resulting in any way from its use. Everyone is granted permission to copy, modify and redistribute this software package and its accompanying documentation, provided that: 1. All copies contain this notice in the main program file and in the supporting documentation. 2. All modified copies carry a prominent notice stating who made the last modifi- cation and the date of such modification. 3. No charge is made for this software or works derived from it, with the exception of a distribution fee to cover the cost of materials and/or transmission. John M. Lee Department of Mathematics Box 354350 University of Washington Seattle, WA 98195-4350 E-mail: [email protected] Web: http://www.math.washington.edu/~lee/ CONTENTS 3 Contents 1 Introduction 6 1.1Overview.............................. -
Arxiv:1412.2393V4 [Gr-Qc] 27 Feb 2019 2.6 Geodesics and Normal Coordinates
Riemannian Geometry: Definitions, Pictures, and Results Adam Marsh February 27, 2019 Abstract A pedagogical but concise overview of Riemannian geometry is provided, in the context of usage in physics. The emphasis is on defining and visualizing concepts and relationships between them, as well as listing common confusions, alternative notations and jargon, and relevant facts and theorems. Special attention is given to detailed figures and geometric viewpoints, some of which would seem to be novel to the literature. Topics are avoided which are well covered in textbooks, such as historical motivations, proofs and derivations, and tools for practical calculations. As much material as possible is developed for manifolds with connection (omitting a metric) to make clear which aspects can be readily generalized to gauge theories. The presentation in most cases does not assume a coordinate frame or zero torsion, and the coordinate-free, tensor, and Cartan formalisms are developed in parallel. Contents 1 Introduction 2 2 Parallel transport 3 2.1 The parallel transporter . 3 2.2 The covariant derivative . 4 2.3 The connection . 5 2.4 The covariant derivative in terms of the connection . 6 2.5 The parallel transporter in terms of the connection . 9 arXiv:1412.2393v4 [gr-qc] 27 Feb 2019 2.6 Geodesics and normal coordinates . 9 2.7 Summary . 10 3 Manifolds with connection 11 3.1 The covariant derivative on the tensor algebra . 12 3.2 The exterior covariant derivative of vector-valued forms . 13 3.3 The exterior covariant derivative of algebra-valued forms . 15 3.4 Torsion . 16 3.5 Curvature .