A Raum with a View: Hermann Weyl and the Problem of Space
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A Geometric Take on Metric Learning
A Geometric take on Metric Learning Søren Hauberg Oren Freifeld Michael J. Black MPI for Intelligent Systems Brown University MPI for Intelligent Systems Tubingen,¨ Germany Providence, US Tubingen,¨ Germany [email protected] [email protected] [email protected] Abstract Multi-metric learning techniques learn local metric tensors in different parts of a feature space. With such an approach, even simple classifiers can be competitive with the state-of-the-art because the distance measure locally adapts to the struc- ture of the data. The learned distance measure is, however, non-metric, which has prevented multi-metric learning from generalizing to tasks such as dimensional- ity reduction and regression in a principled way. We prove that, with appropriate changes, multi-metric learning corresponds to learning the structure of a Rieman- nian manifold. We then show that this structure gives us a principled way to perform dimensionality reduction and regression according to the learned metrics. Algorithmically, we provide the first practical algorithm for computing geodesics according to the learned metrics, as well as algorithms for computing exponential and logarithmic maps on the Riemannian manifold. Together, these tools let many Euclidean algorithms take advantage of multi-metric learning. We illustrate the approach on regression and dimensionality reduction tasks that involve predicting measurements of the human body from shape data. 1 Learning and Computing Distances Statistics relies on measuring distances. When the Euclidean metric is insufficient, as is the case in many real problems, standard methods break down. This is a key motivation behind metric learning, which strives to learn good distance measures from data. -
Computer Oral History Collection, 1969-1973, 1977
Computer Oral History Collection, 1969-1973, 1977 INTERVIEWEES: John Todd & Olga Taussky Todd INTERVIEWER: Henry S. Tropp DATE OF INTERVIEW: July 12, 1973 Tropp: This is a discussion with Doctor and Mrs. Todd in their apartment at the University of Michigan on July 2nd, l973. This question that I asked you earlier, Mrs. Todd, about your early meetings with Von Neumann, I think are just worth recording for when you first met him and when you first saw him. Olga Tauskky Todd: Well, I first met him and saw him at that time. I actually met him at that location, he was lecturing in the apartment of Menger to a private little set. Tropp: This was Karl Menger's apartment in Vienna? Olga Tauskky Todd: In Vienna, and he was on his honeymoon. And he lectured--I've forgotten what it was about, I am ashamed to say. It would come back, you know. It would come back, but I cannot recall it at this moment. It had nothing to do with game theory. I don't know, something in.... John Todd: She has a very good memory. It will come back. Tropp: Right. Approximately when was this? Before l930? Olga Tauskky Todd: For additional information, contact the Archives Center at 202.633.3270 or [email protected] Computer Oral History Collection, 1969-1973, 1977 No. I think it may have been in 1932 or something like that. Tropp: In '32. Then you said you saw him again at Goettingen, after the-- Olga Tauskky Todd: I saw him at Goettingen. -
Council for Innovative Research Peer Review Research Publishing System
ISSN 2347-3487 Einstein's gravitation is Einstein-Grossmann's equations Alfonso Leon Guillen Gomez Independent scientific researcher, Bogota, Colombia E-mail: [email protected] Abstract While the philosophers of science discuss the General Relativity, the mathematical physicists do not question it. Therefore, there is a conflict. From the theoretical point view “the question of precisely what Einstein discovered remains unanswered, for we have no consensus over the exact nature of the theory's foundations. Is this the theory that extends the relativity of motion from inertial motion to accelerated motion, as Einstein contended? Or is it just a theory that treats gravitation geometrically in the spacetime setting?”. “The voices of dissent proclaim that Einstein was mistaken over the fundamental ideas of his own theory and that their basic principles are simply incompatible with this theory. Many newer texts make no mention of the principles Einstein listed as fundamental to his theory; they appear as neither axiom nor theorem. At best, they are recalled as ideas of purely historical importance in the theory's formation. The very name General Relativity is now routinely condemned as a misnomer and its use often zealously avoided in favour of, say, Einstein's theory of gravitation What has complicated an easy resolution of the debate are the alterations of Einstein's own position on the foundations of his theory”, (Norton, 1993) [1]. Of other hand from the mathematical point view the “General Relativity had been formulated as a messy set of partial differential equations in a single coordinate system. People were so pleased when they found a solution that they didn't care that it probably had no physical significance” (Hawking and Penrose, 1996) [2]. -
Arxiv:1601.07125V1 [Math.HO]
CHALLENGES TO SOME PHILOSOPHICAL CLAIMS ABOUT MATHEMATICS ELIAHU LEVY Abstract. In this note some philosophical thoughts and observations about mathematics are ex- pressed, arranged as challenges to some common claims. For many of the “claims” and ideas in the “challenges” see the sources listed in the references. .1. Claim. The Antinomies in Set Theory, such as the Russell Paradox, just show that people did not have a right concept about sets. Having the right concept, we get rid of any contradictions. Challenge. It seems that this cannot be honestly said, when often in “axiomatic” set theory the same reasoning that leads to the Antinomies (say to the Russell Paradox) is used to prove theorems – one does not get to the contradiction, but halts before the “catastrophe” to get a theorem. As if the reasoning that led to the Antinomies was not “illegitimate”, a result of misunderstanding, but we really have a contradiction (antinomy) which we, somewhat artificially, “cut”, by way of the axioms, to save our consistency. One may say that the phenomena described in the famous G¨odel’s Incompleteness Theorem are a reflection of the Antinomies and the resulting inevitability of an axiomatics not entirely parallel to intuition. Indeed, G¨odel’s theorem forces us to be presented with a statement (say, the consistency of Arithmetics or of Set Theory) which we know we cannot prove, while intuition puts a “proof” on the tip of our tongue, so to speak (that’s how we “know” that the statement is true!), but which our axiomatics, forced to deviate from intuition to be consistent, cannot recognize. -
K-Theory and Algebraic Geometry
http://dx.doi.org/10.1090/pspum/058.2 Recent Titles in This Series 58 Bill Jacob and Alex Rosenberg, editors, ^-theory and algebraic geometry: Connections with quadratic forms and division algebras (University of California, Santa Barbara) 57 Michael C. Cranston and Mark A. Pinsky, editors, Stochastic analysis (Cornell University, Ithaca) 56 William J. Haboush and Brian J. Parshall, editors, Algebraic groups and their generalizations (Pennsylvania State University, University Park, July 1991) 55 Uwe Jannsen, Steven L. Kleiman, and Jean-Pierre Serre, editors, Motives (University of Washington, Seattle, July/August 1991) 54 Robert Greene and S. T. Yau, editors, Differential geometry (University of California, Los Angeles, July 1990) 53 James A. Carlson, C. Herbert Clemens, and David R. Morrison, editors, Complex geometry and Lie theory (Sundance, Utah, May 1989) 52 Eric Bedford, John P. D'Angelo, Robert E. Greene, and Steven G. Krantz, editors, Several complex variables and complex geometry (University of California, Santa Cruz, July 1989) 51 William B. Arveson and Ronald G. Douglas, editors, Operator theory/operator algebras and applications (University of New Hampshire, July 1988) 50 James Glimm, John Impagliazzo, and Isadore Singer, editors, The legacy of John von Neumann (Hofstra University, Hempstead, New York, May/June 1988) 49 Robert C. Gunning and Leon Ehrenpreis, editors, Theta functions - Bowdoin 1987 (Bowdoin College, Brunswick, Maine, July 1987) 48 R. O. Wells, Jr., editor, The mathematical heritage of Hermann Weyl (Duke University, Durham, May 1987) 47 Paul Fong, editor, The Areata conference on representations of finite groups (Humboldt State University, Areata, California, July 1986) 46 Spencer J. Bloch, editor, Algebraic geometry - Bowdoin 1985 (Bowdoin College, Brunswick, Maine, July 1985) 45 Felix E. -
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. -
Lecture 2 Tangent Space, Differential Forms, Riemannian Manifolds
Lecture 2 tangent space, differential forms, Riemannian manifolds differentiable manifolds A manifold is a set that locally look like Rn. For example, a two-dimensional sphere S2 can be covered by two subspaces, one can be the northen hemisphere extended slightly below the equator and another can be the southern hemisphere extended slightly above the equator. Each patch can be mapped smoothly into an open set of R2. In general, a manifold M consists of a family of open sets Ui which covers M, i.e. iUi = M, n ∪ and, for each Ui, there is a continuous invertible map ϕi : Ui R . To be precise, to define → what we mean by a continuous map, we has to define M as a topological space first. This requires a certain set of properties for open sets of M. We will discuss this in a couple of weeks. For now, we assume we know what continuous maps mean for M. If you need to know now, look at one of the standard textbooks (e.g., Nakahara). Each (Ui, ϕi) is called a coordinate chart. Their collection (Ui, ϕi) is called an atlas. { } The map has to be one-to-one, so that there is an inverse map from the image ϕi(Ui) to −1 Ui. If Ui and Uj intersects, we can define a map ϕi ϕj from ϕj(Ui Uj)) to ϕi(Ui Uj). ◦ n ∩ ∩ Since ϕj(Ui Uj)) to ϕi(Ui Uj) are both subspaces of R , we express the map in terms of n ∩ ∩ functions and ask if they are differentiable. -
5. the Inverse Function Theorem We Now Want to Aim for a Version of the Inverse Function Theorem
5. The inverse function theorem We now want to aim for a version of the Inverse function Theorem. In differential geometry, the inverse function theorem states that if a function is an isomorphism on tangent spaces, then it is locally an isomorphism. Unfortunately this is too much to expect in algebraic geometry, since the Zariski topology is too weak for this to be true. For example consider a curve which double covers another curve. At any point where there are two points in the fibre, the map on tangent spaces is an isomorphism. But there is no Zariski neighbourhood of any point where the map is an isomorphism. Thus a minimal requirement is that the morphism is a bijection. Note that this is not enough in general for a morphism between al- gebraic varieties to be an isomorphism. For example in characteristic p, Frobenius is nowhere smooth and even in characteristic zero, the parametrisation of the cuspidal cubic is a bijection but not an isomor- phism. Lemma 5.1. If f : X −! Y is a projective morphism with finite fibres, then f is finite. Proof. Since the result is local on the base, we may assume that Y is affine. By assumption X ⊂ Y × Pn and we are projecting onto the first factor. Possibly passing to a smaller open subset of Y , we may assume that there is a point p 2 Pn such that X does not intersect Y × fpg. As the blow up of Pn at p, fibres over Pn−1 with fibres isomorphic to P1, and the composition of finite morphisms is finite, we may assume that n = 1, by induction on n. -
Relativistic Quantum Mechanics 1
Relativistic Quantum Mechanics 1 The aim of this chapter is to introduce a relativistic formalism which can be used to describe particles and their interactions. The emphasis 1.1 SpecialRelativity 1 is given to those elements of the formalism which can be carried on 1.2 One-particle states 7 to Relativistic Quantum Fields (RQF), which underpins the theoretical 1.3 The Klein–Gordon equation 9 framework of high energy particle physics. We begin with a brief summary of special relativity, concentrating on 1.4 The Diracequation 14 4-vectors and spinors. One-particle states and their Lorentz transforma- 1.5 Gaugesymmetry 30 tions follow, leading to the Klein–Gordon and the Dirac equations for Chaptersummary 36 probability amplitudes; i.e. Relativistic Quantum Mechanics (RQM). Readers who want to get to RQM quickly, without studying its foun- dation in special relativity can skip the first sections and start reading from the section 1.3. Intrinsic problems of RQM are discussed and a region of applicability of RQM is defined. Free particle wave functions are constructed and particle interactions are described using their probability currents. A gauge symmetry is introduced to derive a particle interaction with a classical gauge field. 1.1 Special Relativity Einstein’s special relativity is a necessary and fundamental part of any Albert Einstein 1879 - 1955 formalism of particle physics. We begin with its brief summary. For a full account, refer to specialized books, for example (1) or (2). The- ory oriented students with good mathematical background might want to consult books on groups and their representations, for example (3), followed by introductory books on RQM/RQF, for example (4). -
Quantum Mechanics Digital Physics
Quantum Mechanics_digital physics In physics and cosmology, digital physics is a collection of theoretical perspectives based on the premise that the universe is, at heart, describable byinformation, and is therefore computable. Therefore, according to this theory, the universe can be conceived of as either the output of a deterministic or probabilistic computer program, a vast, digital computation device, or mathematically isomorphic to such a device. Digital physics is grounded in one or more of the following hypotheses; listed in order of decreasing strength. The universe, or reality: is essentially informational (although not every informational ontology needs to be digital) is essentially computable (the pancomputationalist position) can be described digitally is in essence digital is itself a computer (pancomputationalism) is the output of a simulated reality exercise History Every computer must be compatible with the principles of information theory,statistical thermodynamics, and quantum mechanics. A fundamental link among these fields was proposed by Edwin Jaynes in two seminal 1957 papers.[1]Moreover, Jaynes elaborated an interpretation of probability theory as generalized Aristotelian logic, a view very convenient for linking fundamental physics withdigital computers, because these are designed to implement the operations ofclassical logic and, equivalently, of Boolean algebra.[2] The hypothesis that the universe is a digital computer was pioneered by Konrad Zuse in his book Rechnender Raum (translated into English as Calculating Space). The term digital physics was first employed by Edward Fredkin, who later came to prefer the term digital philosophy.[3] Others who have modeled the universe as a giant computer include Stephen Wolfram,[4] Juergen Schmidhuber,[5] and Nobel laureate Gerard 't Hooft.[6] These authors hold that the apparentlyprobabilistic nature of quantum physics is not necessarily incompatible with the notion of computability. -
The Orientation Manifesto (For Undergraduates)
The Orientation Manifesto (for undergraduates) Timothy E. Goldberg 11 November 2007 An orientation of a vector space is represented by an ordered basis of the vector space. We think of an orientation as a twirl, namely the twirl that rotates the first basis vector to the second, and the second to the third, and so on. Two ordered bases represent the same orientation if they generate the same twirl. (This amounts to the linear transformation taking one basis to the other having positive determinant.) If you think about it carefully, there are only ever two choices of twirls, and hence only two choices of orientation. n Because each R has a standard choice of ordered basis, fe1; e2; : : : ; eng (where ei is has 1 in the ith coordinates and 0 everywhere else), each Rn has a standard choice of orientation. The standard orientation of R is the twirl that points in the positive direction. The standard orientation of R2 is the counterclockwise twirl, moving from 3 e1 = (1; 0) to e2 = (0; 1). The standard orientation of R is a twirl that sweeps from the positive x direction to the positive y direction, and up the positive z direction. It's like a directed helix, pointed up and spinning in the counterclockwise direction if viewed from above. See Figure 1. An orientation of a curve, or a surface, or a solid body, is really a choice of orientations of every single tangent space, in such a way that the twirls all agree with each other. (This can be made horribly precise, when necessary.) There are several ways for a manifold to pick up an orientation. -
On Manifolds of Negative Curvature, Geodesic Flow, and Ergodicity
ON MANIFOLDS OF NEGATIVE CURVATURE, GEODESIC FLOW, AND ERGODICITY CLAIRE VALVA Abstract. We discuss geodesic flow on manifolds of negative sectional curva- ture. We find that geodesic flow is ergodic on the tangent bundle of a manifold, and present the proof for both n = 2 on surfaces and general n. Contents 1. Introduction 1 2. Riemannian Manifolds 1 2.1. Geodesic Flow 2 2.2. Horospheres and Horocycle Flows 3 2.3. Curvature 4 2.4. Jacobi Fields 4 3. Anosov Flows 4 4. Ergodicity 5 5. Surfaces of Negative Curvature 6 5.1. Fuchsian Groups and Hyperbolic Surfaces 6 6. Geodesic Flow on Hyperbolic Surfaces 7 7. The Ergodicity of Geodesic Flow on Compact Manifolds of Negative Sectional Curvature 8 7.1. Foliations and Absolute Continuity 9 7.2. Proof of Ergodicity 12 Acknowledgments 14 References 14 1. Introduction We want to understand the behavior of geodesic flow on a manifold M of constant negative curvature. If we consider a vector in the unit tangent bundle of M, where does that vector go (or not go) when translated along its unique geodesic path. In a sense, we will show that the vector goes \everywhere," or that the vector visits a full measure subset of T 1M. 2. Riemannian Manifolds We first introduce some of the initial definitions and concepts that allow us to understand Riemannian manifolds. Date: August 2019. 1 2 CLAIRE VALVA Definition 2.1. If M is a differentiable manifold and α :(−, ) ! M is a dif- ferentiable curve, where α(0) = p 2 M, then the tangent vector to the curve α at t = 0 is a function α0(0) : D ! R, where d(f ◦ α) α0(0)f = j dt t=0 for f 2 D, where D is the set of functions on M that are differentiable at p.