Spherical Law of Cosines
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Spheres in Infinite-Dimensional Normed Spaces Are Lipschitz Contractible
PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 88. Number 3, July 1983 SPHERES IN INFINITE-DIMENSIONAL NORMED SPACES ARE LIPSCHITZ CONTRACTIBLE Y. BENYAMINI1 AND Y. STERNFELD Abstract. Let X be an infinite-dimensional normed space. We prove the following: (i) The unit sphere {x G X: || x II = 1} is Lipschitz contractible. (ii) There is a Lipschitz retraction from the unit ball of JConto the unit sphere. (iii) There is a Lipschitz map T of the unit ball into itself without an approximate fixed point, i.e. inffjjc - Tx\\: \\x\\ « 1} > 0. Introduction. Let A be a normed space, and let Bx — {jc G X: \\x\\ < 1} and Sx = {jc G X: || jc || = 1} be its unit ball and unit sphere, respectively. Brouwer's fixed point theorem states that when X is finite dimensional, every continuous self-map of Bx admits a fixed point. Two equivalent formulations of this theorem are the following. 1. There is no continuous retraction from Bx onto Sx. 2. Sx is not contractible, i.e., the identity map on Sx is not homotopic to a constant map. It is well known that none of these three theorems hold in infinite-dimensional spaces (see e.g. [1]). The natural generalization to infinite-dimensional spaces, however, would seem to require the maps to be uniformly-continuous and not merely continuous. Indeed in the finite-dimensional case this condition is automatically satisfied. In this article we show that the above three theorems fail, in the infinite-dimen- sional case, even under the strongest uniform-continuity condition, namely, for maps satisfying a Lipschitz condition. -
Examples of Manifolds
Examples of Manifolds Example 1 (Open Subset of IRn) Any open subset, O, of IRn is a manifold of dimension n. One possible atlas is A = (O, ϕid) , where ϕid is the identity map. That is, ϕid(x) = x. n Of course one possible choice of O is IR itself. Example 2 (The Circle) The circle S1 = (x,y) ∈ IR2 x2 + y2 = 1 is a manifold of dimension one. One possible atlas is A = {(U , ϕ ), (U , ϕ )} where 1 1 1 2 1 y U1 = S \{(−1, 0)} ϕ1(x,y) = arctan x with − π < ϕ1(x,y) <π ϕ1 1 y U2 = S \{(1, 0)} ϕ2(x,y) = arctan x with 0 < ϕ2(x,y) < 2π U1 n n n+1 2 2 Example 3 (S ) The n–sphere S = x =(x1, ··· ,xn+1) ∈ IR x1 +···+xn+1 =1 n A U , ϕ , V ,ψ i n is a manifold of dimension . One possible atlas is 1 = ( i i) ( i i) 1 ≤ ≤ +1 where, for each 1 ≤ i ≤ n + 1, n Ui = (x1, ··· ,xn+1) ∈ S xi > 0 ϕi(x1, ··· ,xn+1)=(x1, ··· ,xi−1,xi+1, ··· ,xn+1) n Vi = (x1, ··· ,xn+1) ∈ S xi < 0 ψi(x1, ··· ,xn+1)=(x1, ··· ,xi−1,xi+1, ··· ,xn+1) n So both ϕi and ψi project onto IR , viewed as the hyperplane xi = 0. Another possible atlas is n n A2 = S \{(0, ··· , 0, 1)}, ϕ , S \{(0, ··· , 0, −1)},ψ where 2x1 2xn ϕ(x , ··· ,xn ) = , ··· , 1 +1 1−xn+1 1−xn+1 2x1 2xn ψ(x , ··· ,xn ) = , ··· , 1 +1 1+xn+1 1+xn+1 are the stereographic projections from the north and south poles, respectively. -
Plane Trigonometry - Lecture 16 Section 3.2: the Law of Cosines
Plane Trigonometry - Lecture 16 Section 3.2: The Law of Cosines Summary: http://www.math.ksu.edu/~gerald/math150/sum16.pdf Course page: http://www.math.ksu.edu/~gerald/math150/ Gerald Hoehn April 1, 2019 Law of cosines Theorem Let ∆ABC any triangle, then c2 = a2 + b2 − 2ab cos γ b2 = a2 + c2 − 2ac cos β a2 = b2 + c2 − 2bc cos α We may reformulate the statement also in word form. Theorem In any triangle, the square of the length of a side equals the sum of the squares of the length of the other two sides minus twice the product of the length of the other two sides and the cosine of the angle between them. Solving Triangles For solving triangles ∆ABC one needs at least three of the six quantities a, b, and c and α, β, γ. One distinguishes six essential different cases forming three classes: I AAA case: Three angles given. I AAS case: Two angles and a side opposite one of them given. I ASA case: Two angles and the side between them given. I SSA case: Two sides and an angle opposite one of them given. I SAS case: Two sides and the angle between them given. I SSS case: Three sides given. The case AAA cannot be solved. The cases AAS, ASA and SSA are solved by using the law of sines. The cases SAS, SSS are solved by using the law of cosines. Solving Triangles: the SAS case For the SAS case a unique solution always exists. Three steps: 1. Use the law of cosines to determine the length of the third side opposite to the given angle. -
6.2 Law of Cosines
6.2 Law of Cosines The Law of Sines can’t be used directly to solve triangles if we know two sides and the angle between them or if we know all three sides. In this two cases, the Law of Cosines applies. Law of Cosines: In any triangle ABC , we have a2 b 2 c 2 2 bc cos A b2 a 2 c 2 2 ac cos B c2 a 2 b 2 2 ab cos C Proof: To prove the Law of Cosines, place triangle so that A is at the origin, as shown in the Figure below. The coordinates of the vertices BC and are (c ,0) and (b cos A , b sin A ) , respectively. Using the Distance Formula, we have a2( c b cos) A 2 (0 b sin) A 2 =c2 2bc cos A b 2 cos 2 A b 2 sin 2 A =c2 2bc cos A b 2 (cos 2 A sin 2 A ) =c22 2bc cos A b =b22 c 2 bc cos A Example: A tunnel is to be built through a mountain. To estimate the length of the tunnel, a surveyor makes the measurements shown in the Figure below. Use the surveyor’s data to approximate the length of the tunnel. Solution: c2 a 2 b 2 2 ab cos C 21222 388 2 212 388cos82.4 173730.23 c 173730.23 416.8 Thus, the tunnel will be approximately 417 ft long. Example: The sides of a triangle are a5, b 8, and c 12. Find the angles of the triangle. -
Convolution on the N-Sphere with Application to PDF Modeling Ivan Dokmanic´, Student Member, IEEE, and Davor Petrinovic´, Member, IEEE
IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 58, NO. 3, MARCH 2010 1157 Convolution on the n-Sphere With Application to PDF Modeling Ivan Dokmanic´, Student Member, IEEE, and Davor Petrinovic´, Member, IEEE Abstract—In this paper, we derive an explicit form of the convo- emphasis on wavelet transform in [8]–[12]. Computation of the lution theorem for functions on an -sphere. Our motivation comes Fourier transform and convolution on groups is studied within from the design of a probability density estimator for -dimen- the theory of noncommutative harmonic analysis. Examples sional random vectors. We propose a probability density function (pdf) estimation method that uses the derived convolution result of applications of noncommutative harmonic analysis in engi- on . Random samples are mapped onto the -sphere and esti- neering are analysis of the motion of a rigid body, workspace mation is performed in the new domain by convolving the samples generation in robotics, template matching in image processing, with the smoothing kernel density. The convolution is carried out tomography, etc. A comprehensive list with accompanying in the spectral domain. Samples are mapped between the -sphere theory and explanations is given in [13]. and the -dimensional Euclidean space by the generalized stereo- graphic projection. We apply the proposed model to several syn- Statistics of random vectors whose realizations are observed thetic and real-world data sets and discuss the results. along manifolds embedded in Euclidean spaces are commonly termed directional statistics. An excellent review may be found Index Terms—Convolution, density estimation, hypersphere, hy- perspherical harmonics, -sphere, rotations, spherical harmonics. in [14]. It is of interest to develop tools for the directional sta- tistics in analogy with the ordinary Euclidean. -
Minkowski Products of Unit Quaternion Sets 1 Introduction
Minkowski products of unit quaternion sets 1 Introduction The Minkowski sum A⊕B of two point sets A; B 2 Rn is the set of all points generated [16] by the vector sums of points chosen independently from those sets, i.e., A ⊕ B := f a + b : a 2 A and b 2 B g : (1) The Minkowski sum has applications in computer graphics, geometric design, image processing, and related fields [9, 11, 12, 13, 14, 15, 20]. The validity of the definition (1) in Rn for all n ≥ 1 stems from the straightforward extension of the vector sum a + b to higher{dimensional Euclidean spaces. However, to define a Minkowski product set A ⊗ B := f a b : a 2 A and b 2 B g ; (2) it is necessary to specify products of points in Rn. In the case n = 1, this is simply the real{number product | the resulting algebra of point sets in R1 is called interval arithmetic [17, 18] and is used to monitor the propagation of uncertainty through computations in which the initial operands (and possibly also the arithmetic operations) are not precisely determined. A natural realization of the Minkowski product (2) in R2 may be achieved [7] by interpreting the points a and b as complex numbers, with a b being the usual complex{number product. Algorithms to compute Minkowski products of complex{number sets have been formulated [6], and extended to determine Minkowski roots and powers [3, 8] of complex sets; to evaluate polynomials specified by complex{set coefficients and arguments [4]; and to solve simple equations expressed in terms of complex{set coefficients and unknowns [5]. -
5.4 Law of Cosines and Solving Triangles (Slides 4-To-1).Pdf
Solving Triangles and the Law of Cosines In this section we work out the law of cosines from our earlier identities and then practice applying this new identity. c2 = a2 + b2 − 2ab cos C: (1) Elementary Functions Draw the triangle 4ABC on the Cartesian plane with the vertex C at the Part 5, Trigonometry origin. Lecture 5.4a, The Law of Cosines Dr. Ken W. Smith Sam Houston State University 2013 In the drawing sin C = y and cos C = x : We may relabel the x and y Smith (SHSU) Elementary Functions 2013 1 / 22 Smith (SHSU) b Elementary Functionsb 2013 2 / 22 coordinates of A(x; y) as x = b cos C and y = b sin C: Solving Triangles and the Law of Cosines One Angle and the Law of Cosines We get information if we compute c2: By the Pythagorean theorem, c2 = (y2) + (a − x)2 = (b sin C)2 + (a − b cos C)2 = b2 sin2 C + a2 − 2ab cos C + b2 cos2 C: c2 = a2 + b2 − 2ab cos C: We use the Pythagorean identity to simplify b2 sin2 C + b2 cos2 C = b2 and so It is straightforward to use the law of cosines when we know one angle and c2 = a2 + b2 − 2ab cos C its two adjacent sides. This is the Side-Angle-Side (SAS) case, in which we may label the angle C and its two sides a and b and so we can solve for the side c. Or, if we have the Side-Side-Side (SSS) situation, in which we know all three sides, we can label one angle C and solve for that angle in terms of the sides a; b and c, using the law of cosines. -
GEOMETRY Contents 1. Euclidean Geometry 2 1.1. Metric Spaces 2 1.2
GEOMETRY JOUNI PARKKONEN Contents 1. Euclidean geometry 2 1.1. Metric spaces 2 1.2. Euclidean space 2 1.3. Isometries 4 2. The sphere 7 2.1. More on cosine and sine laws 10 2.2. Isometries 11 2.3. Classification of isometries 12 3. Map projections 14 3.1. The latitude-longitude map 14 3.2. Stereographic projection 14 3.3. Inversion 14 3.4. Mercator’s projection 16 3.5. Some Riemannian geometry. 18 3.6. Cylindrical projection 18 4. Triangles in the sphere 19 5. Minkowski space 21 5.1. Bilinear forms and Minkowski space 21 5.2. The orthogonal group 22 6. Hyperbolic space 24 6.1. Isometries 25 7. Models of hyperbolic space 30 7.1. Klein’s model 30 7.2. Poincaré’s ball model 30 7.3. The upper halfspace model 31 8. Some geometry and techniques 32 8.1. Triangles 32 8.2. Geodesic lines and isometries 33 8.3. Balls 35 9. Riemannian metrics, area and volume 36 Last update: December 12, 2014. 1 1. Euclidean geometry 1.1. Metric spaces. A function d: X × X ! [0; +1[ is a metric in the nonempty set X if it satisfies the following properties (1) d(x; x) = 0 for all x 2 X and d(x; y) > 0 if x 6= y, (2) d(x; y) = d(y; x) for all x; y 2 X, and (3) d(x; y) ≤ d(x; z) + d(z; y) for all x; y; z 2 X (the triangle inequality). The pair (X; d) is a metric space. -
Lp Unit Spheres and the Α-Geometries: Questions and Perspectives
entropy Article Lp Unit Spheres and the a-Geometries: Questions and Perspectives Paolo Gibilisco Department of Economics and Finance, University of Rome “Tor Vergata”, Via Columbia 2, 00133 Rome, Italy; [email protected] Received: 12 November 2020; Accepted: 10 December 2020; Published: 14 December 2020 Abstract: In Information Geometry, the unit sphere of Lp spaces plays an important role. In this paper, the aim is list a number of open problems, in classical and quantum IG, which are related to Lp geometry. Keywords: Lp spheres; a-geometries; a-Proudman–Johnson equations Gentlemen: there’s lots of room left in Lp spaces. 1. Introduction Chentsov theorem is the fundamental theorem in Information Geometry. After Rao’s remark on the geometric nature of the Fisher Information (in what follows shortly FI), it is Chentsov who showed that on the simplex of the probability vectors, up to scalars, FI is the unique Riemannian geometry, which “contract under noise” (to have an idea of recent developments about this see [1]). So FI appears as the “natural” Riemannian geometry over the manifolds of density vectors, namely over 1 n Pn := fr 2 R j ∑ ri = 1, ri > 0g i Since FI is the pull-back of the map p r ! 2 r it is natural to study the geometries induced on the simplex of probability vectors by the embeddings 8 1 <p · r p p 2 [1, +¥) Ap(r) = :log(r) p = +¥ Setting 2 p = a 2 [−1, 1] 1 − a we call the corresponding geometries on the simplex of probability vectors a-geometries (first studied by Chentsov himself). -
17 Measure Concentration for the Sphere
17 Measure Concentration for the Sphere In today’s lecture, we will prove the measure concentration theorem for the sphere. Recall that this was one of the vital steps in the analysis of the Arora-Rao-Vazirani approximation algorithm for sparsest cut. Most of the material in today’s lecture is adapted from Matousek’s book [Mat02, chapter 14] and Keith Ball’s lecture notes on convex geometry [Bal97]. n n−1 Notation: We will use the notation Bn to denote the ball of unit radius in R and S n to denote the sphere of unit radius in R . Let µ denote the normalized measure on the unit sphere (i.e., for any measurable set S ⊆ Sn−1, µ(A) denotes the ratio of the surface area of µ to the entire surface area of the sphere Sn−1). Recall that the n-dimensional volume of a ball n n n of radius r in R is given by the formula Vol(Bn) · r = vn · r where πn/2 vn = n Γ 2 + 1 Z ∞ where Γ(x) = tx−1e−tdt 0 n−1 The surface area of the unit sphere S is nvn. Theorem 17.1 (Measure Concentration for the Sphere Sn−1) Let A ⊆ Sn−1 be a mea- n−1 surable subset of the unit sphere S such that µ(A) = 1/2. Let Aδ denote the δ-neighborhood n−1 n−1 of A in S . i.e., Aδ = {x ∈ S |∃z ∈ A, ||x − z||2 ≤ δ}. Then, −nδ2/2 µ(Aδ) ≥ 1 − 2e . Thus, the above theorem states that if A is any set of measure 0.5, taking a step of even √ O (1/ n) around A covers almost 99% of the entire sphere. -
On Expansive Mappings
mathematics Article On Expansive Mappings Marat V. Markin and Edward S. Sichel * Department of Mathematics, California State University, Fresno 5245 N. Backer Avenue, M/S PB 108, Fresno, CA 93740-8001, USA; [email protected] * Correspondence: [email protected] Received: 23 August 2019; Accepted: 17 October 2019; Published: 23 October 2019 Abstract: When finding an original proof to a known result describing expansive mappings on compact metric spaces as surjective isometries, we reveal that relaxing the condition of compactness to total boundedness preserves the isometry property and nearly that of surjectivity. While a counterexample is found showing that the converse to the above descriptions do not hold, we are able to characterize boundedness in terms of specific expansions we call anticontractions. Keywords: Metric space; expansion; compactness; total boundedness MSC: Primary 54E40; 54E45; Secondary 46T99 O God, I could be bounded in a nutshell, and count myself a king of infinite space - were it not that I have bad dreams. William Shakespeare (Hamlet, Act 2, Scene 2) 1. Introduction We take a close look at the nature of expansive mappings on certain metric spaces (compact, totally bounded, and bounded), provide a finer classification for such mappings, and use them to characterize boundedness. When finding an original proof to a known result describing all expansive mappings on compact metric spaces as surjective isometries [1] (Problem X.5.13∗), we reveal that relaxing the condition of compactness to total boundedness still preserves the isometry property and nearly that of surjectivity. We provide a counterexample of a not totally bounded metric space, on which the only expansion is the identity mapping, demonstrating that the converse to the above descriptions do not hold. -
Al-Kāshi's Law of Cosines
THEOREM OF THE DAY al-Kashi’s¯ Law of Cosines If A is the angle at one vertex of a triangle, a is the opposite side length, and b and c are the adjacent side lengths, then a2 = b2 + c2 2bc cos A. − = Euclid Book 2, Propositions 12 and 13 + definition of cosine If a triangle has vertices A, B and C and side lengths AB, AC and BC, and if the perpendicular through B to the line through A andC meets this line at D, and if the angle at A is obtuse then BC2 = AB2 + AC2 + 2AC.AD, while if the angle at A is acute then the lastterm on the right-hand-side is subtracted. Euclid’s two propositions supply the Law of Cosines by observing that AD = AB cos(∠DAB) = AB cos 180◦ ∠CAB = AB cos(∠CAB); while in the acute angle − − case (shown above left as the triangle on vertices A, B′, C), the subtracted length AD′ is directly obtained as AB′ cos(∠D′AB′) = AB′ cos(∠CAB′). The Law of Cosines leads naturally to a quadratic equation, as illustrated above right. Angle ∠BAC is given as 120◦; the triangle ABC has base b = 1 and opposite 2 2 2 2 side length a = √2. What is the side length c = AB? We calculate √2 = 1 + c 2 1 c cos 120◦, which gives c + c 1 = 0, with solutions ϕ and 1/ϕ, where − × × − − ϕ = 1 + √5 /2 is the golden ratio. The positive solution is the length of side AB; the negative solution corresponds to the 2nd point where a circle of radius √2 meets the line through A and B.