A Crash Course in Vectors Lecture 4 : Gradient of a Scalar Function
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General Relativity Fall 2018 Lecture 10: Integration, Einstein-Hilbert Action
General Relativity Fall 2018 Lecture 10: Integration, Einstein-Hilbert action Yacine Ali-Ha¨ımoud (Dated: October 3, 2018) σ σ HW comment: T µν antisym in µν does NOT imply that Tµν is antisym in µν. Volume element { Consider a LICS with primed coordinates. The 4-volume element is dV = d4x0 = 0 0 0 0 dx0 dx1 dx2 dx3 . If we change coordinates, we have 0 ! @xµ d4x0 = det d4x: (1) µ @x Now, the metric components change as 0 0 0 0 @xµ @xν @xµ @xν g = g 0 0 = η 0 0 ; (2) µν @xµ @xν µ ν @xµ @xν µ ν since the metric components are ηµ0ν0 in the LICS. Seing this as a matrix operation and taking the determinant, we find 0 !2 @xµ det(g ) = − det : (3) µν @xµ Hence, we find that the 4-volume element is q 4 p 4 p 4 dV = − det(gµν )d x ≡ −g d x ≡ jgj d x: (4) The integral of a scalar function f is well defined: given any coordinate system (even if only defined locally): Z Z f dV = f pjgj d4x: (5) We can only define the integral of a scalar function. The integral of a vector or tensor field is mean- ingless in curved spacetime. Think of the integral as a sum. To sum vectors, you need them to belong to the same vector space. There is no common vector space in curved spacetime. Only in flat spacetime can we define such integrals. First parallel-transport the vector field to a single point of spacetime (it doesn't matter which one). -
Line, Surface and Volume Integrals
Line, Surface and Volume Integrals 1 Line integrals Z Z Z Á dr; a ¢ dr; a £ dr (1) C C C (Á is a scalar ¯eld and a is a vector ¯eld) We divide the path C joining the points A and B into N small line elements ¢rp, p = 1;:::;N. If (xp; yp; zp) is any point on the line element ¢rp, then the second type of line integral in Eq. (1) is de¯ned as Z XN a ¢ dr = lim a(xp; yp; zp) ¢ rp N!1 C p=1 where it is assumed that all j¢rpj ! 0 as N ! 1. 2 Evaluating line integrals The ¯rst type of line integral in Eq. (1) can be written as Z Z Z Á dr = i Á(x; y; z) dx + j Á(x; y; z) dy C CZ C +k Á(x; y; z) dz C The three integrals on the RHS are ordinary scalar integrals. The second and third line integrals in Eq. (1) can also be reduced to a set of scalar integrals by writing the vector ¯eld a in terms of its Cartesian components as a = axi + ayj + azk. Thus, Z Z a ¢ dr = (axi + ayj + azk) ¢ (dxi + dyj + dzk) C ZC = (axdx + aydy + azdz) ZC Z Z = axdx + aydy + azdz C C C 3 Some useful properties about line integrals: 1. Reversing the path of integration changes the sign of the integral. That is, Z B Z A a ¢ dr = ¡ a ¢ dr A B 2. If the path of integration is subdivided into smaller segments, then the sum of the separate line integrals along each segment is equal to the line integral along the whole path. -
Vector Calculus and Multiple Integrals Rob Fender, HT 2018
Vector Calculus and Multiple Integrals Rob Fender, HT 2018 COURSE SYNOPSIS, RECOMMENDED BOOKS Course syllabus (on which exams are based): Double integrals and their evaluation by repeated integration in Cartesian, plane polar and other specified coordinate systems. Jacobians. Line, surface and volume integrals, evaluation by change of variables (Cartesian, plane polar, spherical polar coordinates and cylindrical coordinates only unless the transformation to be used is specified). Integrals around closed curves and exact differentials. Scalar and vector fields. The operations of grad, div and curl and understanding and use of identities involving these. The statements of the theorems of Gauss and Stokes with simple applications. Conservative fields. Recommended Books: Mathematical Methods for Physics and Engineering (Riley, Hobson and Bence) This book is lazily referred to as “Riley” throughout these notes (sorry, Drs H and B) You will all have this book, and it covers all of the maths of this course. However it is rather terse at times and you will benefit from looking at one or both of these: Introduction to Electrodynamics (Griffiths) You will buy this next year if you haven’t already, and the chapter on vector calculus is very clear Div grad curl and all that (Schey) A nice discussion of the subject, although topics are ordered differently to most courses NB: the latest version of this book uses the opposite convention to polar coordinates to this course (and indeed most of physics), but older versions can often be found in libraries 1 Week One A review of vectors, rotation of coordinate systems, vector vs scalar fields, integrals in more than one variable, first steps in vector differentiation, the Frenet-Serret coordinate system Lecture 1 Vectors A vector has direction and magnitude and is written in these notes in bold e.g. -
Chapter 8 Change of Variables, Parametrizations, Surface Integrals
Chapter 8 Change of Variables, Parametrizations, Surface Integrals x0. The transformation formula In evaluating any integral, if the integral depends on an auxiliary function of the variables involved, it is often a good idea to change variables and try to simplify the integral. The formula which allows one to pass from the original integral to the new one is called the transformation formula (or change of variables formula). It should be noted that certain conditions need to be met before one can achieve this, and we begin by reviewing the one variable situation. Let D be an open interval, say (a; b); in R , and let ' : D! R be a 1-1 , C1 mapping (function) such that '0 6= 0 on D: Put D¤ = '(D): By the hypothesis on '; it's either increasing or decreasing everywhere on D: In the former case D¤ = ('(a);'(b)); and in the latter case, D¤ = ('(b);'(a)): Now suppose we have to evaluate the integral Zb I = f('(u))'0(u) du; a for a nice function f: Now put x = '(u); so that dx = '0(u) du: This change of variable allows us to express the integral as Z'(b) Z I = f(x) dx = sgn('0) f(x) dx; '(a) D¤ where sgn('0) denotes the sign of '0 on D: We then get the transformation formula Z Z f('(u))j'0(u)j du = f(x) dx D D¤ This generalizes to higher dimensions as follows: Theorem Let D be a bounded open set in Rn;' : D! Rn a C1, 1-1 mapping whose Jacobian determinant det(D') is everywhere non-vanishing on D; D¤ = '(D); and f an integrable function on D¤: Then we have the transformation formula Z Z Z Z ¢ ¢ ¢ f('(u))j det D'(u)j du1::: dun = ¢ ¢ ¢ f(x) dx1::: dxn: D D¤ 1 Of course, when n = 1; det D'(u) is simply '0(u); and we recover the old formula. -
Mathematical Theorems
Appendix A Mathematical Theorems The mathematical theorems needed in order to derive the governing model equations are defined in this appendix. A.1 Transport Theorem for a Single Phase Region The transport theorem is employed deriving the conservation equations in continuum mechanics. The mathematical statement is sometimes attributed to, or named in honor of, the German Mathematician Gottfried Wilhelm Leibnitz (1646–1716) and the British fluid dynamics engineer Osborne Reynolds (1842–1912) due to their work and con- tributions related to the theorem. Hence it follows that the transport theorem, or alternate forms of the theorem, may be named the Leibnitz theorem in mathematics and Reynolds transport theorem in mechanics. In a customary interpretation the Reynolds transport theorem provides the link between the system and control volume representations, while the Leibnitz’s theorem is a three dimensional version of the integral rule for differentiation of an integral. There are several notations used for the transport theorem and there are numerous forms and corollaries. A.1.1 Leibnitz’s Rule The Leibnitz’s integral rule gives a formula for differentiation of an integral whose limits are functions of the differential variable [7, 8, 22, 23, 45, 55, 79, 94, 99]. The formula is also known as differentiation under the integral sign. H. A. Jakobsen, Chemical Reactor Modeling, DOI: 10.1007/978-3-319-05092-8, 1361 © Springer International Publishing Switzerland 2014 1362 Appendix A: Mathematical Theorems b(t) b(t) d ∂f (t, x) db da f (t, x) dx = dx + f (t, b) − f (t, a) (A.1) dt ∂t dt dt a(t) a(t) The first term on the RHS gives the change in the integral because the function itself is changing with time, the second term accounts for the gain in area as the upper limit is moved in the positive axis direction, and the third term accounts for the loss in area as the lower limit is moved. -
An Introduction to Space–Time Exterior Calculus
mathematics Article An Introduction to Space–Time Exterior Calculus Ivano Colombaro * , Josep Font-Segura and Alfonso Martinez Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08018 Barcelona, Spain; [email protected] (J.F.-S.); [email protected] (A.M.) * Correspondence: [email protected]; Tel.: +34-93-542-1496 Received: 21 May 2019; Accepted: 18 June 2019; Published: 21 June 2019 Abstract: The basic concepts of exterior calculus for space–time multivectors are presented: Interior and exterior products, interior and exterior derivatives, oriented integrals over hypersurfaces, circulation and flux of multivector fields. Two Stokes theorems relating the exterior and interior derivatives with circulation and flux, respectively, are derived. As an application, it is shown how the exterior-calculus space–time formulation of the electromagnetic Maxwell equations and Lorentz force recovers the standard vector-calculus formulations, in both differential and integral forms. Keywords: exterior calculus; exterior algebra; electromagnetism; Maxwell equations; differential forms; tensor calculus 1. Introduction Vector calculus has, since its introduction by J. W. Gibbs [1] and Heaviside, been the tool of choice to represent many physical phenomena. In mechanics, hydrodynamics and electromagnetism, quantities such as forces, velocities and currents are modeled as vector fields in space, while flux, circulation, divergence or curl describe operations on the vector fields themselves. With relativity theory, it was observed that space and time are not independent but just coordinates in space–time [2] (pp. 111–120). Tensors like the Faraday tensor in electromagnetism were quickly adopted as a natural representation of fields in space–time [3] (pp. 135–144). In parallel, mathematicians such as Cartan generalized the fundamental theorems of vector calculus, i.e., Gauss, Green, and Stokes, by means of differential forms [4]. -
Surface Integrals
VECTOR CALCULUS 16.7 Surface Integrals In this section, we will learn about: Integration of different types of surfaces. PARAMETRIC SURFACES Suppose a surface S has a vector equation r(u, v) = x(u, v) i + y(u, v) j + z(u, v) k (u, v) D PARAMETRIC SURFACES •We first assume that the parameter domain D is a rectangle and we divide it into subrectangles Rij with dimensions ∆u and ∆v. •Then, the surface S is divided into corresponding patches Sij. •We evaluate f at a point Pij* in each patch, multiply by the area ∆Sij of the patch, and form the Riemann sum mn * f() Pij S ij ij11 SURFACE INTEGRAL Equation 1 Then, we take the limit as the number of patches increases and define the surface integral of f over the surface S as: mn * f( x , y , z ) dS lim f ( Pij ) S ij mn, S ij11 . Analogues to: The definition of a line integral (Definition 2 in Section 16.2);The definition of a double integral (Definition 5 in Section 15.1) . To evaluate the surface integral in Equation 1, we approximate the patch area ∆Sij by the area of an approximating parallelogram in the tangent plane. SURFACE INTEGRALS In our discussion of surface area in Section 16.6, we made the approximation ∆Sij ≈ |ru x rv| ∆u ∆v where: x y z x y z ruv i j k r i j k u u u v v v are the tangent vectors at a corner of Sij. SURFACE INTEGRALS Formula 2 If the components are continuous and ru and rv are nonzero and nonparallel in the interior of D, it can be shown from Definition 1—even when D is not a rectangle—that: fxyzdS(,,) f ((,))|r uv r r | dA uv SD SURFACE INTEGRALS This should be compared with the formula for a line integral: b fxyzds(,,) f (())|'()|rr t tdt Ca Observe also that: 1dS |rr | dA A ( S ) uv SD SURFACE INTEGRALS Example 1 Compute the surface integral x2 dS , where S is the unit sphere S x2 + y2 + z2 = 1. -
Arxiv:2109.03250V1 [Astro-Ph.EP] 7 Sep 2021 by TESS
Draft version September 9, 2021 Typeset using LATEX modern style in AASTeX62 Efficient and precise transit light curves for rapidly-rotating, oblate stars Shashank Dholakia,1 Rodrigo Luger,2 and Shishir Dholakia1 1Department of Astronomy, University of California, Berkeley, CA 2Center for Computational Astrophysics, Flatiron Institute, New York, NY Submitted to ApJ ABSTRACT We derive solutions to transit light curves of exoplanets orbiting rapidly-rotating stars. These stars exhibit significant oblateness and gravity darkening, a phenomenon where the poles of the star have a higher temperature and luminosity than the equator. Light curves for exoplanets transiting these stars can exhibit deviations from those of slowly-rotating stars, even displaying significantly asymmetric transits depending on the system’s spin-orbit angle. As such, these phenomena can be used as a protractor to measure the spin-orbit alignment of the system. In this paper, we introduce a novel semi-analytic method for generating model light curves for gravity-darkened and oblate stars with transiting exoplanets. We implement the model within the code package starry and demonstrate several orders of magnitude improvement in speed and precision over existing methods. We test the model on a TESS light curve of WASP-33, whose host star displays rapid rotation (v sin i∗ = 86:4 km/s). We subtract the host’s δ-Scuti pulsations from the light curve, finding an asymmetric transit characteristic of gravity darkening. We find the projected spin orbit angle is consistent with Doppler +19:0 ◦ tomography and constrain the true spin-orbit angle of the system as ' = 108:3−15:4 . -
Vector Calculus and Differential Forms with Applications To
Vector Calculus and Differential Forms with Applications to Electromagnetism Sean Roberson May 7, 2015 PREFACE This paper is written as a final project for a course in vector analysis, taught at Texas A&M University - San Antonio in the spring of 2015 as an independent study course. Students in mathematics, physics, engineering, and the sciences usually go through a sequence of three calculus courses before go- ing on to differential equations, real analysis, and linear algebra. In the third course, traditionally reserved for multivariable calculus, stu- dents usually learn how to differentiate functions of several variable and integrate over general domains in space. Very rarely, as was my case, will professors have time to cover the important integral theo- rems using vector functions: Green’s Theorem, Stokes’ Theorem, etc. In some universities, such as UCSD and Cornell, honors students are able to take an accelerated calculus sequence using the text Vector Cal- culus, Linear Algebra, and Differential Forms by John Hamal Hubbard and Barbara Burke Hubbard. Here, students learn multivariable cal- culus using linear algebra and real analysis, and then they generalize familiar integral theorems using the language of differential forms. This paper was written over the course of one semester, where the majority of the book was covered. Some details, such as orientation of manifolds, topology, and the foundation of the integral were skipped to save length. The paper should still be readable by a student with at least three semesters of calculus, one course in linear algebra, and one course in real analysis - all at the undergraduate level. -
Applications of the Hodge Decomposition to Biological Structure and Function Modeling
Applications of the Hodge Decomposition to Biological Structure and Function Modeling Andrew Gillette joint work with Chandrajit Bajaj and John Luecke Department of Mathematics, Institute of Computational Engineering and Sciences University of Texas at Austin, Austin, Texas 78712, USA http://www.math.utexas.edu/users/agillette university-logo Computational Visualization Center , I C E S ( DepartmentThe University of Mathematics, of Texas atInstitute Austin of Computational EngineeringDec2008 and Sciences 1/32 University Introduction Molecular dynamics are governed by electrostatic forces of attraction and repulsion. These forces are described as the solutions of a PDE over the molecular surfaces. Molecular surfaces may have complicated topological features affecting the solution. The Hodge Decomposition relates topological properties of the surface to solution spaces of PDEs over the surface. ∼ (space of forms) = (solutions to ∆u = f 6≡ 0) ⊕ (non-trivial deRham classes)university-logo Computational Visualization Center , I C E S ( DepartmentThe University of Mathematics, of Texas atInstitute Austin of Computational EngineeringDec2008 and Sciences 2/32 University Outline 1 The Hodge Decomposition for smooth differential forms 2 The Hodge Decomposition for discrete differential forms 3 Applications of the Hodge Decomposition to biological modeling university-logo Computational Visualization Center , I C E S ( DepartmentThe University of Mathematics, of Texas atInstitute Austin of Computational EngineeringDec2008 and Sciences 3/32 University Outline 1 The Hodge Decomposition for smooth differential forms 2 The Hodge Decomposition for discrete differential forms 3 Applications of the Hodge Decomposition to biological modeling university-logo Computational Visualization Center , I C E S ( DepartmentThe University of Mathematics, of Texas atInstitute Austin of Computational EngineeringDec2008 and Sciences 4/32 University Differential Forms Let Ω denote a smooth n-manifold and Tx (Ω) the tangent space of Ω at x. -
Surface Integrals
V9. Surface Integrals Surface integrals are a natural generalization of line integrals: instead of integrating over a curve, we integrate over a surface in 3-space. Such integrals are important in any of the subjects that deal with continuous media (solids, fluids, gases), as well as subjects that deal with force fields, like electromagnetic or gravitational fields. Though most of our work will be spent seeing how surface integrals can be calculated and what they are used for, we first want to indicate briefly how they are defined. The surface integral of the (continuous) function f(x,y,z) over the surface S is denoted by (1) f(x,y,z) dS . ZZS You can think of dS as the area of an infinitesimal piece of the surface S. To define the integral (1), we subdivide the surface S into small pieces having area ∆Si, pick a point (xi,yi,zi) in the i-th piece, and form the Riemann sum (2) f(xi,yi,zi)∆Si . X As the subdivision of S gets finer and finer, the corresponding sums (2) approach a limit which does not depend on the choice of the points or how the surface was subdivided. The surface integral (1) is defined to be this limit. (The surface has to be smooth and not infinite in extent, and the subdivisions have to be made reasonably, otherwise the limit may not exist, or it may not be unique.) 1. The surface integral for flux. The most important type of surface integral is the one which calculates the flux of a vector field across S. -
Surface Integrals, Stokes's Theorem and Gauss's Theorem
Surface Integrals, Stokes's Theorem and Gauss's Theorem Specifying a surface: ² Parametric form: X(s; t) = (x(s; t); y(s; t); z(s; t)) in some region D in R2. ² Explicit function: z = g(x; y) where g is a function in some region D in R2. ² Implicit function: g(x; y; z) = 0, for some function g of three variables. Normal vector and unit normal vector: Normal vectors and unit normal vectors to a surface play an important role in surface integrals. Here are some ways to obtain these vectors. ² Geometric reasoning. For surfaces of simple shape (e.g., planes or spherical surfaces), the easiest way to get normal vectors is by geometric arguments. For example, if the surface is spherical and centered at the origin, then x is a normal vector. If the surface is horizontal or vertical, one can take one of the unit basis vectors (or its negative) as normal vectors. Such geometric reasoning requires virtually no calculation, and is usually the quickest way to evaluate a surface integral in situations where it can be applied. ² Surfaces given by an equation g(x; y; z) = 0. In this case, the gradient of g, rg, is normal to the surface. Normalizing this vector, we get a unit normal vector, n = rg=krgk. Similarly, if the surface is given by an equation z = g(x; y), the vector (gx; gy; 1) is normal to the surface. ² Surfaces given by a parametric representation X(s; t). In this case, the vector N = Ts£ Tt is a normal vector, called the standard normal vector of the given parametrization.