Lecture 4: Substitution Rule and Integration by Parts

Total Page:16

File Type:pdf, Size:1020Kb

Lecture 4: Substitution Rule and Integration by Parts Lecture 4: Substitution Rule and Integration by Parts Today: The Substitution Rule, Integration by Parts If we want to evaluate a definite integral of a continuous function, the Fundamental Theorem tells us that all we need to do is to find its antiderivative and evaluate at the endpoints. However, out table of indefinite integrals only provide a limited collection of antiderivatives. We still do not know how to evaluate integrals such as 1 1 2x x e− dx or xe dx. Z0 Z0 In the next three lectures, we will introduce several integration techniques to help us evaluate integrals that are not readily available in a table. The Substitution Rule We first recall the statement of the Chain Rule. Theorem 14 (Chain Rule). If f and g are both differentiable and h = f g, then ◦ h0(x) = f 0(g(x)) g0(x). · If have an integral of the form f(g(x))g0(x) dx, Z and assume that F is an antiderivative of f, that is, F 0 = f, then by the Chain Rule and the Fundamental Theorem of Calculus, we have f(g(x))g0(x) dx = F 0(g(x))g0(x) dx = F (g(x)) + C. Z Z If we make the “substitution” u = g(x), then we have F (g(x)) + C = F (u) + C = F 0(u) du = f(u) du. Z Z Hence, we obtain the Substitution Rule for indefinite integrals. Theorem 15 (Substitution Rule for Indefinite Integrals). If u = g(x) is a differentiable function whose range is an interval I, and f is continuous on I, then f(g(x))g0(x) dx = f(u) du. Z Z 26 Remark. One way to remember the Substitution Rule is to think of the dx and du as differentials. If u = g(x), then du = g0(x) dx, and thus f(u) du = f(g(x)) g0(x) dx. · Adding the integral sign to both sides, we get the statement of the Substitution Rule. 2x Example. Evaluate the indefinite integral e− dx. We make the substitution u = 2x. Then duR = 2 dx, which means dx = du/2. Thus − − − u 2x 2x u du 1 u e e− e− dx = e = e du = + C = + C. · − 2 −2 − 2 − 2 Z Z Z Example. Evaluate the indefinite integral x3 cos(x4 + 2) dx. We make the substitution u = x4 + 2. ThenRdu = 4x3 dx, which means x3 dx = du/4. Thus 1 sin(u) sin(x4 + 2) x3 cos(x4 + 2) dx = cos(u) du = + C = + C. 4 4 4 Z Z Example. Evaluate the indefinite integral tan(x) dx. First, we write tangent as a quotient of sineR and cosine: sin(x) tan(x) dx = dx. cos(x) Z Z We make the substitution u = cos(x). Then du = sin(x) dx, so sin(x) dx = du. Thus − − sin(x) du tan(x) dx = dx = = ln u + C = ln cos(x) + C. cos(x) − u − | | − | | Z Z Z Logarithm has the property that ln(a) = ln(1/a). Thus we can also write − tan(x) dx = ln sec(x) + C. | | Z Although we need to be cautious here because sec(x) is not a continuous function, so this indefinite integral only holds true for the domains of continuity of sec(x). The Substitution Rule on Definite Integrals When we have a definite integral that requires integration by substitution, we can always evaluate the indefinite integral first, and then apply the Evaluation Theorem to get the result. Alternatively, we could also change the limits of integration when the variable is substituted. 27 Theorem 16 (Substitution Rule for Definite Integrals). If g0 is continuous on [a, b] and f is continuous on the range of u = g(x), then b g(b) f(g(x))g0(x) dx = f(u) du. Za Zg(a) 2 2x Example. Evaluate the definite integral 1 e− dx. We make the substitution u = 2x. ThenRdu = 2 dx. Thus − − 2 u(2) 4 4 4 2 2 4 2x 1 u 1 − u 1 u − e− e− e− e− e− dx = e du = e du = e = − = − . 1 −2 u(1) −2 2 −2 2 − 2 2 Z Z Z− h i− e ln(x) Example. Evaluate the definite integral 1 x dx. We make the substitution u = ln(x). ThenR du = dx/x, and thus e ln(x) u(e) 1 u2 1 1 dx = u du = u du = = . 1 x u(1) 0 2 0 2 Z Z Z h i 1 3 Example. Evaluate the definite integral 1 sin(x ) dx. − We split the first integral in two pieces R 1 0 1 sin(x3) dx = sin(x3) dx + sin(x3) dx. 1 1 0 Z− Z− Z In the first term, we make the substitution u = x, then x = u, du = dx and dx = du. − − − − Thus 0 u(0) 0 1 sin(x3) dx = sin( u3) ( du) = sin(u3) du = sin(x3) dx. 1 u( 1) − · − 1 − 0 Z− Z − Z Z Adding on the second term, we get 1 sin(x3) dx = 0. 1 Z− The last example above uses the fact that sine is an odd function, i.e., sin( x) = sin(x). − − In fact, we have the following theorem regarding definite integrals of symmetric functions over symmetric intervals. Theorem 17. Let a > 0 be a positive real number, and let f be continuous on [ a, a]. − (1) If f is an odd function, i.e., f( x) = f(x) for all x [ a, a], then − − ∈ − a f(x) dx = 0. a Z− (2) If f is an even function, i.e., f( x) = f(x) for all x [ a, a], then − ∈ − a a f(x) dx = 2 f(x) dx. a 0 Z− Z 28 Integration by Parts We first recall the statement of the Product Rule. Theorem 18 (Product Rule). If f and g are both differentiable, then d [f(x)g(x)] = f 0(x)g(x) + f(x)g0(x). dx If we integrate both sides with respect to x in the statement of the Product Rule, we would get d [f(x)g(x)] dx = g(x)f 0(x) dx + f(x)g0(x) dx. dx Z Z Z We can rearrange this equation to get the formula for integration by parts: f(x)g0(x) dx = f(x)g(x) g(x)f 0(x) dx. − Z Z Remark. We can make the following substitutions to help with remembering the formula. Let u = f(x) and v = g(x). Then du = f 0(x) dx and dv = g0(x) dx, and the formula for integration by parts becomes u dv = uv v du. − Z Z Example. Evaluate the indefinite integral xex dx. We make the choice R u = x, dv = ex dx. Then du = dx, v = ex. Thus by the integration by parts formula, xex dx = xex ex dx = xex ex + C = (x 1)ex + C. − − − Z Z Remark. The idea of using integration by parts is to get a simpler integral than the one we started with. In the example above, we use integration by parts to transform the integral xex dx to ex dx, which we know how to integrate. When we make the choice of u and dv, Rwe shall keepR in mind that our goal is to get a v du that is simpler to integrate. Example. Evaluate the indefinite integral x2 sin(x) dx. We make the choice R u = x2, dv = sin(x) dx. 29 Then du = 2x dx, v = cos(x). − By the integration by parts formula, x2 sin(x) dx = x2 cos(x) ( cos(x)) 2x dx = x2 cos(x) + 2 x cos(x) dx. − − − · − Z Z Z Now we need to use integration by parts again for the second integral. Choose u = x, dv = cos(x) dx. Then du = dx, v = sin(x). Thus x cos(x) dx = x sin(x) sin(x) dx = x sin(x) + cos(x) + C. − Z Z Combine with the first equation, we get, x2 sin(x) dx = x2 cos(x) + 2(x sin(x) + cos(x)) + C = (2 x2) cos(x) + 2x sin(x) + C. − − Z Example. Evaluate the indefinite integral sin(x)ex dx. Notice that neither sin(x) nor ex has a simplerR derivative. Let’s try u = sin(x) and dv = ex dx. Then du = cos(x) dx, v = ex, and sin(x)ex dx = sin(x)ex ex cos(x) dx. − Z Z Integrate by parts again on the second integral by choosing u = cos(x), dv = ex dx; du = sin(x) dx. v = ex. − Then ex cos(x) dx = cos(x)ex ex ( sin(x)) dx = cos(x)ex + ex sin(x) dx. − · − Z Z Z Combine the two equations together, we get sin(x)ex dx = sin(x)ex cos(x)ex ex sin(x) dx. − − Z Z At this point, we can treat the integral ex sin(x) dx as an unknown, and solve to get R (sin(x) cos(x))ex sin(x)ex dx = − + C. 2 Z 30 1 x Example. Evaluate the definite integral 0 xe dx. From the first example, we know that theR indefinite integral xex dx = (x 1)ex + C. − Z Apply the Evaluation Theorem, we get 1 1 xex dx = (x 1)ex = 0 e ( 1) 1 = 1. 0 − 0 · − − · Z h i Remark. If we combine the integration by parts formula with the Evaluation Theorem, we can evaluate definite integrals by parts in the following way: b b b f(x)g0(x) dx = f(x)g(x) g(x)f 0(x) dx.
Recommended publications
  • Notes on Calculus II Integral Calculus Miguel A. Lerma
    Notes on Calculus II Integral Calculus Miguel A. Lerma November 22, 2002 Contents Introduction 5 Chapter 1. Integrals 6 1.1. Areas and Distances. The Definite Integral 6 1.2. The Evaluation Theorem 11 1.3. The Fundamental Theorem of Calculus 14 1.4. The Substitution Rule 16 1.5. Integration by Parts 21 1.6. Trigonometric Integrals and Trigonometric Substitutions 26 1.7. Partial Fractions 32 1.8. Integration using Tables and CAS 39 1.9. Numerical Integration 41 1.10. Improper Integrals 46 Chapter 2. Applications of Integration 50 2.1. More about Areas 50 2.2. Volumes 52 2.3. Arc Length, Parametric Curves 57 2.4. Average Value of a Function (Mean Value Theorem) 61 2.5. Applications to Physics and Engineering 63 2.6. Probability 69 Chapter 3. Differential Equations 74 3.1. Differential Equations and Separable Equations 74 3.2. Directional Fields and Euler’s Method 78 3.3. Exponential Growth and Decay 80 Chapter 4. Infinite Sequences and Series 83 4.1. Sequences 83 4.2. Series 88 4.3. The Integral and Comparison Tests 92 4.4. Other Convergence Tests 96 4.5. Power Series 98 4.6. Representation of Functions as Power Series 100 4.7. Taylor and MacLaurin Series 103 3 CONTENTS 4 4.8. Applications of Taylor Polynomials 109 Appendix A. Hyperbolic Functions 113 A.1. Hyperbolic Functions 113 Appendix B. Various Formulas 118 B.1. Summation Formulas 118 Appendix C. Table of Integrals 119 Introduction These notes are intended to be a summary of the main ideas in course MATH 214-2: Integral Calculus.
    [Show full text]
  • Anti-Chain Rule Name
    Anti-Chain Rule Name: The most fundamental rule for computing derivatives in calculus is the Chain Rule, from which all other differentiation rules are derived. In words, the Chain Rule states that, to differentiate f(g(x)), differentiate the outside function f and multiply by the derivative of the inside function g, so that d f(g(x)) = f 0(g(x)) · g0(x): dx The Chain Rule makes computation of nearly all derivatives fairly easy. It is tempting to think that there should be an Anti-Chain Rule that makes antidiffer- entiation as easy as the Chain Rule made differentiation. Such a rule would just reverse the process, so instead of differentiating f and multiplying by g0, we would antidifferentiate f and divide by g0. In symbols, Z F (g(x)) f(g(x)) dx = + C: g0(x) Unfortunately, the Anti-Chain Rule does not exist because the formula above is not Z always true. For example, consider (x2 + 1)2 dx. We can compute this integral (correctly) by expanding and applying the power rule: Z Z (x2 + 1)2 dx = x4 + 2x2 + 1 dx x5 2x3 = + + x + C 5 3 However, we could also think about our integrand above as f(g(x)) with f(x) = x2 and g(x) = x2 + 1. Then we have F (x) = x3=3 and g0(x) = 2x, so the Anti-Chain Rule would predict that Z F (g(x)) (x2 + 1)2 dx = + C g0(x) (x2 + 1)3 = + C 3 · 2x x6 + 3x4 + 3x2 + 1 = + C 6x x5 x3 x 1 = + + + + C 6 2 2 6x Since these answers are different, we conclude that the Anti-Chain Rule has failed us.
    [Show full text]
  • A Quotient Rule Integration by Parts Formula Jennifer Switkes ([email protected]), California State Polytechnic Univer- Sity, Pomona, CA 91768
    A Quotient Rule Integration by Parts Formula Jennifer Switkes ([email protected]), California State Polytechnic Univer- sity, Pomona, CA 91768 In a recent calculus course, I introduced the technique of Integration by Parts as an integration rule corresponding to the Product Rule for differentiation. I showed my students the standard derivation of the Integration by Parts formula as presented in [1]: By the Product Rule, if f (x) and g(x) are differentiable functions, then d f (x)g(x) = f (x)g(x) + g(x) f (x). dx Integrating on both sides of this equation, f (x)g(x) + g(x) f (x) dx = f (x)g(x), which may be rearranged to obtain f (x)g(x) dx = f (x)g(x) − g(x) f (x) dx. Letting U = f (x) and V = g(x) and observing that dU = f (x) dx and dV = g(x) dx, we obtain the familiar Integration by Parts formula UdV= UV − VdU. (1) My student Victor asked if we could do a similar thing with the Quotient Rule. While the other students thought this was a crazy idea, I was intrigued. Below, I derive a Quotient Rule Integration by Parts formula, apply the resulting integration formula to an example, and discuss reasons why this formula does not appear in calculus texts. By the Quotient Rule, if f (x) and g(x) are differentiable functions, then ( ) ( ) ( ) − ( ) ( ) d f x = g x f x f x g x . dx g(x) [g(x)]2 Integrating both sides of this equation, we get f (x) g(x) f (x) − f (x)g(x) = dx.
    [Show full text]
  • 9.2. Undoing the Chain Rule
    < Previous Section Home Next Section > 9.2. Undoing the Chain Rule This chapter focuses on finding accumulation functions in closed form when we know its rate of change function. We’ve seen that 1) an accumulation function in closed form is advantageous for quickly and easily generating many values of the accumulating quantity, and 2) the key to finding accumulation functions in closed form is the Fundamental Theorem of Calculus. The FTC says that an accumulation function is the antiderivative of the given rate of change function (because rate of change is the derivative of accumulation). In Chapter 6, we developed many derivative rules for quickly finding closed form rate of change functions from closed form accumulation functions. We also made a connection between the form of a rate of change function and the form of the accumulation function from which it was derived. Rather than inventing a whole new set of techniques for finding antiderivatives, our mindset as much as possible will be to use our derivatives rules in reverse to find antiderivatives. We worked hard to develop the derivative rules, so let’s keep using them to find antiderivatives! Thus, whenever you have a rate of change function f and are charged with finding its antiderivative, you should frame the task with the question “What function has f as its derivative?” For simple rate of change functions, this is easy, as long as you know your derivative rules well enough to apply them in reverse. For example, given a rate of change function …. … 2x, what function has 2x as its derivative? i.e.
    [Show full text]
  • Calculus Terminology
    AP Calculus BC Calculus Terminology Absolute Convergence Asymptote Continued Sum Absolute Maximum Average Rate of Change Continuous Function Absolute Minimum Average Value of a Function Continuously Differentiable Function Absolutely Convergent Axis of Rotation Converge Acceleration Boundary Value Problem Converge Absolutely Alternating Series Bounded Function Converge Conditionally Alternating Series Remainder Bounded Sequence Convergence Tests Alternating Series Test Bounds of Integration Convergent Sequence Analytic Methods Calculus Convergent Series Annulus Cartesian Form Critical Number Antiderivative of a Function Cavalieri’s Principle Critical Point Approximation by Differentials Center of Mass Formula Critical Value Arc Length of a Curve Centroid Curly d Area below a Curve Chain Rule Curve Area between Curves Comparison Test Curve Sketching Area of an Ellipse Concave Cusp Area of a Parabolic Segment Concave Down Cylindrical Shell Method Area under a Curve Concave Up Decreasing Function Area Using Parametric Equations Conditional Convergence Definite Integral Area Using Polar Coordinates Constant Term Definite Integral Rules Degenerate Divergent Series Function Operations Del Operator e Fundamental Theorem of Calculus Deleted Neighborhood Ellipsoid GLB Derivative End Behavior Global Maximum Derivative of a Power Series Essential Discontinuity Global Minimum Derivative Rules Explicit Differentiation Golden Spiral Difference Quotient Explicit Function Graphic Methods Differentiable Exponential Decay Greatest Lower Bound Differential
    [Show full text]
  • A General Chain Rule for Distributional Derivatives
    proceedings of the american mathematical society Volume 108, Number 3, March 1990 A GENERAL CHAIN RULE FOR DISTRIBUTIONAL DERIVATIVES L. AMBROSIO AND G. DAL MASO (Communicated by Barbara L. Keyfitz) Abstract. We prove a general chain rule for the distribution derivatives of the composite function v(x) = f(u(x)), where u: R" —>Rm has bounded variation and /: Rm —>R* is Lipschitz continuous. Introduction The aim of the present paper is to prove a chain rule for the distributional derivative of the composite function v(x) = f(u(x)), where u: Q —>Rm has bounded variation in the open set ilcR" and /: Rw —>R is uniformly Lip- schitz continuous. Under these hypotheses it is easy to prove that the function v has locally bounded variation in Q, hence its distributional derivative Dv is a Radon measure in Q with values in the vector space Jz? m of all linear maps from R" to Rm . The problem is to give an explicit formula for Dv in terms of the gradient Vf of / and of the distributional derivative Du . To illustrate our formula, we begin with the simpler case, studied by A. I. Vol pert, where / is continuously differentiable. Let us denote by Su the set of all jump points of u, defined as the set of all xef! where the approximate limit u(x) does not exist at x. Then the following identities hold in the sense of measures (see [19] and [20]): (0.1) Dv = Vf(ü)-Du onß\SH, and (0.2) Dv = (f(u+)-f(u-))®vu-rn_x onSu, where vu denotes the measure theoretical unit normal to Su, u+ , u~ are the approximate limits of u from both sides of Su, and %?n_x denotes the (n - l)-dimensional Hausdorff measure.
    [Show full text]
  • Math 212-Lecture 8 13.7: the Multivariable Chain Rule
    Math 212-Lecture 8 13.7: The multivariable chain rule The chain rule with one independent variable w = f(x; y). If the particle is moving along a curve x = x(t); y = y(t), then the values that the particle feels is w = f(x(t); y(t)). Then, w = w(t) is a function of t. x; y are intermediate variables and t is the independent variable. The chain rule says: If both fx and fy are continuous, then dw = f x0(t) + f y0(t): dt x y Intuitively, the total change rate is the superposition of contributions in both directions. Comment: You cannot do as in one single variable calculus like @w dx @w dy dw dw + = + ; @x dt @y dt dt dt @w by canceling the two dx's. @w in @x is only the `partial' change due to the dw change of x, which is different from the dw in dt since the latter is the total change. The proof is to use the increment ∆w = wx∆x + wy∆y + small. Read Page 903. Example: Suppose w = sin(uv) where u = 2s and v = s2. Compute dw ds at s = 1. Solution. By chain rule dw @w du @w dv = + = cos(uv)v ∗ 2 + cos(uv)u ∗ 2s: ds @u ds @v ds At s = 1, u = 2; v = 1. Hence, we have cos(2) ∗ 2 + cos(2) ∗ 2 ∗ 2 = 6 cos(2): We can actually check that w = sin(uv) = sin(2s3). Hence, w0(s) = 3 2 cos(2s ) ∗ 6s . At s = 1, this is 6 cos(2).
    [Show full text]
  • Chapter 4 Differentiation in the Study of Calculus of Functions of One Variable, the Notions of Continuity, Differentiability and Integrability Play a Central Role
    Chapter 4 Differentiation In the study of calculus of functions of one variable, the notions of continuity, differentiability and integrability play a central role. The previous chapter was devoted to continuity and its consequences and the next chapter will focus on integrability. In this chapter we will define the derivative of a function of one variable and discuss several important consequences of differentiability. For example, we will show that differentiability implies continuity. We will use the definition of derivative to derive a few differentiation formulas but we assume the formulas for differentiating the most common elementary functions are known from a previous course. Similarly, we assume that the rules for differentiating are already known although the chain rule and some of its corollaries are proved in the solved problems. We shall not emphasize the various geometrical and physical applications of the derivative but will concentrate instead on the mathematical aspects of differentiation. In particular, we present several forms of the mean value theorem for derivatives, including the Cauchy mean value theorem which leads to L’Hôpital’s rule. This latter result is useful in evaluating so called indeterminate limits of various kinds. Finally we will discuss the representation of a function by Taylor polynomials. The Derivative Let fx denote a real valued function with domain D containing an L ? neighborhood of a point x0 5 D; i.e. x0 is an interior point of D since there is an L ; 0 such that NLx0 D. Then for any h such that 0 9 |h| 9 L, we can define the difference quotient for f near x0, fx + h ? fx D fx : 0 0 4.1 h 0 h It is well known from elementary calculus (and easy to see from a sketch of the graph of f near x0 ) that Dhfx0 represents the slope of a secant line through the points x0,fx0 and x0 + h,fx0 + h.
    [Show full text]
  • Integration by Parts
    3 Integration By Parts Formula ∫∫udv = uv − vdu I. Guidelines for Selecting u and dv: (There are always exceptions, but these are generally helpful.) “L-I-A-T-E” Choose ‘u’ to be the function that comes first in this list: L: Logrithmic Function I: Inverse Trig Function A: Algebraic Function T: Trig Function E: Exponential Function Example A: ∫ x3 ln x dx *Since lnx is a logarithmic function and x3 is an algebraic function, let: u = lnx (L comes before A in LIATE) dv = x3 dx 1 du = dx x x 4 v = x 3dx = ∫ 4 ∫∫x3 ln xdx = uv − vdu x 4 x 4 1 = (ln x) − dx 4 ∫ 4 x x 4 1 = (ln x) − x 3dx 4 4 ∫ x 4 1 x 4 = (ln x) − + C 4 4 4 x 4 x 4 = (ln x) − + C ANSWER 4 16 www.rit.edu/asc Page 1 of 7 Example B: ∫sin x ln(cos x) dx u = ln(cosx) (Logarithmic Function) dv = sinx dx (Trig Function [L comes before T in LIATE]) 1 du = (−sin x) dx = − tan x dx cos x v = ∫sin x dx = − cos x ∫sin x ln(cos x) dx = uv − ∫ vdu = (ln(cos x))(−cos x) − ∫ (−cos x)(− tan x)dx sin x = −cos x ln(cos x) − (cos x) dx ∫ cos x = −cos x ln(cos x) − ∫sin x dx = −cos x ln(cos x) + cos x + C ANSWER Example C: ∫sin −1 x dx *At first it appears that integration by parts does not apply, but let: u = sin −1 x (Inverse Trig Function) dv = 1 dx (Algebraic Function) 1 du = dx 1− x 2 v = ∫1dx = x ∫∫sin −1 x dx = uv − vdu 1 = (sin −1 x)(x) − x dx ∫ 2 1− x ⎛ 1 ⎞ = x sin −1 x − ⎜− ⎟ (1− x 2 ) −1/ 2 (−2x) dx ⎝ 2 ⎠∫ 1 = x sin −1 x + (1− x 2 )1/ 2 (2) + C 2 = x sin −1 x + 1− x 2 + C ANSWER www.rit.edu/asc Page 2 of 7 II.
    [Show full text]
  • The Chain Rule in Partial Differentiation
    THE CHAIN RULE IN PARTIAL DIFFERENTIATION 1 Simple chain rule If u = u(x, y) and the two independent variables x and y are each a function of just one other variable t so that x = x(t) and y = y(t), then to find du/dt we write down the differential of u ∂u ∂u δu = δx + δy + .... (1) ∂x ∂y Then taking limits δx 0, δy 0 and δt 0 in the usual way we have → → → du ∂u dx ∂u dy = + . (2) dt ∂x dt ∂y dt Note we only need straight ‘d’s’ in dx/dt and dy/dt because x and y are function of one variable t whereas u is a function of both x and y. 2 Chain rule for two sets of independent variables If u = u(x, y) and the two independent variables x, y are each a function of two new independent variables s, t then we want relations between their partial derivatives. 1. When u = u(x, y), for guidance in working out the chain rule, write down the differential ∂u ∂u δu = δx + δy + ... (3) ∂x ∂y then when x = x(s, t) and y = y(s, t) (which are known functions of s and t), the chain rule for us and ut in terms of ux and uy is ∂u ∂u ∂x ∂u ∂y = + (4) ∂s ∂x ∂s ∂y ∂s ∂u ∂u ∂x ∂u ∂y = + . (5) ∂t ∂x ∂t ∂y ∂t 2. Conversely, when u = u(s, t), for guidance in working out the chain rule write down the differential ∂u ∂u δu = δs + δt + ..
    [Show full text]
  • Failure of the Chain Rule for the Divergence of Bounded Vector Fields
    FAILURE OF THE CHAIN RULE FOR THE DIVERGENCE OF BOUNDED VECTOR FIELDS GIANLUCA CRIPPA, NIKOLAY GUSEV, STEFANO SPIRITO, AND EMIL WIEDEMANN ABSTRACT. We provide a vast class of counterexamples to the chain rule for the divergence of bounded vector fields in three space dimensions. Our convex integration approach allows us to produce renormalization defects of various kinds, which in a sense quantify the breakdown of the chain rule. For instance, we can construct defects which are absolutely continuous with respect to the Lebesgue measure, or defects which are not even measures. MSC (2010): 35F05 (PRIMARY); 35A02, 35Q35 KEYWORDS: Chain Rule, Convex Integration, Transport and Continuity Equations, Renormaliza- tion 1. INTRODUCTION In this paper we consider the classical problem of the chain rule for the divergence of a bounded vector field. Specifically, the problem can be stated in the following way: d d Let W ⊂ R be a domain with Lipschitz boundary. Given a bounded vector field v : W ! R tangent to the boundary and a bounded scalar function r : W ! R, one asks whether it is possible to express the quantity div(b(r)v), where b is a smooth scalar function, only in terms of b, r and the quantities m = divv and l = div(rv). Indeed, formally we should have that div(b(r)v) = (b(r) − rb 0(r))m + b 0(r)l: (1.1) However, the extension of (1.1) to a nonsmooth setting is far from trivial. The chain rule problem is particularly important in view of its applications to the uniqueness and compactness of transport and continuity equations, whose analysis is nowadays a fundamental tool in the study of various equations arising in mathematical physics.
    [Show full text]
  • Chain Rule & Implicit Differentiation
    INTRODUCTION The chain rule and implicit differentiation are techniques used to easily differentiate otherwise difficult equations. Both use the rules for derivatives by applying them in slightly different ways to differentiate the complex equations without much hassle. In this presentation, both the chain rule and implicit differentiation will be shown with applications to real world problems. DEFINITION Chain Rule Implicit Differentiation A way to differentiate A way to take the derivative functions within of a term with respect to functions. another variable without having to isolate either variable. HISTORY The Chain Rule is thought to have first originated from the German mathematician Gottfried W. Leibniz. Although the memoir it was first found in contained various mistakes, it is apparent that he used chain rule in order to differentiate a polynomial inside of a square root. Guillaume de l'Hôpital, a French mathematician, also has traces of the chain rule in his Analyse des infiniment petits. HISTORY Implicit differentiation was developed by the famed physicist and mathematician Isaac Newton. He applied it to various physics problems he came across. In addition, the German mathematician Gottfried W. Leibniz also developed the technique independently of Newton around the same time period. EXAMPLE 1: CHAIN RULE Find the derivative of the following using chain rule y=(x2+5x3-16)37 EXAMPLE 1: CHAIN RULE Step 1: Define inner and outer functions y=(x2+5x3-16)37 EXAMPLE 1: CHAIN RULE Step 2: Differentiate outer function via power rule y’=37(x2+5x3-16)36 EXAMPLE 1: CHAIN RULE Step 3: Differentiate inner function and multiply by the answer from the previous step y’=37(x2+5x3-16)36(2x+15x2) EXAMPLE 2: CHAIN RULE A biologist must use the chain rule to determine how fast a given bacteria population is growing at a given point in time t days later.
    [Show full text]