Inverse trig functions and implicit differentiation are powerful tools for solving complex calculus problems. They let us find derivatives of tricky functions and tackle real-world scenarios involving changing rates.

These techniques open doors to optimization and problems. By using implicit differentiation, we can analyze situations where multiple variables change over time, helping us solve practical math challenges in various fields.

Inverse Trigonometric Functions and Implicit Differentiation

Derivatives of inverse trigonometric functions

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  • Inverse trigonometric functions defined implicitly enable differentiation using the implicit differentiation technique
    • y=arcsin(x)y = \arcsin(x) implicitly defined as x=sin(y)x = \sin(y) (yy is the angle whose sine is xx)
    • y=arccos(x)y = \arccos(x) implicitly defined as x=cos(y)x = \cos(y) (yy is the angle whose cosine is xx)
    • y=arctan(x)y = \arctan(x) implicitly defined as x=tan(y)x = \tan(y) (yy is the angle whose tangent is xx)
  • Differentiating both sides of the implicit equation with respect to xx yields the derivative of the inverse trigonometric function
    • For y=arcsin(x)y = \arcsin(x), differentiate x=sin(y)x = \sin(y):
      • 1=cos(y)dydx1 = \cos(y) \cdot \frac{dy}{dx} (using the )
      • dydx=1cos(y)\frac{dy}{dx} = \frac{1}{\cos(y)} (solving for dydx\frac{dy}{dx})
      • dydx=11x2\frac{dy}{dx} = \frac{1}{\sqrt{1-x^2}} (substituting y=arcsin(x)y = \arcsin(x) and simplifying)
    • For y=arccos(x)y = \arccos(x), differentiate x=cos(y)x = \cos(y):
      • 1=sin(y)dydx1 = -\sin(y) \cdot \frac{dy}{dx} (using the chain rule and the derivative of cosine)
      • dydx=1sin(y)\frac{dy}{dx} = -\frac{1}{\sin(y)} (solving for dydx\frac{dy}{dx})
      • dydx=11x2\frac{dy}{dx} = -\frac{1}{\sqrt{1-x^2}} (substituting y=arccos(x)y = \arccos(x) and simplifying)
    • For y=arctan(x)y = \arctan(x), differentiate x=tan(y)x = \tan(y):
      • 1=sec2(y)dydx1 = \sec^2(y) \cdot \frac{dy}{dx} (using the chain rule and the derivative of tangent)
      • dydx=1sec2(y)\frac{dy}{dx} = \frac{1}{\sec^2(y)} (solving for dydx\frac{dy}{dx})
      • dydx=11+x2\frac{dy}{dx} = \frac{1}{1+x^2} (substituting y=arctan(x)y = \arctan(x) and simplifying)
  • Related rates problems involve multiple variables changing with respect to time, related by an equation
  • Solving related rates problems:
    1. Identify variables and write an equation relating them
    2. Differentiate both sides of the equation with respect to time (tt)
    3. Substitute known values and solve for the desired rate
  • Example: A 10 ft ladder rests against a vertical wall. The bottom slides away at 1 ft/sec. How fast is the top sliding down when the bottom is 6 ft from the wall?
    • xx: distance from bottom of ladder to wall, yy: distance from top of ladder to ground
    • Pythagorean theorem: x2+y2=102x^2 + y^2 = 10^2
    • Differentiate with respect to time: 2xdxdt+2ydydt=02x\frac{dx}{dt} + 2y\frac{dy}{dt} = 0
    • Substitute known values: 2(6)(1)+2ydydt=02(6)(1) + 2y\frac{dy}{dt} = 0
    • Solve for dydt\frac{dy}{dt} when x=6x = 6 (and y=8y = 8): dydt=68=0.75\frac{dy}{dt} = -\frac{6}{8} = -0.75 ft/sec

Optimization with implicit functions

  • Optimization problems involve finding maximum or minimum values of a function subject to constraints
  • For implicitly defined functions, use implicit differentiation to find critical points
  • Example: Find points on the ellipse x2a2+y2b2=1\frac{x^2}{a^2} + \frac{y^2}{b^2} = 1 farthest from and closest to the origin
    • Distance from point (x,y)(x, y) to origin: d=x2+y2d = \sqrt{x^2 + y^2}
    • Substitute ellipse equation: d=a2(x2a2)+b2(y2b2)=a2+b2a2(y2b2)d = \sqrt{a^2(\frac{x^2}{a^2}) + b^2(\frac{y^2}{b^2})} = \sqrt{a^2 + b^2 - a^2(\frac{y^2}{b^2})}
    • Find critical points by differentiating with respect to yy and setting equal to zero:
      • ddy(a2+b2a2(y2b2))=0\frac{d}{dy}(\sqrt{a^2 + b^2 - a^2(\frac{y^2}{b^2})}) = 0
      • a2(2yb2)a2+b2a2(y2b2)=0\frac{-a^2(\frac{2y}{b^2})}{\sqrt{a^2 + b^2 - a^2(\frac{y^2}{b^2})}} = 0
      • y=0y = 0 (maximum) or y=±by = \pm b (minimum)
    • Points farthest from origin: (0,±b)(0, \pm b), points closest to origin: (±a,0)(\pm a, 0)

Logarithmic Functions

Differentiation of logarithmic functions

  • Logarithmic functions can be differentiated using implicit differentiation
  • Natural logarithm function ln(x)\ln(x) implicitly defined as ey=xe^y = x
    • Differentiate both sides with respect to xx: eydydx=1e^y \cdot \frac{dy}{dx} = 1
    • Solve for dydx\frac{dy}{dx}: dydx=1ey\frac{dy}{dx} = \frac{1}{e^y}
    • Substitute y=ln(x)y = \ln(x) to get ddx(ln(x))=1x\frac{d}{dx}(\ln(x)) = \frac{1}{x}
  • General logarithm function logb(x)\log_b(x) expressed in terms of natural logarithm: logb(x)=ln(x)ln(b)\log_b(x) = \frac{\ln(x)}{\ln(b)}
    • Differentiate using chain rule: ddx(logb(x))=1ln(b)1x\frac{d}{dx}(\log_b(x)) = \frac{1}{\ln(b)} \cdot \frac{1}{x}
  • Logarithmic differentiation used for functions like y=xxy = x^x or y=(f(x))g(x)y = (f(x))^{g(x)}
    1. Take natural logarithm of both sides
    2. Differentiate using implicit differentiation
    • Example: Differentiate y=xxy = x^x
      • ln(y)=xln(x)\ln(y) = x\ln(x)
      • 1ydydx=ln(x)+1\frac{1}{y} \cdot \frac{dy}{dx} = \ln(x) + 1 (using implicit differentiation and the chain rule)
      • dydx=xx(ln(x)+1)\frac{dy}{dx} = x^x(\ln(x) + 1) (solving for dydx\frac{dy}{dx} and substituting y=xxy = x^x)

Key Terms to Review (16)

Chain Rule: The chain rule is a fundamental technique in calculus used to differentiate composite functions, allowing us to find the derivative of a function that is made up of other functions. This rule is crucial for understanding how different rates of change are interconnected and enables us to tackle complex differentiation problems involving multiple layers of functions.
Circles: A circle is a geometric shape consisting of all points in a plane that are equidistant from a fixed center point. The distance from the center to any point on the circle is known as the radius. Understanding circles is essential in implicit differentiation, particularly when dealing with equations that define them, as they often require finding derivatives without explicitly solving for one variable in terms of another.
Differential Equation: A differential equation is a mathematical equation that relates a function to its derivatives, capturing how the function changes with respect to one or more variables. These equations are essential for modeling various phenomena in fields like physics, engineering, and biology, where they describe relationships involving rates of change. Understanding differential equations involves finding solutions that satisfy these relationships, which can be either explicit or implicit functions.
Dy/dx: The notation $$\frac{dy}{dx}$$ represents the derivative of a function, indicating the rate at which the dependent variable $$y$$ changes with respect to the independent variable $$x$$. This concept is essential for understanding how functions behave and helps in solving problems related to tangents, slopes, and rates of change. The derivative encapsulates the instantaneous rate of change, allowing for the analysis of motion and the dynamics of systems.
E^x + y² = 0: The equation $e^x + y^2 = 0$ represents a relationship between the variables x and y where the exponential function and a squared term are combined. In this context, it is crucial to recognize how implicit differentiation can be used to find the derivative of y with respect to x when y is defined implicitly by this equation. This highlights the importance of treating y as a function of x, allowing us to analyze changes in y relative to changes in x even though y isn't explicitly solved for in terms of x.
Ellipses: Ellipses are closed, curved shapes that can be defined as the set of all points where the sum of the distances to two fixed points (foci) is constant. They have unique properties that make them important in various fields like astronomy, physics, and engineering, particularly when analyzing orbital paths and the geometry of conic sections.
First Derivative: The first derivative of a function represents the rate at which the function's value changes with respect to changes in its input. It provides essential information about the behavior of the function, such as its slope at any given point, and is fundamental in analyzing how functions increase or decrease, as well as in understanding relationships between variables through implicit differentiation.
Implicit function: An implicit function is a relationship between variables defined by an equation in which one variable cannot be expressed solely in terms of the other. This often arises when differentiating equations that define relationships between x and y, rather than expressing y as a function of x directly. Implicit functions allow us to find derivatives using implicit differentiation, which is especially useful in cases where it’s difficult or impossible to solve for one variable explicitly.
Implicit Function Theorem: The Implicit Function Theorem is a fundamental result in calculus that provides conditions under which a relation defined by an equation can be expressed as a function. This theorem states that if a function is continuously differentiable and certain conditions are met, then you can locally express one variable in terms of others around a point. This concept connects to implicit differentiation, as it underpins the reasoning for differentiating variables that are not explicitly defined as functions of each other.
Mean Value Theorem: The Mean Value Theorem states that for a function that is continuous on a closed interval and differentiable on the open interval, there exists at least one point where the derivative equals the average rate of change of the function over that interval. This theorem provides a bridge between the behavior of a function and its derivatives, showing how slopes relate to overall changes.
Partial Derivative: A partial derivative is a derivative taken with respect to one variable while keeping other variables constant in a multivariable function. This concept allows for the examination of how a function changes as one specific input changes, providing insight into the function's behavior in multiple dimensions. Understanding partial derivatives is essential when dealing with functions of several variables, as it helps in determining rates of change and analyzing surfaces and curves defined by these functions.
Product Rule: The product rule is a fundamental principle in calculus that provides a method for finding the derivative of the product of two functions. It states that if you have two functions, say $$u(x)$$ and $$v(x)$$, the derivative of their product can be calculated using the formula: $$ (uv)' = u'v + uv' $$, where $$u'$$ and $$v'$$ are the derivatives of $$u$$ and $$v$$ respectively. This concept is crucial in understanding how derivatives work when dealing with more complex functions that are products of simpler ones.
Related rates: Related rates involve finding the rate at which one quantity changes with respect to another when both quantities are related by an equation. This concept is vital in understanding how different variables affect each other over time, especially when dealing with geometric shapes and motion, allowing us to use derivatives to analyze dynamic situations.
Second Derivative: The second derivative is the derivative of the derivative of a function, providing insight into the function's rate of change in relation to its own rate of change. This concept helps us understand not just how a function is changing, but also how the rate of that change is itself changing, revealing key features like concavity and potential inflection points. Additionally, the second derivative plays a significant role in analyzing the behavior of composite functions and the implications of implicit differentiation.
Tangent Line: A tangent line is a straight line that touches a curve at a single point without crossing it, representing the instantaneous rate of change of the curve at that point. This concept connects deeply with the ideas of slope, derivatives, and the behavior of functions, providing crucial insight into how functions change locally.
X² + y² = r²: The equation x² + y² = r² defines a circle in the Cartesian coordinate system, where (x, y) represents any point on the circle and r is the radius. This relationship is crucial for understanding implicit differentiation as it allows us to differentiate equations that are not explicitly solved for one variable in terms of another. It shows how to find the slope of the tangent line to a circle at any given point using implicit differentiation techniques.
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