Let’s quickly recap what we’ve done with this new calculus object, the derivative:
We defined the derivative at a point (Definition 2.1.1) to find the slope of a line touching a graph of a function \(f(x)\) at a single point. We call this the “slope of the tangent line” at a point.
Once we calculated this slope, we quickly found a way to think about the derivative as a function (Definition 2.1.2) that connects \(x\)-values with the slope of the line tangent to \(f(x)\) at that \(x\)-value.
We thought about how we could interpret the derivative as more than just a slope (Section 2.2). We can think about this as an instantaneous rate of change, and use it to add detail to how we think about mathematical models of different things.
We spent some time building up shortcuts, noticing patterns, and generalizing ways of finding these derivative functions for specific functions (Section 2.3) as well as combinations of those functions (Section 2.4 and Section 2.5).
Our goal, now, is to generalize this a bit. What happens when we push past the restriction of only dealing with functions? Can we think of some reasonable non-functions that might produce curves? Might we think about tangent lines and slopes in these contexts?
Definition3.1.1.Explicitly and Implicitly Defined Curves.
A function or curve that is defined explicitly is one where the relationship between the variables is stated in with an equation like \(y=f(x)\text{.}\) Here, \(x\) is the input variable and we can find each corresponding value of the \(y\)-variable by applying some operations to \(x\text{.}\) As an example, we might consider the following function:
A function or curve that is defined implicitly is one where the relationship between the variables is stated with an equation connecting the variables, but not necessarily one which is solved for a single variable. Here, the relationship between variables is not stated with the typical input and output variables. As an example, we might consider the same function as above, but defined as:
Unfortunately, this only displays the upper half of the circle, since the square root will only output positive values. In this case, we can get around this by defining the circle with two functions.
As we move forward, let’s work with this circle using the implicitly defined version (\(x^2+y^2=1\)). How might we find a slope of a line tangent to this circle at some point?
Let’s recall back to Notation for Derivatives. We talked about how we can use the notation \(\ddx{f(x)}\) as a kind of action: the notation says “find the derivative of \(f(x)\) with respect to \(x\text{.}\)” When we say “with respect to \(x\text{,}\)” we mean that we are treating \(x\) as an input variable, and trying to find out how \(f\) changes based on changes to that input. The notation says, “find the rate at which \(f(x)\) changes as \(x\) increases.”
Because this notation is a call to action, we can use it when we’re dealing with an equation. We can call back to our early algebra days, where we learned that whatever we do to one side of an equation needs to be done to the other side, in order to maintain the equality.
When do we need to use the Chain Rule? When do we need to use some linking derivative to connect the function we’re looking at with the variable we care about?
Point out the locations on the unit circle where you would expect to see tangent lines that are perfectly horizontal. What do you think the value of the derivative, \(\dydx\text{,}\) would be at these points?
Point out the locations on the unit circle where you would expect to see tangent lines that are perfectly vertical. What do you think the value of the derivative, \(\dydx\text{,}\) would be at these points?
This curve is a special curve with some interesting mathematical properties, and is actually a part of a family of curves called elliptic curves. For now, let’s just consider it as a fun curve to look at, and use implicit differentiation to think about it.
This example was pretty similar to the first activity: in both of these, we use the Chain Rule to differentiate \(\ddx{y^2}\text{.}\) Let’s look at another example.
Think carefully about these derivatives. For each of the three, how will you approach it? What kinds of nuances or rules or strategies will you need to think about? Why?
Are any of these derivatives involving a variable other than \(x\text{,}\) the input variable (based on our \(\dydx\) notation, since we are thinking about how \(y\) changes with regard to\(x\)).
We need to apply the Chain Rule to \(\ddx{\sin(y)}\) and then we need to apply the Product Rule \(\ddx{x^2y^2}\text{.}\) Notice that when we find the derivative of \(y^2\) for the Product Rule, we need to use the Chain Rule!
Now we need to solve for \(\dydx\) or \(y'\text{,}\) whichever you are using. While this equation can look complicated, we can notice something about the “location” of \(\dydx\) or \(y'\) in our equation.
The first thing we can notice is that we have talked through how to employ two of the three big derivative rules: we used the Chain Rule throughout these examples, and in Activity 3.1.3 we needed to use the Product Rule in order to differentiate \(\ddx{x^2y^2}\text{.}\) We have a glaring omission from our examples so far, though. Where is the Quotient Rule?
The only difference, really, is that the curve with the division is not defined at \(x=0\text{.}\) As long as we keep those domain issues in mind, we can multiply everything by \(x\) to get our familiar equation:
We use the Chain Rule whenever we differentiate something like \(\dd{}{y}\left(f(y)\right)\text{.}\) We differentiate whatever the function is, and multiply by the derivative of \(y\text{:}\)\(f'(y)y'\text{.}\)
This generalizes more: any time the variable in our derivative notation does not match the variable in the function/term, we need to use the Chain Rule:
We use the Product Rule whenever we differentiate a term with some combination of \(x\) and \(y\) variables. More generally, we can use the Product Rule any time we have a combination of at least two variables. We have to treat these as different kinds of functions getting multiplied!
From here on out, we will use the ideas of implicit differentiation to accomplish two things:
We have a bit more flexibility with how we think of derivatives! We do not need to be restricted to only thinking about functions in order to think about rates of change or slopes at a point. We can think about any curve, any relationship between variables, and think about the relationship between them based on how one changes with regard to the other.
Implicit differentiation will be a very useful tool. Even when we have functions that can be written explicitly, they might be hard to deal with -- overly complex or maybe involving functions that we aren’t used to. It is absolutely possible, and a really useful strategy, to rewrite the relationship between variables implicitly! We can maybe create a version of these equations that we can differentiate!
We’re going to use this second idea first: in the next section we’ll be thinking about inverse functions. We do not have any idea of how to think about derivatives of logarithmic functions, like \(y=\ln(x)\text{.}\)
Use implicit differentiation to find \(\dydx\) or \(y'\text{.}\) Make a note of when you are using the product or chain rule, and make sure you know why you are using them.
Pick 2 problems from Practice Problem 3, above, that you can solve for \(y\) explicitly. Find the derivative \(\dydx\) or \(y'\) this way, and confirm that your answers are the same.
Pick 2 problems from Practice Problem 3, above, that you cannot solve for \(y\) explicitly. Explain why implicit differentiation is a useful method here.
A crab is walking along a path defined by the parabola \(y=x^2+1\text{.}\) It moves horizontally forward at a rate of 2 units/second, \(\frac{dx}{dt}=2\text{.}\) If it is currently at the point \((2,5)\text{,}\) what is the crab’s vertical speed, \(\frac{dy}{dt}\text{?}\)
Person A is holding a balloon 30m away from another Person B. If the balloon is released and floats into the air, rising straight up at a speed of 0.5m/s. Person B watches the balloon, their eye-line forming an angle \(\theta\) with the ground. When the balloon is 10m up in the air, what is the speed at which \(\theta\) changes, \(\frac{d\theta}{dt}\text{?}\)
A paper cup shaped like a cone is leaking water out of the bottom. The cup is 4 inches tall, and the radius is 1/3 of the height. If the water is leaking at a rate of 1.5 in\(^3\)/s while the the cup is full, how quickly is the height of the water in the cup decreasing?
A 12 foot ladder is leaning against a vertical wall. Someone is pushing the base of the ladder closer to the wall at a speed of 0.5 ft/s. If the ladder is currently 6 feet away from the wall, how quickly does the top of the ladder move up the wall?
A spherical water balloon is leaking water. The radius of the balloon is currently 2 inches, and we notice that it is decreasing at a rate of 1 in/min. How fast is the water leaking, in in\(^3\)/min?