Differentiating When y Isn’t Isolated: Implicit and Higher-Order Derivatives
Implicit Differentiation
What “implicit” means (and why you need a new technique)
In many problems, you learn differentiation by writing a function explicitly, like , where is already isolated on one side. Then you can apply derivative rules directly.
But equations often describe relationships where is not isolated. For example, a circle might be written as
This is an implicit relationship: and are tied together by an equation, and the equation may represent a curve that doesn’t pass the vertical line test (so it might not even be a function globally). Still, you often want the slope of the tangent line, which is , at a point on that curve.
Implicit differentiation is the method that lets you differentiate both sides of an equation with respect to without first solving for . It’s powerful because solving for can be messy, impossible in elementary functions, or it can introduce extra work.
The core idea: treat as a function of
The key mindset shift is this:
- Even if the equation doesn’t say explicitly, along the curve, typically _depends on_ .
- So when you differentiate an expression containing with respect to , you must use the Chain Rule.
A simple example of why the Chain Rule appears: if depends on , then
That extra factor is the “receipt” for remembering that changes when changes.
Notation you’ll see (and how it all connects)
In AP Calculus AB, implicit differentiation is usually written with derivative notation like , but you might also see other forms.
| Meaning | Common notation | Notes |
|---|---|---|
| derivative of with respect to | Most common in implicit problems | |
| derivative of with respect to | Equivalent to | |
| derivative of a function | Useful when differentiating both sides |
No matter the notation, you are finding the slope of the curve in terms of and .
The algorithm (how implicit differentiation works)
When you’re given an equation involving and , here is the reliable process:
Differentiate both sides with respect to .
- Treat as the variable.
- Treat as a function of .
Whenever you differentiate something involving , multiply by (Chain Rule).
- Examples:
- Examples:
Collect the terms that contain on one side.
Factor out and solve for it.
This structure prevents a common mistake: trying to “solve for ” too early before you’ve gathered all the terms.
Why this matters on graphs (tangent lines and local behavior)
Even if the equation represents a shape like a circle or sideways parabola, implicit differentiation still gives you:
- the slope of the tangent line at a point,
- whether the tangent is horizontal or vertical (or undefined),
- information that connects to motion and rates later (related rates often start from implicit relationships).
A particularly AP-relevant use: once you have , you can plug in a point to get a numerical slope and write the tangent line.
Worked Example 1: A circle
Differentiate implicitly and find for
Step 1: Differentiate both sides with respect to .
Step 2: Solve for .
This answer makes sense geometrically: on the top half of the circle where , the slope is negative when and positive when .
Tangent line at a point: Suppose you want the tangent line at (which lies on the circle because ). Then
Using point-slope form:
Worked Example 2: Product Rule plus Chain Rule (classic AP style)
Find if
This problem is designed to test whether you can combine:
- Product Rule for
- Chain Rule for
- Solving for
Step 1: Differentiate both sides.
For , use Product Rule: .
For , use Chain Rule: .
So:
Step 2: Collect terms.
Step 3: Factor and solve.
A common “looks small but is huge” mistake here is forgetting that is not —you must include .
How to recognize and handle special tangent lines
Implicit differentiation is especially good for detecting when tangents are horizontal or vertical.
If
then:
- Horizontal tangent when , which usually means and .
- Vertical tangent when is undefined, which usually means and .
You typically must also ensure the point lies on the original curve.
Worked Example 3: Horizontal and vertical tangents on a curve
Consider
Step 1: Differentiate both sides.
Distribute the right side:
Step 2: Collect terms.
Step 3: Factor and solve.
You can simplify by factoring 3:
Horizontal tangents: require
so
But the point must also satisfy the original equation. Substitute into
This becomes
If , then works. If , divide by :
So
and then
You usually can leave coordinates in exact form unless the question asks for decimals.
Vertical tangents: require
so
and again you would substitute into the original equation to find the points.
The big idea: “horizontal tangent” and “vertical tangent” are not just algebra conditions; they are calculus conditions plus the requirement that the point lies on the curve.
Exam Focus
- Typical question patterns
- “Find for the curve given by …” where the equation mixes polynomials with trig or exponential terms like or .
- “Find the equation of the tangent line (or normal line) at the point …” using implicit differentiation to get the slope.
- “Find where the tangent is horizontal/vertical” by setting the numerator or denominator of to zero and checking points on the curve.
- Common mistakes
- Forgetting Chain Rule on -expressions (writing instead of ).
- Doing Product Rule incorrectly for mixed terms like (it should become ).
- Finding candidate points for horizontal/vertical tangents from but not verifying they satisfy the original equation.
Higher-Order Derivatives
What “higher-order” means in an implicit setting
A higher-order derivative is any derivative beyond the first, such as the second derivative (also written ). Conceptually:
- tells you the **slope** (rate of change of with respect to ).
- tells you how that slope is **changing** as changes.
In graph terms, the second derivative connects to concavity:
- If , the curve is concave up (slopes are increasing).
- If , the curve is concave down (slopes are decreasing).
In explicit functions, you can compute by differentiating . With implicit equations, you do the same thing—but you must remember that often contains , and depends on .
Why this matters (beyond just “compute another derivative”)
Higher-order derivatives show up in AP Calculus AB because they let you analyze curves defined implicitly in much richer ways:
- You can describe the curve’s local shape (concavity) even when you can’t solve for .
- You can identify where curvature changes, and you can support graphical reasoning.
- You practice careful Chain Rule thinking, because at the second-derivative level it’s very easy to “drop” a factor of .
The key mechanism: differentiate and substitute back
A reliable method for implicit higher-order derivatives is:
- Use implicit differentiation to find .
- Differentiate both sides of that equation with respect to to find .
- Replace any that appears with the expression you found in step 1 (this is optional but often simplifies).
A crucial warning: when you differentiate something like , you are differentiating a quotient that involves . So you need Quotient Rule (or write it as a product) and Chain Rule.
Worked Example 1: Second derivative of a circle
Start with
We already found
Now find .
Step 1: Differentiate with respect to .
Write it as
Differentiate using Product Rule (or treat as a product of and ):
- Derivative of is .
- Derivative of is (Chain Rule).
So
Simplify:
Step 2: Substitute .
Combine into one fraction:
Using the original equation , you can rewrite:
This is a great simplification and is very typical of AP problems: the original relationship often helps you simplify a derivative expression.
Interpretation:
- On the upper semicircle, , so and , meaning the curve is concave down.
- On the lower semicircle, , so and , meaning concave up.
That matches the geometry of a circle.
Worked Example 2: Second derivative when is embedded in the first derivative equation
Sometimes it’s cleaner not to solve completely for before differentiating again. You can do it either way, but you must be consistent.
Given
From earlier:
Now differentiate this equation again to get .
Step 1: Differentiate both sides with respect to .
Differentiate each term carefully:
- uses Product Rule:
uses Product Rule again. Let and .
First, .
So
- Right side:
Putting it together:
Step 2: Combine like terms and solve for .
Group the terms:
Group the terms:
So the equation becomes:
Now solve for :
If the problem also gives a specific point, you would compute at that point first, then substitute to get a numerical value for .
A practical tip: expect to appear inside
In implicit higher-order derivatives, it’s normal for to initially contain . You can:
- Leave in terms of , , and if the problem allows, or
- Substitute your expression for to rewrite everything in terms of and .
On AP-style questions that ask for a value of at a point, substitution is the cleanest approach because you can evaluate numbers directly.
Common conceptual pitfalls (what tends to go wrong)
Higher-order implicit problems are less about memorizing a formula and more about staying disciplined with differentiation rules.
- Forgetting that is a function of . When you differentiate something like , the result is not just . You need Product Rule and get .
- Dropping parentheses around . It’s easy to accidentally write something like in your head and then mishandle it. Treat as a single object.
- Not simplifying with the original equation. As in the circle example, substituting can dramatically simplify your final form.
Exam Focus
- Typical question patterns
- “Find for the curve …” often after you find .
- “Find at the point …” which requires computing at the point first, then using it to evaluate .
- “Determine concavity at a point on an implicitly defined curve” using the sign of .
- Common mistakes
- Differentiating incorrectly (missing Product Rule), leading to a missing term.
- Forgetting Chain Rule when differentiating trig/exponential functions of (for instance, must include ).
- Plugging in the point too early in a way that hides dependence on (it’s usually safer to derive a correct symbolic expression first, then evaluate).