Differentials and Chain Rule

Table of Contents

1. Total Differential

Given function \(f(x,y,z)\), we have

\[ \text{d}f = f_x\text{d}x + f_y\text{d}y + f_z\text{d}z \]

In this way, these differentials encode how changes in \(x\), \(y\), and \(z\) affect the function \(f\). Notice that it is similar to our formula for linear approximations, and so they can also be thought of as a placeholder for the small variations \(\Delta x\), \(\Delta y\), and \(\Delta z\).

2. Chain Rule

We can also divide by something like \(\text{d}t\) to get a rate of change if they depend on some external parameter \(t\), such as when \(x=x(t)\), \(y=y(t)\), and \(z=z(t)\), to get the chain rule:

\[ \frac{\text{d}f}{\text{d}t} = f_x\frac{\text{d}x}{\text{d}t} + f_y\frac{\text{d}y}{\text{d}t} + f_z\frac{\text{d}z}{\text{d}t} \]

2.1. Proof

From our formula for linear approximation, we have that:

\[ \Delta f \approx f_x \Delta x + f_y \Delta y + f_z \Delta z \]

Dividing everything by a change in time \(\Delta t\), we have:

\[ \frac{\Delta f}{\Delta t} \approx f_x\frac{\Delta x}{\Delta t} +f_y \frac{\Delta y}{\Delta t} + f_z \frac{\Delta z}{\Delta t} \]

Now, as we take the limit as \(\Delta t\) tends to zero, we get the following equality which is the chain rule:

\[ \lim_{\Delta t \to 0}{\frac{\Delta f}{\Delta t}} = \frac{\text{d}f}{\text{d}t} = f_x\frac{\text{d}x}{\text{d}t} + f_y\frac{\text{d}y}{\text{d}t} + f_z\frac{\text{d}z}{\text{d}t} \]

3. Applications of Chain Rule

3.1. Product Rule

We can use multivariable calculus and the chain rule to justify the product rule. Given a function \(f=uv\), where \(u=u(t)\) and \(v=v(t)\), we have that:

\[ \frac{\text{d}(uv)}{\text{d}t} = f_u \frac{\text{d}u}{\text{d}t} + f_v \frac{\text{d}v}{\text{d}t} = v \frac{\text{d}u}{\text{d}t} + u \frac{\text{d}v}{\text{d}t} \]

3.2. Quotient Rule

Given a function \(g=\frac{u}{v}\), where \(u=u(t)\) and \(v=v(t)\), we have:

\[ \frac{\text{d}(\frac{u}{v})}{\text{d}t} = \frac{1}{v} \frac{\text{d}u}{\text{d}t} - \frac{u}{v^2} \frac{\text{d}v}{\text{d}t} \]

3.3. Multiple Intermediate Variables

If we have a function \(f(u,v)\) where we have \(u(x,y)\) and \(v(x,y)\), we now have two intermediate variables \(x\) and \(y\). If we actually calculate the chain rule out, we have the following formulas:

\begin{aligned} \frac{\partial f}{\partial u} = \frac{\partial f}{\partial x} \frac{\partial x}{\partial u} + \frac{\partial f}{\partial y} \frac{\partial y}{\partial u} \\ \frac{\partial f}{\partial v} = \frac{\partial f}{\partial x} \frac{\partial x}{\partial v} + \frac{\partial f}{\partial y} \frac{\partial y}{\partial v} \end{aligned}
Last modified: 2025-06-21 18:47