Partial Derivatives in Multivariable Calculus

Partial derivatives help analyze functions with multiple variables, essential for physics, economics, and engineering applications.

Neetesh Kumar

Neetesh Kumar | February 08, 2025                                      \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space \space Share this Page on: Reddit icon Discord icon Email icon WhatsApp icon Telegram icon


Table of Content:


Definition of Partial Derivatives:

Partial Derivatives:
Partial derivatives are used when a function depends on two or more variables. A partial derivative represents the rate of change of the function with respect to one variable, while keeping the other variables constant.

If f(x,y)f(x, y) is a function of two variables xx and yy, the partial derivative of ff with respect to xx is denoted as: fx\boxed{\frac{\partial f}{\partial x}}

Similarly, the partial derivative of ff with respect to yy is denoted as: fy\boxed{\frac{\partial f}{\partial y}}

In general, for a function f(x1,x2,...,xn)f(x_1, x_2, ..., x_n), the partial derivative with respect to any variable xix_i is: fxi\boxed{\frac{\partial f}{\partial x_i}}


Formula Used:

The general formula for the partial derivative of a multivariable function f(x1,x2,...,xn)f(x_1, x_2, ..., x_n) with respect to one variable xix_i is:

fxi=limh0f(x1,x2,...,xi+h,...,xn)f(x1,x2,...,xn)h\boxed{\frac{\partial f}{\partial x_i} = \lim_{h \to 0} \frac{f(x_1, x_2, ..., x_i + h, ..., x_n) - f(x_1, x_2, ..., x_n)}{h}}

This means we differentiate the function with respect to one variable, while holding all other variables constant.


Derivative Examples with Solutions:

Example 1: Partial Derivative of a Multivariable Polynomial

Differentiate f(x,y)=3x2y+2xy25x+yf(x, y) = 3x^2y + 2xy^2 - 5x + y with respect to xx.

Solution:

We apply the partial derivative with respect to xx, treating yy as a constant:

x(3x2y+2xy25x+y)\dfrac{\partial}{\partial x} \left( 3x^2y + 2xy^2 - 5x + y \right)

Differentiating each term:

  • x(3x2y)=6xy\frac{\partial}{\partial x} (3x^2y) = 6xy
  • x(2xy2)=2y2\frac{\partial}{\partial x} (2xy^2) = 2y^2
  • x(5x)=5\frac{\partial}{\partial x} (-5x) = -5
  • x(y)=0\frac{\partial}{\partial x} (y) = 0 (since yy is constant)

Thus, the partial derivative is: 6xy+2y25\boxed{6xy + 2y^2 - 5}


Example 2: Partial Derivative of an Exponential Function

Differentiate f(x,y)=exyf(x, y) = e^{xy} with respect to yy.

Solution:

We apply the partial derivative with respect to yy, treating xx as a constant:

y(exy)\dfrac{\partial}{\partial y} \left( e^{xy} \right)

Using the chain rule:

y(exy)=exyy(xy)\dfrac{\partial}{\partial y} \left( e^{xy} \right) = e^{xy} \cdot \dfrac{\partial}{\partial y} (xy)

Since y(xy)=x\dfrac{\partial}{\partial y} (xy) = x, we get:

y(exy)=xexy\dfrac{\partial}{\partial y} \left( e^{xy} \right) = x e^{xy}

Thus, the partial derivative is: xexy\boxed{x e^{xy}}


Example 3: Partial Derivative of a Logarithmic Function

Differentiate f(x,y)=ln(x2+y2)f(x, y) = \ln(x^2 + y^2) with respect to xx.

Solution:

We apply the partial derivative with respect to xx, treating yy as a constant:

x(ln(x2+y2))\dfrac{\partial}{\partial x} \left( \ln(x^2 + y^2) \right)

Using the chain rule:

x(ln(u))=1uux\dfrac{\partial}{\partial x} \left( \ln(u) \right) = \dfrac{1}{u} \cdot \dfrac{\partial u}{\partial x}

Here, u=x2+y2u = x^2 + y^2, so ux=2x\dfrac{\partial u}{\partial x} = 2x.

Thus:

x(ln(x2+y2))=1x2+y22x\dfrac{\partial}{\partial x} \left( \ln(x^2 + y^2) \right) = \dfrac{1}{x^2 + y^2} \cdot 2x

So, the final answer is: 2xx2+y2\boxed{\frac{2x}{x^2 + y^2}}


Conclusion:

  • Partial derivatives are used to find the rate of change of a function with respect to one variable while holding other variables constant.
  • They are fundamental in multivariable calculus, appearing in applications such as optimization, economics, and physics.
  • The chain rule and product rule often work in conjunction with partial derivatives to solve real-world problems.