ADVERTISEMENT

Math Calculators ▶ Saddle Point Calculator

**Adblocker Detected**

We always struggled to serve you with the best online calculations, thus, there's a humble request to either disable the AD blocker or go with premium plans to use the AD-Free version for calculators.

Disable your Adblocker and refresh your web page 😊

ADVERTISEMENT

**Table of Content**

An online saddle point calculator helps you to determine the saddle point of a multivariable function.

Let us focus on the conceptual structure of the saddle point.

In the light of saddle point calculus,

“**a point where the second partial derivatives of a multivariable function become zero with no minimum or maximum value.”**

You can find saddle point when the following condition is fulfilled:

$$ \frac{\partial^{2}}{\partial {(x,y)}^{2}}\ F{\left(x, y\right)} = 0 $$

Finding saddle points is somehow or what a little bit tricky but not tough. Let us solve the following saddle point

example to get a hands-on grip.

**Example # 01:**

Find saddle point for the function given below:

$$ F{\left(x, y\right)} = \left(x^{3} – 5 x y^{2} + y\right) $$

**Solution:**

As we already know that the condition for a saddle point is:

$$ \frac{\partial^{2}}{\partial {(x,y)}^{2}} F{\left(x, y\right)} = 0 $$

For the function given, we have:

$$ \frac{\partial^{2}}{\partial {(x,y)}^{2}} \left(x^{3} – 5 x y^{2} + y\right) = 0 $$

**1st derivative steps w.r.t x:**

$$ \frac{\partial}{\partial x}\left(x^{3} – 5 x y^{2} + y\right) $$ (click partial derivative calculator for calculations)

**The derivative is:**

$$ \frac{\partial}{\partial x}\left(x^{3} – 5 x y^{2} + y\right) = 3x^2 + 5y^2 $$

**2nd derivative w.r.t.x:**

$$ \frac{\partial}{\partial x}\left(3 x^{2} – 5 y^{2}\right) $$ (click partial derivative calculator for calculations)

**The derivative is:**

$$ \frac{\partial}{\partial x}\left(3 x^{2} – 5 y^{2}\right) = 6x $$

now, we have;

**1st partial derivative w.r.t y:**

$$ \frac{\partial}{\partial y}\left(x^{3} – 5 x y^{2} + y\right) $$ (click partial derivative calculator for calculations)

**The derivative is:**

$$ \frac{\partial}{\partial y}\left(x^{3} – 5 x y^{2} + y\right) = -10x + 1 $$

**2nd partial derivative w.r.t y:**

$$ \frac{\partial}{\partial y}\left(- 10 x y + 1\right) $$ (click partial derivative calculator for calculations)

**The derivative is:**

$$ \frac{\partial}{\partial y}\left(- 10 x y + 1\right) = -10x $$

**Finding saddle points:**

To find saddle points put f”(x,y) = 0

**6x=0**

**x = 0 / 6**

**x = 0**

**−10x=0**

**x = 0 / -10**

**x = 0**

**Roots: {x:0}**

Which is the required saddle point.

If you are looking for instant results, use online saddle point calculator.

**Example # 02:**

Find saddle points of the function below:

$$ F{\left(x, y\right)} = \left(x^{4} – 5 x y + y^{3}\right) $$

**Solution:**

We know that for saddle points:

$$ \frac{\partial^{2}}{\partial {(x,y)}^{2}} F{\left(x, y\right)} = 0 $$

For the function given, we have:

$$ \frac{\partial^{2}}{\partial {(x,y)}^{2}} \left(x^{4} – 5 x y + y^{3}\right) = 0 $$

**1st derivative steps w.r.t x:**

$$ \frac{\partial}{\partial x}\left(x^{4} – 5 x y + y^{3}\right) $$ (click partial derivative calculator for calculations)

**The derivative is:**

$$ \frac{\partial}{\partial x}\left(x^{4} – 5 x y + y^{3}\right) = 4x^{3} – 5y $$

**2nd derivative w.r.t.x:**

$$ \frac{\partial}{\partial x}\left(4 x^{3} – 5 y\right) $$ (click partial derivative calculator for calculations)

**The derivative is:**

$$ \frac{\partial}{\partial x}\left(4 x^{3} – 5 y\right) = 12x^{2} $$

**1st partial derivative w.r.t y:**

$$ \frac{\partial}{\partial y}\left(x^{4} – 5 x y + y^{3}\right) $$ (click partial derivative calculator for calculations)

**The derivative is:**

$$ \frac{\partial}{\partial y}\left(x^{4} – 5 x y + y^{3}\right) = -5x + 3y^{2} $$

**2nd partial derivative w.r.t y:**

$$ \frac{\partial}{\partial y}\left(- 5 x + 3 y^{2}\right) $$ (click partial derivative calculator for calculations)

**The derivative is:**

$$ \frac{\partial}{\partial y}\left(- 5 x + 3 y^{2}\right) = 6y $$

**Finding saddle points:**

To find saddle points put f”(x,y) = 0

**12x^{2}=0**

**x = 0**

**6y = 0**

**y = 0**

**Roots: {x:0, y:0}**

If you have any doubt about the calculations you performed, you can verify the results using our free online saddle point calculator.

Performing manual calculations to find saddle points may take a lot of time. Apart from this, we have introduced you to a free online saddle points calculator.

Let us see what we need to do:

**Input:**

- Write your functions in the menu bar
- Click’ calculate’

**Output:**

The saddle point calculator calculates:

- First-order derivatrive w.r.t x
- Second-order derivative w.r.t x
- First-order derivative w.r.t y
- Second-order derivative w.r.t y
- Step by step calculations
- Saddle point for the function given

In the real-world, the surface of a handkerchief is a good example of a saddle point.

The point where we can get the minimum or maximum value of a function is termed as extremum.

For each value, you have to test an x-value slightly smaller and slightly larger than that x-value. If both are smaller than f(x), then it is a maximum. If both are larger than f(x), then it is a minimum.

There are two types of stationary points: saddle points and turning points. While turning points correspond to local extrema, saddle points do not

In saddle points calculus, a saddle point or minimax point is a point on the surface of the graph for a function where the slopes in perpendicular directions become zero (acritical point), but which is not a local extremum of the function. Mathematicians and engineers always have to find saddle point when doing an analysis of a surface. For this purpose, our free online saddle points calculator is a beneficial tool designed so far.

From the source of Wikipedia: Saddle surface, Maxima and minima, Functions of more than one variable.

From the source of khan academy: Second partial derivative test, Loose intuition, Gradient descent

From the source of lumen learning: Functions of Several Variables, Limits and Continuity, Partial Derivatives, Linear Approximation, The Chain Rule, Maximum and Minimum Values, Lagrange Multiplers, Optimization in Several Variables.