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Dated: 30-10-2024

Examples

Example

\[f(x) = \sqrt{x^2 + y^2}\]
\[f_x(x,y) = \frac{x}{\sqrt{x^2 + y^2}}\]
\[f_y(x,y) = \frac{y}{\sqrt{x^2 + y^2}}\]

The partial derivatives1 exists at all points except for origin.

\[f_x = 0 \text{ only if } x = 0\]
\[f_y = 0 \text{ only if } y = 0\]

The only critical point2 is \((0, 0)\) and \(f(0, 0) = 0\)
Since, \(f(x, y) \ge 0\) for all \((x, y)\), \(f(0, 0) = 0\) is the absolute minimum3 value of \(f\).

Second Partial Derivative1 Test

\[D = f_{xx}(x_0, y_0) \cdot f_{yy}(x_0, y_0) - f^2_{xy}(x_0, y_0)\]
  1. If \(D > 0\) and \(f_{xx}(x_0, y_0) > 0\) then \(f(x, y)\) has relative minimum3 at \((x_0, y_0)\)
  2. If \(D > 0\) and \(f_{xx}(x_0, y_0) < 0\) then \(f(x, y)\) has relative maximum3 at \((x_0, y_0)\)
  3. If \(D < 0\) then \(f(x, y)\) has a saddle point3 at \((x_0, y_0)\)
  4. If \(D = 0\) then no conclusion can be drawn.

Example

\[f(x, y) = 2x^2 - 4x + xy^2 - 1\]
\[f_x(x, y) = 4x - 4 + y^2 \text{ and } f_{xx}(x, y) = 4\]
\[f_y(x, y) = 2xy \text{ and } f_{yy}(x, y) = 2x\]
\[f_{xy}(x, y) = f_{yx}(x, y) = 2y\]

Putting the partial derivatives1 equal to \(0\), we have

\[4x - 4 + y^2 = 0\]
\[2xy = 0\]

Try solving for variables and we will get following critical points2

\[(1, 0)\]
\[(0, 2)\]
\[(0 ,-2)\]

Checking the nature of the points

\[f_{xx}(1, 0) = 4\]
\[f_{yy}(1, 0) = 2\]
\[f_{xy}(1, 0) = 0\]
\[D = f_{xx}(1, 0) \cdot f_{yy}(1, 0) - f_{xy}^2(1, 0)\]
\[D = 4 \cdot 2 - 0^2 = 8 > 0\]

Hence, the function4 \(f(x, y)\) has relative minimum3 at \((1, 0)\)

\[f_{xx}(0, -2) = 4\]
\[f_{yy}(0, -2) = 0\]
\[f_{xy}(0, -2) = -4\]
\[D = f_{xx}(0, -2) \cdot f_{yy}(0, -2) - f_{xy}^2(0, -2)\]
\[D = 4 \cdot 0 - (-4)^2 = -16 < 0\]

Hence, the function4 \(f(x, y)\) has saddle point3 at \((0, -2)\)

\[f_{xx}(0, 2) = 4\]
\[f_{yy}(0, 2) = 0\]
\[f_{xy}(0, 2) = 4\]
\[D = f_{xx}(0, 2) \cdot f_{yy}(0, 2) - f_{xy}^2(0, 2)\]
\[D = 4 \cdot 0 - 4^2 = -16 < 0\]

Hence, the function4 \(f(x, y)\) has saddle point3 at \((0, 2)\)

References

Read more about notations and symbols.


  1. Read more about partial derivative

  2. Read more about critical points

  3. Read more about extreme values

  4. Read more about function