```markdown
### Image Description

The image shows a comparison of optimization techniques using contour plots for a nonquadratic function:

\[ f(x_1, x_2) = e^{x_1 + 3x_2 - 0.1} + e^{x_1 - 3x_2 - 0.1} + e^{-x_1 - 0.1} \]

#### Left Plot: Backtracking Line Search
- Displays contour lines representing levels of the function.
- Shows an iterative optimization path starting from \( x^{(0)} \) to \( x^{(1)} \), \( x^{(2)} \), and so on.
- The path zigzags, indicating multiple steps to reach closer to the minimum.

#### Right Plot: Exact Line Search
- Similar contour lines representing the same function.
- Displays a more direct optimization path from \( x^{(0)} \) to \( x^{(1)} \).
- Fewer steps are shown, indicating a more efficient approach in reaching the minimum.

Both plots illustrate the performance differences between backtracking and exact line search methods on the same function.

*Source: A. d’Aspremont. Convex Optimization M2.*
```
