Autonomous differential equations

In summary, the conversation discusses an autonomous differential equation and how to plot and classify its critical points as asymptotically stable or unstable. The critical point at y=0 is determined to be unstable, despite some initial confusion.
  • #1
DivGradCurl
372
0
Consider the autonomous differential equation that follows

[tex]\frac{dy}{dt} = e^y - 1, \qquad -\infty < y_0 < \infty \mbox{.}[/tex]

I'm supposed to plot [tex]f(y)[/tex] versus [tex]y[/tex], and determine the critical (equilibrium) points, and classify each one as asymptotically stable or unstable. Anyhow, you can find my plot at

http://mygraph.cjb.net/

which gives

[tex]y_0 < 0 \Longrightarrow \left\{ \begin{array}{ll} y^{\prime} < 0 & \mbox{(y is decreasing),} \\ y^{\prime \prime} < 0 & \mbox{(y is concave down),} \end{array} \right.[/tex]

and

[tex]y_0 > 0 \Longrightarrow \left\{ \begin{array}{ll} y^{\prime} > 0 & \mbox{(y is increasing),} \\ y^{\prime \prime} > 0 & \mbox{(y is concave up).} \end{array} \right.[/tex]

However, I picture the critical point [tex]y = \phi (t) = 0[/tex] to be semistable. The book says it is unstable, but I really can't find my mistake.

Any help is highly appreciated.
 
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  • #2
thiago_j said:
Consider the autonomous differential equation that follows

[tex]\frac{dy}{dt} = e^y - 1, \qquad -\infty < y_0 < \infty \mbox{.}[/tex]



[tex]y_0 < 0 \Longrightarrow \left\{ \begin{array}{ll} y^{\prime} < 0 & \mbox{(y is decreasing),} \\ y^{\prime \prime} < 0 & \mbox{(y is concave down),} \end{array} \right.[/tex]

and

[tex]y_0 > 0 \Longrightarrow \left\{ \begin{array}{ll} y^{\prime} > 0 & \mbox{(y is increasing),} \\ y^{\prime \prime} > 0 & \mbox{(y is concave up).} \end{array} \right.[/tex]

However, I picture the critical point [tex]y = \phi (t) = 0[/tex] to be semistable. The book says it is unstable, but I really can't find my mistake.

When a negative number decreases its absolute value increases so it goes away further from the origin.

ehild
 
  • #3
Absolutely! I see it now. Thanks
 

1. What are autonomous differential equations?

Autonomous differential equations are mathematical equations that describe the relationship between a variable and its derivative, where the derivative is only a function of the variable itself. In other words, the rate of change of the variable is not dependent on any other variables, making the equation "self-contained" or "autonomous."

2. What are some real-world applications of autonomous differential equations?

Autonomous differential equations are commonly used to model natural phenomena such as population growth, chemical reactions, and mechanical systems. They are also used in engineering and physics to study the behavior of systems that are not influenced by external factors.

3. How are autonomous differential equations different from non-autonomous differential equations?

The main difference between autonomous and non-autonomous differential equations is that non-autonomous equations include variables that are not dependent on the variable being differentiated. This means that the rate of change of the variable is affected by external factors, making the equation more complex and dynamic.

4. What are the key properties of solutions to autonomous differential equations?

One key property of solutions to autonomous differential equations is that they are time-invariant, meaning that the solution does not change over time. Additionally, solutions to autonomous equations are often periodic or exhibit steady-state behavior, where the variable reaches a constant value over time.

5. How are autonomous differential equations solved?

Autonomous differential equations can be solved using various methods, such as separation of variables, substitution, and numerical methods like Euler's method. The specific method used depends on the complexity of the equation and the desired level of accuracy for the solution.

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