Using a bifurcation diagrams and time dependent parameters

In summary, the conversation discusses the difficulty in sketching solutions for a bifurcation diagram with a time-dependent parameter and how the cusp normal form could potentially provide an easier approach. The speaker also mentions finding someone else with a similar problem and struggling to find any relevant problems in their resources. They also mention the potential impact of the parameter on the bifurcations and their efforts to gain a better understanding of the system.
  • #1
MathCreature
3
0
Hello,

I'm lost at where to go after drawing bifurcation diagram of
$$\dot{x} = r + x - x^3.$$ If we also assume our parameter is time dependent such that
$$\dot{r} = -\delta x.$$ How could we use our initial bifurcation diagram to sketch solutions for small δ?
 
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  • #2
Is there a reason why you would not want to consider the planar system
$$
\left\{
\begin{aligned}
\dot{x} &= r + x - x^3\\
\dot{r} &= -\delta x
\end{aligned}
\right.
$$
in a neighborhood of ##(x, r) = (0,0)## and with (time-independent) parameter ##\delta## (which I suppose is small and positive)?

Another thing to note is that for time-independent ##r## the equation for ##\dot{x}## is the cusp normal form with parameters ##\beta_1 = r## and ##\beta_2 = 1##, but although I have heard of it, I am not sufficiently familiar with "slowly time-varying parameters" to see immediately how that normal form could provide an easier approach than when we just start with the planar system.
 
Last edited:
  • #3
Thanks for the reply.

I believe I found someone who has the same problem: https://math.stackexchange.com/questions/2935059/bifurcation-of-time-dependent-parameters

I've gone through my "Strogatz's Nonlinear Dynamics and Chaos" and haven't found any problems like this, so I'm at a loss at how we can qualitatively sketch solutions. If $$\delta \approx 0,$$ then our parameter is almost constant for small x, though as x→±∞ we should eventually hit the bifurcations.
I don't believe we are using the system, but I've been looking done that path just to get an intuition of what's going on.
 

1. What is a bifurcation diagram?

A bifurcation diagram is a graphical representation that shows how the behavior of a system changes as a specific parameter is varied. It is a useful tool in understanding the dynamics of a system and identifying different types of behavior, such as steady states, periodic oscillations, and chaotic behavior.

2. How is a bifurcation diagram used in scientific research?

Bifurcation diagrams are commonly used in fields such as physics, chemistry, biology, and economics to study nonlinear systems. They help researchers to visualize and analyze the complex behaviors of these systems as parameters are changed, providing insights into the underlying mechanisms and potential outcomes.

3. What are time dependent parameters?

Time dependent parameters are variables that change over time in a system. They can be physical properties, such as temperature or pressure, or they can represent external factors that influence the system, such as external forces or inputs. By varying these parameters, researchers can observe how the system responds and how its behavior changes.

4. How do bifurcation diagrams and time dependent parameters relate?

Bifurcation diagrams are used to study the behavior of a system as one or more parameters are varied. Time dependent parameters allow for the examination of how a system's behavior changes over time. By combining these two tools, researchers can gain a deeper understanding of the dynamic behavior of a system and how it is affected by changing parameters.

5. What are some limitations of using bifurcation diagrams and time dependent parameters?

One limitation is that bifurcation diagrams only show the behavior of a system for a specific range of parameter values. If the parameters are changed outside of this range, the behavior may be different. Additionally, time dependent parameters can be difficult to measure accurately, which can affect the reliability and reproducibility of results. Finally, bifurcation diagrams may not capture all possible behaviors of a system, especially for highly complex or chaotic systems.

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