Bifurcations, steady states, model analysis

In summary, the conversation discusses steady states and stability in a piecewise defined model. The steady states are when $N_{t+1} = N_t = N_*$. The values for the steady states are $N_* = \sqrt[b]{r}$ and $N_* = 0$. To check for stability, three cases are considered: $N_t < 0$, $0 < N_t < \sqrt[b]{r}$, and $\sqrt[b]{r} < N_t$. Depending on the values of $N_t$ and $N_{t+1}$ in each case, it can be determined if 0 or $\sqrt[b]{r}$ is stable. Both can be unstable at the same time,
  • #1
Dustinsfl
2,281
5
$N_{t + 1} =\begin{cases}rN_t^{1 - b}, & N_t > K\\
rN_t, & N_t < K
\end{cases}$The steady states are when $N_{t + 1} = N_t = N_*$.
$$
N_{*} =\begin{cases}rN_*^{1 - b}, & N_* > K\\
rN_*, & N_* < K
\end{cases}
$$
So the steady states are $N_* = \sqrt{r}$ and $N_* = 0$.

I am not sure how to check for stability and bifurcations values for a piece wise defined model.
 
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  • #2
Look at three cases:

1) Suppose $N_t< 0$. What is $N_{t+1}$? Is it larger than $N_t$ so that the sequence is heading toward 0 or is it smaller so the sequence is heading away from 0?

2) Suppose $0< N_t<\sqrt{r}$. What is $N_{t+1}$? Is it less than $N_t$ so the sequence is heading toward 0 or is it larger so it is heading toward $\sqrt{r}$?

3) Suppose $\sqrt{r}< N_t$. What is $N_{t+1}$? Is it less than $N_t$ so the sequence is heading toward $\sqrt{r}$ or is it larger so it is heading away?

If in 1 and 2 you said that the sequence was heading toward 0, then 0 is stable. If in 2 and 3 you said that the sequence was heading toward $\sqrt{r}$ then that is stable. Notice that is is not possible for both 0 and $\sqrt{r}$ both to be stable- if in 2, the sequence is heading toward 0, it cannot be heading toward $\sqrt{r}$. It is, however, possible for them both to be unstable.
 

FAQ: Bifurcations, steady states, model analysis

What is a bifurcation in a scientific context?

A bifurcation refers to a qualitative change in the behavior of a system as a parameter is changed. This can occur in various scientific fields such as physics, chemistry, biology, and economics.

What is a steady state in a scientific model?

A steady state is a state in which the variables of a system remain constant over time. In other words, the system is in equilibrium and there is no net change in the system. This is often represented by a point where the system's equations intersect.

How do you analyze a model in science?

Model analysis involves studying the behavior of a system by using mathematical equations or computer simulations. This includes identifying steady states, determining parameter values for bifurcations, and examining the stability of the system.

What are some common methods for studying bifurcations and steady states?

Some common methods for studying bifurcations and steady states include phase plane analysis, bifurcation diagrams, and stability analysis. These methods use mathematical tools and visualizations to understand the behavior of a system.

What are the applications of bifurcations and steady states in scientific research?

Bifurcations and steady states are often used to understand complex systems and predict their behavior. They have applications in various fields such as ecology, climate science, and neuroscience. They can also help in designing and controlling systems to achieve desired outcomes.

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