Recursive logistic map vs continuous logistic function

In summary, the logistic function is characterized by the differential equation df(x)/dx = f(x)(1-f(x)), while the continuous version of the logistic map is given by the recursive function xn+1 = xn(1-xn). However, the two may not behave similarly as the approximation of a differential equation by a recurrence relation is not the same as the discrete-time system given by x_{n+1} = f(x_n).
  • #1
nomadreid
Gold Member
1,668
203
how is the logistic function characterized by the differential equation
df(x)/dx = f(x)(1-f(x))
[with solution f(x)=1/(1+e-x), but this is irrelevant to the question]
the continuous version of the logistic map, given by the recursive function:
xn+1 = xn(1-xn)?
It would seem to me that, in order for the limit of the latter, as n goes to zero, to go to the former, you would need the latter to look like this:
xn+1-xn = xn(1-xn)

A second question: usually the logistic map is given by
xn+1 = r.xn(1-xn) for some real r.
when taking the continuous version, does the r survive as
df(x)/dx = r.f(x)(1-f(x))?

Thanks.
 
Physics news on Phys.org
  • #2
nomadreid said:
how is the logistic function characterized by the differential equation
df(x)/dx = f(x)(1-f(x))
the continuous version of the logistic map, given by the recursive function:
xn+1 = xn(1-xn)?

It depends on what you mean by "continuous version". Given a suitable [itex]f(x)[/itex], you can either turn it into a continuous-time system by setting
[tex]
\dot x = f(x)
[/tex]
or a discrete-time system by setting
[tex]
x_{n+1} = f(x_n).
[/tex]
But it is not always the case that the two will behave similarly.

A different idea is the approximation of a differential equation by a recurrence relation. If one sets [itex]t = nh[/itex] and [itex]x_n = x(nh)[/itex] for some [itex]h > 0[/itex] then one can approximate [itex]\dot x(t)[/itex] by [itex](x_{n+1} - x_n)/h[/itex] to obtain
[tex]x_{n+1} = x_n + hf(x_n).[/tex]
But this is not the same recurrence relation as [itex]x_{n+1} = f(x_n)[/itex].
 

What is the difference between a recursive logistic map and a continuous logistic function?

A recursive logistic map is a mathematical model that describes the behavior of a system over time, while a continuous logistic function is a mathematical function that describes the growth or decay of a population. The main difference between the two is that a recursive logistic map is a discrete process, meaning it is calculated at specific time intervals, while a continuous logistic function is a continuous process, meaning it is calculated at every point in time.

How do you determine the stability of a recursive logistic map?

The stability of a recursive logistic map can be determined by analyzing the values of its parameters, specifically the growth rate and carrying capacity. If the growth rate is less than one, the map will eventually converge to a stable point. If the growth rate is greater than one, the map will exhibit chaotic behavior and will not converge to a stable point.

Why is the recursive logistic map a useful tool in studying population dynamics?

The recursive logistic map allows scientists to model and predict the behavior of a population over time. By adjusting the parameters of the map, they can simulate different scenarios and observe how the population will respond. This can help in understanding the factors that influence population growth or decline and inform management and conservation efforts.

Can a recursive logistic map accurately predict the behavior of real-world populations?

While a recursive logistic map can provide valuable insights into population dynamics, it is important to note that it is a simplified mathematical model and may not accurately reflect the complexities of real-world populations. Factors such as external influences, environmental changes, and interactions with other species may not be accounted for in the model.

What are the limitations of using a continuous logistic function in population studies?

The continuous logistic function assumes that population growth is continuous and infinite. This may not be true for all populations, as they may experience fluctuations or reach a carrying capacity where growth is limited. Additionally, the function may not accurately capture the effects of external factors on population dynamics, such as resource availability or competition.

Similar threads

Replies
1
Views
1K
Replies
2
Views
1K
  • Calculus
Replies
12
Views
508
Replies
8
Views
2K
Replies
14
Views
2K
  • Calculus
Replies
3
Views
1K
Replies
3
Views
1K
Replies
1
Views
956
  • Calculus
Replies
1
Views
958
Back
Top