Equilibrium in system of non-linear difference equations

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Discussion Overview

The discussion revolves around finding equilibrium solutions for a system of non-linear difference equations. Participants explore methods to calculate equilibrium points as the iteration index approaches infinity, with examples provided to illustrate the concepts involved.

Discussion Character

  • Exploratory, Technical explanation, Conceptual clarification

Main Points Raised

  • One participant inquires about processes to find equilibrium solutions for a specific system of difference equations, expressing uncertainty about the approach.
  • Another participant suggests eliminating one variable to express the others as a function of the remaining variables, defining a function on ℝ³ to identify fixed points as equilibrium solutions.
  • A later reply reiterates the same approach but introduces a different system of equations, indicating that the principles remain applicable.
  • Further, it is noted that the new system corresponds to a mapping on ℝ⁴, and a stationary solution is described as a fixed point of this mapping. The participant mentions that finding fixed points can sometimes be done analytically or may require numerical methods.

Areas of Agreement / Disagreement

There is no explicit consensus on the methods to find equilibrium points, as participants present different systems and approaches without resolving the overall uncertainty in the process.

Contextual Notes

Participants express varying levels of familiarity with the topic, indicating that some foundational knowledge may be necessary to fully engage with the discussion. The complexity of the systems and the potential need for numerical methods suggest limitations in straightforward analytical solutions.

math4everyone
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I have a little question. I want to know if there is a process in which I can find equilibrium solutions to some system of difference equations. For example, if I have something crazy like
$$\begin{cases} x[n+1]=(x[n])^2y[n]+z[n]e^{-ax[n]} \\
y[n+1]= z[n]x[n]+x[n+1]y[n+1]\\
z[n+1]= \frac{x[n]}{1+x[n]}
\end{cases}$$
I would like to know how to calculate equilibrium points when $$n \rightarrow \infty$$
 
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Using the equation for ##x_{n+1}## first write ##y_{n+1}## as a function of ##(x_n,y_n,z_n)##. (So, eliminate ##x_{n+1}##). After this, the right-hand side of your system defines a function ##f## on ##\mathbb{R}^3##, as
$$
\begin{bmatrix}
x_{n+1}\\
y_{n+1}\\
z_{n+1}
\end{bmatrix}
= f(x_n,y_n,z_n).
$$
Your equilibrium points are the fixed points of ##f##.
 
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Krylov said:
Using the equation for ##x_{n+1}## first write ##y_{n+1}## as a function of ##(x_n,y_n,z_n)##. (So, eliminate ##x_{n+1}##). After this, the right-hand side of your system defines a function ##f## on ##\mathbb{R}^3##, as
$$
\begin{bmatrix}
x_{n+1}\\
y_{n+1}\\
z_{n+1}
\end{bmatrix}
= f(x_n,y_n,z_n).
$$
Your equilibrium points are the fixed points of ##f##.
Thanks for the reply, but this was just an example. I apologize for not stating the real problem.The real system of difference equations I have is the following
$$
\begin{cases}
X_j [n+1] = (1-m_j - \theta - \delta N[n])X_j[n]+\alpha X_a[n] e^{-\beta X_a [n]} \\
X_a[n+1]=(1-m_a-H[n]-\delta N[n])X_a[n] + \theta X_j[n]\\
N[n+1] = \frac{\gamma K X_a [n]}{K+\gamma X_a[n]} \\
H[n+1] = q \left( \frac{a(P_f q X_a [n]-C_f - \pi \omega_\tau)}{1+b(P_f q X_a [n]-C_f - \pi \omega_\tau)}+E_{min} \right)
\end{cases}
$$
I am really new to this topic, so I don't fully understand what I have to do.
 
It's the same principle: This system corresponds to a mapping ##f## on (a domain in) ##\mathbb{R}^4## that takes as inputs the state ##(X_j[n], X_a[n], N[n], H[n])## at the (discrete) time ##n \in \mathbb{Z}_+## and produces the state
$$
\begin{bmatrix}
X_j[n+1]\\
X_a[n+1]\\
N[n+1]\\
H[n+1]
\end{bmatrix}
= f(X_j[n], X_a[n], N[n], H[n])
$$
at time ##n + 1##. A stationary solution of the difference equations then corresponds to a state that does not change in time. Such a state is precisely a fixed point of ##f##. I did not calculate the fixed points myself, that is up to you. Sometimes they can be found analytically, but sometimes you need to resort to numerical root finders such as Newton's (and Newton-like) method(s).

This and related topics (such as stability determination of the stationary solutions) are typically treated in courses and books on discrete-time dynamical systems ("iterated maps").
 
Last edited:
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