Find the equilibrium points and their stability in the system

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SUMMARY

The discussion focuses on finding equilibrium points and their stability in the system defined by the equations xdot = xy - 2y - x + 2 and ydot = xy + x. Two critical points are identified: (2, -1) and (0, 1). The Jacobian matrix is constructed for each critical point, yielding eigenvalues that determine stability. The eigenvalues for (2, -1) are real and unequal, indicating a saddle point and instability, while the eigenvalues for (0, 1) are pure imaginary, classifying it as a center point, which is marginally stable.

PREREQUISITES
  • Understanding of differential equations and dynamical systems
  • Knowledge of Jacobian matrices and their applications
  • Familiarity with eigenvalues and their significance in stability analysis
  • Experience with critical point analysis in nonlinear systems
NEXT STEPS
  • Study the classification of equilibrium points in nonlinear systems
  • Learn about the implications of pure imaginary eigenvalues in stability analysis
  • Explore numerical methods for analyzing nonlinear dynamical systems
  • Investigate the behavior of systems with saddle points and centers
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Students and professionals in mathematics, physics, and engineering who are analyzing dynamical systems and seeking to understand equilibrium points and their stability characteristics.

bjohnson2001
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Homework Statement



Find the equilibrium points and their stability in the system

xdot = xy - 2y - x + 2

ydot = xy + x

Homework Equations



Jacobian matrix = g'(x)

The Attempt at a Solution



first find the points that a critical point would satisfy

rewrite xdot = x(y-1) - 2(y-1) = 0
rewrite ydot = x(y+1) = 0

if x = 2 then y = -1
if y = 1 then x = 0

This yields two critical points:

(2,-1)
(0,1)

construct the jacobian matrix and determine eigenvalues for each critical point

g'(x) = [(y-1) (x-2); (y+1) x]

A_1 = g'((2,-1)) = (-2 0; 0 2)

A_2 = g'((0,1)) = (0 -2; 2 0)

det(A_1-lambda*I) = (lambda-2)(lambda+2)

yields the roots: lambda_1 = 2, lambda_2 = -2

Since the roots are real and unequal with the opposite sign, the critical point is a
saddle point and is unstable

det(A_2-lambda*I) = (lambda-2i)(lambda+2i)

yields the roots: lambda_1 = 2i, lambda_2 = -2i

Since the roots are pure imaginary, the solution is an ellipse that is marginally stable?


I don't know how to classify the stability of pure imaginary eigenvalues. Do I call this marginally stable? Is this still called a center point even though it is centered around (0,1) rather than the origin?

Also I am concerned about how much work I am showing and the completeness of the solution. The if x then y procedure seems especially informal..I want to provide the most complete solution possible to demonstrate I understand the concept.

Any advice or criticism is encouraged and appreciated! Thank you
 

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Physics news on Phys.org
Eigenvalues which are pure imaginary are "centers" no matter where they're located and are stable since they remain bounded however this may not always reflect the behavior of the non-linear system. That is, the non-linear system may in fact be a spiral source or sink which only does so slowly. Nice plot.
 

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