Seems like a bug. M. Macauley (Clemson) Lecture 4.6: Phase portraits, complex eigenvalues Di erential Equations 6 / 6 We define the equilibrium solution/point for a homogeneous system of differential equations and how phase portraits can be used to determine the stability of the equilibrium solution. The reason for this in this particular case is that the x-coordinates of solutions tend to 0 much more quickly than the y-coordinates.This The x, y plane is called the phase y plane (because a point in it represents the state or phase of a system). But the eigenvalues should be complex, not real: λ1≈1.25+0.66i λ2≈1.25−0.66i. Case 2: Distinct real eigenvalues are of opposite signs. The eigenvalues appear as two points on this complex plane, and will be along the x-axis (the real axis) if the eigenvalues are real. It is convenient to rep resen⎩⎪t the solutions of an autonomous system x˙ = f(x) (where x = ) by means of a phase portrait. Phase line, 1-dimensional case The phase portrait … Complex eigenvalues. ... 5.2.4 Taking Screen Shots to copy Pplane phase portraits. But I'd like to know what the general form of the phase portrait would look like in the case that there was a zero eigenvalue. The phase portrait is a circle of radius 2 about the origin ( Figure 3.4.3 ). 3 + 2i), the attractor is unstable and the system will move away from steady-state operation given a disturbance. It is indicated in the picture to the right. The attractor is a spiral if it has complex eigenvalues. The type of phase portrait of a homogeneous linear autonomous system -- a companion system for example -- depends on the matrix coefficients via the eigenvalues or equivalently via the trace and determinant. So we have the case where the eigenvalues are both complex … We also show the formal method of how phase portraits are constructed. Phase portraits and eigenvectors. In this section we will give a brief introduction to the phase plane and phase portraits. The "quiver" function may be ideal to plot phase-plane portraits. In this type of phase portrait, the trajectories given by the eigenvectors of the negative eigenvalue initially start at infinite-distant away, move toward and eventually converge at the critical point. 3.1 Real Distinct Eigenvalues 43 (a) (b) Figure 3.3 Phase portraits for a sink and a source. Figure 3.4.3. Phase Portraits: Matrix Entry. If the real portion of the complex eigenvalue is positive (i.e. Complex eigenvalues and eigenvectors generate solutions in the form of sines and cosines as well as exponentials. Repeated eigenvalues (proper or improper node depending on the number of eigenvectors) Purely complex (ellipses) And complex with a real part (spiral) So you can see they haven't taught us about zero eigenvalues. 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