Linear Algebra, Interactive EditionXYZ Homework Edition

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5.2 Hunting the Eigenline

The last section was a rigged hunt: four candidate lines were drawn in advance, and you merely had to judge them. Suppose nobody marks the candidates. The honest search is continuous — sweep a line through every direction and watch for the moment the field stops crossing it.

The figure below stages that search in the horizontal plane z=0z = 0, where our matrix from the last section acts by (x,y)(2x+y,x+2y)(x, y) \mapsto (2x + y, \; x + 2y). A thick amber test line runs through the origin at angle aa, controlled by a slider that rotates it from 00 to 3.143.14 — nearly a half-turn, which is all a line needs, since a line at angle a+πa + \pi is the same line. Two dashed answer lines are hidden in the scene; leave them hidden until step 4.

A cube of small arrows for the vector field F(x) = Ax, colored by length, with a thick amber test line through the origin in the horizontal plane. A slider named a rotates the test line from angle 0 to about pi; at exactly two angles the arrows sitting on the line point along it instead of across it. Two dashed answer lines are hidden until revealed.Explore in 3D (opens in a new tab)
The field F(𝐱)=A𝐱F(\mathbf{x}) = A\mathbf{x} with an amber test line (tcosa,tsina,0)(t\cos a, \; t\sin a, \; 0) through the origin, rotated by the slider aa. At exactly two angles in the sweep, the arrows sitting on the line point along it instead of across it; dashed answer lines are hidden until you reveal them.

Explore the figure

  1. Start at the default a=0.3a = 0.3 and zoom toward the arrows sitting on the amber line. They cross it at a visible angle — this direction is being turned, so it is no eigenline. Notice that a=0a = 0 would be the xx-axis: the dashed decoy from last section, now just one more failed angle.
  2. Sweep aa slowly upward and watch only the arrows on the line. Somewhere near a0.79a \approx 0.79 they swing into perfect alignment, pointing outward along the line and noticeably long. Park there.
  3. Keep sweeping. Alignment breaks, then returns near a2.36a \approx 2.36 — but differently: the arrows again lie along the line, yet they are shorter, matching the position vectors in length. Two alignments in the whole sweep, with two different strengths.
  4. Reveal the two hidden dashed lines, answer: (t,t,0)(t, t, 0) and answer: (t,t,0)(t, -t, 0). Drive the slider to each and confirm your parked angles were π/4\pi/4 and 3π/43\pi/4. Every other angle in the continuum — infinitely many candidates — lost the audition.

The alignment condition

The test direction at angle aa is 𝐝=(cosa,sina)\mathbf{d} = (\cos a, \; \sin a), and the field there is A𝐝=(2cosa+sina,cosa+2sina)A\mathbf{d} = (2\cos a + \sin a, \; \cos a + 2\sin a). Alignment means A𝐝A\mathbf{d} is parallel to 𝐝\mathbf{d}, and two plane vectors are parallel exactly when their cross-term vanishes:

cos a ( cos a + 2 sin a ) sin a ( 2 cos a + sin a ) = cos 2 a sin 2 a = cos 2 a \cos a \, (\cos a + 2\sin a) - \sin a \, (2\cos a + \sin a) = \cos^2 a - \sin^2 a = \cos 2a

The mixed products cancel, and the entire misalignment of this field collapses to the function cos2a\cos 2a. On the slider's range, cos2a=0\cos 2a = 0 exactly at a=π/40.79a = \pi/4 \approx 0.79 and a=3π/42.36a = 3\pi/4 \approx 2.36 — the two places your sweep caught. Eigen-hunting is root-finding: a smooth misalignment function of the candidate direction, whose isolated roots are the eigenlines. That is why the winners are so rare, and it is the same rarity you met when a span collapsed at a single slider value in Chapter 2: special directions are knife-edge events, not neighborhoods.

One picture makes the two roots and their two eigenvalues visible at once. Feed the unit circle to AA instead of a single test direction: every direction is tested simultaneously, and the circle comes back as an ellipse.

Interactive figureThe two eigenlines of A, and what A does to the unit squareDrag inside the figure to pan; scroll to zoom.
A dashed unit circle centered at the origin, and the tilted ellipse it becomes under the matrix. The ellipse reaches furthest along the line y = x, out to a distance of 3, and least far along the perpendicular line y = -x, out to a distance of 1; those two distances are the eigenvalues, and those two lines are the eigenlines. Both are drawn dashed and extend across the whole figure. The first matrix column is a red arrow from the origin to (2, 1) and the second a blue arrow to (1, 2). A readout in the corner gives the determinant as 3, which is the product of the two eigenvalues. Every other point of the circle lands off the ray it started on. Viewing window: x from -6.13 to 6.13, y from -3.71 to 3.71.
XYZ Graph · viewer build 5edf91b
The unit circle (dashed) and its image under AA. The two dashed lines through the origin are the eigenlines; the ellipse's long and short axes lie exactly along them, and their half-lengths are the eigenvalues 33 and 11.
  1. Find the ellipse's longest radius. It points along y=xy = x — the a=π/4a = \pi/4 direction you parked at — and reaches 33 units, which is the eigenvalue there.
  2. Find the shortest radius. It points along y=xy = -x, the a=3π/4a = 3\pi/4 direction, and reaches only 11: that direction is held still, not stretched.
  3. Every other point of the circle lands off the ray it started on — that is what "the direction was turned" looks like when all directions are tested at once. Only where the ellipse touches its own axes did a direction survive.
  4. The readout gives det=3\det = 3. Check it against the two eigenvalues: 3×1=33 \times 1 = 3. A determinant is the product of the eigenvalues, which is the next section's fact, arriving early and for free.
34·L+L23 - 4 \cdot L + L^{2}
The in-plane characteristic polynomial ✓ Computed · mojocas 0.1.0 ✓ Agrees with the text The in-plane characteristic polynomial, computed exactly by mojocas 0.1.0, and confirmed to agree with the result stated in the text.

The characteristic polynomial of the in-plane matrix with rows (2,1)(2, 1) and (1,2)(1, 2), expanded by a computer algebra system: det(AλI)=λ24λ+3\det(A - \lambda I) = \lambda^2 - 4\lambda + 3. (LL stands for λ\lambda.) The sweep found its roots with a slider; the next block finds them by algebra.

3,13,\; 1
The in-plane eigenvalues ✓ Computed · mojocas 0.1.0 ✓ Agrees with the text The in-plane eigenvalues, computed exactly by mojocas 0.1.0, and confirmed to agree with the result stated in the text.

The two winning angles of the sweep, recovered as the roots of the characteristic polynomial by a computer algebra system: λ=3\lambda = 3 (the long outward arrows at π/4\pi/4) and λ=1\lambda = 1 (the pointwise fix at 3π/43\pi/4).

An original work of XYZ Homework, built around interactive XYZ 3D figures. Its chapter sequence is aligned to Interactive Linear Algebra (Margalit & Rabinoff, Georgia Tech, GNU FDL); this work is original, copies nothing from it, and is not affiliated with or endorsed by its authors. License: CC-BY-NC-SA-4.0.

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