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Diagonal eigenmodes · First eigenvalue a=2; Second eigenvalue b=-1.5

Use the completed matrix transformation at the animation endpoint. Find the image of (1,1), the determinant, and the unsigned area of the square's image. Givens: First eigenvalue a=2; Second eigenvalue b=-1.5.

Try the question, use a hint when you need one, and compare your reasoning with the worked solution. The animation starts with this chapter’s values; changing its controls explores a new case.

01 · Make a prediction

Your practice question

A diagonal linear map is A=diag(2,-1.5). Apply it to (1,1) and the unit square. Use the completed matrix transformation at the animation endpoint. Find the image of (1,1), the determinant, and the unsigned area of the square's image.

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02 · Explore the model

See the mathematical relationship move.

Use Play, Pause, and the timeline to inspect the construction. Reset restores the question’s original settings. The displayed assumptions describe where this model applies.

Watch the relationship

Paused
Diagonal eigenmodes · First eigenvalue a=2; Second eigenvalue b=-1.5. Image x coordinate: 1. Image y coordinate: 1. Current determinant: 1. Final determinant: -3Two independently scaled directionsxy0Dashed: unit squareFilled: current imageEqual axis scales · coordinates in the readouts
The animation shows interpolation of matrices, not matrix powers or a physical trajectory. The input is fixed at (1,1). Determinants can be zero or negative, and signed area differs from ordinary nonnegative area.

Starts paused. Play once, pause anywhere, or use Step to inspect the mathematics. Playback stops when this panel leaves the screen.

Make it your experiment

Change one value. Notice what follows.

The controls adjust the model. Numbers below describe the current frame. Decimals are rounded.

Image x coordinate
1
Image y coordinate
1
Current determinant
1
Final determinant
-3

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From experiment to screen.

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The mathematical idea

A diagonal map scales the coordinate axes independently, so those axes are eigen-directions. Applying the map to (1,1) makes the two scale factors visible together. A negative factor reverses orientation along an axis, while a zero factor loses a dimension. A diagonal linear map is A=diag(2,-1.5). Apply it to (1,1) and the unit square. Use the completed matrix transformation at the animation endpoint. The requested state occurs at 100% playback; use the exact target stated in the question for your calculation.

A=diag(a,b); B(t)=(1−t)I+tA

03 · Reflect and transfer

Explain what changes and why.

Compare a negative determinant with a zero determinant. Which represents a reflection and which represents loss of dimension?

This is a distinct guided scenario using a reusable mathematical model. Similar-looking diagrams can represent different given values and conclusions; they are not different mathematical theories.