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Graduate · Contraction estimates · 509 of 650

Contraction estimates · Contraction slope q=-0.5; Constant b=1.5

Use n=7 iterations. Find the fixed point, seventh iterate, and exact absolute error from the fixed point. Givens: Contraction slope q=-0.5; Constant b=1.5.

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01 · Make a prediction

Your practice question

Iterate T(x)=(-0.5)x+(1.5) on the complete real line, starting with x₀=3. Use n=7 iterations. Find the fixed point, seventh iterate, and exact absolute error from the fixed point.

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02 · Explore the model

See the mathematical relationship move.

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Watch the relationship

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Contraction estimates · Contraction slope q=-0.5; Constant b=1.5. Iteration: 0. Current iterate: 3. Unique fixed point: 1. Exact absolute error: 2An exact contraction error estimate030612iterateiteration n → · labeled axes rescale to this model
The domain is the complete metric space R, the map is affine, and |q|≤0.8. The initial iterate is fixed at three. The explicit identity is stronger than a general contraction bound and does not describe every nonlinear iteration.

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Make it your experiment

Change one value. Notice what follows.

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Iteration
0
Current iterate
3
Unique fixed point
1
Exact absolute error
2

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From experiment to screen.

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The mathematical idea

A contraction controls all pairs of inputs, not just the sampled orbit. For this affine map, the Lipschitz constant is |q|<1 on complete real space, yielding a unique fixed point. The explicit error identity lets the animation illustrate the theorem without replacing its hypotheses with empirical convergence. Iterate T(x)=(-0.5)x+(1.5) on the complete real line, starting with x₀=3. Use n=7 iterations. The requested state occurs at 60% playback; use the exact target stated in the question for your calculation.

T(x)=qx+b; x*=b/(1−q); |xₙ−x*|=|q|ⁿ|3−x*|

03 · Reflect and transfer

Explain what changes and why.

Compare a positive and negative slope with the same absolute value. Which convergence feature changes and which error bound stays identical?

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.