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HL AA Paper 3 · Practice

HL AA Paper 3 Practice

Two extended, investigation-style questions in the style of the 2026 Paper 3 exam. Each has 5–7 linked sub-parts. Attempt each part first, then click Reveal worked solution.

Total: 55 marks · Recommended time: 60 minutes · Calculator permitted

Question 1 · The doubling map and chaotic dynamics

Topics: functions, iteration, sequences, logarithms · 28 marks

Define the doubling map T:[0,1)[0,1) by

T(x)=2xmod1={2xif 0x<122x1if 12x<1

The orbit of a starting point x0 is the sequence x0,x1,x2, where xn+1=T(xn). Throughout this question you may express numbers in binary using the notation 0.b1b2b32 where each bi{0,1}.

(a) [3 marks]

Compute the first five terms of the orbit starting at x0=13.

Reveal worked solution

Step 1. Apply T repeatedly.

x1=T(13)=23 (since 13<12)
x2=T(23)=2231=13
x3=T(13)=23,x4=13

Observation: the orbit is a period-2 cycle 132313 (A1 · A1 · A1)

(b) [4 marks]

Let x0=0.b1b2b32 be a binary expansion. Prove that x1=T(x0)=0.b2b3b42.

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(c) [3 marks]

Deduce that every rational x0(0,1) has an eventually periodic orbit.

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(d) [5 marks]

Two starting points x0=0.0101012 and y0=0.0101102 differ from the 5th binary digit onwards. Prove that after n applications of T, |xnyn|2(4n) for n4, and that the orbits diverge to be at least 14 apart by step 4.

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(e) [5 marks]

Prove by mathematical induction that for any x0[0,1) whose binary expansion starts with k zeros (b1=b2==bk=0), xk=2kx0.

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(f) [4 marks]

The Lyapunov exponent of the doubling map at x0 is defined as λ(x0)=limn1ni=0n1ln|T(xi)| wherever T exists. Show that λ(x0)=ln2 for every x0 where the derivative is defined.

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(g) [4 marks]

Explain, using parts (b) and (f), why despite being deterministic the doubling map is unpredictable in practice.

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Question 2 · Random walk on a triangle

Topics: probability, matrices, sequences, limits · 27 marks

A robot sits at one of three vertices of an equilateral triangle labelled A, B, C. At each step the robot moves to one of the other two vertices with probability 12 each, independently of past moves. Let pn, qn, rn denote the probability that the robot is at A, B, C respectively after n steps.

Let vn=(pnqnrn) be the state vector at step n.

(a) [3 marks]

Write down the transition matrix M such that vn+1=Mvn.

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(b) [3 marks]

The robot starts at A: v0=(1,0,0)T. Compute v1, v2 and v3.

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(c) [4 marks]

By symmetry, qn=rn for all n1. Show that pn+1=1pn12(1pn) and deduce the recurrence pn+1=12(1pn).

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(d) [6 marks]

Solve the recurrence pn+1=12(1pn) with p0=1 to obtain a closed form for pn.

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(e) [3 marks]

Deduce limnvn and interpret it.

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(f) [4 marks]

The matrix M has eigenvalues λ1=1 and λ2=λ3=12. Explain — without diagonalising M — how the eigenvalues predict both the long-run limit in (e) and the geometric decay rate in (d).

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(g) [4 marks]

A biased robot now stays put with probability b[0,1) and moves to each other vertex with probability 1b2. Predict the new dominant transient eigenvalue as a function of b, and hence how many steps roughly are needed for the state to be within 103 of the stationary distribution when b=0.9.

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