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A Level · Cambridge (CIE) · 9709

Check geometric convergence and interpret a sum to infinity

Establish the ratio condition before using a limiting sum, handle alternating series and separate an idealised total from a finite-stage result.

Pure Mathematics 1 · Series · 1.6

Pure Mathematics 1 (Paper 1) · AS & A Level Mathematics 9709, 2026–2027. Use positive-integer binomial powers and positive-integer term indices. Written practice is self-checked.

Before you begin

  • Use the finite GP sum and solve compound inequalities.
  • Interpret a limiting value and include repeated journeys in a distance total.

Work on paper. Try each question before revealing help, and explain why your method works.

Quick readiness check

Which non-zero GP has a convergent sum to infinity?

What you will learn

  • Use |r| < 1 to establish convergence of a non-zero geometric series.
  • Find sums to infinity, remainders and parameter ranges, and apply them to a stated model.
Four terms and a limiting totalPieces: 15 m · Pale remainder: 1 m84211First four: 8 + 4 + 2 + 1 = 15 mLimiting sum: 16 mEach later piece keeps halving
In a 16 m stock-length model, the first four pieces are 8, 4, 2 and 1 m. Together they occupy 15 m of the top bar; the pale right-hand remainder is 1 m. Each next piece is half the previous one. The ideal infinite GP has limiting sum 16 m, shown by the equally scaled bottom bar. No finite stage in this model removes the entire limiting total; both bars use the same length scale.

The finite sums must approach one value

For a non-zero first term a, a GP has a convergent sum to infinity precisely when |r| < 1, meaning −1 < r < 1. Then rⁿ tends to zero and the finite formula Sₙ = a(1 − rⁿ)/(1 − r) approaches S∞ = a/(1 − r). A negative ratio can converge: its terms alternate with decreasing magnitude and its partial sums approach the same limit from alternate sides.

If r = 1, the non-zero terms never shrink; if r = −1, partial sums alternate rather than approaching one value; if |r| > 1, term magnitudes grow. A negative ratio is not automatically invalid, but a small positive first term does not guarantee convergence. The identically zero series with a = 0 is a trivial exception: every partial sum is zero for any ratio, so the stated non-zero-first-term condition matters.

A limit does not claim a finite process is already finished

For a = 8 and r = 1/2, S∞ = 16. After four terms the sum is 8 + 4 + 2 + 1 = 15 and the remaining limiting contribution is 1. In general, subtracting Sₙ from S∞ gives a rⁿ/(1 − r), whose sign can alternate for negative ratios. An infinite cutting or bouncing model is an idealisation; it does not promise a physical process can carry out infinitely many steps.

If the ratio contains a parameter, solve −1 < r < 1 before using the infinite-sum formula. For first term 9 and ratio 2k − 1, convergence requires 0 < k < 1, and S∞ = 9/[2(1 − k)] there. If a distance model contains a first drop followed by repeated upward and downward journeys, count the first drop once and each later bounce height twice; those heights alone are not the total distance.

Pause and explain

For first term 9 and ratio 2k − 1, which parameter range gives convergence?

Put the idea to work

Worked example

A GP has first term 9 and ratio 2k − 1. Find the convergence interval and k if its sum to infinity is 18.

Show the worked solution
  1. Convergence requires −1 < 2k − 1 < 1, which simplifies to 0 < k < 1.
  2. On that interval, S∞ = 9/[1 − (2k − 1)] = 9/[2(1 − k)].
  3. Set the expression equal to 18 to get 2(1 − k) = 1/2, hence k = 3/4. Its ratio is 1/2, satisfying the convergence condition.

Answer Converges for 0 < k < 1; S∞ = 18 when k = 3/4.

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From guided practice to a new situation

Write your answer and reasoning first. Use a hint only if you are stuck. The model solution is for self-checking; your written work is not automatically marked.

1 · Guided

A GP has a = 12 and r = 1/3. Find S∞ and the limiting contribution remaining after its first four terms.

Give me a hint

Check convergence, then subtract the finite sum or use the remainder formula.

Compare my reasoning
  1. Since |1/3| < 1, S∞ = 12/(1 − 1/3) = 18.
  2. The first-four sum is 18[1 − (1/3)⁴] = 160/9.
  3. The remaining limiting contribution is 18 − 160/9 = 2/9; it is not zero at a finite stage.

S∞ = 18; remainder after four terms 2/9.

Look for these in your work

  • Establish convergence before applying the limiting formula.
  • Distinguish the finite total from the remaining contribution.
2 · Independent

For 10, −5, 5/2, …, find S∞, S₄ and S∞ − S₄ exactly.

Give me a hint

Keep the negative ratio inside its power and denominator brackets.

Compare my reasoning
  1. The ratio is −1/2, so the series converges and S∞ = 10/(3/2) = 20/3.
  2. S₄ = 10[1 − (−1/2)⁴]/(3/2) = 25/4.
  3. Subtract to get 20/3 − 25/4 = 5/12; the alternating remainder sign depends on which finite stage is chosen.

S∞ = 20/3; S₄ = 25/4; S∞ − S₄ = 5/12.

Look for these in your work

  • Use the actual signed ratio in both formulae.
  • Subtract the exact partial sum from the limit.
3 · Transfer

In an idealised vertical model, a ball first drops 12 m and then rebounds to 3/5 of its previous fall height after every impact. Find its total limiting distance, counting upward and downward travel.

Give me a hint

The rebound heights form a GP, but each is travelled twice after the initial drop.

Compare my reasoning
  1. The rebound heights start at 12(3/5) = 36/5 m, with ratio 3/5, which has magnitude below 1.
  2. Their infinite sum is (36/5)/(1 − 3/5) = 18 m.
  3. Total distance is the initial 12 m plus twice that height sum: 12 + 2(18) = 48 m. This is the limit of the supplied model, rather than a claim about infinitely many physical bounces.

48 m in the idealised limiting model.

Look for these in your work

  • Identify the first rebound term separately from the first drop.
  • Count each rebound's upward and downward legs and state the model limitation.

Common mistakes

  • Check |r| < 1 before claiming a non-zero GP has a finite sum to infinity.
  • A negative ratio can converge; a ratio of magnitude 1 does not.
  • Count both upward and downward travel after a bounce, and distinguish an ideal limit from a finite stage.
Recall without your notes

What can you explain now?

Find the sum to infinity of 10, −5, 5/2, … and explain why it exists.

Compare with the explanation

20/3, because r = −1/2 has |r| < 1.

Use 10/[1 − (−1/2)] = 20/3; alternating signs do not prevent convergence when magnitudes shrink.

After trying it yourself, choose your next review. This is your self-assessment.

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Make it stick

Explain why a shrinking alternating GP can converge, derive its limiting sum from Sₙ and identify which finite stages or repeated journeys a model actually counts.

If you needed the solution, close it and solve the problem again from a blank page. A correct answer is stronger when you can explain the reason for each step.

Keep learning Mathematics

Course scope and assessment

312 sequenced lessons provide 936 guided, independent and application problems covering the 160 objectives in sections 1.1–1.8, 2.1–2.6, 3.1–3.9, 4.1–4.5, 5.1–5.5 and 6.1–6.5. The map lists all 38 sections across six alternative components; all eight Pure Mathematics 1 sections and all six Pure Mathematics 2 sections, from Paper 2 Algebra through Numerical solution of equations, currently have full teaching sequences. Paper 3 Algebra, section 3.1, links the six shared foundation lessons plus six lessons on partial fractions and rational binomial expansions; Paper 3 logarithms, trigonometry and numerical equations use the shared lessons, with the Paper 1 graph foundation linked into trigonometry. Paper 3 differentiation combines the shared methods with its inverse-tangent derivative lesson. Paper 3 Integration links four shared standard and identity lessons plus seven advanced lessons, covering all six section 3.5 requirements. Eight Vectors lessons cover all six section 3.7 requirements, with 2D and 3D line and solid applications. Nine Differential equations lessons cover all four section 3.8 requirements, including Paper 3 integration techniques, initial conditions, equilibrium solutions and conditional model interpretations. Eleven Complex numbers lessons cover all eight section 3.9 requirements, with seven Argand diagrams and explicit argument and boundary checks. All nine Pure Mathematics 3 sections now have teaching linked to every mapped requirement. Nine Forces and equilibrium lessons cover all seven section 4.1 requirements, with six force diagrams, signed incline-friction intervals, reaction-dependent pull and push limits and separate-body third-law checks. Nine Kinematics lessons cover the four official section 4.2 requirements, with the graph requirement mapped to three relationships. Six motion diagrams support directed quantities, graph slopes and signed areas, Paper 1 time-calculus methods, reversal distances, constant-acceleration stages and shared-clock particle meetings. Six Momentum lessons cover both section 4.3 requirements, including signed system totals, conservation assumptions, outgoing velocities, coalescence, unknown masses and successive impacts. Four diagrams show system momentum through the stipulated events, and supplied kinetic-energy checks distinguish conservation of momentum from changes in kinetic energy. Twelve Newton’s laws lessons cover all four section 4.4 requirements, with vertical support and release stages, rough horizontal and incline motion, inferred parameters, hanging and surface pulley systems, rigid tow-bar thrust and slack-string transitions. Seven force diagrams support the separate-particle balances. Nine Energy, work and power lessons cover all five section 4.5 requirements, with angle-dependent work, kinetic and reference potential energy, signed net-work balances, smooth curved slides, rough and driven slopes, ideal connected-system energy and instantaneous power on hills. Five diagrams distinguish the energy inputs, losses and valid positive-speed force model. All five Mechanics sections now have teaching and staged practice linked to their mapped requirements. Thirteen Representation of data lessons cover all five section 5.1 requirements, including choice and limitations of displays, ordered and back-to-back stems, raw summaries and box plots, unequal-width density histograms, cumulative-frequency interpolation, descriptive moment calculations, grouped estimates, coding, combining two datasets and correcting totals. Six accessible diagrams retain repeated observations and distinguish numerical spread, frequency area and estimated readings. Ten Permutations and combinations lessons cover both official section 5.2 requirements, with selection and ordered roles, repeated objects, adjacency blocks, non-adjacency gaps, leading-zero cases, labelled multi-row seating and mixed restrictions. Six accessible diagrams show outcome trees, ordered versus unordered choices, repeated copies, blocks, gaps and distinct row seats. Eleven Probability lessons cover all four section 5.3 requirements, with equiprobable elementary outcomes, selection-based probabilities, complements and disjoint regions, independence tests, restricted sample spaces, two-way tables, replacement and removal trees, reversed conditions and unknown parameters. Seven accessible diagrams show dice outcomes, random subsets, event regions, a conditioned grid, a count table and two probability trees. Twelve Discrete random variables lessons cover all three official section 5.4 requirements, with complete probability tables, moment and parameter checks, binomial assumptions, exact probabilities and moments, geometric first-success probabilities, tails, expectation and integer reliability thresholds. Six accessible diagrams distinguish outcome grouping, weighted moments, fixed trials, discrete probability bars, waiting conventions and integer tail deadlines. Twelve Normal distribution lessons cover all three official section 5.5 requirements, with continuous-area interpretation, MF19 cumulative tables, full standardisation, tail and interval regions, conditional probabilities, percentiles, one- and two-parameter inference, binomial suitability, continuity corrections and approximate integer thresholds. Seven accessible diagrams show model areas, table reading, aligned scales, intervals, quantiles, matched binomial and normal shapes and whole integer cells. All five Statistics 1 sections now have teaching and staged practice linked to their mapped requirements. Fourteen Poisson distribution lessons cover all five official section 6.1 requirements, with homogeneous event-count assumptions, exposure scaling, exact masses and tails, conditional count events, moments, parameter inference, probability duration targets, disjoint and overlapping windows, rare-count binomial approximations, matched normal approximations and continuity corrections. Nine accessible diagrams show event exposures, unit conversions, discrete bars, complete tail complements, population moments, shared windows, approximate count models and integer cells. Exact checks distinguish approximate and exact close-target decisions. Fourteen Linear combinations lessons cover the six listed results in official section 6.2, with affine moments, signed scales and constant cases, expectation without independence, independent squared variance contributions, fixed and random fees, independent copies versus reused values, affine normal events, independent normal sums and differences, weighted and conditional areas, coefficient inference, exact independent Poisson sums and overlapping exposure limits. Nine accessible diagrams distinguish scale changes, variance contributions, component costs, copy mechanisms, aligned normal scales, summed areas, Poisson count pairs and unsupported distribution claims. Fourteen Continuous random variables lessons cover both official section 6.3 requirements, with density validity and units, support-aware intervals, complements and conditional regions, first and second moments, percentiles by direct density areas, symmetry checks, parameter inference, infinite-support power and exponential integrals, divergent-moment limits and combined applications. Nine accessible diagrams distinguish density height from probability, normalisation, negative-density failures, central and conditional areas, mean versus median, percentile locations and partial infinite tails. Explicit cumulative distribution function knowledge is not required. Eighteen Sampling and estimation lessons cover all eight official section 6.4 requirements, with population and frame definitions, random-number selection, sampling-quality limits, independent sample-mean moments, normal means, CLT conditions, SE scaling, raw, summarised and coded unbiased estimates, known-variance and large-sample mean intervals, repeated-sampling interpretation, precision planning, proportion intervals, sparse-outcome limits and contextual applications. Ten accessible diagrams distinguish selection frames, number rejection, repeated sample means, population versus mean density, CLT models, variance divisors, interval targets, illustrative coverage, integer size checks and proportion margins. Eighteen Hypothesis tests lessons cover all five official section 6.5 requirements, with pre-specified alternatives, inclusive count tails, explicit equal-tail conventions, integer critical regions and actual significance, exposure-aware Poisson tests, continuity-corrected count approximations, normal and large-sample mean tests, confidence-interval connections, error classifications, fixed-region binomial, Poisson and normal error probabilities and sample-size power comparisons. Nine accessible diagrams show the testing procedure, exact count regions, unequal Poisson tails, discrete significance jumps, corrected count boundaries, matching mean intervals and alternative error distributions. All shared lessons are counted once in the course total. All 38 sections now link teaching and practice. Eight earlier overview lessons remain available, but do not count as full section coverage. This is a content-availability measure, not full programme completion or exam readiness. Written practice is self-checked, not officially marked. Check the 2028–2030 syllabus separately if sitting an examination from 2028; this teaching map uses 2026–2027 requirements.

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