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A Level · Cambridge (CIE) · 9709

Use conjugate pairs to solve real coefficient polynomials

Pair non-real roots of a real-coefficient polynomial, form a real quadratic factor and solve the remaining cubic or quartic factors.

Pure Mathematics 3 · Complex numbers · 3.9
Exam scope and assessment notes

Pure Mathematics 3 (Paper 3, A Level) · Mathematics 9709, 2026–2027, section 3.9. Paper 1 algebra and radian trigonometry are assumed. Use Cartesian working for products, quotients and the two square roots of a non-zero complex number. Arguments usually use −π < θ ≤ π; an alternative interval 0 ≤ θ < 2π is acceptable unless specified. The argument of zero is undefined. General nth-root methods are beyond this mapped sequence. Written practice is self-checked; human subject-teacher review remains pending.

Before you begin

  • Apply the factor theorem and divide a polynomial.
  • Solve quadratic equations and expand Cartesian products.

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

Quick readiness check

What real quadratic factor comes from roots 2 ± i?

What you will learn

  • Explain why non-real roots occur in conjugate pairs for real coefficients.
  • Use a supplied non-real root to solve cubic and quartic equations.

Real coefficients are essential

Conjugating a sum or product conjugates each complex term; a real coefficient is unchanged. Thus if a polynomial p with real coefficients has p(a + bi) = 0, conjugating the equality gives p(a − bi) = 0. For b ≠ 0 these are distinct roots. Their product factor is [z − (a + bi)][z − (a − bi)] = (z − a)² + b², a quadratic with real coefficients.

This conclusion depends on real coefficients. The polynomial z − i has the root i but not −i, since its constant coefficient is complex. Repeated non-real roots also pair with the same multiplicity for real coefficients. Knowing a conjugate pair does not determine every other root without using the remaining coefficients or polynomial factor.

Reduce a cubic or quartic before solving

For z³ − 5z² + 9z − 5 = 0, a supplied root 2 + i gives the second root 2 − i and factor z² − 4z + 5. Polynomial division leaves z − 1, so the three roots are 1 and 2 ± i. Expand (z² − 4z + 5)(z − 1) to check every coefficient. This is stronger than merely guessing a remaining root from one term.

For a quartic a conjugate pair similarly removes a quadratic factor. If the remaining factor is another real quadratic, solve it with completing the square or the quadratic formula. It may give real roots or another conjugate pair. When unknown coefficients are real, express the polynomial as the conjugate quadratic times the remaining real factor and equate all relevant coefficients.

Pause and explain

A real-coefficient cubic has root 1 + 2i. What other root is guaranteed?

Put the idea to work

Worked example

Given that 2 + i is a root of z³ − 5z² + 9z − 5 = 0, find all roots.

Show the worked solution
  1. Real coefficients imply the conjugate root 2 − i.
  2. The pair gives (z − 2)² + 1 = z² − 4z + 5.
  3. Division gives the remaining factor z − 1; expansion verifies the complete factorisation.

Answer z = 1, 2 + i, 2 − i.

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Choose Easy, Normal or Difficult. Save your answers and open worked review after finishing.

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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

Solve z² + 4z + 13 = 0 over the complex numbers and check the pair.

Give me a hint

Complete the square and use the two square roots of a negative real number.

Compare my reasoning
  1. Write (z + 2)² + 9 = 0, so (z + 2)² = −9.
  2. Hence z + 2 = ±3i and z = −2 ± 3i.
  3. The roots are conjugates; their factors multiply back to z² + 4z + 13.

z = −2 + 3i and −2 − 3i.

Look for these in your work

  • Keep both roots of the squared expression.
  • Check the real quadratic factor.
2 · Independent

Given the root 1 + 2i of z⁴ + 3z² + 6z + 10 = 0, find all four roots.

Give me a hint

Remove its real conjugate quadratic before solving the remaining quadratic.

Compare my reasoning
  1. The partner is 1 − 2i, giving factor z² − 2z + 5.
  2. Division leaves z² + 2z + 2 = (z + 1)² + 1.
  3. Its roots are −1 ± i; the two quadratic factors multiply to the stated quartic.

z = 1 ± 2i and −1 ± i.

Look for these in your work

  • Use the real-coefficient conjugate partner.
  • Solve and verify both quadratic factors.
3 · Transfer

The real-coefficient cubic z³ + az² + bz + 15 = 0 has root 1 + 2i. Find real a and b and the third root.

Give me a hint

The pair gives z² − 2z + 5; use the constant term of the remaining linear factor.

Compare my reasoning
  1. Write the cubic as (z² − 2z + 5)(z − c), where c is the third root.
  2. The constant −5c = 15 gives c = −3.
  3. Expansion with z + 3 gives z³ + z² − z + 15, so a = 1 and b = −1.

a = 1, b = −1; third root −3.

Look for these in your work

  • Form a real quadratic from the non-real pair.
  • Use and check all coefficients, including the constant sign.

Common mistakes

  • Check the coefficients are real before asserting a conjugate partner.
  • Form (z − a)² + b² with the right signs.
  • Solve and check the remaining factor; one conjugate pair may not finish the equation.
Recall without your notes

What can you explain now?

Does the root i of z − i force −i to be a root?

Compare with the explanation

No: the coefficient −i is not real.

The conjugate-pair theorem requires every polynomial coefficient to be real.

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

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Make it stick

State the real-coefficient condition, form a conjugate quadratic and use it to solve or reconstruct a polynomial.

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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