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A Level · Cambridge (CIE) · 9709

Classify line-circle intersections with substitution

Turn common points into an equation and use its real solutions to distinguish chords, tangency and no intersection.

Pure Mathematics 1 · Coordinate geometry · 1.3

Pure Mathematics 1 (Paper 1) · AS & A Level Mathematics 9709, 2026–2027. Use algebra and elementary geometry; implicit differentiation is outside this section. Written practice is self-checked.

Before you begin

  • Use circle equations and solve quadratic equations.
  • Interpret a discriminant and solve inequalities involving a square.

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

Quick readiness check

Substitute y = x + 2 into x² + y² = 10. Which equation follows?

What you will learn

  • Find exact intersections of a line and a circle.
  • Find parameter conditions for two intersections, tangency or no real intersections.

Choose the substitution to suit the line

A common point satisfies both the circle and line equations. For a non-vertical line y = mx + c, substitute this expression for every y in the circle, keeping brackets when squaring. Solve the resulting quadratic in x, then recover the y-coordinate for each root. A vertical line x = t instead supplies x directly and leaves an equation in y.

For (x − 2)² + (y + 1)² = 25 and x = t, the intersection equation is (y + 1)² = 25 − (t − 2)². Two points occur when the right side is positive; zero gives one point; a negative value gives none. Thus two intersections require −3 < t < 7, tangency occurs at t = −3 or 7, and otherwise the line misses the circle.

The discriminant gives the same geometric classification

For a genuine intersection quadratic, D > 0 gives two distinct points, D = 0 gives a tangent and D < 0 gives no real common points. The circle's centre-to-line distance gives an equivalent interpretation: less than the radius means a chord, equal means a tangent, and greater means no intersection. You can use elementary geometry or substitution rather than assuming a point count from a rough sketch.

For x² + y² = 10 and y = x + k, substitution gives 2x² + 2kx + k² − 10 = 0. Its discriminant is 80 − 4k². Therefore the line meets twice when |k| < 2√5, touches when |k| = 2√5 and misses when |k| > 2√5. At tangency, x = −k/2 and y = k/2. Include both signs when solving a condition on k².

Pause and explain

What is the line-circle geometry when the genuine intersection quadratic has D < 0?

Put the idea to work

Worked example

Classify the intersections of x = t with (x − 2)² + (y + 1)² = 25 for real t.

Show the worked solution
  1. Substitute x = t to obtain (y + 1)² = 25 − (t − 2)².
  2. Two real y-values require (t − 2)² < 25, or −3 < t < 7.
  3. Equality gives t = −3 or 7 with y = −1; outside those limits the squared quantity would need to be negative.

Answer Two intersections for −3 < t < 7; tangent at (−3, −1) or (7, −1) for t = −3 or 7; none for t < −3 or t > 7.

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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

Find both intersections of y = 3 with x² + y² = 25.

Give me a hint

Replace y by 3, then include both signs when solving for x.

Compare my reasoning
  1. Substitute to get x² + 9 = 25.
  2. Thus x² = 16, giving x = −4 or 4.
  3. Pair each root with the common y-coordinate 3 and check the circle equation.

(−4, 3) and (4, 3).

Look for these in your work

  • Retain both square-root branches.
  • State both complete intersection coordinates.
2 · Independent

Find all intersections of y = x + 2 with x² + y² = 10.

Give me a hint

Expand the substituted square before factorising.

Compare my reasoning
  1. Write x² + (x + 2)² = 10, giving 2x² + 4x − 6 = 0.
  2. Divide by 2 and factor (x + 3)(x − 1) = 0, so x = −3 or 1.
  3. The corresponding line outputs are −1 and 3; both pairs satisfy the circle.

(−3, −1) and (1, 3).

Look for these in your work

  • Expand the cross term correctly.
  • Recover and verify both y-coordinates.
3 · Transfer

For x² + y² = 10 and y = x + k, find all k giving two intersections, tangency or none. State the tangent point in terms of k.

Give me a hint

Apply the discriminant to 2x² + 2kx + k² − 10 = 0.

Compare my reasoning
  1. The discriminant is (2k)² − 8(k² − 10) = 80 − 4k².
  2. It is positive for k² < 20, zero for k² = 20 and negative for k² > 20.
  3. At either tangent value k = ±2√5, the repeated root is x = −k/2 and the line gives y = k/2.

Two for |k| < 2√5; tangent for k = ±2√5 at (−k/2, k/2); none for |k| > 2√5.

Look for these in your work

  • Classify strict and equality cases from the correct discriminant.
  • Retain both tangent parameter values and recover their coordinates.

Common mistakes

  • A vertical line is substituted as x = constant, rather than forced into y = mx + c.
  • Recover the second coordinate for every root.
  • Include both signs in a squared parameter condition and keep tangent equality separate.
Recall without your notes

What can you explain now?

Find the common point of y = 5 and x² + y² = 25, and classify the line.

Compare with the explanation

(0, 5); y = 5 is a tangent.

Substitution gives x² = 0, one repeated real root, so there is one distinct common point.

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

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Make it stick

Explain why a line-circle substitution can give two roots, a repeated root or no real roots. Derive one parameter condition and connect it to a geometric sketch.

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.

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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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