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GuidePublished 7 Aug 2026Updated 13 Aug 20267 min readBy Kevin JoginFermat teststrong pseudoprimeMiller RabinCarmichael number
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Classical Primality and Factoring

Fermat and Strong Pseudoprime Tests

The Fermat test, its failure on Carmichael numbers, and the strong pseudoprime test that repairs it.

Engineering / MathematicsClassical Primality and Factoring8 min readKV-MATH-0647

The Fermat test is the starting point for all compositeness testing. It has a fatal flaw which the strong test repairs, and the repair costs essentially nothing.

The Fermat test

a^(n-1) = 1 (mod n) for every a coprime to n, if n is primeFailure proves compositeness; success proves nothing.

Pitfall

Carmichael numbers pass the Fermat test for every base coprime to them. They are composite and no choice of base exposes them, so the Fermat test is not merely weak but genuinely unsound as a primality indicator. There are infinitely many.

The strong test

Write the exponent as an odd number times a power of two. For a prime, the sequence of repeated squarings from the odd power must reach one through a specific pattern.

n - 1 = d * 2^s with d oddThen either a^d = 1, or a^(d*2^r) = -1 for some r below s.

The strong pseudoprime test

  1. Factor out powers of twoFrom one less than the candidate.
  2. Compute the odd powerBy binary powering.
  3. Check for oneIf the result is one, the test passes.
  4. Square repeatedlyChecking for minus one at each step.
  5. Declare compositeIf neither condition is met.

Why it is stronger

Key point

The strong test additionally exploits the fact that a prime modulus has only two square roots of one. Finding a different square root of one during the squaring chain proves compositeness, and this is what Carmichael numbers cannot evade.

Error probability

Probability a composite passes a random base < 1/4And in practice far smaller for most composites.
Error probability with independent random bases
Number of random basesError bound
1Below one quarter
10Below one in a million
20Below one in a trillion
40Negligible for any practical purpose

Note

The one quarter bound is worst case and is essentially never attained. For a random composite the probability of passing even one base is astronomically smaller, which is why so few bases are needed in practice.

Deterministic variants

Caution

Fixed small base sets give deterministic tests below explicit bounds, and these are widely tabulated. But an adversary who knows the base set can construct a composite passing it. For adversarial input, random bases are essential.

Finding a factor

Key point

When the test finds a non-trivial square root of one, the GCD of that root plus or minus one with the modulus is a factor. This is rare but free, and it is the mechanism underlying Pollard's p-1 method.

Source. Henri Cohen, A Course in Computational Algebraic Number Theory, Springer GTM 138 — 8.2. Structural reference unverified: the source file was not available during authoring; chapter and section numbers are taken from the published edition and have not been checked against a physical copy.

Related pages

  • Binary Powering and Exponentiation Chains
  • The Baillie-PSW Compositeness Test
  • Primality Versus Factoring: Framing the Problems
  • Lucas Sequences and Lucas Pseudoprimes

Handbook application: from concept to controlled practice

Purpose. This expanded section turns the original page into a practical handbook. It preserves the supplied material and adds a repeatable way to apply, check and review Fermat and Strong Pseudoprime Tests. It does not replace a contract, legislation, a controlled standard, competent engineering judgement or specialist advice.

The operating aim is to turn a compact mathematical statement into a usable chain of definitions, claims, examples and checks. Read the original explanation first, then use the workflow and checks below to convert knowledge into evidence.

Treat Fermat and Strong Pseudoprime Tests as a network of definitions and implications, not as a list of formulas. The working vocabulary on this page—test, fermat, strong, pseudoprime, carmichael—should be made explicit before any proof or computation begins. Record the ambient set or structure, the permitted operations and the equality or equivalence relation in use. A compact theorem often changes meaning when the base field, finiteness condition, commutativity assumption or direction of an action changes.

For a proof, write the hypotheses as a checklist and mark the line at which each one is used. For a computation, state the representation of the input, the arithmetic model, the termination condition and the output invariant. For a classification problem, distinguish existence from uniqueness and distinguish an object from its representation. These separations prevent a correct local calculation from being mistaken for the general result.

A useful worked example should be small enough to inspect completely but rich enough to exercise the main mechanism. Compute the result in two ways where practical: symbolically and by substitution, structurally and numerically, or directly and through a normal form. Then include one near-miss example in which a hypothesis fails. The contrast explains why the theorem is shaped as it is and gives the reader a diagnostic pattern for later problems.

Verification is part of the mathematics. Check domains and codomains, substitute proposed solutions, test identity and zero cases, compare dimensions or cardinalities, and confirm that maps respect the required operations. In numerical work, report precision, conditioning and a residual rather than digits alone. In algorithmic work, separate mathematical correctness from implementation complexity and resource limits.

Step-by-step operating method

  1. Fix the setting. State the objects, ambient structure, notation and assumptions before manipulating symbols.
  2. Separate claims. Distinguish definitions, hypotheses, conclusions, equivalent conditions and consequences.
  3. Choose a method. Select proof, construction, calculation or algorithm according to the question actually asked.
  4. Work a small case. Use the smallest non-trivial example to expose the mechanism and test edge behaviour.
  5. Verify independently. Substitute back, check invariants, test boundary cases or use an alternative derivation.

Worked-example protocol

Illustrative method—not a source theorem. Start with a small admissible input and list the definitions it must satisfy. Carry out each transformation on a separate line, citing the property that permits it. Preserve exact values until approximation is necessary. At the end, verify the output against the original definition and one invariant such as dimension, degree, determinant, order, norm or residual. Then alter one hypothesis and observe which step ceases to be valid. This protocol creates a reusable example without inventing a theorem-specific numerical answer.

StageRecordQuality check
InputObjects, domain, notation, assumptionsEvery symbol is defined
MethodPermitted operation or cited result at each stepAll hypotheses hold
OutputExact result and representationCorrect type, domain and form
VerificationSubstitution, invariant or alternative derivationIndependent agreement
Boundary testZero, identity, degenerate or failed hypothesisScope is understood

Common failure modes and recovery actions

1. Watch for

Using a theorem without checking every hypothesis.

Recovery: Return to the governing definition or requirement and restate the decision in one sentence.

2. Watch for

Treating a suggestive example as a proof of the general case.

Recovery: Separate evidence from assumption, assign an owner and set a date for validation.

3. Watch for

Changing notation or conventions part-way through an argument.

Recovery: Run a small counterexample, boundary test, pilot or independent check before proceeding.

4. Watch for

Hiding a division-by-zero, convergence, finiteness or commutativity assumption.

Recovery: Record the consequence, decision and rationale, then update the controlled baseline.

5. Watch for

Reporting a computed result without a residual, substitution or structural check.

Recovery: Escalate when the issue affects safety, compliance, acceptance, material value or an agreed tolerance.

Review checklist

  • Can every symbol be traced to a definition or prior result?
  • Which hypothesis does each major step use?
  • Does the method cover zero, identity, degenerate and boundary cases?
  • Can the conclusion be checked by a second representation or calculation?
  • Are mandatory requirements distinguished from recommendations and illustrative values?
  • Are sources, assumptions, units, dates and versions recorded closely enough to reproduce the decision?
  • Have safety, legal, ethical, stakeholder and operational consequences been considered at the appropriate level?
  • Is there a named owner and a trigger for review, escalation, change or retirement?

Questions for deeper application

What is the most important distinction a practitioner must preserve when applying Fermat and Strong Pseudoprime Tests?

Answer with a fact or cited source where available. Where evidence is incomplete, record the assumption, consequence, responsible owner and next validation action.

Which assumption about test would change the result most if it proved false?

Answer with a fact or cited source where available. Where evidence is incomplete, record the assumption, consequence, responsible owner and next validation action.

What evidence would allow an independent reviewer to reproduce or challenge the conclusion?

Answer with a fact or cited source where available. Where evidence is incomplete, record the assumption, consequence, responsible owner and next validation action.

Which boundary, exception or failure case has not yet been tested?

Answer with a fact or cited source where available. Where evidence is incomplete, record the assumption, consequence, responsible owner and next validation action.

What must be handed over, monitored or reviewed after the immediate work is complete?

Answer with a fact or cited source where available. Where evidence is incomplete, record the assumption, consequence, responsible owner and next validation action.

Authoritative references and use notes

The sources below were selected as institutional or primary guidance for the broader practice. They support the handbook method; they do not imply that every statement or clause in a source applies to every project. Confirm the current edition, jurisdiction, contract and application before treating any requirement as mandatory.

  • MIT OpenCourseWare — Number Theory I — Massachusetts Institute of Technology. Used for algebraic and analytic number theory. Accessed 2026-08-13.
  • MIT OpenCourseWare — Algebra I — Massachusetts Institute of Technology. Used for groups, vector spaces, linear transformations and linear groups. Accessed 2026-08-13.

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