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analyze-prime-numbers

Analyze prime numbers using primality tests, factorization algorithms, prime distribution analysis, and sieve methods. Covers trial division, Miller-Rabin, Sieve of Eratosthenes, and the Prime Number Theorem. Use when determining whether an integer is prime or composite, finding prime factorizations, counting or listing primes up to a bound, or investigating prime properties within a number-theoretic proof or computation.

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Analyze Prime Numbers

Analyze prime numbers by selecting and applying the appropriate algorithm for the task at hand: primality testing, integer factorization, or prime distribution analysis. Verify results computationally and relate findings to the Prime Number Theorem.

When to Use

  • Determining whether a given integer is prime or composite
  • Finding the complete prime factorization of an integer
  • Counting or listing primes up to a given bound
  • Verifying the Prime Number Theorem approximation for a specific range
  • Investigating properties of primes in a number-theoretic proof or computation

Inputs

  • Required: The integer(s) to analyze, or a bound for distribution analysis
  • Required: Task type -- one of: primality test, factorization, or distribution analysis
  • Optional: Preferred algorithm (trial division, Miller-Rabin, Sieve of Eratosthenes, Pollard's rho)
  • Optional: Whether to produce a formal proof of primality or just a computational verdict
  • Optional: Output format (factor tree, prime list, count, table)

Procedure

Step 1: Determine the Task Type

Classify the request into one of three categories and select the appropriate algorithmic path.

  1. Primality test: Given a single integer n, determine whether n is prime.
  2. Factorization: Given a composite integer n, find its complete prime factorization.
  3. Distribution analysis: Given a bound N, analyze the primes up to N (count, list, gaps, density).

Record the task type and the input value(s).

Expected: A clear classification with the input values recorded.

On failure: If the input is ambiguous (e.g., "analyze 60"), ask the user to clarify whether they want a primality test, factorization, or distribution analysis. Default to factorization for composite numbers and primality confirmation for suspected primes.

Step 2: Apply Primality Testing (if task = primality)

Test whether n is prime using an algorithm matched to the size of n.

  1. Handle trivial cases: n < 2 is not prime. n = 2 or n = 3 is prime. If n is even and n > 2, it is composite.

  2. Small n (n < 10^6): Use trial division.

    • Test divisibility by all primes p up to floor(sqrt(n)).
    • Optimization: test 2, then odd numbers 3, 5, 7, ... or use a 6k +/- 1 wheel.
    • If no divisor found, n is prime.
  3. Large n (n >= 10^6): Use Miller-Rabin probabilistic test.

    • Write n - 1 = 2^s * d where d is odd.
    • For each witness a in {2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37}:
      • Compute x = a^d mod n.
      • If x = 1 or x = n - 1, this witness passes.
      • Otherwise, square x up to s - 1 times. If x ever equals n - 1, pass.
      • If no pass, n is composite (a is a witness).
    • For n < 3.317 * 10^24, the witnesses {2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37} give a deterministic result.
  4. Record the verdict: prime or composite, with the witness or certificate.

Small primes reference (first 25):

IndexPrimeIndexPrimeIndexPrime
1210291967
2311312071
3512372173
4713412279
51114432383
61315472489
71716532597
8191759
9231861

Expected: A definitive answer (prime or composite) with the algorithm used and any witnesses or divisors found.

On failure: If Miller-Rabin reports "probably prime" but certainty is required, escalate to a deterministic test (e.g., AKS or ECPP). For trial division, if computation is too slow, switch to Miller-Rabin.

Step 3: Apply Factorization (if task = factorization)

Factor n completely into its prime power decomposition.

  1. Extract small factors by trial division:

    • Divide out 2 as many times as possible, recording the exponent.
    • Divide out odd primes 3, 5, 7, 11, ... up to a cutoff (e.g., 10^4 or sqrt(n) if n is small).
    • After each division, update n to the remaining cofactor.
  2. If cofactor > 1 and cofactor < 10^12: Continue trial division up to sqrt(cofactor).

  3. If cofactor > 1 and cofactor >= 10^12: Apply Pollard's rho algorithm.

    • Choose f(x) = x^2 + c (mod n) with random c.
    • Use Floyd's cycle detection: x = f(x), y = f(f(y)).
    • Compute d = gcd(|x - y|, n) at each step.
    • If 1 < d < n, d is a non-trivial factor. Recurse on d and n/d.
    • If d = n, retry with a different c.
  4. Verify: Multiply all found prime factors (with exponents) and confirm the product equals the original n. Test each factor for primality.

  5. Present the result in standard form: n = p1^a1 * p2^a2 * ... * pk^ak with p1 < p2 < ... < pk.

Algorithm complexity notes:

AlgorithmComplexityBest for
Trial divisionO(sqrt(n))n < 10^12
Pollard's rhoO(n^{1/4}) expectedn up to ~10^18
Quadratic sieveL(n)^{1+o(1)}n up to ~10^50
GNFSL(n)^{(64/9)^{1/3}+o(1)}n > 10^50

Expected: A complete prime factorization in canonical form, verified by multiplication.

On failure: If Pollard's rho fails to find a factor after many iterations (cycle detected without a non-trivial gcd), try different values of c (at least 5 attempts). If all fail, the cofactor may be prime -- confirm with a primality test.

Step 4: Apply Distribution Analysis (if task = distribution)

Analyze the distribution of primes up to a given bound N.

  1. Generate primes using the Sieve of Eratosthenes:

    • Create a boolean array of size N + 1, initialized to true.
    • Set indices 0 and 1 to false (not prime).
    • For each p from 2 to floor(sqrt(N)):
      • If p is still marked true, mark all multiples p^2, p^2 + p, p^2 + 2p, ... as false.
    • Collect all indices still marked true.
  2. Count primes: Compute pi(N) = number of primes up to N.

  3. Compare with the Prime Number Theorem:

    • PNT approximation: pi(N) ~ N / ln(N).
    • Logarithmic integral approximation: Li(N) = integral from 2 to N of 1/ln(t) dt.
    • Compute the relative error: |pi(N) - N/ln(N)| / pi(N).
  4. Analyze prime gaps (optional):

    • Compute gaps between consecutive primes.
    • Report the maximum gap, average gap, and any twin primes (gap = 2).
    • Average gap near N is approximately ln(N).
  5. Present findings in a summary table:

Bound N:       1,000,000
pi(N):         78,498
N/ln(N):       72,382
Li(N):         78,628
Relative error (N/ln(N)):  7.79%
Relative error (Li(N)):    0.17%
Max prime gap:  148 (between 492113 and 492227)
Twin primes:    8,169 pairs

Expected: A count of primes with PNT comparison and optional gap analysis.

On failure: If N is too large for in-memory sieving (N > 10^9), use a segmented sieve that processes the range in blocks. If only a count is needed (not a list), use the Meissel-Lehmer algorithm for pi(N) directly.

Step 5: Verify Results Computationally

Cross-check all results using an independent computation method.

  1. For primality: If trial division was used, verify with a quick Miller-Rabin pass (or vice versa). For known primes, check against published prime tables or OEIS sequences.

  2. For factorization: Multiply all factors and confirm equality with the original input. Independently test each claimed prime factor for primality.

  3. For distribution: Spot-check by testing 3-5 individual numbers from the sieve output for primality. Compare pi(N) against published values for standard benchmarks (pi(10^k) for k = 1, ..., 9).

Published values of pi(N):

Npi(N)
104
10025
1,000168
10,0001,229
100,0009,592
10^678,498
10^7664,579
10^85,761,455
10^950,847,534
  1. Document the verification with the method used and the outcome.

Expected: All results independently verified with no discrepancies.

On failure: If verification reveals a discrepancy, re-run the original computation with extra checks enabled (e.g., verbose trial division logging). The most common errors are off-by-one in sieve bounds, integer overflow in modular arithmetic, and mistaking a pseudoprime for a prime.

Validation

  • Task type is correctly classified (primality, factorization, or distribution)
  • Algorithm is appropriate for the input size
  • Trivial cases (n < 2, n = 2, even n) are handled before general algorithms
  • Primality verdicts are definitive (not "probably prime" without qualification)
  • Factorizations multiply back to the original number
  • Every claimed prime factor has been tested for primality
  • Sieve bounds include sqrt(N) coverage for marking composites
  • PNT comparison uses the correct formula (N/ln(N) or Li(N))
  • Results are verified by an independent method or against published values
  • Edge cases (n = 0, 1, 2, negative inputs) are addressed

Common Pitfalls

  • Forgetting n = 1 is not prime: By convention, 1 is neither prime nor composite. Many algorithms silently misclassify it.

  • Integer overflow in modular exponentiation: When computing a^d mod n for Miller-Rabin, naive exponentiation overflows. Use modular exponentiation (repeated squaring with mod at each step).

  • Sieve off-by-one errors: The sieve must mark composites starting from p^2, not from 2p. Starting from 2p wastes time but is correct; starting from p+1 is wrong.

  • Pollard's rho cycle with d = n: If gcd(|x - y|, n) = n, the algorithm has found the trivial factor. Retry with a different polynomial constant c, not just a different starting point.

  • Carmichael numbers fooling Fermat's test: Numbers like 561 = 3 * 11 * 17 pass Fermat's primality test for all coprime bases. Always use Miller-Rabin, not plain Fermat.

  • Confusing pi(n) with the constant pi: The prime counting function pi(n) and the circle constant 3.14159... share notation. Context must be unambiguous.

Related Skills

  • solve-modular-arithmetic -- Modular arithmetic underpins Miller-Rabin and many factorization methods
  • explore-diophantine-equations -- Prime factorization is a prerequisite for solving many Diophantine equations
  • formulate-quantum-problem -- Shor's algorithm for integer factorization connects primes to quantum computing

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