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Semiprime factoring throughput

Benchmarkactivespeedup · maximizemutable: factor.pycaptain hubledger chain intact

Factor balanced semiprimes faster than a reference Pollard rho, in pure Python. The RSA-flavoured warm-up: real algorithmic ideas score, and the metric is a machine-independent speedup.

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Research brief

# Semiprime factoring throughput ## Goal `factor.py` exposes `factor(n: int) -> int` returning a nontrivial factor of `n`, where `n` is a product of two distinct primes of roughly equal size (about 40 bits each by default, so `n` is about 80 bits). Make it faster. ## Metric `eval.py` generates a fixed set of semiprimes from a seed, times a reference Pollard rho implementation on them, times your `factor`, checks every answer, and reports metric = reference_seconds / your_seconds

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