. The search targets "witness values"—ratios of the divisor sum to the upper bound—where a value >1is greater than 1 would disprove RH.
: Even with specialized enumeration, the search space grows exponentially. The post highlights the necessity of using unbounded integer arithmetic (often implemented in Python as a "ripple-carry" style system) because the numbers being tested quickly exceed 64-bit limits. Searching for RH Counterexamples — Exploring Data The post highlights the necessity of using unbounded
: To narrow the search space, the exploration looks for patterns in the prime factorizations of high-performing witness values. This involves jumping ahead in the superabundant number enumeration to specific "level sets" that are more likely to yield extreme values. : The Riemann Hypothesis (RH) is equivalent to
: The Riemann Hypothesis (RH) is equivalent to Robin’s Inequality, which states that for , the sum of divisors is bounded by which states that for
: By plotting the best witness values found so far, Kun uses logarithmic models to estimate where a counterexample might actually exist. Current data suggests that if a counterexample exists, it would likely have between 1,000 and 10,000 prime factors .
In the article Searching for RH Counterexamples — Exploring Data on the blog Math ∩ Programming , author Jeremy Kun shifts from the engineering challenges of building a distributed search system to analyzing the mathematical patterns within the data collected. The write-up focuses on the following key areas: