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Theoretical analysis reveals strong correlations between error terms in prime counting functions, indicating an equivalence between persistent error inequalities and the Riemann hypothesis.
Standard prime-number counting functions, such as ψ(x), θ(x), and π(x), have error terms with limiting logarithmic distributions once suitably normalized. The same is true of weighted versions of those sums, like πr(x)=∑p≤x1p and πℓ(x)=∑p≤xlog(1−1p)−1, that were studied by Mertens. These limiting distributions are all identical, but passing to the limit loses information about how these error terms are correlated with one another. In this paper, we examine these correlations, showing, for example, that persistent inequalities between certain pairs of normalized error terms are equivalent to the Riemann hypothesis (RH). Assuming both RH and LI, the linear independence of the positive imaginary parts of the zeros of ζ(s), we calculate the logarithmic densities of the set of real numbers on which two different error terms have prescribed signs. For example, we conditionally show that ψ(x)−x and ∑n≤xΛ(n)n−(logx−C0) have the same sign on a set of logarithmic density ≈0.9865.
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Bhattacharya et al. (2026) studied this question.
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