The first digit frequencies of primes and Riemann zeta zeros tend to uniformity following a size-dependent generalized Benford's law
Bartolo Luque, Lucas Lacasa

TL;DR
This paper demonstrates that the distribution of leading digits in primes and Riemann zeta zeros follows a size-dependent generalized Benford's law, revealing underlying regularities linked to prime distribution and the prime number theorem.
Contribution
It introduces a generalized Benford's law that accurately models the leading digit distribution of primes and zeta zeros, connecting these patterns to prime number theory.
Findings
Prime leading digits follow a size-dependent generalized Benford's law.
Riemann zeta zeros exhibit a reciprocal pattern consistent with this law.
New approximation to the prime counting function pi(n) is derived.
Abstract
Prime numbers seem to distribute among the natural numbers with no other law than that of chance, however its global distribution presents a quite remarkable smoothness. Such interplay between randomness and regularity has motivated sci- entists of all ages to search for local and global patterns in this distribution that eventually could shed light into the ultimate nature of primes. In this work we show that a generalization of the well known first-digit Benford's law, which addresses the rate of appearance of a given leading digit d in data sets, describes with astonishing precision the statistical distribution of leading digits in the prime numbers sequence. Moreover, a reciprocal version of this pattern also takes place in the sequence of the nontrivial Riemann zeta zeros. We prove that the prime number theorem is, in the last analysis, the responsible of these patterns. Some new…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsBenford’s Law and Fraud Detection · Computability, Logic, AI Algorithms · Complex Systems and Time Series Analysis
