Riemann hypothesis Notion
Terence Tao (@tao@mathstodon.xyz)
There has been a remarkable breakthrough towards the Riemann hypothesis (though still very far from fully resolving this conjecture) by Guth and Maynard making the first substantial improvement to a classical 1940 bound of Ingham regarding the zeroes of the Riemann zeta function (and more generally, controlling the large values of various Dirichlet series): https://arxiv.org/abs/2405.20552 Let 𝑁(σ,𝑇) denote the number of zeroes of the Riemann zeta function with real part at least σ and imaginary part at most 𝑇 in magnitude. The Riemann hypothesis tells us that 𝑁(σ,𝑇) vanishes for any σ>1/2. We of course can't prove this unconditionally. But as the next best thing, we can prove zero density estimates, which are non-trivial upper bounds on 𝑁(σ,𝑇). It turns out that the value σ=3/4 is a key value. In 1940, Ingham obtained the bound \(N(3/4,T) \ll T^{3/5+o(1)}\). Over the next eighty years, the only improvement to this bound has been small refinements to the 𝑜(1) error. This has limited us from doing many things in analytic number theory: for instance, to get a good prime number theorem in almost all short intervals of the form \((x,x+x^\theta)\), we have long been limited to the range \(\theta>1/6\), with the main obstacle being the lack of improvement to the Ingham bound. (1/3)
https://mathstodon.xyz/@tao/112557248794707738
Mathematician Yitang Zhang Confirms Partial Solution to Riemann Hypothesis
Yitang (Tom) Zhang, a Chinese-American mathematician who recently revealed that he had solved the Landau-Siegel zeros conjecture, delivered an online speech at Peking University on November 8 to answer external questions on his newly published 111-page paper. On November 7, Zhang's new paper, "Discrete Mean Estimates and the Landau-Siegel Zero," was officially launched on arXiv, an open-access repository of electronic preprints and postprints.
https://pandaily.com/mathematician-yitang-zhang-confirms-partial-solution-to-riemann-hypothesis/

The fact that Jarred Sumner, the human, gave almost no mathematical hints and mainly offered encouragement like “Keep going” and “You can do it”
Modern AI systems may decide on their own that a difficult problem is “impossible” and give up the search too early; encouragement or strong instructions may help increase the search budget and broaden the search space. However, it is still unclear why this actually works. This is an example of how human meta-level steering, telling the model “don’t give up; keep searching”, can significantly improve performance.
An unpublished Claude research model did not solve the Riemann hypothesis itself, but it significantly improved the lower bound for the proportion of Riemann zeta function zeros that can be proven to lie on the critical line, from 41.6% to 67.2%.
Building on results from Baluyot, Goldston, and others, and combining them with Bombieri’s existing techniques, Claude developed a quadratic-form/rank inequality that treats zeros on and off the critical line together as positive and negative definite subspaces. In Claude Code, it generated ideas, ran numerical checks, and conducted cross-review using 31M output tokens, about 60 subagents, 2,400 shell commands, and hundreds of Python scripts. Afterward, Claude searched 54 papers to check whether the result was already known and also produced an independent reproving. Anthropic mathematicians and external experts reviewed the work, and a formal Lean proof was also released.
Learning more about Claude's mathematical capabilities
An unreleased version of Claude has made strides on a problem related to the Riemann hypothesis. It improved the lower bound for the fraction of zeros of the Riemann zeta function that satisfy the hypothesis, increasing it from 41.6% to 67.2%.
https://www.anthropic.com/research/riemann-zeta


Seonglae Cho