Submitted:
30 December 2025
Posted:
31 December 2025
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Abstract
Keywords:
1. Introduction
- Formulation of the Erdos–Ingham problem. Let be a sequence of integers satisfyingand define the Dirichlet seriesErdos and Ingham asked whetherEven for very simple finite sets , no general method is known to exclude zeros on the line under the sole hypothesis . Unlike the classical L-function setting, one does not in general have an Euler product, a functional equation, or a spectral interpretation available, so the established techniques for zero-free regions do not directly apply here.
- Aim and point of view of this paper. The purpose of this paper is not to claim a resolution of (2), but to propose a new angle of attack based on modern dynamical systems and the Bohr–Hardy theory of Dirichlet series.
2. Preliminaries
2.1. General Dirichlet Series and Dirichlet Groups
2.2. Hardy Spaces of Dirichlet Series
2.3. Multipliers and Distance in
2.4. Ergodic and Dynamical Preliminaries
3. A Bohr–Hardy Reformulation of Erdos Problem #967
3.1. Setup
3.2. Exact Correspondence Along the Line
3.3. Reformulation as an Avoidance Property
- (i)
- for every .
- (ii)
- for every .
- (iii)
- for every .
- (iv)
- .
3.4. A Uniform Separation Criterion
4. A Quantitative Dynamical–Entropy Approach
4.1. Time Averages and Small-Value Sets
4.2. A Power-Law Small-Ball Condition and a Uniform Gap
- (a)
- The characters are rationally independent, so the Kronecker flow on Ω is uniquely ergodic.
- (b)
- The Bohr lift f is continuous on and hence on Ω.
- (c)
- There exist constants , and such that
4.3. Why the Exponent Is Crucial
4.4. Discussion of Constants and Optimisation
- The exponent is crucial: for the tail series does not converge fast enough to force the necessary contradiction.
- The constant C controls the size of at moderate scales; smaller C allows a larger admissible .
- The threshold enters only through the index at which starts to hold.
5. Partial Results Under Diophantine Conditions
5.1. Small-Ball Conjecture
5.2. Empirical Small-Ball Analysis and Numerical Evidence
5.2.1. Power-Law Decay of Small-Ball Measures
5.2.2. Decay of the Exponent with Increasing Truncation
5.2.3. Time-Series Behavior and Distance Statistics
5.2.4. Implications for Conjecture 5.1
- Existence of power-law decay. For each finite truncation N, the small-ball measure satisfies with . This is precisely the finite-dimensional analogue of the conjecture.
- Persistence of exponent above 1. Although decreases with N, the extrapolation suggests would remain strictly greater than 1 for this particular sequence. This lends credence to the possibility that the full infinite series might also satisfy a bound with .
5.2.5. Outlook and Further Numerical Investigations
- Varying growth rates: Testing sequences for different to see how depends on the decay rate of .
- Arithmetic perturbations: Introducing deliberate rational relations among the to study the effect of resonances on small-ball measures.
- Large-scale computations: Increasing N up to or with optimized algorithms to obtain more reliable extrapolations of .
- Direct uniform gap estimation: Computing and comparing it with the prediction from the fitted power law.
5.3. Finite Dirichlet polynomials
5.4. Limitations and Outlook
- The exponent as , so Theorem 4.2 () fails.
- The tail requires uniform tail bounds near , depending on the decay of .
5.5. Potential Obstructions and Critical Sequences
5.6. Summary of the Current Status
5.7. Numerical Evidence Towards Nonvanishing
Lyapunov-like Growth Estimates.
Relation to Small-Ball Behaviour
6. Conclusions and Future Work
6.1. Future Work: Pathways Toward Solving Erdős Problem #967
6.1.1. Analytic Refinement of Small-Ball Estimates
- Gradient and curvature analysis near : If f is smooth and its gradient is non-degenerate near the level set, the coarea formula yields . To achieve , one needs higher-order nondegeneracy (e.g., Morse condition) or quantitative curvature estimates.
- Hardy-space and multiplier techniques: Using the identification , one may apply multiplier theory for Dirichlet series [14] to derive pointwise lower bounds on from the -norm of f.
- Tail estimates for infinite series: For the full series , the tail must be controlled uniformly in t. Merging Bohr–Hardy theory with summation methods will be essential.
6.1.2. Arithmetic and Diophantine Refinements
- Weakening the Diophantine condition: Replace Definition 5.3 with a metric Diophantine condition that holds for almost all , then apply measure-theoretic arguments.
- Lacunary and structured sequences: For (lacunary case), the Kronecker flow equidistributes rapidly, potentially improving the exponent .
- Prime-supported sequences: The special case (primes) is of number-theoretic interest. Here have known Diophantine properties that may be exploited.
6.1.3. Dynamical and Ergodic Approaches
- Large deviation principles for quasi-periodic cocycles: Establishing such principles would quantify the probability that , directly informing .
- Entropy and slow entropy: While Kronecker flows have zero topological entropy, their slow entropy may capture the complexity of visits to . Upper bounds here could imply power-law decay.
- Renormalization for nearly resonant frequencies: In nearly resonant cases, a KAM-type renormalization scheme may control the time spent near , leveraging the condition .
6.1.4. Probabilistic and Random Models
- Random coefficient models: Study with random. Prove almost-sure small-ball bounds, then use concentration arguments to transfer results to the deterministic case.
- Transference principles: If “typical” sequences satisfy Conjecture 5.1, one may use transference techniques from metric number theory to cover all sequences.
6.1.5. Systematic Numerical Exploration
- Map the exponent landscape: Compute for families (), primes, squares, etc., identifying trends and critical cases.
- High-precision extrapolation: Use larger N (up to ) to fit asymptotic models for and , providing empirical evidence for/against Conjecture 5.1.
- Direct zero searches: Implement optimized algorithms to check for large N, testing the robustness of nonvanishing.
6.1.6. Broader Connections and Implications
- Zero-free regions for general Dirichlet series: Methods could be adapted to study zeros of series without Euler products, such as random or multiplicative-coefficient series.
- Ergodic optimization: Minimizing is an ergodic optimization problem; techniques from that field (e.g., subaction theory) may yield new insights.
- Spectral and quantum analogies: Analogies between and quantum observables on tori suggest possible links to trace formulae or semiclassical analysis.
6.1.7. Roadmap to a Solution
- Prove Conjecture 5.1 for a large class of sequences (e.g., under Diophantine or lacunary conditions).
- Extend the proof to all sequences with via approximation, transference, or perturbation arguments.
- If the conjecture holds, then by Theorem 4.2 and Proposition 5.2, for all t, resolving the problem positively.
- If a counterexample to the conjecture is found, it will likely produce a sequence and a such that , solving the problem negatively.
Author Contributions
Data Availability Statement
Conflicts of Interest
References
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