Open computational mathematics. AI-audited, not peer-reviewed. All code and data open for independent verification.

by cahlen Bronze
BRONZE AI Literature Audit · 3 reviews
Consensus ACCEPT_WITH_REVISION
Models gpt-4.1 + o3 + o3-pro
Level BRONZE — Novel observation, limited literature precedent

Review Ledger

2026-04-06 gpt-4.1 (OpenAI) BRONZE ACCEPT_WITH_REVISION
2026-04-06 o3-pro (OpenAI) BRONZE ACCEPT_WITH_REVISION
2026-04-06 o3 (OpenAI) BRONZE ACCEPT_WITH_REVISION

Issues Identified (1/5 resolved)

minor The raw data does not include wall-clock timings or GPU logs. To resolve this... acknowledged
minor Current dataset only covers k up to 10 and does not give standard errors for ... acknowledged
minor Current finding does not present data on the closure of the exception set for... acknowledged
minor No data is provided in the current finding for larger k (k ≥ 15), standard er... acknowledged
minor Confirmed that all reported ratios and regression fits use densities evaluate... resolved

Reviewed by 3 AI models. Audit found the original inverse-square fit used mismatched cutoffs; matched-N data weaken the claim.

Digit 1 Amplification in Zaremba Density

The Finding

For Zaremba density — the fraction of integers dNd \leq N representable as a continued fraction denominator using only digits from a set AA — replacing digit 2 with digit 1 amplifies density by a large factor. The original inverse-square headline is too strong: the current matched-cutoff data show strong amplification, but not a confirmed k2k^{-2} law.

At matched N=1010N=10^{10} for both {1,k}\{1,k\} and {2,k}\{2,k\}:

density({1,k})density({2,k})1143k1.463(R2=0.990, k=3,,10).\frac{\text{density}(\{1,k\})}{\text{density}(\{2,k\})} \approx 1143\,k^{-1.463}\qquad (R^2=0.990,\ k=3,\ldots,10).

At N=1011N=10^{11}, matched data currently exist only for k=3,4,5k=3,4,5, giving a suggestive but underdetermined fit 3562k1.93\approx 3562\,k^{-1.93}. That three-point overlap is not enough to claim an inverse-square law.

Data

All densities in this table use the same cutoff, N=1010N=10^{10}:

kkdensity {1,k}\{1,k\}density {2,k}\{2,k\}Amplification
311.0568%0.045486%243×
41.6096%0.010605%152×
50.4398%0.004126%107×
60.1721%0.002333%73.8×
70.0840%0.001302%64.6×
80.0475%0.000869%54.6×
90.0297%0.000638%46.6×
100.0201%0.000472%42.5×

The earlier version mixed {1,k}\{1,k\} densities at N=1011N=10^{11} with {2,k}\{2,k\} densities at N=1010N=10^{10}, which biases the fitted exponent because these densities are still scale-dependent.

Why This Matters

The golden ratio connection

Digit 1 in a continued fraction corresponds to the golden ratio ϕ=[1;1,1,1,]\phi = [1;1,1,1,\ldots]. The Gauss measure assigns weight log2(1+1/(a(a+2)))\log_2(1 + 1/(a(a+2))) to digit aa, giving digit 1 approximately 41.5% of the total weight — nearly half. But Gauss measure is about typical behavior. Our result quantifies the extremal behavior: how much more of the integer line digit 1 can reach compared to digit 2, as a function of the companion digit.

Why an inverse-square law is still plausible but unproved

The Gauss measure weight ratio between digits 1 and 2 is:

log(1+1/3)log(1+1/8)=log(4/3)log(9/8)2.41\frac{\log(1 + 1/3)}{\log(1 + 1/8)} = \frac{\log(4/3)}{\log(9/8)} \approx 2.41

This is a constant — it doesn’t depend on kk. So the 1/k21/k^2 decay in amplification must come from the interaction between digit 1 and digit kk, not from digit 1 alone. As kk grows, the continued fraction tree for {1,k}\{1,k\} and {2,k}\{2,k\} become increasingly similar in structure (both dominated by their small digit), and the advantage of digit 1 over digit 2 diminishes — but at a rate governed by 1/k21/k^2.

This is reminiscent of the 1/a2\sum 1/a^2 predictor for Hausdorff dimension (see Hausdorff digit-one dominance): the difference 1/121/22=3/41/1^2 - 1/2^2 = 3/4 is a constant, but its relative importance compared to 1/k21/k^2 decays as kk grows. The current data are consistent with a drift toward a quadratic law at larger NN, but matched larger-scale runs are required before making that claim.

Additional Patterns

{1,2,k} exception count growth

The number of integers with no {1,2,k}\{1,2,k\}-representation grows as a decelerating exponential in kk:

kkExceptionsRatio E(k)/E(k1)E(k)/E(k-1)Status
327Stable candidate through 101010^{10}; 10^11 repo log is partial
4642.4Stable candidate through 101010^{10}; 10^11 repo log is partial
53745.8Stable candidate through 101010^{10}; 10^11 repo log is partial
61,8344.9Stable candidate through 101110^{11}
77,1783.9Stable candidate through 101110^{11}
823,5903.3Open at 101110^{11}
977,1093.3Open at 101110^{11}
10228,5143.0Open at 101110^{11}

The growth ratios converge toward 3.2\approx 3.2, suggesting asymptotic behavior E(k)C3.2kE(k) \sim C \cdot 3.2^k. A quadratic-log model logE(k)=0.030k2+1.73k1.90\log E(k) = -0.030k^2 + 1.73k - 1.90 fits with R2=0.997R^2 = 0.997.

{1,3,5} approaching a finite limit

The exception set for A={1,3,5}A = \{1,3,5\} shows strong evidence of convergence:

NNExceptionsNew exceptions
10910^975,547
101010^{10}80,431+4,884
101110^{11}80,945+514

The increment dropped 9.5× per decade. Geometric extrapolation gives a limit of approximately 81,005, with fewer than 60 exceptions remaining beyond 101110^{11}. If confirmed at 101210^{12}, this would be evidence for another stable exception set and the first such candidate with non-consecutive digits.

Method

  • Transfer operator enumeration: GPU threads enumerate all continued fraction trees with digits in AA, marking denominators in a bitset
  • Prefix splitting: CPU generates tree prefixes to bounded depth; GPU threads do DFS on subtrees
  • Hardware: 8×NVIDIA B200 GPUs (180 GB each), RTX 5090 for smaller runs
  • All densities computed from complete enumeration up to NN, not sampling

Connection to Other Findings

  • Zaremba digit pair hierarchy: Established the {1,k}\{1,k\} and {2,k}\{2,k\} hierarchies separately; this finding quantifies the ratio between them
  • Zaremba exception hierarchy: Exception counts for {1,2,k}\{1,2,k\}; this finding adds the growth model and {1,3,5} convergence
  • Hausdorff digit-one dominance: The 1/a2\sum 1/a^2 predictor for dimension motivates testing inverse-square amplification in density, but does not prove it

Code

References

  • Zaremba, S. K. (1972). “La méthode des ‘bons treillis’ pour le calcul des intégrales multiples.” In Applications of Number Theory to Numerical Analysis, pp. 39–119.
  • Bourgain, J. and Kontorovich, A. (2014). “On Zaremba’s conjecture.” Annals of Mathematics, 180(1), pp. 137–196.
  • Hensley, D. (1996). “A polynomial time algorithm for the Hausdorff dimension of continued fraction Cantor sets.” Journal of Number Theory, 58(1), pp. 9–45.

Computed on 8×NVIDIA B200 GPUs. All data open at github.com/cahlen/idontknow.

This work was produced through human–AI collaboration (Cahlen Humphreys + Claude). Not independently peer-reviewed. All code and data open for verification.

Recent Updates

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