2203.15315
Box-counting dimension in one-dimensional random geometry of multiplicative cascades
Kenneth J. Falconer, Sascha Troscheit
correcthigh confidence
- Category
- Not specified
- Journal tier
- Strong Field
- Processed
- Sep 28, 2025, 12:56 AM
- arXiv Links
- Abstract ↗PDF ↗
Audit review
The uploaded paper proves exactly the box-dimension formula for f(E_a) under assumptions (1.2) and (1.8), see Theorem 1.10 (eq. (1.11)) with γ = −E(log_2 W) . The candidate solution correctly invokes this result and sketches the same two-step argument (E_α case, then transfer via eventual separation). Minor issues: it mislabels the cited theorem as “Theorem 1.12” (the PDF shows Theorems 1.9 and 1.10) and its moment condition should match (1.8), which (as stated in the paper) is used for the lower bound and entails the integrability needed for second derivatives . Apart from these cosmetic points, the model’s solution aligns with the paper.
Referee report (LaTeX)
\textbf{Recommendation:} minor revisions \textbf{Journal Tier:} strong field \textbf{Justification:} This work gives an exact almost-sure box-dimension formula for images of decreasing sequences under multiplicative cascades, complementing KPZ-type results for Hausdorff dimension. The approach—balancing spine large deviations with branching counts and then transferring via eventual separation—is both insightful and robust. The results sharpen our understanding of how set structure (beyond dimension) impacts image dimensions in random geometry. Minor clarifications on notation and assumptions would further improve readability.