Abstract

We introduce dynamical blanket times, which quantify how quickly the empirical distribution along a typical orbit approximates the invariant measure. These can be viewed as a measure-theoretic analogue of the previously introduced dynamical cover time, which measures how quickly an orbit becomes dense in the space. Motivated by analogous comparability questions for random walks on graphs, we investigate how much longer it takes for a dynamical system to ``blanket'' than to ``cover''. For finite-branch, uniformly expanding interval maps, we obtain upper bounds on the expected blanket time in terms of the spatial scale and the precision of approximation. In the special case where the invariant measure is absolutely continuous with respect to Lebesgue, this yields comparability between the expected blanket and cover times, uniformly across all sufficiently small scales. Our approach combines two main ingredients. First, we establish large deviation estimates for hitting times which are uniform over both the target location and the spatial scale. Second, using methods from multifractal analysis, we construct a finite discretisation of the invariant measure which reduces the problem to a suitably controlled discrete model.

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Audited against arXiv v1

Not a correctness certificate. A “Correct” result may include yellow typos or minor formal corrections that do not affect substantive soundness. It means this audit found no unresolved substantive error under the stated criteria; it does not replace expert scrutiny or formal verification.

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Detailed mathematical audit

Generated August 18, 2026
01Statements2 reported findingsCorrect

The expected blanket-time estimate and its absolutely continuous invariant-measure corollary are correct under the stated hyperbolic and Gibbs assumptions.

Theorem 1.3Correct

The blanket-time upper bound has the claimed dimension and logarithmic scale

Pages 3–5 and Sections 2–4 · Theorem 1.3 · arXiv:2606.18926v1

The multifractal discretization partitions the target family into finitely many mass scales, and the uniform hitting-time deviation estimate controls the failure probability on each scale. Summing the resulting geometric tail yields the factor δDlog(1/δ)\delta^{-D}\log(1/\delta) and the stated dependence of the constant on the tolerance parameter. The covering exponent used in the union bound is exactly the dimension appearing in the theorem.

Absolutely continuous invariant-measure corollaryCorrect

Uniform density comparison gives the announced specialization

Pages 4–5 · corollary following Theorem 1.3 · arXiv:2606.18926v1

When the invariant density is bounded above and below on the relevant region, metric balls have uniformly comparable mass and the local dimensions collapse to the ambient dimension. Substitution in Theorem 1.3 gives the displayed order and the stated tolerance dependence without adding an unstated regularity assumption.

02Proofs2 reported findingsCorrect

The proof combines a quantitative target discretization with a uniform hitting-time large-deviation estimate, and the probability summation closes with the stated constants.

Proposition 2.4Correct and complete

Uniform hitting-time large deviations

Pages 9 and 14–20 · Section 5 · arXiv:2606.18926v1

Inducing on each Markov target gives transfer operators with a spectral gap and pressure functions analytic in the tilt. The first two pressure derivatives are controlled uniformly in the target, so the Chernoff parameter may be chosen proportional to its measure. The cylinder estimates then give an exponential tail in nμ(A)n\mu(A) with constants independent of the Markov interval, exactly the uniformity needed by the later union bound.

Proposition 2.3Correct and complete

Multifractal target discretization

Pages 9 and 21–25 · Section 6 · arXiv:2606.18926v1

For an absolutely continuous invariant measure, a canonical cylinder partition immediately supplies the required approximation and exponential sum. In the multifractal case, Proposition 6.3 separates high-mass intervals from the low-mass region controlled by the endpoint spectrum Fμ(D)<1F_\mu(D)<1. The two cardinality estimates have positive residual powers of δ\delta, and their union approximates every radius-δ\delta ball up to the prescribed relative mass error, yielding the scale-uniform bound in Proposition 2.3.

03Novelty0 reported findingsNo non-novelty findings

No non-novelty findings.

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Paper
arXiv:2606.18926v1
Authors listed
Natalia Jurga, Mike Todd
Audit date
August 18, 2026
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