arXiv:2603.20483v2

Convergence Analysis of the Random Bisection Method

Ludovick Bouthat, Philippe-André Luneau, Philippe Petitclerc

math.NAmath.PR65H0560G1047N4037H9937A50

Abstract

We propose a generalized version of the bisection method where the cutting point between the two subintervals is chosen at random following an arbitrary distribution. We compute expected convergence rates with respect to any arbitrary a priori distribution for the position of the root in the initial interval and proved that it depends only on the the expectation E[c(1c)]\mathbb{E}[c(1-c)] of the cut cc. We also provide a generalization of the method for KK random cuts and study its convergence properties. Most probabilistic derivations are kept fairly simple for the ease of understanding of a larger audience. Our theoretical results are then validated numerically using statistical simulation.

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Audit summary

Audited against arXiv v2

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
01Statements3 reported findingsCorrect

The distributional identities, independence result, convergence of the random bisection root to the uniform law, and the multi-cut expected-length formula are correct.

Single-step and independence theoremsCorrect

The normalized root and scaling-factor laws are computed correctly

Sections 2–4 · single-bisection distribution and independence results · arXiv:2603.20483v2

Conditioning on the random cut and selected subinterval gives the displayed piecewise density and moment formulas. With a uniform initial normalized root, the joint density factorizes, proving independence from the length multiplier. Iteration therefore yields the stated product formula for expected interval length.

Theorem 10 and Corollary 14Correct

The normalized-root law converges to uniformity

Pages 11–15 · Section 3 · arXiv:2603.20483v2

The transition operator preserves constants and acts triangularly on polynomial densities, with every nonconstant diagonal eigenvalue strictly inside the unit circle under the stated nondegeneracy hypotheses. Polynomial approximation, followed by the operator's L1L^1 contraction, extends convergence to the announced classes of starting densities. Corollary 14 then combines this convergence with the exact one-step length formula to obtain the limiting expected contraction.

Propositions 15–16 and Corollary 17Correct

Stationarity and contraction for the multi-cut procedure

Pages 16–18 · Section 4 · arXiv:2603.20483v2

Conditioning on the ordered cuts partitions the root coordinate into K+1K+1 exchangeable spacings. Integrating the rescaled root over each spacing proves that the uniform law is stationary. For independent uniform cuts, the selected interval is size-biased among Dirichlet(1,,1)(1,\ldots,1) spacings, whose squared lengths sum in expectation to 2/(K+2)2/(K+2); this is exactly the expected retained-length factor displayed in Corollary 17.

02Proofs1 reported findingCorrect

The conditional-density calculations and the operator convergence argument are complete. The paper does not overstate its epsilon-dependent convergence estimate as a uniform spectral rate.

Markov-operator convergence proofCorrect and complete

Polynomial convergence is validly extended to general densities

Convergence-analysis section · arXiv:2603.20483v2

Every polynomial component is handled by the triangular action of the transition operator, and the invariant constant is fixed by total mass. Approximating an arbitrary density and using contraction gives the claimed convergence. The constants in the final estimate are permitted to depend on the approximation tolerance, so the proof does not assert an unsupported uniform exponential rate.

03Novelty0 reported findingsNo non-novelty findings

No non-novelty findings.

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Paper
arXiv:2603.20483v2
Authors listed
Ludovick Bouthat, Philippe-André Luneau, Philippe Petitclerc
Audit date
August 18, 2026
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