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[#P2914] A rigorous stochastic-dominance counterexample in one-dimensional coalescence

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Problem. In the one-dimensional red-blue coalescence process, let \(U\) be uniform on \([1,1.01]\), let a red interval have length \(R=U\), and let a blue interval have length \(B=U-1\) when \(U<1.0008\) and \(B=U\) otherwise. Prove that blue wins almost surely under every complete legal coalescence order, even though \(R\) strictly stochastically dominates \(B\).

A flat mathematical diagram showing one-dimensional particles moving and merging over time.
A schematic view of one-dimensional particles moving and merging over time.
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Definitions and notation

1Context

The paper already supplies the infinite-process reduction. Tables for the finite distribution, interval enclosures, and rare-event decompositions can be reused to replace its Monte Carlo step with a proof.

2Definitions

Definition 1 (The initial state). The initial state is a bi-infinite alternating sequence of red and blue intervals whose lengths are independent with the stated color laws. A legal move recolors an interval that is shorter than each of its two opposite-color neighbors, then merges the resulting three adjacent intervals.

Definition 2 (A coalescence order). A coalescence order is complete if every move that remains legal is eventually performed. Blue wins if every fixed point of the line eventually lies in a blue interval.

3What counts as a solution

  • Give a rigorous bound establishing the finite probability inequality required by the published coalescence criterion for the stated distribution, then derive almost-sure blue victory for every complete legal order.
  • All computer-assisted probability bounds must use exact or outward-rounded arithmetic, publish the event definition and parameter vector, and include replayable code or a finite certificate.

1Status

Saved packet · July 31, 2026

What counts as a solution

Saved packet status (Current status and unresolved remainder). UNKNOWN as of 2026-07-31. The published paper reports this distribution as a counterexample with overwhelming simulation confidence. Its Claim 2.3 depends on a finite probability inequality verified numerically, and the authors explain that an analytic finite calculation could convert it into a theorem. Give a rigorous bound establishing the finite probability inequality required by the published coalescence criterion for the stated distribution, then derive almost-sure blue victory for every complete legal order.[1]

1Packet records

2 records

Notes and companion material

Original intake status. UNKNOWN as of 2026-07-31. The published paper reports this distribution as a counterexample with overwhelming simulation confidence. Its Claim 2.3 depends on a finite probability inequality verified numerically, and the authors explain that an analytic finite calculation could convert it into a theorem.

  • The published Transactions of the AMS article and arXiv:1610.07430 were checked. For the stated distribution they reduce blue victory to a finite estimate q(n0,r)<0.058 with n0=2,000,000 and report 987 successes in 1000 trials rather than a proof of that estimate.
  • The paper's simulation gives a p-value below 10^{-12} against the adverse threshold, which makes the example a strong candidate for interval arithmetic, exact convolution, or a concentration bound. Statistical confidence alone is outside the acceptance test.
  • A local corpus search for coalescence, stochastic dominance, red-blue intervals, and the numerical distribution found no duplicate.

Recorded example 1. For every t, Pr(R>t)>=Pr(B>t), with strict inequality for some t, because B either equals U or is shifted down by one. The claimed winner therefore runs against the interval-length stochastic order.

Computational notes

  • The published experiment reports 987 successful trials out of 1000 for the finite criterion at n0=2,000,000. The record treats this as evidence and asks for a certified replacement.
How the 2 records connect
The overview places each record once. The relation list includes shared dependencies and names both ends of each link.

ProblemA rigorous stochastic-dominance counterexample in one-dimensional coalescence

All 1 recorded relations between these records and the problem

2See also

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Plain text
“A rigorous stochastic-dominance counterexample in one-dimensional coalescence.” TheoremDB. P2914. Problem statement; statement text SHA-256 f810291b1416dc8a69036ec1994dc9906d2539c01bed14eedc013dd1d933c22b. https://theoremdb.org/statement/?ref=P2914
BibTeX
@misc{theoremdb-problem-f810291b1416dc8a69036ec1994dc9906d2539c01bed14eedc013dd1d933c22b,
  title = {{A rigorous stochastic-dominance counterexample in one-dimensional coalescence}},
  howpublished = {TheoremDB},
  note = {Problem statement; statement text SHA-256 f810291b1416dc8a69036ec1994dc9906d2539c01bed14eedc013dd1d933c22b},
  url = {https://theoremdb.org/statement/?ref=P2914}
}

This problem includes 2 records joined by 1 typed links, sourced from mathoverflow.net[1], current as of July 31, 2026.

1References

  1. Packet source. MathOverflow: Alternating colors on a line, infinitely often or converge?. Question 56048, its answer, and every visible comment were checked on 2026-07-27; the numerical distribution and proof gap come from the paper linked in the answer. Question 56048, its answer, and every visible comment were checked on 2026-07-27; the numerical distribution and proof gap come from the paper linked in the answer. ↗forum · discovery source · checked 2026-07-31Source use: original summary.UNKNOWN as of 2026-07-27. The published paper reports this distribution as a counterexample with overwhelming simulation confidence. Its Claim 2.3 depends on a finite probability inequality verified numerically, and the authors explain that an analytic finite calculation could convert it into a theorem.Also cited at See dataset.references[0] for the exact external source and locator.Also cited at Editorial research route recorded 2026-07-31.Source used to formulate or check the problem record.Source used to assess the problem's recorded status.For A rigorous stochastic-dominance counterexample in one-dimensional coalescence: UNKNOWN as of 2026-07-27. The published paper reports this distribution as a counterexample with overwhelming simulation confidence. Its Claim 2.3 depends on a finite probability inequality verified numerically, and the authors explain that an analytic finite calculation could convert it into a theorem.Source named by the research packet.
  2. Paul Balister, Béla Bollobás, Jonathan Lee, and Bhargav Narayanan, “Coalescence on the real line”. Transactions of the American Mathematical Society 371(3) (2018), 1583-1619. DOI 10.1090/tran/7391. Status evidence identified in the source record and checked at the linked publication. ↗ open copy ↗journal article · primary source · arXiv:1610.07430, checked 2026-07-31 · checked 2026-07-31Source use: original summary.UNKNOWN as of 2026-07-27. The published paper reports this distribution as a counterexample with overwhelming simulation confidence. Its Claim 2.3 depends on a finite probability inequality verified numerically, and the authors explain that an analytic finite calculation could convert it into a theorem.Also cited at Full journal article relevant to A rigorous stochastic-dominance counterexample in one-dimensional coalescence.Source used to assess the problem's recorded status.For A rigorous stochastic-dominance counterexample in one-dimensional coalescence: UNKNOWN as of 2026-07-27. The published paper reports this distribution as a counterexample with overwhelming simulation confidence. Its Claim 2.3 depends on a finite probability inequality verified numerically, and the authors explain that an analytic finite calculation could convert it into a theorem.

An original CC0 reformulation motivated by the cited MathOverflow thread and its linked coalescence paper; no source prose was copied.

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