Terminal Defects, Growing Multiplicity, and Variance Extremality in the Double Dixie Cup Problem

Fuente: arXiv
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Main Author: Long, Christopher D.
Format: Preprint
Published: 2026
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author Long, Christopher D.
author_facet Long, Christopher D.
contents We develop a terminal-defect method for the double Dixie cup problem and use it to prove the finite-variance extremality conjecture of Doumas and Papanicolaou. For every \(m\ge1\) and \(N\ge2\), among all positive coupon probability vectors \(p=(p_1,\ldots,p_N)\), the variance of the time \(T_m(N)\) to collect \(m\) complete sets is uniquely minimized at the uniform vector. We prove the stronger radial statement that the variance is strictly increasing along every ray from the uniform vector. The proof is finite-\(N\) and exact: after Poissonization, the completion time is a maximum of independent Erlang variables, and the radial derivative of its distribution is compared to a size-biased law using a monotone-likelihood-ratio argument based on a log-scale monotonicity property of the Gamma reverse hazard. The same framework gives a growing-multiplicity Gumbel theorem in the equal-probability case, with expectation and variance asymptotics on the inverse gamma-tail scale. This recovers the fixed-\(m\) equal-probability variance asymptotic stated as Conjecture 1 by Doumas and Papanicolaou, classically known for \(m=1\), and extends the mechanism to \(m=m_N\). We also illustrate the unequal-probability theory with endpoint-Laplace limits for power-law probabilities.
format Preprint
id arxiv_https___arxiv_org_abs_2604_25108
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Terminal Defects, Growing Multiplicity, and Variance Extremality in the Double Dixie Cup Problem
Long, Christopher D.
Probability
Combinatorics
60C05, 60F05, 60G70, 60E15
We develop a terminal-defect method for the double Dixie cup problem and use it to prove the finite-variance extremality conjecture of Doumas and Papanicolaou. For every \(m\ge1\) and \(N\ge2\), among all positive coupon probability vectors \(p=(p_1,\ldots,p_N)\), the variance of the time \(T_m(N)\) to collect \(m\) complete sets is uniquely minimized at the uniform vector. We prove the stronger radial statement that the variance is strictly increasing along every ray from the uniform vector. The proof is finite-\(N\) and exact: after Poissonization, the completion time is a maximum of independent Erlang variables, and the radial derivative of its distribution is compared to a size-biased law using a monotone-likelihood-ratio argument based on a log-scale monotonicity property of the Gamma reverse hazard. The same framework gives a growing-multiplicity Gumbel theorem in the equal-probability case, with expectation and variance asymptotics on the inverse gamma-tail scale. This recovers the fixed-\(m\) equal-probability variance asymptotic stated as Conjecture 1 by Doumas and Papanicolaou, classically known for \(m=1\), and extends the mechanism to \(m=m_N\). We also illustrate the unequal-probability theory with endpoint-Laplace limits for power-law probabilities.
title Terminal Defects, Growing Multiplicity, and Variance Extremality in the Double Dixie Cup Problem
topic Probability
Combinatorics
60C05, 60F05, 60G70, 60E15
url https://arxiv.org/abs/2604.25108