Sharp small-deviation inequalities for sums of independent nonnegative random variables

Weibo Fu, Yanjun Han, Guanyang Wang, Jun Yan, Peng Zhang, Zhengqing Zhou

For independent nonnegative random variables X₁,…,Xₙ with E[Xᵢ]≤1 and S=ΣXᵢ, Fu, Han, Wang, Yan, Zhang and Zhou prove P(S<E[S]+δ)≥δ(n/(n+δ))ⁿ for 0<δ<1, and ≥(1−1/(n+δ))ⁿ for δ≥1. The second finite-n bound is sharp and implies Feige’s unit-slack e⁻¹ conjecture.

Sources for this record

What was already known

Feige conjectured the unit-slack e⁻¹ guarantee. The cited calibration and centroid inequalities existed, but their combination into this sharp range was new in the assessed paper.

AI involvement AI-led

The paper credits ChatGPT 5.6 Pro with the initial proof combining the calibration and centroid inequalities. The six human authors checked, revised and explained the argument.

The source expressly credits the model with the initial proof; humans checked and reworked the retained argument.

Importance Major

Settles the longstanding unit-slack conjecture and proves a sharp finite-n bound throughout δ≥1.

Limitations

The 0<δ<1 estimate is not claimed sharp. The six authors report checking and rewriting the model’s proof; a later independent unit-slack proof does not check this paper’s full δ range.

Technical verification Formal (human)

The authors explicitly report checking the initial proof and rewriting the final argument; this is a source-reported author check.

Independent checking

Authors report checking, revising and rewriting the model proof.

Checker
Fu, Han, Wang, Yan, Zhang and Zhou
Scope
Theorem 1.1 across the stated δ ranges
Basis
Reported by the linked checker
Evidence source

Human understanding Full

The authors explain the Dirichlet-calibration and convex-geometric proof route in §§1.2–2.

Correction and publication history