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The Ibragimov–Iosifescu conjecture for φ-mixing sequences

Astra constructs a strictly stationary real process Xt=ξt+K(ξt1,ξt2,), X_t=\xi_t+K(\xi_{t-1},\xi_{t-2},\ldots), where the innovations ξt\xi_t are i.i.d. Gaussian variables convolved with a symmetric rare-spike law, and KK is bounded, continuous, and odd. The process is φ\varphi-mixing, centered, square-integrable, and satisfies Var(Sn). \operatorname{Var}(S_n)\to\infty. Nevertheless there are times njn_j\to\infty such that SnjVar(Snj)0 \frac{S_{n_j}}{\sqrt{\operatorname{Var}(S_{n_j})}}\to0 in probability. Therefore the normalized sums cannot converge in distribution to N(0,1)N(0,1). The same example also rules out Iosifescu's stronger weak invariance-principle conjecture, since Brownian convergence would imply the CLT at time 11.

Exact FrontierDelta

Prior state unknowndisproved

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Occurred: Sep 5, 2026

Delta type: SOURCE CLAIM

Assumptions: VibeMathed verification: lean-checked. Publication: announcement. AI contribution: ai-discovered. VibeMathed editorial classifications, scores, notes, relations, and dataset structure are CC BY 4.0. Source statements and linked content retain their own rights.

Canonical aliases: The Ibragimov–Iosifescu conjecture for φ-mixing sequences · $\varphi$-mixing CLT

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VibeMathed
registry · event recorded by

Tom Adamczewski
human · human collaborator

GPT-6 Astra (pre-release)
model · ai model contributor · OpenAI

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The Ibragimov–Iosifescu conjecture for φ-mixing sequences parent of this event

Challenge.lean: the compared statement evidence for this event

Peligrad (1990), On Ibragimov–Iosifescu conjecture for φ-mixing sequences evidence for this event

VibeMathed record: The Ibragimov–Iosifescu conjecture for φ-mixing sequences evidence for this event

The Ibragimov–Iosifescu conjecture for φ-mixing sequences evidence for this event

This event attributed to Tom Adamczewski

Astra constructs a strictly stationary real process Xt=ξt+K(ξt1,ξt2,), X_t=\xi_t+K(\xi_{t-1},\xi_{t-2},\ldots), where the innovations ξt\xi_t are i.i.d. Gaussian variables convolved with a symmetric rare-spike law, and KK is bounded, continuous, and odd. The process is φ\varphi-mixing, centered, square-integrable, and satisfies Var(Sn). \operatorname{Var}(S_n)\to\infty. Nevertheless there are times njn_j\to\infty such that SnjVar(Snj)0 \frac{S_{n_j}}{\sqrt{\operatorname{Var}(S_{n_j})}}\to0 in probability. Therefore the normalized sums cannot converge in distribution to N(0,1)N(0,1). The same example also rules out Iosifescu's stronger weak invariance-principle conjecture, since Brownian convergence would imply the CLT at time 11. parent of this event

This event attributed to GPT-6 Astra (pre-release)

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