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Bibliographic Details
Main Author: Kogan, David
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2512.07816
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author Kogan, David
author_facet Kogan, David
contents We prove universality for Approximate Message Passing (AMP) with polynomial nonlinearities applied to symmetric sub-Gaussian matrices $A\in\mathbb R^{N\times N}$. Our approach is combinatorial: we represent AMP iterates as sums over trees and define a Wick pairing algebra that counts the number of valid row-wise pairings of edges. The number of such pairings coincides with the trees contribution to the state evolution formulas. This algebra works for non-Gaussian entries. For polynomial nonlinearities of degree at most $D$, we show that the moments of AMP iterates match their state evolution predictions for $t \lesssim \frac{\log N}{D\log D}$ iterations. The proof controls all "excess" trees via explicit enumeration bounds, showing non "Wick-paired" contributions vanish in the large-$N$ limit. The same framework should apply, with some modifications, to spiked AMP and tensor AMP models.
format Preprint
id arxiv_https___arxiv_org_abs_2512_07816
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Universality of AMP via Tree Pairings
Kogan, David
Probability
We prove universality for Approximate Message Passing (AMP) with polynomial nonlinearities applied to symmetric sub-Gaussian matrices $A\in\mathbb R^{N\times N}$. Our approach is combinatorial: we represent AMP iterates as sums over trees and define a Wick pairing algebra that counts the number of valid row-wise pairings of edges. The number of such pairings coincides with the trees contribution to the state evolution formulas. This algebra works for non-Gaussian entries. For polynomial nonlinearities of degree at most $D$, we show that the moments of AMP iterates match their state evolution predictions for $t \lesssim \frac{\log N}{D\log D}$ iterations. The proof controls all "excess" trees via explicit enumeration bounds, showing non "Wick-paired" contributions vanish in the large-$N$ limit. The same framework should apply, with some modifications, to spiked AMP and tensor AMP models.
title Universality of AMP via Tree Pairings
topic Probability
url https://arxiv.org/abs/2512.07816