The Constructive Cavity Method for the Ising Perceptron

We apply the Constructive Cavity Method (CCM) to the Ising perceptron. The process starts from positive soft channels admitting an auxiliary representation $$ U(x)=\int_{\mathbb{R}} e^{tx}ρ(\mathrm{d}t),\qquad ρ\ge0, $$ with an auxiliary measure having a finite exponential quadratic moment. This rewrites the perceptron as a dense, bipartite Gaussian model with an Ising layer and a continuous auxiliary layer. The CCM blanket geometry then gives two constructive variance profiles, $Q_\ell$ on the Ising side and $Γ_\ell$ on the auxiliary side. The bipartite shell scale is $$ Q_{\ell+1}Γ_{\ell+1}-Q_\ellΓ_\ell, $$ and Gaussian core comparison removes the core contribution $ΔQ_\ellΔΓ_\ell$ under blanket refinement. The scalar cavity functional has three terms, $$ \mathcal{A}_{\mathrm{perc}}(ν)=\mathbb{E}\left[\log\langle2\cosh x\rangle_ν+α\log\langle U(s)\rangle_ν-\log\langle e^y\rangle_ν\right], $$ where $x$ is the new-spin field, $s$ is the new-constraint field, and $y$ is the cavity correction. CCM identifies the constructive cavity variables with the Aizenman--Sims--Starr random overlap structure (ROSt) variables. Parisi's recursive averaging then gives $$ \mathcal{G}_{\mathrm{perc}}^{\mathrm{CCM}}(ζ,Q,Γ)=X_0(0)+αY_0(0)-\frac{1}{2}\sum_{\ell=0}^{R}ζ_\ell\left(Q_{\ell+1}Γ_{\ell+1}-Q_\ellΓ_\ell\right). $$ The replica-symmetric specialization gives Gardner's formula for the generalized Ising perceptron. Specializing the constraint terminal to the hard channel gives the Krauth--Mézard functional for the binary perceptron.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-10-29
DOI
https://doi.org/10.48550/arxiv.2610.39141
Primary Topic
Theoretical and Computational Physics
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

The Constructive Cavity Method for the Ising Perceptron

Simone Franchini, Giampiero Bardella, Francesco Concetti
arXiv (Cornell University)
Theoretical and Computational Physics
preprint

The Constructive Cavity Method for the Ising Perceptron

Simone Franchini, Giampiero Bardella, Francesco Concetti
preprint en

Abstract

We apply the Constructive Cavity Method (CCM) to the Ising perceptron. The process starts from positive soft channels admitting an auxiliary representation $$ U(x)=\int_{\mathbb{R}} e^{tx}ρ(\mathrm{d}t),\qquad ρ\ge0, $$ with an auxiliary measure having a finite exponential quadratic moment. This rewrites the perceptron as a dense, bipartite Gaussian model with an Ising layer and a continuous auxiliary layer. The CCM blanket geometry then gives two constructive variance profiles, $Q_\ell$ on the Ising side and $Γ_\ell$ on the auxiliary side. The bipartite shell scale is $$ Q_{\ell+1}Γ_{\ell+1}-Q_\ellΓ_\ell, $$ and Gaussian core comparison removes the core contribution $ΔQ_\ellΔΓ_\ell$ under blanket refinement. The scalar cavity functional has three terms, $$ \mathcal{A}_{\mathrm{perc}}(ν)=\mathbb{E}\left[\log\langle2\cosh x\rangle_ν+α\log\langle U(s)\rangle_ν-\log\langle e^y\rangle_ν\right], $$ where $x$ is the new-spin field, $s$ is the new-constraint field, and $y$ is the cavity correction. CCM identifies the constructive cavity variables with the Aizenman--Sims--Starr random overlap structure (ROSt) variables. Parisi's recursive averaging then gives $$ \mathcal{G}_{\mathrm{perc}}^{\mathrm{CCM}}(ζ,Q,Γ)=X_0(0)+αY_0(0)-\frac{1}{2}\sum_{\ell=0}^{R}ζ_\ell\left(Q_{\ell+1}Γ_{\ell+1}-Q_\ellΓ_\ell\right). $$ The replica-symmetric specialization gives Gardner's formula for the generalized Ising perceptron. Specializing the constraint terminal to the hard channel gives the Krauth--Mézard functional for the binary perceptron.

arXiv (Cornell University)
Theoretical and Computational Physics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon