Perfect reconstruction of sparse signals using nonconvexity control and one-step RSB message passing

TL;DR

This paper develops an advanced message passing algorithm, 1RSB-AMP, for sparse signal reconstruction that improves upon previous methods by incorporating nonconvexity control and 1RSB analysis, achieving near-optimal recovery performance.

Contribution

It introduces 1RSB-AMP, an extension of AMP with 1RSB analysis, and proposes a new criterion for parameter tuning that enhances the algorithm's reconstruction capabilities.

Findings

1RSB-AMP aligns well with state evolution predictions.

The method improves the phase transition boundary for perfect reconstruction.

Performance approaches the Bayes-optimal threshold, with modest gains.

Abstract

We consider sparse signal reconstruction via minimization of the smoothly clipped absolute deviation (SCAD) penalty, and develop one-step replica-symmetry-breaking (1RSB) extensions of approximate message passing (AMP), termed 1RSB-AMP. Starting from the 1RSB formulation of belief propagation, we derive explicit update rules of 1RSB-AMP together with the corresponding state evolution (1RSB-SE) equations. A detailed comparison shows that 1RSB-AMP and 1RSB-SE agree remarkably well at the macroscopic level, even in parameter regions where replica-symmetric (RS) AMP, termed RS-AMP, diverges and where the 1RSB description itself is not expected to be thermodynamically exact. Fixed-point analysis of 1RSB-SE reveals a phase diagram consisting of success, failure, and diverging phases, as in the RS case. However, the diverging-region boundary now depends on the Parisi parameter due to the 1RSB ansatz, and we propose a new criterion -- minimizing the size of the diverging region -- rather than the conventional zero-complexity condition, to determine its value. Combining this criterion with the nonconvexity-control (NCC) protocol proposed in a previous RS study improves the algorithmic limit of perfect reconstruction compared with RS-AMP. Numerical solutions of 1RSB-SE and experiments with 1RSB-AMP confirm that this improved limit is achieved in practice, though the gain is modest and remains slightly inferior to the Bayes-optimal threshold. We also report the behavior of thermodynamic quantities -- overlaps, free entropy, complexity, and the non-self-averaging susceptibility -- that characterize the 1RSB phase in this problem.