Beyond Frequency Marching: Orbit Recovery in Dihedral and Projected Multireference Alignment

2026-06-10

AI Summary

This work addresses the problem of hidden signal recovery in dihedral multi-reference alignment (MRA) and its projection variant, where observations are corrupted by unknown translations, reflections, or tomographic projections. Focusing on signals whose length is a power of two, the authors propose the first polynomial-time algorithm that provably succeeds for generic signals. The method integrates third-order moment tensors, symbolic matrix rank analysis, and a recursive divide-and-conquer strategy to decompose the original problem into tractable subproblems. This approach overcomes fundamental limitations of existing techniques in both dihedral and projection MRA. Its correctness hinges on a conjecture regarding the rank of a symbolic matrix, which is amenable to computational verification and, under the stated conditions, enables exact signal recovery with high probability.

Abstract

Multireference alignment (MRA) is the task of recovering a hidden "signal" vector, given many noisy copies that have been cyclically shifted by unknown offsets. This task belongs to the class of orbit recovery problems, in which the observed samples are affected by some group action. These problems have a variety of practical motivations, including the reconstruction of 3-dimensional molecular structure from cryogenic electron microscopy (cryo-EM) images. We consider two variants of MRA: dihedral MRA, where the cyclic group is replaced by the dihedral group, allowing for reversals of the vector in addition to shifts; and projected MRA, where the observations are passed through a projection operator akin to the tomographic projection present in cryo-EM. We apply the method of moments and aim to recover the signal from the third moment tensor of the samples. This inverse problem is well understood for basic MRA, but for the variants we consider there is no polynomial-time algorithm known to succeed for generic signals. We give the first such algorithm for both of these variants. Our method requires the signal length to be a power of two, and recursively subdivides the problem into smaller problems of half the size. The algorithm's success for generic signals is proven, conditional on a conjecture about the rank of a certain symbolic matrix of polynomials. For any given problem size, this conjecture can be verified on a computer.

Problem

• orbit recovery
• multireference alignment
• dihedral group
• projected MRA
• cryo-EM

Innovation

• multireference alignment
• method of moments
• dihedral group
• projected MRA
• polynomial-time algorithm