English

Projected multi-reference alignment

Signal Processing 2026-05-26 v1 Information Theory math.IT Statistics Theory Statistics Theory

Abstract

Motivated by structural biology applications, we study the projected multi-reference alignment (MRA) model, in which an unknown signal is observed through noisy samples, each generated by applying a random cyclic shift followed by a fixed projection. The projection merges reflection-symmetric index pairs, thereby discarding orientation information. The goal is to recover the dihedral orbit of the signal. We prove that in the high-noise regime, the first three moments of the projected observations determine a generic dihedral orbit. The main mechanism is a reduction, at the moment level, from projected MRA to the reflection-invariant phase-coupling structure of dihedral MRA. In Fourier-cosine coordinates adapted to the projection, the first moment determines the mean component, the second moment determines the Fourier magnitudes, and selected third moments yield the cosine phase-coupling relations appearing in the dihedral bispectrum. These relations lead to a constructive recovery scheme from moments up to order three. We complement the population theory with finite-sample experiments comparing expectation--maximization (EM), direct moment optimization, and direct Fourier-cosine moment optimization. The results show that, in the high-noise regime, both EM and direct moment optimization are consistent with the predicted third-moment sample-complexity scaling nσ6n \gtrsim \sigma^6, where nn is the number of observations and σ2\sigma^2 is the noise variance.

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Cite

@article{arxiv.2605.25533,
  title  = {Projected multi-reference alignment},
  author = {Amnon Balanov and Josh Katz and Tamir Bendory and Dan Edidin},
  journal= {arXiv preprint arXiv:2605.25533},
  year   = {2026}
}