Asymptotic mutual information in quadratic estimation problems over compact groups
<|reference_start|>Asymptotic mutual information in quadratic estimation problems over compact groups: Motivated by applications to group synchronization and quadratic assignment on random data, we study a general problem of Bayesian inference of an unknown ``signal'' belonging to a high-dimensional compact group, given noisy pairwise observations of a featurization of this signal. We establish a quantitative comparison between the signal-observation mutual information in any such problem with that in a simpler model with linear observations, using interpolation methods. For group synchronization, our result proves a replica formula for the asymptotic mutual information and Bayes-optimal mean-squared-error. Via analyses of this replica formula, we show that the conjectural phase transition threshold for computationally-efficient weak recovery of the signal is determined by a classification of the real-irreducible components of the observed group representation(s), and we fully characterize the information-theoretic limits of estimation in the example of angular/phase synchronization over $SO(2)$/$U(1)$. For quadratic assignment, we study observations given by a kernel matrix of pairwise similarities and a randomly permutated and noisy counterpart, and we show in a bounded signal-to-noise regime that the asymptotic mutual information coincides with that in a Bayesian spiked model with i.i.d. signal prior.<|reference_end|>
@article{yang2024asymptotic,
    title={Asymptotic mutual information in quadratic estimation problems over
  compact groups},
    author={Kaylee Y. Yang, Timothy L. H. Wee, Zhou Fan},
    journal={arXiv preprint arXiv:2404.10169},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.10169},
    primaryClass={math.ST cs.IT math.IT stat.TH}
}