Publications

Journal Articles

A Message-Passing Perspective on Ptychographic Phase Retrieval

Published in IEEE Transactions on Computational Imaging, 2025

We introduce a probabilistic approach to ptychographic reconstruction in computational imaging. This paper formulates ptychography as a Bayesian inverse problem and derives an inference algorithm, Ptycho-EP, based on belief propagation and Vector Approximate Message Passing (VAMP). The method integrates prior knowledge of the object into the model and provides uncertainty quantification for the reconstructed image. Experiments demonstrate that the proposed algorithm achieves reconstruction accuracy near the information-theoretic limit and performs robustly even when the probe is unknown, through an Expectation–Maximization extension.

Recommended citation: H. Ueda, S. Katakami, and M. Okada, “A Message-Passing Perspective on Ptychographic Phase Retrieval,” *IEEE Transactions on Computational Imaging*, vol. 11, pp. 1–15, 2025. doi:10.1109/TCI.2025.3622992
Download Paper

Bayesian Estimation of Phonon Dispersion Relation from Thermal Diffuse Scattering

Published in Journal of the Physical Society of Japan, 2025

We present a Bayesian framework for estimating the phonon dispersion relation from X-ray thermal diffuse scattering (TDS) patterns, with full uncertainty quantification.
By analyzing TDS patterns with random incident orientations, the method achieves more accurate reconstruction of phonon dispersions compared to conventional high-symmetry-plane measurements.
The approach leverages the Exchange Monte Carlo (EMC) algorithm for efficient sampling from complex probabilistic landscapes, providing a robust estimation strategy for lattice dynamics.

Recommended citation: K. Yui, H. Ueda, S. Katakami, J. Christiansen-Salameh, Z. Tian, J. Shiomi, and M. Okada, “Bayesian Estimation of Phonon Dispersion Relation from Thermal Diffuse Scattering,” *Journal of the Physical Society of Japan*, vol. 94, no. 8, p. 083601, 2025. doi:10.7566/JPSJ.94.083601
Download Paper

Destabilization of spin-Peierls phase via a charge-spin modulated Floquet state induced by intramolecular vibrational excitation

Published in Communications Physics, 2024

We demonstrate light-induced control of the spin-Peierls phase in a quasi-one-dimensional molecular solid, K-tetracyanoquinodimethane (TCNQ).
Using phase-locked mid-infrared pulses to excite intramolecular vibrations, we observed charge–spin modulated Floquet states that destabilize the spin-Peierls dimerization.
Time-resolved reflectivity measurements revealed high-frequency oscillations associated with electron- and spin-density modulations synchronized with the vibrational mode.
These results establish intramolecular vibrational excitation as an effective approach for Floquet engineering in molecular solids.

Recommended citation: D. Sakai, T. Yamakawa, H. Ueda, R. Ikeda, T. Miyamoto, and H. Okamoto, “Destabilization of spin-Peierls phase via a charge-spin modulated Floquet state induced by intramolecular vibrational excitation,” *Communications Physics*, vol. 7, no. 1, p. 40, 2024. doi:10.1038/s42005-024-01524-w
Download Paper

Conference Papers

Three-dimensional Deconvolution for Large-angle Illumination ADF-STEM Depth Sectioning

Published in Microscopy and Microanalysis (M&M) 2025, 2025

We propose a three-dimensional deconvolution algorithm for large-angle illumination ADF-STEM depth sectioning, enabling improved depth resolution in atomic-scale imaging.
The method is based on Vector Approximate Message Passing (VAMP), a Bayesian inference algorithm that incorporates prior knowledge of the reconstructed image.
Applied to simulated datasets of Ce-doped w-AlN, the approach achieves sharper localization of dopant atoms along the depth axis compared to conventional methods, demonstrating its effectiveness for 3D defect characterization in crystalline materials.

Recommended citation: T. Kusumi, H. Ueda, T. Futazuka, M. Hanai, S. Katakami, K. Kawahara, R. Ishikawa, N. Shibata, and M. Okada, “Three-dimensional Deconvolution for Large-angle Illumination ADF-STEM Depth Sectioning,” *Microscopy and Microanalysis*, vol. 31, suppl. 1, ozaf048.712, July 2025. doi:10.1093/mam/ozaf048.712
Download Paper

Stochastic Vector Approximate Message Passing with Applications to Phase Retrieval

Published in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025

We propose a stochastic extension of Vector Approximate Message Passing (VAMP) for large-scale Bayesian inverse problems.
The algorithm enables efficient uncertainty quantification and improved convergence in phase retrieval tasks under measurement noise.
Experiments demonstrate that the proposed stochastic VAMP method achieves robust reconstruction and faster convergence than deterministic baselines.

Recommended citation: H. Ueda, S. Katakami, and M. Okada, “Stochastic Vector Approximate Message Passing with Applications to Phase Retrieval,” *Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing (ICASSP)*, Hyderabad, India, pp. 1–5, 2025. doi:10.1109/ICASSP49660.2025.10888482
Download Paper

Hajime Ueda