Adam K Taras | Searcharxiv

arXiv2026

Seidr update: photonic 'black magic' for high-contrast interferometry using kernel-nulling and photonic lanterns

Seidr is a new interferometric beam combiner within the Asgard Suite, utilizing infrastructure common to the BIFROST instrument at the Very Large Telescope Interferometer. Seidr combines hybrid mode-selective photonic lantern injection modules with a kernel-nulling photonic chip backend to enable deep H-band nulling for high-contrast studies of exoplanets, exomoons, and circumstellar dust. This instrument update summarizes Seidr's current design maturity and recent simulations of the point source - to - lantern outputs. We also outline progress on our neural network-based wavefront estimation scheme, which uses the photonic lantern outputs to sense phase fluctuations, designed to feed back to Baldr's deformable mirror, and improve nuller light injection.

physics.optics↗

arXiv2026

Overcoming the low signal-to-noise problem for hybrid mode-selective photonic lantern-based wavefront correction using machine learning

Hybrid mode-selective photonic lanterns transform an input complex point-spread function into several single-mode outputs, where a selected core feeds the fundamental mode to a photonic science instrument, while the remaining cores are used for wavefront sensing in a closed-loop adaptive optics system. A neural network maps the intensities of the wavefront sensing cores to an estimated wavefront correction, which is applied to an upstream deformable mirror. However, there exists a trade between maximizing the amount of light reserved for the photonic instrument and the reduced signal-to-noise ratios for the wavefront sensing cores. We explore wavefront correction for the Seidr instrument, a part of the Asgard Suite for the Very Large Telescope Interferometer. We evaluate different neural network architectures, comparing wavefront estimation performance for different wavefront error types, as a first step toward addressing the signal-to-noise trade-off. Results show transformer neural networks as a promising solution for temporal photonic lantern-based wavefront estimation.

physics.optics↗