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Abstract Coronagraphs allow for faint off-axis exoplanets to be observed, but are limited to angular separations greater than a few beam widths. Accessing closer-in separations would greatly increase the expected number of detectable planets, which scales inversely with the inner working angle. The vortex fiber nuller (VFN) is an instrument concept designed to characterize exoplanets within a single beam width. It requires few optical elements and is compatible with many coronagraph designs as a complementary characterization tool. However, the peak throughput for planet light is limited to about 20%, and the measurement places poor constraints on the planet location and flux ratio. We propose to augment the VFN design by replacing its single-mode fiber with a six-port mode-selective photonic lantern, retaining the original functionality while providing several additional ports that reject starlight but couple planet light. We show that the photonic lantern can also be used as a nuller without a vortex. We present monochromatic simulations characterizing the response of the photonic lantern nuller (PLN) to astrophysical signals and wavefront errors, and show that combining exoplanet flux from the nulled ports significantly increases the overall throughput of the instrument. We show using synthetically generated data that the PLN detects exoplanets more effectively than the VFN. Furthermore, with the PLN, the exoplanet can be partially localized, and its flux ratio constrained. The PLN has the potential to be a powerful characterization tool complementary to traditional coronagraphs in future high-contrast instruments. 

Inner working angle is a key parameter for enabling scientific discovery in direct exoplanet imaging and characterization. Approaches to improving the inner working angle to reach the diffraction limit center on the sensing and control of wavefront errors, starlight suppression via coronagraphy, and differential techniques applied in post-processing. These approaches are ultimately limited by the shot noise of the residual starlight, placing a premium on the ability of the adaptive optics system to sense and control wavefront errors so that the coronagraph can effectively suppress starlight reaching the science focal plane. Photonic lanterns are attractive for use in the science focal plane because of their ability to spatially filter light using a finite basis of accepted modes and effectively couple the results to diffraction-limited spectrometers, providing a compact and cost-effective means to implement post-processing based on spectral diversity. We aim to characterize the ability of photonic lanterns to serve as focal-plane wavefront sensors, allowing the adaptive optics system to control aberrations affecting the science focal plane and reject additional stellar photon noise. By serving as focal-plane wavefront sensors, photonic lanterns can improve sensitivity to exoplanets through both direct and coronagraphic observations. We have studied the sensing capabilities of photonic lanterns in the linear and quadratic regimes with analytical and numerical treatments for different lantern geometries (including non-mode-selective, mode-selective, and hybrid geometries) as a function of port number. In this presentation we report on the sensitivity of such lanterns and comment on the relative suitability and sensitivity impacts of different lantern geometries for focal-plane wavefront sensing. 

A focal plane wavefront sensor offers major advantages to adaptive optics, including removal of non-commonpath error and providing sensitivity to blind modes (such as petalling). But simply using the observed point spread function (PSF) is not sufficient for wavefront correction, as only the intensity, not phase, is measured. Here we demonstrate the use of a multimode fiber mode converter (photonic lantern) to directly measure the wavefront phase and amplitude at the focal plane. Starlight is injected into a multimode fiber at the image plane, with the combination of modes excited within the fiber a function of the phase and amplitude of the incident wavefront. The fiber undergoes an adiabatic transition into a set of multiple, single-mode outputs, such that the distribution of intensities between them encodes the incident wavefront. The mapping (which may be strongly non-linear) between spatial modes in the PSF and the outputs is stable but must be learned. This is done by a deep neural network, trained by applying random combinations of spatial modes to the deformable mirror. Once trained, the neural network can instantaneously predict the incident wavefront for any set of output intensities. We demonstrate the successful reconstruction of wavefronts produced in the laboratory with low-wind-effect, and an on-sky demonstration of reconstruction of low-order modes consistent with those measured by the existing pyramid wavefront sensor, using SCExAO observations at the Subaru Telescope.