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We consider the problem of trajectory planning for optimal relative orbit determination in the cislunar environment. The recent interest in cislunar space has created a need to develop autonomous tracking technologies that can maintain situational awareness of this dynamically complex regime. Optical sensors provide an ideal observation platform because of their low cost and versatility in tracking both cooperative and non-cooperative space objects. The estimation performance of an optical observer can be significantly enhanced through manuevering. This work develops a trajectory planning tool, compatible with low-thrust propulsion, for tracking one or multiple targets operating in proximity to the observer. We formulate an objective function that is a convex combination of the mutual information between target states and measurements, and the low-thrust control effort. The subsequent optimal control problem is solved via direct collocation using the successive convexification algorithm, which, we argue, is well suited for a potential onboard trajectory planning application. We demonstrate the tool for several relevant scenarios with one and multiple targets operating around periodic orbits in the circular restricted three-body problem. A sequential estimator's performance is evaluated using the Cramer-Rao lower bound and, compared to a purely passive observer, we show that optimizing the observer's trajectory can decrease this bound by up to several orders of magnitude within a planning window. This investigation provides an initial proof-of-concept to future onboard planning technologies for relative tracking in the cislunar domain. 

We present a novel machine-learning approach for detecting faint point sources in high-contrast adaptive optics (AO) imaging data sets. The most widely used algorithms for primary subtraction aim to decouple bright stellar speckle noise from planetary signatures by subtracting an approximation of the temporally evolving stellar noise from each frame in an imaging sequence. Our approach aims to improve the stellar noise approximation and increase the planet detection sensitivity by leveraging deep learning in a novel direct imaging post-processing algorithm. We show that a convolutional autoencoder neural network, trained on an extensive reference library of real imaging sequences, accurately reconstructs the stellar speckle noise at the location of a potential planet signal. This tool is used in a post-processing algorithm we call Direct Exoplanet Detection with Convolutional Image Reconstruction, orConStruct. The reliability and sensitivity ofConStructare assessed using real Keck/NIRC2 angular differential imaging data sets. Of the 30 unique point sources we examine,ConStructyields a higher signal-to-noise ratio than traditional principal component analysis-based processing for 67% of the cases and improves the relative contrast by up to a factor of 2.6. This work demonstrates the value and potential of deep learning to take advantage of a diverse reference library of point-spread function realizations to improve direct imaging post-processing.ConStructand its future improvements may be particularly useful as tools for post-processing high-contrast images from JWST and extreme AO instruments, both for the current generation and those being designed for the upcoming 30 m class telescopes.

 

We present the direct-imaging discovery of a giant planet orbiting the young star AF Lep, a 1.2M_⊙member of the 24 ± 3 MyrβPic moving group. AF Lep was observed as part of our ongoing high-contrast imaging program targeting stars with astrometric accelerations between Hipparcos and Gaia that indicate the presence of substellar companions. Keck/NIRC2 observations in$L\prime$with the vector vortex coronagraph reveal a point source, AF Lep b, at ≈340 mas, which exhibits orbital motion at the 6σlevel over the course of 13 months. A joint orbit fit yields precise constraints on the planet’s dynamical mass of${3.2}_{-0.6}^{+0.7}$M_Jup, semimajor axis of${8.4}_{-1.3}^{+1.1}$au, and eccentricity of${0.24}_{-0.15}^{+0.27}$. AF Lep hosts a debris disk located at ∼50 au, but it is unlikely to be sculpted by AF Lep b, implying there may be additional planets in the system at wider separations. The stellar inclination (i_*=${54}_{-9}^{+11}°$) and orbital inclination (i_o=${50}_{-12}^{+9}°$) are in good agreement, which is consistent with the system having spin–orbit alignment. AF Lep b is the lowest-mass imaged planet with a dynamical mass measurement and highlights the promise of using astrometric accelerations as a tool to find and characterize long-period planets.

 

Benchmark brown dwarf companions with well-determined ages and model-independent masses are powerful tools to test substellar evolutionary models and probe the formation of giant planets and brown dwarfs. Here, we report the independent discovery of HIP 21152 B, the first imaged brown dwarf companion in the Hyades, and conduct a comprehensive orbital and atmospheric characterization of the system. HIP 21152 was targeted in an ongoing high-contrast imaging campaign of stars exhibiting proper-motion changes between Hipparcos and Gaia, and was also recently identified by Bonavita et al. (2022) and Kuzuhara et al. (2022). Our Keck/NIRC2 and SCExAO/CHARIS imaging of HIP 21152 revealed a comoving companion at a separation of 0.″37 (16 au). We perform a joint orbit fit of all available relative astrometry and radial velocities together with the Hipparcos-Gaia proper motions, yielding a dynamical mass of${24}_{-4}^{+6}{M}_{\mathrm{Jup}}$, which is 1–2σlower than evolutionary model predictions. Hybrid grids that include the evolution of cloud properties best reproduce the dynamical mass. We also identify a comoving wide-separation (1837″ or 7.9 × 10⁴au) early-L dwarf with an inferred mass near the hydrogen-burning limit. Finally, we analyze the spectra and photometry of HIP 21152 B using the Saumon & Marley (2008) atmospheric models and a suite of retrievals. The best-fit grid-based models havef_sed= 2, indicating the presence of clouds,T_eff= 1400 K, and$\log g=4.5\mathrm{dex}$. These results are consistent with the object’s spectral type of T0 ± 1. As the first benchmark brown dwarf companion in the Hyades, HIP 21152 B joins the small but growing number of substellar companions with well-determined ages and dynamical masses.