Kerri Cahoy’s research while affiliated with Massachusetts Institute of Technology and other places

Atmospheric rivers (ARs) are long filaments that transport large amounts of water vapor from the Tropics to mid- and high latitudes. They are directly related to heavy precipitation and extreme weather leading to flooding and mud slides. Accurate identification of AR structures over the ocean is important to improve the forecast of their landfall location and timing. GNSS radio occultation (RO) is a space-based technique that can measure meteorological variables with high vertical resolution. While RO can observe structures like ARs in individual RO profiles, RO observations have non-uniform and sparse spatial and temporal sampling, so it is not yet possible to fully characterize AR morphology using RO alone. In this work, we use previous research in which we applied machine learning (ML) to enhance the spatial and temporal resolution of RO observations. Here, we train neural networks (NNs) to map RO observations and help resolve ARs. Analyses using existing RO data, such as from the COSMIC-2 mission, showed that the sampling density is insufficient to resolve and geo-locate ARs. Adding observations from the other available missions (for example METOP) improved matters, but was still insufficient to reliably reconstruct AR structure. We undertake a study to determine how many LEO RO satellites would be needed to quantify the structure, location, and timing of ARs. We simulate RO observations as would be obtained with Walker constellations of 12, 24, 36, 48 and 60 LEO RO satellites. First, we investigate possible constellations for proper AR monitoring. We aim for constellations that lead to hourly RO counts that change as little as possible during the AR (up to several days). This allows us to resolve ARs with similar accuracy during the scenario. We conclude that 3 or 6 orbital planes and inclinations between 85° and 90° perform best. Second, we make use of 12-h forecasts of the European Centre for Medium-range Weather Forecasts (ECMWF) system to interpolate the forecasts to the simulated RO constellation sampling coordinates. Third, we use the ECMWF-based RO observations to train ML models and map them to the ECMWF grid. We compare ML-mapped RO sampled grids to ECMWF products in a closed-loop validation. Initially, we map RO refractivity at 2 km geopotential height, where small-scale structures related to water vapor are visible. We find that at least 36 RO satellites are needed to characterize the morphology of ARs in the Pacific basin with useful precision and accuracy (from the ML produced maps). Then, we use a framework with two consecutive NNs to map column-integrated water vapor (IWV) from profiles of RO. The first NN maps the refractivity into IWV, and the second NN maps the IWV spatially. In this case, we find that a constellation of 48 satellites is needed to continuously map IWV fields accurately and thus reconstruct the morphology of ARs with useful precision and accuracy. Finally, when using RO, we find that mapping refractivity into IWV is less accurate over land than over oceans. To further improve the AR mapping over land, we made use of IWV from ground-based (GB) GNSS. The significantly higher spatial and temporal resolutions of GB data compared to RO lead to much improved IWV fields and thus AR path and shape over land.

Maintaining wavefront stability while directly imaging exoplanets over long exposure times is an ongoing problem in the field of high-contrast imaging. Robust and efficient high-order wavefront sensing and control systems are required for maintaining wavefront stability to counteract mechanical and thermal instabilities. Dark zone maintenance (DZM) has been proposed to address quasi-static optical aberrations and maintain high levels of contrast for coronagraphic space telescopes. To further experimentally test this approach for future missions, such as the Habitable Worlds Observatory, this paper quantifies the differences between the theoretical closed-loop contrast bounds and DZM performance on the High-contrast Imager for Complex Aperture Telescopes(HiCAT) testbed. The quantification of DZM is achieved by traversing important parameters of the system, specifically the total direct photon rate entering the aperture of the instrument, ranging from $1.85 \times 10^6$ to $1.85 \times 10^8$ photons per second, and the wavefront error drift rate, ranging from $\sigma_{drift}$ = 0.3 - 3 $nm/\sqrt{iteration}$, injected via the deformable mirror actuators. This is tested on the HiCAT testbed by injecting random walk drifts using two Boston Micromachines kilo deformable mirrors (DMs). The parameter scan is run on the HiCAT simulator and the HiCAT testbed where the corresponding results are compared to the model-based theoretical contrast bounds to analyze discrepancies. The results indicate an approximate one and a half order of magnitude difference between the theoretical bounds and testbed results.

Laser communications (lasercom) can enable more efficient and higher bandwidth communications than conventional radio frequency (RF) systems, but requires more sophisticated pointing and tracking (PAT) systems to acquire and maintain links. Liquid lens arrays can provide compact, nonmechanical beam steering as an alternative to fast-steering mirrors and mechanical gimbals. An array of two liquid lenses offset in perpendicular axes along with a third on-axis lens in the array are used for beam steering and divergence control, respectively. The Miniature Optical Steered Antenna for Intersatellite Communications (MOSAIC) project applies liquid lens technology to create a transceiver for laser communications on spacecraft to enable wide field-of-view communications. This work provides analytical models of beam steering in order to inform subsystem sizing, and uses simulation studies along with previous work on space environment evaluation of liquid lenses to produce representative link budgets for a liquid lens based lasercom transceiver. A 25 Mbps link with 4 W transmit power at 1550 nm (optical C band) and 16-ary pulse position modulation (16-PPM) can be maintained up to 175 km separation with 3 dB margin, using larger pressure-actuated liquid lenses from Optotune arranged for hemispherical steering, potentially allowing for high speed optical links between formation flying swarms for applications such as interferometry.

Global Navigation Satellite System (GNSS) radio occultation (RO) is a space-based remote sensing technique that measures the bending angle of GNSS signals as they traverse the Earth's atmosphere. Profiles of the microwave index of refraction can be calculated from the bending angles. High accuracy, long-term stability, and all-weather capability make this technique attractive to meteorologists and climatologists. Meteorologists routinely assimilate RO observations into numerical weather models. RO-based climatologies, however, are complicated to construct as their sampling densities are highly non-uniform and too sparse to resolve synoptic variability in the atmosphere. In this work, we investigate the potential of machine learning (ML) to construct RO climatologies and compare the results of an ML construction with Bayesian interpolation (BI), a state-of-the-art method to generate maps of RO products. We develop a feed-forward neural network applied to Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) RO observations and evaluate the performance of BI and ML by analysis of residuals when applied to test data. We also simulate data taken from the atmospheric analyses produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) in order to test the resolving power of BI and ML. Atmospheric temperature, pressure, and water vapor are used to calculate microwave refractivity at 2, 3, 5, 8, 15, and 20 km in geopotential height, with each level representing a different dynamical regime of the atmosphere. The simulated data are the values of microwave refractivity produced by ECMWF at the geolocations of the COSMIC-2 RO constellation, which fall equatorward of 46° in latitude. The maps of refractivity produced using the neural networks better match the true maps produced by ECMWF than maps using BI. The best results are obtained when fusing BI and ML, specifically when applying ML to the post-fit residuals of BI. At the six iso-heights, we obtain post-fit residuals of 10.9, 9.1, 5.3, 1.6, 0.6, and 0.3 N units for BI and 8.7, 6.6, 3.6, 1.1, 0.3, and 0.2 N units for the fused BI&ML. These results are independent of season. The BI&ML method improves the effective horizontal resolution of the posterior longitude–latitude refractivity maps. By projecting the original and the inferred maps at 2 km in iso-height onto spherical harmonics, we find that the BI-only technique can resolve refractivity in the horizontal up to spherical harmonic degree 8, while BI&ML can resolve maps of refractivity using the same input data up to spherical harmonic degree 14.

Epsilon Eridani is one of the first debris disk systems detected by the Infrared Astronomical Satellite. However, the system has thus far eluded detection in scattered light with no components having been directly imaged. Its similarity to a relatively young solar system combined with its proximity makes it an excellent candidate to further our understanding of planetary system evolution. We present a set of coronagraphic images taken using the Space Telescope Imaging Spectrograph coronagraph on the Hubble Space Telescope at a small inner working angle to detect a predicted warm inner debris disk inside 1″. We used three different postprocessing approaches—nonnegative matrix factorization (NMF), Karhunen–Loève Image Processing (KLIP), and classical reference differential imaging, to best optimize reference star subtraction—and find that NMF performed the best overall while KLIP produced the absolute best contrast inside 1″. We present limits on scattered light from warm dust, with constraints on surface brightness at 6 mJy as ⁻² at our inner working angle of 0.″6. We also place a constraint of 0.5 mJy as ⁻² outside 1″, which gives us an upper limit on the brightness for outer disks and substellar companions. Finally, we calculated an upper limit on the dust albedo at ω < 0.487.

Laser communications (lasercom) can enable more efficient and higher bandwidth communications than conventional radio frequency (RF) systems, but requires more sophisticated pointing and tracking (PAT) systems to acquire and maintain links. Liquid lens arrays can provide compact, nonmechanical beam steering as an alternative to fast-steering mirrors and mechanical gimbals. An array of two liquid lenses offset in perpendicular axes along with a third on-axis lens in the array are used for beam steering and divergence control, respectively. The Miniature Optical Steered Antenna for Intersatellite Communications (MOSAIC) project applies liquid lens technology to create a transceiver for laser communications on spacecraft to enable wide field-of-view communications. This work provides analytical models of beam steering in order to inform subsystem sizing, and uses simulation studies along with previous work on space environment evaluation of liquid lenses to produce representative link budgets for a liquid lens based lasercom transceiver. A 25 Mbps link with 4 W transmit power at 1550 nm (optical C band) and 16-ary pulse position modulation (16-PPM) can be maintained up to 300 km separation with 3 dB margin, using larger pressure-actuated liquid lenses from Optotune arranged for hemispherical steering.

Laser communications (lasercom) can enable more efficient and higher bandwidth communications than conventional radio frequency (RF) systems, but requires more sophisticated pointing and tracking (PAT) systems to acquire and maintain links. Liquid lens arrays can provide compact, nonmechanical beam steering as an alternative to fast-steering mirrors and mechanical gimbals. An array of two liquid lenses offset in perpendicular axes along with a third on-axis lens in the array are used for beam steering and divergence control, respectively. The Miniature Optical Steered Antenna for Intersatellite Communications (MOSAIC) project applies liquid lens technology to create a transceiver for laser communications on spacecraft to enable wide field-of-view communications. This work provides analytical models of beam steering in order to inform subsystem sizing, and uses simulation studies along with previous work on space environment evaluation of liquid lenses to produce representative link budgets for a liquid lens based lasercom transceiver. A 25 Mbps link with 4 W transmit power at 1550 nm (optical C band) and 16-ary pulse position modulation (16-PPM) can be maintained up to 300 km separation with 3 dB margin, using larger pressure-actuated liquid lenses from Optotune arranged for hemispherical steering.