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NASA NTRS2020

Synergistic Use of Hyperspectral UV-Visible OMI and Broadband Meteorological Imager MODIS Data for a Merged Aerosol Product

The retrieval of optimal aerosol datasets by the synergistic use of hyperspectral ultraviolet(UV)–visible and broadband meteorological imager (MI) techniques was investigated. The Aura Ozone Monitoring Instrument (OMI) Level 1B (L1B) was used as a proxy for hyperspectral UV–visible instrument data to which the Geostationary Environment Monitoring Spectrometer (GEMS) aerosol algorithm was applied. Moderate-Resolution Imaging Spectroradiometer (MODIS) L1B and dark target aerosol Level 2 (L2) data were used with a broadband MI to take advantage of the consistent time gap between the MODIS and the OMI. First, the use of cloud mask information from the MI infrared (IR) channel was tested for synergy. High-spatial-resolution and IR channels of the MI helped mask cirrus and sub-pixel cloud contamination of GEMS aerosol, as clearly seen in aerosol optical depth (AOD) validation with Aerosol Robotic Network (AERONET) data. Second, dust aerosols were distinguished in the GEMS aerosol-type classification algorithm by calculating the total dust confidence index (TDCI) from MODIS L1B IR channels. Statistical analysis indicates that the Probability of Correct Detection (POCD) between the forward and inversion aerosol dust models (DS) was increased from 72% to 94% by use of the TDCI for GEMS aerosol-type classification, and updated aerosol types were then applied to the GEMS algorithm. Use of the TDCI for DS type classification in the GEMS retrieval procedure gave improved single-scattering albedo (SSA) values for absorbing fine pollution particles (BC) and DS aerosols. Aerosol layer height (ALH) retrieved from GEMS was compared with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data, which provides high-resolution vertical aerosol profile information. The CALIOP ALH was calculated from total attenuated backscatter data at 1064 nm, which is identical to the definition of GEMS ALH. Application of the TDCI value reduced the median bias of GEMS ALH data slightly. The GEMS ALH bias approximates zero, especially for GEMS AOD values of>~0.4 and GEMS SSA values of<~0.95.Finally, the AOD products from the GEMS algorithm and MI were used in aerosol merging with the maximum-likelihood estimation method, based on a weighting factor derived from the standard deviation of the original AOD products. With the advantage of the UV–visible channel in retrieving aerosol properties over bright surfaces, the combined AOD products demonstrated better spatial data availability than the original AOD products, with comparable accuracy. Furthermore, pixel-level error analysis of GEMS AOD data indicates improvement through MI synergy.

aerosol↗

NASA NTRS2016

WFIRST/AFTA coronograph contrast performance sensitivity studies: simulation versus experiment

The WFIRST/AFTA 2.4 m space telescope currently under study includes a stellar coronagraph for the imaging and the spectral characterization of extrasolar planets. The coronagraph employs sequential deformable mirrors to compensate for phase and amplitude errors. Using the optical model of an Occulting Mask Coronagraph (OMC) testbed at the Jet Propulsion Laboratory, we have investigated through modeling and simulations the sensitivity of dark hole contrast in a Hybrid Lyot Coronagraph (HLC) for several error cases, including lateral and longitudinal translation errors of two deformable mirrors, DM1 and DM2, lateral and/or longitudinal translation errors of an occulting mask and a Lyot-Stop, clocking errors of DM1 and DM2, and the mismatch errors between the testbed and the model sensitivity matrices. We also investigated the effects of a control parameter, namely the actuator regularization factor, on the control efficiency and on the final contrast floor. We found several error cases which yield contrast results comparable to that observed on the HLC testbed. We present our findings in this paper.

Nemati, Bijan↗

NASA NTRS2017

Coronagraph Design Optimization for Segmented Aperture Telescopes

The goal of directly imaging Earth-like planets in the habitable zone of other stars has motivated the design of coronagraphs for use with large segmented aperture space telescopes. In order to achieve an optimal trade-o between planet light throughput and di racted starlight suppression, we consider coronagraphs comprised of a stage of phase control implemented with deformable mirrors (or other optical elements), pupil plane apodization masks (gray scale or complex valued), and focal plane masks (either amplitude only or complex-valued, including phase only such as the vector vortex coronagraph). The optimization of these optical elements, with the goal of achieving 10 or more orders of magnitude in the suppression of on-axis (starlight) di racted light, represents a challenging non-convex optimization problem with a nonlinear dependence on control degrees of freedom. We develop a new algorithmic approach to the design optimization problem, which we call the "Auxiliary Field Optimization" (AFO) algorithm. The central idea of the algorithm is to embed the original optimization problem, for either phase or amplitude (apodization) in various planes of the coronagraph, into a problem containing additional degrees of freedom, speci cally ctitious "auxiliary" electric elds which serve as targets to inform the variation of our phase or amplitude parameters leading to good feasible designs. We present the algorithm, discuss details of its numerical implementation, and prove convergence to local minima of the objective function (here taken to be the intensity of the on-axis source in a "dark hole" region in the science focal plane). Finally, we present results showing application of the algorithm to both unobscured o -axis and obscured on-axis segmented telescope aperture designs. The application of the AFO algorithm to the coronagraph design problem has produced solutions which are capable of directly imaging planets in the habitable zone, provided end-to-end telescope system stability requirements can be met. Ongoing work includes advances of the AFO algorithm reported here to design in additional robustness to a resolved star, and other phase or amplitude aberrations to be encountered in a real segmented aperture space telescope.

Redding, Dave↗

NASA NTRS2017

Dynamic Testbed Demonstration of WFIRST Coronagraph Low Order Wavefront Sensing and Control (LOWFS/C)

To maintain the required performance of WFIRST Coronagraph in a realistic space environment, a Low Order Wavefront Sensing and Control (LOWFS/C) subsystem is necessary. The LOWFS/C uses a Zernike wavefront sensor (ZWFS) with the phase shifting disk combined with the starlight rejecting occulting mask. For wavefront error corrections, WFIRST LOWFS/C uses a fast steering mirror (FSM) for line-of-sight (LoS) correction, a focusing mirror for focus drift correction, and one of the two deformable mirrors (DM) for other low order wavefront error (WFE) correction. As a part of technology development and demonstration for WFIRST Coronagraph, a dedicated Occulting Mask Coronagraph (OMC) testbed has been built and commissioned. With its configuration similar to the WFIRST flight coronagraph instrument the OMC testbed consists of two coronagraph modes, Shaped Pupil Coronagraph (SPC) and Hybrid Lyot Coronagraph (HLC), a low order wavefront sensor (LOWFS), and an optical telescope assembly (OTA) simulator which can generate realistic LoS drift and jitter as well as low order wavefront error that would be induced by the WFIRST telescope’s vibration and thermal changes. In this paper, we will introduce the concept of WFIRST LOWFS/C, describe the OMC testbed, and present the testbed results of LOWFS sensor performance. We will also present our recent results from the dynamic coronagraph tests in which we have demonstrated of using LOWFS/C to maintain the coronagraph contrast with the presence of WFIRST-like line-of-sight and low order wavefront disturbances.

Zhou, Hanying↗

NASA NTRS2018

WFIRST Low Order Wavefront Sensing and Control Testbed Performance under Flight Like Photon Flux

To maintain the required performance for the WFIRST Coronagraph Instrument (CGI) in a realistic space environment, a Low Order Wavefront Sensing and Control (LOWFS/C) subsystem is necessary. The WFIRST CGI LOWFS/C subsystem would use the Zernike wavefront sensor, which has the phase-shifting disk combined with the coronagraph’s focal plane mask, to sense the low-order wavefront drift and line-of-sight (LoS) error using the rejected starlight. The dynamic tests on JPL’s on the Occulting Mask Coronagraph (OMC) Testbed have demonstrated that LOWFS/C can maintain coronagraph contrast to better than 10-8 in presence of WFIRST-like line of sight and low order wavefront disturbances in both Shaped Pupil Coronagraph (SPC) and Hybrid Lyot Coronagraph (HLC) modes. However, the previous dynamic tests have been done using a bright source with photon flux equivalent to stellar magnitude of Mv = -3.5. The LOWFS/C technology development continues on the OMC testbed especially in evaluating and improving the LOWFS/C performance under the realistic photon flux that is equivalent to WFIRST Coronagraph target stars. Our recent testbed tests have demonstrated that the LOWFS/C can work cohesively with the stellar light suppression wavefront control, which brings broad band coronagraph contrast from 1x10-6 to 6x10-9, while LOWF/C is simultaneously suppressing the WFIRST like LoS and low order wavefront drift disturbances on a source that photon flux is equivalent to a Mv = 2 star. This demonstration mimics the CGI initial dark hole establish process on a bright reference star. We also demonstrated on the testbed that LOWFS/C can maintain the coronagraph contrast by suppressing the WFIRST like line-of-sight disturbances on a fainter Mv = 5 star. This mimics scenario of CGI science target observations. In this paper we will present the recent testbed results on LOWFS/C LoS loops and low order wavefront error correction loop performance on the flight like photon flux.

Truong, Tuan↗

NASA NTRS2019

The LUVOIR Extreme Coronagraph for Living Planetary Systems (ECLIPS) II. Performance Evaluation, Aberration Sensitivity Analysis and Exoplanet Detection Simulations

Future space missions such as the Large UV-Optical-Infrared Surveyor (LUVOIR) and the Habitable Exoplanet Observatory (HabEx) require coronagraphs with active wavefront control to suppress starlight to discover and characterize habitable exoplanets. The Extreme Coronagraph for Living Planetary Systems (ECLIPS) is the coronagraph instrument on the LUVOIR Surveyor mission concept, an 8–15m segmented telescope. ECLIPS is split into three channels: UV (200 to 400 nm), optical (400 nm to 850 nm), and NIR (850 nm to 2.0 microns), with each channel equipped with two deformable mirrors for wavefront control, a suite of coronagraph masks, a low-order/out-of-band wavefront sensor, and separate science imagers and spectrographs. The Apodized Pupil Lyot Coronagraph (APLC) and the Vector Vortex Coronagraph (VVC) are the baselined mask technologies for ECLIPS to enable the required 10 -10 contrast for observations in the habitable zones of nearby stars. Their performance depends on active wavefront sensing and control, as well as metrology subsystems to compensate for aberrations induced by segment errors (piston and tip/tilt, among others), secondary mirror misalignment, and global low-order wavefront errors. Here we present the latest results of the simulation of these effects for the two technologies and discuss the achieved contrast for exoplanet detection and characterization after closed-loop wavefront estimation and control algorithms have been applied. Finally, we show simulated observations using high-fidelity spatial and spectral input models of complete planetary systems generated with the Haystacks code framework.

Roser Juanola-Parramon↗

NASA NTRS2020

The TESS-Keck Survey. I. A Warm Sub-Saturn-mass Planet and a Caution about Stray Light in TESS Cameras

We report the detection of a Saturn-size exoplanet orbiting HD 332231 (TOI 1456) in light curves from the Transiting Exoplanet Survey Satellite (TESS). HD 332231—an F8 dwarf star with a V-band magnitude of 8.56—was observed by TESS in Sectors 14 and 15. We detect a single-transit event in the Sector 15 presearch data conditioning (PDC) light curve. We obtain spectroscopic follow-up observations of HD 332231 with the Automated Planet Finder, Keck I, and SONG telescopes. The orbital period we infer from radial velocity (RV) observations leads to the discovery of another transit in Sector 14 that was masked by PDC due to scattered light contamination. A joint analysis of the transit and RV data confirms the planetary nature of HD 332231 b, a Saturn-size (0.867 (+0.027,-0.025 R(J)), sub-Saturn-mass (0.244 ± 0.021M(J)) exoplanet on a 18.71 day circular orbit. The low surface gravity of HD 332231 b and the relatively low stellar flux it receives make it a compelling target for transmission spectroscopy. Also, the stellar obliquity is likely measurable via the Rossiter–McLaughlin effect, an exciting prospect given the 0.14 au orbital separation of HD 332231 b. The spectroscopic observations do not provide substantial evidence for any additional planets in the HD 332231 system, but continued RV monitoring is needed to further characterize this system. We also predict that the frequency and duration of masked data in the PDC light curves for TESS Sectors 14–16 could hide transits of some exoplanets with orbital periods between 10.5 and 17.5 days.

Paul A. Dalba↗

NASA NTRS2022

A Novel Machine Learning-Based Gap-Filling of Fine-Resolution Remotely Sensed Snow Cover Fraction Data By Combining Downscaling and Regression

Satellite-based remotely sensed observations of snow cover fraction (SCF) can have data gaps in spatially distributed coverage from sensor and orbital limitations. We mitigate these limitations in the example fine-resolution Moderate Resolution Imaging Spectroradiometer (MODIS) data by gap-filling using auxiliary 1-km datasets that either aid in downscaling from coarser-resolution (5 km) MODIS SCF wherever not fully covered by clouds, or else by themselves via regression wherever fully cloud covered. This study’s prototype predicts a 1-km version of the 500-m MOD10A1 SCF target. Due to noncollocatedness of spatial gaps even across input and auxiliary datasets, we consider a recent gap-agnostic advancement of partial convolution in computer vision for both training and predictive gap-filling. Partial convolution accommodates spatially consistent gaps across the input images, effectively implementing a two-dimensional masking. To overcome reduced usable data from noncollocated spatial gaps across inputs, we innovate a fully generalized three-dimensional masking in this partial convolution. This enables a valid output value at a pixel even if only a single valid input variable and its value exist in the neighborhood covered by the convolutional filter zone centered around that pixel. Thus, our gap-agnostic technique can use significantly more examples for training (∼67%) and prediction (∼100%), instead of only less than 10% for the previous partial convolution. We train an example simple three-layer legacy super-resolution convolutional neural network (SRCNN) to obtain downscaling and regression component performances that are better than baseline values of either climatology or MOD10C1 SCF as relevant. Our generalized partial convolution can enable multiple Earth science applications like downscaling, regression, classification, and segmentation that were hindered by data gaps.

Soni Yatheendradas↗

NASA NTRS2022

An Algorithm for Statistical Audibility Prediction (SAP) of an Arbitrary Signal in the Presence of Noise

A method for predicting the audibility of an arbitrary time-varying noise (signal) in the presence of masking noise has been developed. The statistical audibility prediction (SAP) method relies on the specific loudness, or loudness perceived through the individual auditory filters, for accurate statistical estimation of audibility vs. time. More recent development has focused on derivation and inclusion of frequency-dependent correction factors in SAP’s model to account for the ability to hear signals below the level of the masking noise. Audibility prediction vs. time is intuitive since it captures changes in audibility with time as it occurs, which is critical for the study of human response to noise. Concurrently time-frequency prediction of audibility may also provide valuable information about the root cause(s) for audibility useful for the design and operation of sources of noise. Empirical data, gathered under a three-alternative forced-choice (3AFC) test paradigm for low-frequency sound, has been used to examine the accuracy of SAP.

audibility↗

NASA NTRSDate not supplied

Habitability Assessments And Lessons-learned From 3-day And 11-day Enriched Oxygen Hypobaric Chamber Tests At NASA Johnson Space Center

INTRODUCTION: Decompression sickness (DCS) is a risk to the health and performance of astronauts and high-altitude aircrew. Tolerance to flammability, hypoxia, prebreathe duration, and DCS risk varies across different organizations, vehicles, suits, and destinations, necessitating a variety of DCS risk mitigation approaches. Existing models of altitude DCS risk are often insufficient to enable accurate risk-informed decisions during hardware development, mission planning, and flight operations. METHODS: NASA completed outfitting of a dedicated facility at Johnson Space Center to support testing of up to eight human subjects for multiple days in hypobaric and enriched oxygen atmospheres. The primary purpose of the testing capability is validation of DCS risk mitigation protocols for Artemis missions to the Moon; however, it will also support development and validation of a generalizable altitude DCS risk estimation tool. A 3-day and an 11-day prebreathe validation test were completed in 2022, each with 8 human subjects living at 56.5 kPa (8.2 psia), 34% O2, 66% N2, with 5 simulated EVAs performed on masks at 29.6 kPa (4.3 psi), 85% O2, 15% N2. Facility and organizational lessons-learned and process improvements were recorded during and following the tests, and subjective habitability ratings were recorded daily during the 11-day test. Hypoxia and DCS-related physiological and cognitive outcome measures were recorded during both tests and are reported in companion presentations. RESULTS & DISCUSSION: All subjects completed each of the tests. Primary habitability issues related to mask discomfort during simulated EVAs and poor sleep quality due to thin mattresses. Polybenzimidazole (PBI) clothing was worn by all subjects due to the increased fire risk and may be required for Artemis missions; clothing was found to be acceptable overall with the worst ratings being due to poor fit and inelasticity. Chamber O2 and CO2 sensor inconsistency was observed that did not result in test termination but required post-test follow-up. Forward plans include additional hypobaric testing and integration of existing and future physiological outcome data into an open-source Aerospace Estimation Tool for Hypobaric Exposure Risk (AETHER). NASA is also working to make the testing capability available to commercial companies.

Andrew F J Abercromby↗

NASA NTRSDate not supplied

Evolution of Hardware and Philosophy of Emergency Response Actions on the International Space Station and Future Spacecrafts

Human spaceflight is dangerous for numerous reasons. This ranges from the dynamic environment of launching on a rocket, flying in space among the thousands and thousands pieces of space debris, to the hazards of re-entry & landing, as well as being surrounded by vehicle systems containing hazardous materials or gasses. In-flight emergencies fall into four categories: Rapid Depressurization, Fire, Toxic Spill, and Medical emergency. This paper will address the first three, which fall under the responsibility of the Environmental Control and Life Support (ECLS) Systems flight control and engineering teams. It will review the evolution of the International Space Station’s emergency response philosophy, procedures, training, and equipment changes over the years. The ISS emergency equipment has evolved over the last two decades of operations in many ways, but in some it has remained the same. The core actions the flight crew takes to ensure team safety, personal safety, vehicle safety, and equipment safety has not changed. However, the equipment and capabilities provided to them have. From early days of minimal capability when the ISS consisted of a few modules, to today’s 30,000 ft^3 vehicle with over a dozen isolatable segments. From use of Russian gas masks to positive pressure O2 masks, to the development of respirators. From a lack of procedures for a deadly ammonia leak scenario to a memorized response utilizing numerous atmosphere measurement systems. This paper will review all these various areas that fall under the umbrella of “on-board emergencies”. In addition, the comparison to the planned emergency operations on the Orion vehicle will be reviewed. The Orion vehicle differs from the ISS in that it has no isolatable volume, being approximately 2% the size of ISS, as well as not having a quick return to earth capability.

Emergency↗

NASA NTRSDate not supplied

WET Water Resources: A Google Earth Engine Python API Tool to Automate Wetland Extent Mapping Using Radar Satellite Sensors for Wetland Management and Monitoring

Wetland ecosystems are annually or seasonally wet transition zones between land and water. They provide a range of ecosystem services such as water filtration, flood mitigation, and carbon sequestration, as well as hosting biodiversity hotspots. Although they fulfill fundamental physical and natural processes, wetland extent and health are threatened by anthropogenic influences related to urbanization, population increase, pollution, and climate change. Recognizing the need to quantitatively monitor changes in these recently threatened ecosystems in a timely and cost-effective way, we developed a Google Earth Engine (GEE) Python API tool for automated wetland extent mapping using optical and radar satellite sensors that can be applied globally. The tool will significantly improve wetland change analysis and monitoring as the optical and SAR data proves high resolution (5-10 m) imagery, and SAR data is unaffected by cloud cover and light availability (day vs. night), which are common limitations for other remotely sensed sensors. The tool utilizes Copernicus Sentinel-1 C-band and NISAR L-band synthetic aperture radar (SAR) imagery. During image preprocessing, we applied a MODIS snow mask product to mask global snow coverage, which would affect land classification sensitivity. Calibration and validation were conducted through a historical change and sensitivity analysis of the Sudd watershed located in central Sudan. The tool was the first of its kind, as it enables NISAR data processing through an open-source GEE repository, further expanding and improving the utility of NASA Earth observations and contributing to NASA Open Science initiatives. We anticipate the tool will be used by researchers and practitioners interested in wetland monitoring and management..

Lori Berberian↗

NASA NTRS2021

Lunar Terrain Coverage Analysis Data Delivery Workflow

In this work, we are developing a lunar terrain database to enable fast rendering of sun illumination and earth visibility for a proposed coverage analysis tool. This development will advance lunar mission design and formulation for current and future communications architectures, and will aid in lunar surface mission planning and communications/navigation operations. Our effort can be described in three steps: (1) we parallelize a brute force algorithm, which computes elevation masks from laser altimetry data acquired by the Lunar Reconnaissance Orbiter’s (LRO) Lunar Orbiter Laser Altimeter (LOLA); (2) we investigate parallel I/O methods to store terrain mask information from step (1) into a parallel file system; and (3) we finally deliver data to the terrain coverage analysis tool.

Michels, Dominik↗

NASA NTRS2021

Results From The Laboratory Demonstration Of A PIAACMC Coronagraph With A Segmented Aperture

The phase-induced amplitude apodization complex mask coronagraph (PIAACMC) provides high throughput and small inner working angle with little loss in image quality. Coronagraph compatibility with segmented apertures is essential for the success of habitable planet characterization with future large aperture space telescopes, such as the Large UV/Optical/Infrared (LUVOIR) and HabEx telescope mission concepts. The PIAACMC is compatible with such segmented telescope apertures with little loss of performance. We report the contrast and other performance results of a PIAACMC coronagraph with a LUVOIR-like pupil mask assembled and tested in a vacuum chamber at the JPL high contrast imaging testbed (HCIT). The goals of the demonstration were to achieve 1e-9 mean contrast over a semi-annular field of view from 2 λ/D to 8 λ/D, first with monochromatic light at 650nm, and then over a 10% spectral bandwidth. In addition, the measurement of jitter and its effect on PIAACMC performance will be discussed. As the success of electric field conjugation (EFC) to achieve best contrast on the testbed is dependent upon a diffraction model of the coronagraph, we will also discuss variations of the testbed and its diffraction model with the PIAACMC design, including suspected sources of knowledge error in the EFC diffraction model.

Wilson, Daniel↗

NASA NTRS2021

Optial Experiments and Model Validation of Perturbed Starshade Designs

Starshades are a leading technology to enable the direct detection and spectroscopic characterization of Earth- like exoplanets. Critical starshade technologies are currently being advanced through the S5 Project and at the Princeton starshade testbed. We report on the status of Milestone 2 of the S5 Project, optical model validation. We present results from optical experiments of starshades with intentional perturbations built into their design. These perturbations are representative of the type of perturbations possible in a flight design and serve as points of validation for dffraction models and error budgets. We show experimental results for two perturbed shapes, a mask with all petals shifted radially outward by 5 um and a mask with shallow sine waves built into two petals. We compare these data to outputs of the optical model and demonstrate better than 25% agreement. We also present images taken in crossed polarized light and use those data to constrain physical parameters of the optical edge. Bringing in previously obtained results for other perturbed shapes, we show an agreement between experiment and model of better than 25% and argue that this satisfies the Milestone 2 criteria.

Galvin, Michael↗

NASA NTRS2023

Aurora Detection From Nighttime Lights for Earth and Space Science Applications

This research leverages data from the Day/Night Band (DNB) of the Visible Infrared Imaging Radiometer (VIIRS) instrument onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. We demonstrate the value of mining the VIIRS DNB for aurora and describe our use of unsupervised machine learning to create a binary mask for aurora occurrence. This mask can be used to flag aurora-contaminated observations for NASA's nighttime lights products for Earth science applications. The identification of auroral regions can also be used for Space Weather applications, for example, for comparison with aurora forecast model and with other satellite- or ground-based aurora observations. The DNB is a broadband channel that is sensitive to wavelengths from 500 to 900 nm, which covers most of the visible light spectrum, and as the name implies, captures light even at night with a sensitivity at the nanowatt level. This band is suitable for aurora observations since the light emitted by the aurora tends to be dominated by emissions from atomic oxygen, resulting in a greenish glow at a wavelength of 557.7 nm, especially at an altitude of 110 km. This study compares the global nighttime derived aurora regions for 17 and 18 March with the NOAA Space Weather Prediction Center's (SWPC) probability product for the St. Patrick's Day geomagnetic storm in 2015. VIIRS sensors are slated to be added to the next generation of polar-orbiting operational satellites. Our novel automated approach to aurora identification opens up an efficient way to leverage this unique data source.

Aurora↗

NASA NTRS2022

Modeling and Performance Analysis of the LUVOIR Coronagraph Instrument

Future space missions such as the Large UV/Optical/Infrared Surveyor (LUVOIR) and the Habitable Exoplanet Observatory, when equipped with coronagraphs with active wavefront control to suppress starlight, will allow the discovery and characterization of habitable exoplanets. The Extreme Coronagraph for Living Planetary Systems (ECLIPS) is the coronagraph instrument on the LUVOIR Surveyor mission concept, an 8- to 15-m segmented telescope. ECLIPS is split into three channels, namely, UV (200 to 400 nm), optical (400 to 850 nm), and near IR (850 nm to 2 μm), with each channel equipped with two deformable mirrors for wavefront control, a suite of coronagraph masks, a low-order/out-of-band wavefront sensor, and separate science imagers and spectrographs. The apodized pupil Lyot coronagraph and the vector vortex coronagraph are the baselined mask technologies for ECLIPS to enable the required 10−10 contrast for observations in the habitable zones of nearby stars for LUVOIR-A (15-m telescope) and LUVOIR-B (8-m telescope), respectively. Their performance depends on active wavefront sensing and control, as well as metrology subsystems to compensate for aberrations induced by segment errors (e.g., piston and tip/tilt), secondary mirror misalignment, and global low-order wavefront errors. Here, we present the latest results of the simulation of these effects for the LUVOIR coronagraph instrument and discuss the achieved contrast for exoplanet detection and characterization after closed-loop wavefront estimation and control algorithms have been applied. Finally, we show simulated observations using high-fidelity spatial and spectral input models of complete planetary systems generated with the Haystacks code framework.

Roser Juanola-Parramon↗

NASA NTRSDate not supplied

Habitability Assessments And Lessons-learned From 3-day And 11-day Enriched Oxygen Hypobaric Chamber Tests At NASA Johnson Space Center

Andrew Abercromby↗