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Noyes, Matthew

Publications and source records attributed to Noyes, Matthew.

11 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Active Wide-Field Sky Simulator Design for the JPL Astrometry Testbed

Exoplanet detection through astrometry will provide mass measurements that are key to our understanding of exoplanet demographics. Astrometric surveys are also critical pre-cursor observations for identifying targets for future direct imaging missions, such as the HabEx and LUVOIR mission concepts. However, Earth-mass planets orbiting Sun-like stars within 10 pc only cause a 0.3 uas astrometric signal, which is about two orders of magnitude smaller than the current state-of-the-art. In order to advance the technologies needed for future astrometry instruments, a testbed capable of simulating and measuring equivalent Earth-like exoplanet astrometric signals was created. The testbed has a stable light source that simulates a field of stars and can introduce a sub-uas astrometric signal onto a central artificial target star. This is done by illuminating an array of pinholes lithographically printed onto a glass substrate and translating, with picometer resolution, a target-star pinhole located on a centrally cut flexure feature. To detect this motion, a diffractive pupil is used to calibrate the limiting optical distortions of an Offner relay. Presented in this paper are the requirements, design, and implementation of the wide-field astrometry testbed’s light source.

Bendek, Eduardo↗
NASA NTRS2021

The Twin Decadal Survey Testbeds in the High Contrast Imaging Testbed facility at NASA’s Jet Propulsion Laboratory

Direct imaging of an Earth-like exoplanet will require future missions, such as the proposed HabEx or LUVOIR concepts, to achieve starlight suppression with planet/star contrast ratios on the order of 10−10 at angular separations <100 milliarcseconds in visible wavelengths. To facilitate the technology and algorithm development required to enable this ambitious scientific goal, NASA’s Exoplanet Exploration Program (ExEP) High Contrast Imaging Testbed (HCIT) facility at the Jet Propulsion Laboratory (JPL) recently commissioned the Decadal Survey Testbed (DST), a state-of-the-art, flexible, and extremely stable coronagraph testbed. This testbed integrates years of experience and lessons learned at HCIT and has now demonstrated contrast ratios as low as few times 10−10 in 10% bandwidth. Following the success of DST, the HCIT team has developed a companion testbed, the Decadal Survey Testbed 2 (DST2) that further implements lessons learned from DST, and will provide the HCIT with additional coronagraph testbed capacity and efficiency. Commissioning for DST2 is currently targeted for Fall 2021. Here we provide an update on the status of DST, and report on the design, performance modeling simulations, and status of integration and testing for DST2, highlighting updates to the design from the original DST.

Siegler, Nick↗
NASA NTRS2021

Deriving Deformable Mirror Performance Requirements in Simulation with Experimental Verification

Coronagraph instruments rely on predictable and stable deformable mirror (DM) surface displacement to achieve the contrast required to detect Earth-sized exoplanets orbiting nearby Solar-type stars. Anomalous DM behavior, such as unstable or pinned actuators, can limit contrast in coronagraphs. Simulating how these undesired behaviors affect the performance of a high contrast imaging architecture is important for developing requirements on their associated hardware. Simulating a vortex coronagraph (VC) with two deformable mirrors, this study quantifies how the number of pinned actuators affect the performance of Focal Plane Wavefront Sensing and Control algorithms using both Grid Search Electric Field Conjugation (EFC) and Planned EFC, which uses Beta-Bumping. The simulation also quantifies how various types of voltage noise such as zero-mean Gaussian noise, zero-mean periodic noise, and drift can affect the contrast of a VC during an observation run. A tolerance of a change in the Mean Normalized Intensity of ${1\times10^{-11}}$ is allocated to both types of error. If Planned EFC is used, only 1 pinned actuator on both DMs can be tolerated. If only pure Grid Search EFC is used the DMs cannot have any pinned actuators. For the case of zero-mean Gaussian noise and zero-mean periodic noise, one can tolerate a noise standard deviation of no more than ${\sigma = 0.45 \text{ mV}}$. For drift, we can only tolerate ${\sigma = 0.30 \text{ mV}}$ or less. These results show that the DM electronics and the DM themselves need to be nearly defect free to avoid having more than 1 pinned actuator. The electronics need to be tested for different types of noise statistics and that both the average and standard deviation of the noise should be measured.

Dean L. Palmer↗
NASA NTRS2020

Status of NASA’s stellar astrometry testbeds for exoplanet detection: Science and technology overview

Accurate measurement of exoplanetary masses is a critical step in addressing key aspects of NASA's science vision. Measuring masses of Earth-analogs around FGK stars out to 10 pc requires sub-microarcsecond astrometric accuracy, which is not within the capabilities of current instrumentation. Thus, new technology will be required to build an astrometric instrument capable of achieving such performance. This will immediately empower the possibility for dedicated astrometric missions, and perhaps most enticing, it will enable astrometric observing modes to be added (with relatively low cost and impact) to any mission boasting a sufficiently stable direct imaging platform. In this paper, we provide an overview of the scientifi?c goals and technology utilized on two of NASA's astrometry testbeds dedicated to advancing stellar astrometry for exoplanet detection. The ?first one, located at the Jet Propulsion Laboratory (JPL), is dedicated to imaging stellar astrometry on sparse ?fields. The goal of this testbed is to mature the Diffractive Pupil (DP) technology to TRL-5, demonstrating high-?fidelity performance in a relevant environment. This testbed operates in a vacuum tank at the High Contrast Imaging Testbed (HCIT) at JPL. The second testbed, located at NASA Ames Research Center, is dedicated to advancing narrow angle relative astrometry to detect exoplanets around nearby binary stars. The key technology in this testbed is a DP specially designed to measure the angle between two sources on the sky. This testbed operates in air and aims to bring this technology to TRL-4.

Guyon, Olivier↗
NASA NTRS2019

Deep Learning Applications in Manned Spaceflight

This presentation discusses a basic overview of Deep Machine Learning (DML) fundamentals, and two JSC applications of DML to create an Intelligent Personal Coach for exercise applications on deep-space missions, and the training of a neural network using the SingleShotPose algorithm from Microsoft to detect object 6 degree of freedom pose information from 2D image data for use in an Intelligent Procedure Assistant. The presentation concludes with a discussion about conceptual future uses of DML for space missions.

augmented reality↗
NASA NTRS2017

NASA's Hybrid Reality Lab: One Giant Leap for Full Dive

This presentation demonstrates how NASA is using consumer VR headsets, game engine technology and NVIDIA's GPUs to create highly immersive future training systems augmented with extremely realistic haptic feedback, sound, additional sensory information, and how these can be used to improve the engineering workflow. Include in this presentation is an environment simulation of the ISS, where users can interact with virtual objects, handrails, and tracked physical objects while inside VR, integration of consumer VR headsets with the Active Response Gravity Offload System, and a space habitat architectural evaluation tool. Attendees will learn how the best elements of real and virtual worlds can be combined into a hybrid reality environment with tangible engineering and scientific applications.

Delgado, Francisco J.↗
NASA NTRS2016

Hybrid Reality Lab Capabilities - Video 2

Our Hybrid Reality and Advanced Operations Lab is developing incredibly realistic and immersive systems that could be used to provide training, support engineering analysis, and augment data collection for various human performance metrics at NASA. To get a better understanding of what Hybrid Reality is, let's go through the two most commonly known types of immersive realities: Virtual Reality, and Augmented Reality. Virtual Reality creates immersive scenes that are completely made up of digital information. This technology has been used to train astronauts at NASA, used during teleoperation of remote assets (arms, rovers, robots, etc.) and other activities. One challenge with Virtual Reality is that if you are using it for real time-applications (like landing an airplane) then the information used to create the virtual scenes can be old (i.e. visualized long after physical objects moved in the scene) and not accurate enough to land the airplane safely. This is where Augmented Reality comes in. Augmented Reality takes real-time environment information (from a camera, or see through window, and places digitally created information into the scene so that it matches with the video/glass information). Augmented Reality enhances real environment information collected with a live sensor or viewport (e.g. camera, window, etc.) with the information-rich visualization provided by Virtual Reality. Hybrid Reality takes Augmented Reality even further, by creating a higher level of immersion where interactivity can take place. Hybrid Reality takes Virtual Reality objects and a trackable, physical representation of those objects, places them in the same coordinate system, and allows people to interact with both objects' representations (virtual and physical) simultaneously. After a short period of adjustment, the individuals begin to interact with all the objects in the scene as if they were real-life objects. The ability to physically touch and interact with digitally created objects that have the same shape, size, location to their physical object counterpart in virtual reality environment can be a game changer when it comes to training, planning, engineering analysis, science, entertainment, etc. Our Project is developing such capabilities for various types of environments. The video outlined with this abstract is a representation of an ISS Hybrid Reality experience. In the video you can see various Hybrid Reality elements that provide immersion beyond just standard Virtual Reality or Augmented Reality.

Delgado, Francisco J.↗