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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Accelerating the Deployment of Space-Based Quantum Sensors

Quantum sensors rely on quantum mechanical properties, such as wave-particle duality, atomic energy levels, or entanglement, to measure physical, optical, or electromagnetic information from a target. Examples include Rydberg sensors, nitrogen-vacancy magnetometers, HOM (Hong-Ou-Mandel) interferometers, and SQUIDs (Superconducting Quantum Interference Devices). In general, as quantum sensors rely on interrogation at the atomic and photonic level rather than on classical mechanical measurements, these technologies promise advantages over their traditional counterparts in sensitivity, accuracy, and SWaP (Size, Weight, and Power). Conceptually, the use of quantum sensors unlocks the new phenomenology of sensor entanglement. While an ultra-low TRL (Technology Readiness Level) prospect for most sensor types, multi-sensor entanglement is a high risk, high reward strategy with a potential for exquisite sensitivity and SWaP improvements entirely inaccessible to classical sensors.

Grace Caroline Wusk↗
NASA NTRSDate not supplied

NASA and External Quantum Sensing Capability Assessment for NASA Space-Based Science Measurements

The Subject Matter Experts in the Sensors & Instrumentation Quantum Sensing Community of Practice (CoP) requested an independent technical assessment of the agency's capabilities in QS to understand NASA's internal needs and competencies related to QS and compare agency capabilities with those available externally including industry, academia, and other government agencies. The outcomes of the assessment will help the agency in establishing appropriate strategies and investments to develop and maintain the state-of-the-art sensing competence and capabilities required to meet the agency’s future needs. NASA Engineering and Safety Center Review Board approved the assessment request and assigned NASA Technical Fellow to lead and conduct the assessment by engaging NASA Centers, NASA HQ and an independent, non-commercial, and highly credible Quantum Sensing Experts from Academia, Department of Defense, other Government Agencies. The assessment started in October 2021 and final report was completed in October 2023.

External Quantum Sensing↗
NASA NTRSDate not supplied

Sampling Biases of Space-Based Observations of XCO2 Associated With South American Biomass Burning Events During 2017-2020

- We examine time series of OCO-2 xCO 2 observations coincident with other remotely sensed and in-situ observations to better understand external sampling effects. - The OCO-2 Level 3 assimilation product fills in gaps where OCO-2 does not have observations. - Although the Level 3 clearly shows the increased CO 2 over the Amazon associated with the September 2017 biomass burning event, the total amount of CO 2 may be underestimated because of a sampling bias. - Since TCCON is also a remotely sensed product, it may suffer the same sampling biases associated with biomass burning events as OCO-2. - Aircraft data show that there is significant variation in xCO 2 with altitude. - The OCO-2 fused products created by kriging may be better than the assimilated product at detecting deviations from the average state.

OCO↗
NASA NTRSDate not supplied

How to Train Your Jacobian: Least-Squares System Identification for Space-Based Coronagraphy

Stellar coronagraphs use closed-loop focal-plane wavefront sensing and control algorithms to create high-contrast dark zones suitable for imaging exoplanets and exozodiacal dust clouds around nearby stars. Model-based algorithms are susceptible to model mismatch, wherein a departure of the coronagraph's true optical characteristics from the assumed model causes reduced control loop performance. Here, we describe a simple technique for empirically tuning the wavefront control Jacobian matrix using applied deformable mirror commands and observed images. This mitigates model mismatch and recovers near-optimal control loop performance.

coronagraphy↗
NASA NTRSDate not supplied

Sampling Biases of Space-Based Observations of XCO 2 Associated With South American Biomass Burning Events

We examine time series of OCO-2 xCO2 observations from 2017-2020 coincident with other remotely sensed and in-situ observations to better understand external sampling effects associated with biomass burning events. The GES DISC will publish How-To documents as Jupyter Notebooks to describe how to aggregate OCO-2 Level 2 data and create similar time series.

Kristan Morgan↗