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This paper presents a new technology program, within the fundamental physics, focusing on four quantum technology areas: quantum atomics, quantum optics, space superconductivity and quantum sensor technology, and quantum field based sensor and modeling technology.
This paper presents a new technology program, within the fundamental physics research program, focusing on four quantum technology areas: quantum atomics, quantum optics, space superconductivity and quantum sensor technology, and quantum fluid based sensor and modeling technology.
Harness the power of quantum technologies to assure the availability of UAS communications against disruptions. Make use of quantum computing (e.g. quantum optimization) and quantum communication (e.g. quantum key distribution) to address the availability cybersecurity challenge. Our approach is three-fold: (1) Utilize quantum optimization algorithms to design robust network with routing redundancy that can respond adaptively to dynamically changing real-time environment and disruptions, (2) Utilize quantum optimization algorithms resource allocation for detection, localization, and tracking of mobile communication disruption agents, (3) Utilize quantum key distribution (QKD) to execute secure key sharing in high data rate optical communication and/or anti-jamming protocols for secure RF communication.
The areas discussed are still under development: I. Nano structured materials for TE applications a) SiGe and Be.Te; b) Nano particles and nanoshells. II. Quantum technology for optical devices: a) Quantum apertures; b) Smart optical materials; c) Micro spectrometer. III. Bio-template oriented materials: a) Bionanobattery; b) Bio-fuel cells; c) Energetic materials.
Recent advances in small Unmanned Aerial System (sUAS) technologies lower the barriers for use by both private and commercial entities. However, these advances are also likely to lead to greater vehicle densities, a more heterogenous mix of vehicles and equipment and greater levels of vehicle autonomy, which can increase the chance for communications disruptions. For the safe and secure operation of these vehicles, it is essential to have a robust communications network. This work is focused on harnessing the power of quantum technologies to enable this robust communications network by: (1) utilizing quantum optimization algorithms to design robust network with routing redundancy that can respond adaptively to dynamically changing real-time environment and disruptions, (2) utilize quantum optimization algorithms resource allocation for detection, localization, and tracking of mobile communication disruption agents and (3) utilize quantum key distribution (QKD) to execute secure key sharing in anti-jamming protocols for secure radio frequency (RF) communication. Efforts to map these quantum optimization algorithms to commercially available quantum annealers and soon to be available general-purpose gate-model quantum hardware architectures will be reviewed, and plans for testing the solutions to these algorithms through indoor sUAS flight tests will be discussed. Lastly, efforts to miniaturize and practically deploy Quantum Key Distribution (QKD) hardware, which could ultimately be used to securely exchange encryption keys, in sUAS networks will be reviewed.
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Explore the source record for details and available documents.
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Explore the source record for details and available documents.
Mechatronics is the synergistic application of mechanics, electronics, control engineering, and computer science in the development of electromechanical products and systems, through integrated design. This paper proposes to extend the mechatronics course beyond traditional engineering topics, and to modernize the mechatronics instructions with complementary quantum engineering topics. With the recent rapid advances in quantum technologies such as quantum communications, sensing, computers, and algorithms, it is imperative to train the next generation of engineers and prepare them for their future careers in the ever-changing industry in such areas. Furthermore, due to such progress and advances in the fields associated with quantum mechanics, the integration of quantum technologies with classical mechanical systems will be inevitable both in terms of educational and technological standpoints in future. To address the educational needs of the future engineers in such areas of significant importance, quantum entanglement and quantum cryptography experiments, as two fundamental topics in quantum mechanics, are brought into the mechatronics course in an initiative that is reported in this paper. The integrated quantum and mechatronics topics also provides opportunities for open discussions on exploring the interface of quantum technologies and classical engineering systems, which can potentially push the engineering boundaries beyond classical possibilities by accessing the quantum advantages. An innovative online remote demonstration of such quantum experiments are developed and presented to the students. This course has been offered to undergraduate students once with successful results. The students were able to remotely access the experiments, perform the experiments and collect data. The successful result of such quantum experiments is also reflected in a course survey, presented in this paper, even though the quantum mechanics topics offered in this course are unfamiliar to engineering students and hence more challenging. The paper reports, and aims to promote, the integration of selected quantum technology topics with the mechatronics course for training engineering students in this rapidly growing area.
We explore the feasibility of ultra-high density memory based on quantum devices. Starting from overall constraints on chip area, power consumption, access speed, and noise margin, we deduce boundaries on single cell parameters such as required operating voltage and standby current. Next, the possible role of quantum devices is examined. Since the most mature quantum device, the resonant tunneling diode (RTD) can easily be integrated vertically, it naturally leads to the issue of 3D integrated memory. We propose a novel method of addressing vertically integrated bistable two-terminal devices, such as resonant tunneling diodes (RTD) and Esaki diodes, that avoids individual physical contacts. The new concept has been demonstrated experimentally in memory cells of field effect transistors (FET's) and stacked RTD's.
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Space platforms offer unique environment for and measurements of quantum world and fundamental physics. Quantum technology and measurements enhance measurement capabilities in space and result in greater science returns.
Feed forward artificial neural networks are very convenient for performing correlated interpolation of pairs of complex noisy data sets as well as detecting small changes in image data. Image-to-image, image-to-variable and image-to-index applications have been tested at Glenn. Early demonstration applications are summarized including image-directed alignment of optics, tomography, flow-visualization control of wind-tunnel operations and structural-model-trained neural networks. A practical application is reviewed that employs neural-net detection of structural damage from interference fringe patterns. Both sensor-based and optics-only calibration procedures are available for this technique. These accomplishments have generated the knowledge necessary to suggest some other applications for NASA and Government programs. A tomography application is discussed to support Glenn's Icing Research tomography effort. The self-regularizing capability of a neural net is shown to predict the expected performance of the tomography geometry and to augment fast data processing. Other potential applications involve the quantum technologies. It may be possible to use a neural net as an image-to-image controller of an optical tweezers being used for diagnostics of isolated nano structures. The image-to-image transformation properties also offer the potential for simulating quantum computing. Computer resources are detailed for implementing the black box calibration features of the neural nets.
The accomplishments of Physics, the increasing power of its instruments, and its expanding reach into other sciences have generated an unprecedented set of scientific opportunities. The committee has identified six such Grand Challenges listed below in no particular order: Developing quantum technologies. Creating new materials. Understanding complex systems. Unifying the forces of Nature. Exploring the universe Applying Physics to Biology.