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are developing machine learning-driven autonomous metrology research systems, with the goal of accelerating the development of self-correcting photonic and quantum sensor networks. These systems combine machine
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Description We are using innovative processing to develop novel superconducting materials with enhanced properties for quantum circuit applications. Critical elements for development of these materials
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NIST only participates in the February and August reviews. In many application areas, materials development increasingly involves manipulating the local atomic order to optimize properties
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, plays an important role at NIST in the development and interpretation of new measurement techniques, as well as aiding the understanding of the behavior of new materials in existing measurements. In
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of the constraints on sequencing (read length, depth), and informatics (e.g., database composition, algorithm biases). Proposals should address these challenges with strategies to evaluate the metagenomic
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-eddy simulation and direct numerical simulation of the phenomena. Topics of interest include algorithm development numerical combustion, scientific visualization, and data analysis. key words Buoyancy
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are developing high order integral equation methods and numerical tools for computational electromagnetics. This research focuses on the frequency domain electromagnetic field solvers that involve automatic
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further enriches the available data from which material behavior can be extracted. Separate work is being done to develop robust algorithms to quantitatively compare the physical and simulated experimental
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Sonmez Turan meltem.turan@nist.gov 301.975.4391 Description NIST standardized cryptographic algorithms are intended to be "bulletproof". That is, the computational complexity needed to break them is
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301.538.9058 Description Generation, control and detection of optical radiation either spectrally, temporally, or spatially is fundamental to optical technologies. Developing a versatile, manufacturable, and