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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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We describe a genome compiler which complies s-expressions to machine code, resulting in significant speedup of individual evaluations over standard GP systems.
The effects of the NASA Health Related Fitness Program (HRFP), which includes a 12-week educational component (EC) and quarterly fitness retests (RT), on the results of periodic testing of fitness, body composition, and blood lipids were evaluated in three goups of pilots. These included the group of compliers (those who completed EC and not less than 75 percent RT), the noncompliers (completed EC and lesss than 75 percent RT), and the dropouts from EC. Results show that beneficial changes in physical activity found two years after the completion of the HRFP were related to both the completion of the EC and the periodic fitness reevaluations. These changes were associated with maximal oxygen consumption, percent body fat, body weight, and blood lipids.
In this report we present qcor - a language extension to C++ and compiler implementation that enables heterogeneous quantum-classical programming, compilation, and execution in a single-source context. Our work provides a first-of-its-kind C++ compiler enabling high-level quantum kernel (function) expression in a quantum-language agnostic manner, as well as a hardware-agnostic, retargetable compiler workflow targeting a number of physical and virtual quantum computing backends. qcor leverages novel Clang plugin interfaces and builds upon the XACC system-level quantum programming framework to provide a state-of-the-art integration mechanism for quantum-classical compilation that leverages the best from the community at-large. qcor translates quantum kernels ultimately to the XACC intermediate representation, and provides user-extensible hooks for quantum compilation routines like circuit optimization, analysis, and placement. This work details the overall architecture and compiler workflow for qcor, and provides a number of illuminating programming examples demonstrating its utility for near-term variational tasks, quantum algorithm expression, and feed-forward error correction schemes.
We describe a genetic programming system which learns nonlinear predictive models for lossless image compression.