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C++ and Python support for the CUDA Quantum programming model
CUDA-Q is an open-source platform for developing hybrid quantum-classical applications using a unified programming model across CPUs, GPUs, and quantum processing units. It provides a full toolchain that includes compilers, runtimes, and libraries for writing quantum programs in both C++ and Python. The platform is designed to be hardware-agnostic, allowing developers to run applications on different quantum backends or simulate them efficiently using GPU acceleration when physical quantum...
...It has been applied to simulate different types of particles: for example antiprotons, positrons, 39K+ , highly charged ions, negatively charged particles.
Simbuca also has been applied to simulate Penning/Paul traps, Mr-TOFs, RFQs, ...
More info on the wiki: https://sourceforge.net/p/simbuca/wiki
An experimental ISS for freescale's e500v2 core. It is meant to simulate only cpu and memory subsystem and is purely intended for academic/learning purposes only.
Simulate the optical reflectance from an infinite turbid medium under an ideal oblique incidence optical source.
Two versions are implemented: CPU and GPU. They both generate statistically the same results but GPU version works much faster.
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