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Open Quantum Systems Decoherence
Quantum Machine Learning
Parallel time integration using Batched BLAS (Basic Linear Algebra Subprograms) routines
arXiv
Authors: Konstantin Herb, Pol Welter
Year
2021
Paper ID
62339
Status
Preprint
Abstract Read
~2 min
Abstract Words
87
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Abstract
We present an approach for integrating the time evolution of quantum systems. We leverage the computation power of graphics processing units (GPUs) to perform the integration of all time steps in parallel. The performance boost is especially prominent for small to medium-sized quantum systems. The devised algorithm can largely be implemented using the recently-specified batched versions of the BLAS routines, and can therefore be easily ported to a variety of platforms. Our PARAllelized Matrix Exponentiation for Numerical Time evolution (PARAMENT) implementation runs on CUDA-enabled graphics processing units.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2021 reference point for readers tracking recent quantum research.
- We present an approach for integrating the time evolution of quantum systems.
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