Current quantum computing devices have different strengths and weaknesses depending on their architectures. This means that flexible approaches to circuit design are necessary. We address this task by introducing a novel space-efficient quantum optimization algorithm for the graph coloring problem. Our circuits are deeper than the ones of the standard approach. However, the number of required qubits is exponentially reduced in the number of colors. We present extensive numerical simulations demonstrating the performance of our approach. Furthermore, to explore currently available alternatives, we also perform a study of random graph coloring on a quantum annealer to test the limiting factors of that approach, too.
The ParaPhrase Refactoring Tool for Erlang (PaRTE) provides automatic, comprehensive and reliable pattern candidate discovery to locate parallelisable components in Erlang programs. It uses semi-automatic and semantics-preserving program transformations to reshape source code and to introduce high level parallel patterns that can be mapped adaptively to the available hardware resources. This paper describes the main PaRTE tools and demonstrates that significant parallel speedups can be obtained.
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