2020/12/10 by Thomas Grurl, Grurl, Thomas, Jürgen Fuß +3 · 1 citation
Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Physical sciences #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Physics (quant-ph)
paper · pdf · doi:10.48550/arxiv.2012.05629
openalex publication_date 2020/12/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
By using quantum mechanical effects, quantum computers promise significant\nspeedups in solving problems intractable for conventional computers. However,\ndespite recent progress they remain limited in scaling and availability-making\nquantum software and hardware development heavily reliant on quantum simulators\nrunning on conventional hardware. However, most of those simulators mimic\nperfect quantum computers and, hence, ignore the fragile nature of quantum\nmechanical effects which frequently yield to decoherence errors in real quantum\ndevices. Considering those errors during the simulation is complex, but\nnecessary in order to tailor quantum algorithms for specific devices. Thus far,\nmost state-of-the-art simulators considering decoherence errors rely on\n(exponentially) large array representations. As an alternative, simulators\nbased on decision diagrams have been shown very promising for simulation of\nquantum circuits in general, but have not supported decoherence errors yet. In\nthis work, we are closing this gap. We investigate how the consideration of\ndecoherence errors affects the simulation performance of approaches based on\ndecision diagrams and propose advanced solutions to mitigate negative effects.\nExperiments confirm that this yields improvements of several orders of\nmagnitudes compared to a naive consideration of errors.\n