2021/01/09 by Alexey N. Pyrkov, Pyrkov, Alexey N., Yurii Zotov +5
Computer Science · Decision Sciences · Physics and Astronomy · #FOS: Physical sciences #Model Reduction and Neural Networks #Numerical Methods and Algorithms #Probabilistic and Robust Engineering Design #Quantum Computing Algorithms and Architecture #Quantum Physics (quant-ph)
paper · pdf · doi:10.48550/arxiv.2101.03349
openalex publication_date 2021/01/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The Trotter-Suzuki decomposition is one of the main approaches for\nrealization of quantum simulations on digital quantum computers. Variance-based\nglobal sensitivity analysis (the Sobol method) is a wide used method which\nallows to decompose output variance of mathematical model into fractions\nallocated to different sources of uncertainty in inputs or sets of inputs of\nthe model. Here we developed a method for application of the global sensitivity\nanalysis to the optimization of Trotter-Suzuki decomposition. We show with a\nproof-of-concept example that this approach allows to reduce the number of\nexponentiations in the decomposition and provides a quantitative method for\nfinding and truncation 'unimportant' terms in the system Hamiltonian.\n