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Taking a quantum leap in time to solution for simulations of high-Tc superconductors

机译:在时间延时到解高TC超导体的仿真

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We present a new quantum cluster algorithm to simulate models of high-Tc superconductors. This algorithm extends current methods with continuous lattice self-energies, thereby removing artificial long-range correlations. This cures the fermionic sign problem in the underlying quantum Monte Carlo solver for large clusters and realistic values of the Coulomb interaction in the entire temperature range of interest. We find that the new algorithm improves time-to-solution by nine orders of magnitude compared to current, state of the art quantum cluster simulations. An efficient implementation is given, which ports to multi-core as well as hybrid CPU-GPU systems. Running on 18,600 nodes on ORNL's Titan supercomputer enables us to compute a converged value of Tc/t = 0.053±0.0014 for a 28 site cluster in the 2D Hubbard model with U/t = 7 at 10% hole doping. Typical simulations on Titan sustain between 9.2 and 15.4 petaflops (double precision measured over full run), depending on configuration and parameters used.
机译:我们提出了一种模拟高TC超导体模型的新量子集群算法。该算法利用连续晶格自能延伸电流方法,从而去除人工远程相关性。这会在底层量子蒙特卡罗求解器中固化Fermionic标志问题,以进行大型簇,并在整个温度范围内的库仑相互作用的逼真。我们发现,与电流,最新的Quantum集群模拟相比,新算法通过九个数量级提高了溶液。给出了一种有效的实现,其中包括多核和混合CPU-GPU系统的端口。 ORNL的Titan SuperComputer上的18,600个节点运行使我们能够在2D Hubbard模型中计算TC / T = 0.053±0.0014的融合值,在2D Hubbard模型中,在10%孔掺杂中的U / T = 7。泰坦的典型模拟维持在9.2和15.4的Petaflops(通过完全运行中测量的双精度),具体取决于所使用的配置和参数。

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