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

机译:在时间上实现飞跃,以解决高Tc超导体的仿真问题

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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:我们提出了一种新的量子簇算法来模拟高Tc超导体的模型。该算法扩展了具有连续晶格自能量的当前方法,从而消除了人为的长期关联。这解决了潜在的量子蒙特卡洛求解器中的费米离子征象问题,该问题适用于整个目标温度范围内的大簇和库仑相互作用的实际值。我们发现,与当前最新的量子簇模拟相比,新算法将求解时间缩短了9个数量级。给出了一种有效的实现方式,该实现方式可移植到多核以及混合CPU-GPU系统。在ORNL的Titan超级计算机上的18,600个节点上运行,使我们能够计算10%空穴掺杂下2D Hubbard模型中U / t = 7的28个站点簇的Tc / t = 0.053±0.0014的收敛值。在Titan上进行的典型仿真维持在9.2到15.4 petaflops之间(在整个运行过程中测得的双精度),这取决于所使用的配置和参数。

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