提升量子蒙特卡罗方法并缓解符号问题的Gutzwiller投影
Boosting quantum Monte Carlo and alleviating sign problem by Gutzwiller projection
AI总结：
本文提出一种结合无偏零温确定性QMC与变分MC的Gutzwiller投影QMC方法，通过最小能量试波函数加速收敛并减少计算时间，显著缓解符号问题。
摘要：
本文开发了一种新的项目量子蒙特卡罗（QMC）模拟方案，结合无偏零温（项目）确定性QMC和基于Gutzwiller投影波函数的变分蒙特卡罗，称为"Gutzwiller投影QMC"。数值结果表明，使用最小能量的Gutzwiller投影试波函数显著加速计算结果的收敛，从而大幅减少模拟的计算时间。更值得注意的是，我们展示了在Gutzwiller投影QMC中符号问题被显著缓解，尤其是在符号问题严重的区域。因此，我们相信Gutzwiller投影QMC为提高效率和缓解QMC模拟中相互作用费米子系统中的符号问题开辟了新途径。
英文摘要：
Here we develop a new scheme of projective quantum Monte-Carlo (QMC) simulation combining unbiased zero-temperature (projective) determinant QMC and variational Monte-Carlo based on Gutzwiller projection wave function, dubbed as ``Gutzwiller projection QMC''. The numerical results demonstrate that employment of Gutzwiller projection trial wave function with minimum energy strongly speed up the convergence of computational results, thus tremendously reducing computational time in the simulation. More remarkably, we present an example that sign problem is enormously alleviated in the Gutzwiller projection QMC, especially in the regime where sign problem is severe. Hence, we believe that Gutzwiller projection QMC paves a new route to improving the efficiency, and alleviating sign problem in QMC simulation on interacting fermionic systems.
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