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arXiv 2302.08373nucl-thcond-mat.str-el
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配对哈密顿量的本征向量延拓

Eigenvector continuation for the pairing Hamiltonian

Margarida Companys Franzke, Alexander Tichai, Kai Hebeler, Achim Schwenk

AI总结:

本工作将本征向量延拓(EC)应用于配对哈密顿量,证明EC重和微扰理论与精确解定性一致,且基于EC的模拟器能用极少训练点稳健预测基态能量及从正常态到超流态的相变。

摘要:

近年来,用于评估多体观测量模拟器的发展受到越来越多的关注。特别是当哈密顿量具有参数依赖性时,本征向量延拓(EC)框架已被认为是一种强大的工具。通过在一组训练数据上训练模拟器,在许多情况下可以稳健地预测任意参数值的多体解。此外,它还可用于重和原本发散的微扰展开。在本工作中,我们将EC应用于配对哈密顿量,并表明EC重和微扰理论与精确解在定性上是一致的,并且一旦适当选择训练数据,基于EC的模拟器能稳健地预测基态能量。特别是,使用极少量的训练点就能定量预测从正常态到超流态的相变。

英文摘要:

The development of emulators for the evaluation of many-body observables has gained increasing attention over the last years. In particular the framework of eigenvector continuation (EC) has been identified as a powerful tool when the Hamiltonian admits for a parametric dependence. By training the emulator on a set of training data the many-body solution for arbitrary parameter values can be robustly predicted in many cases. Furthermore, it can be used to resum perturbative expansions that otherwise diverge. In this work, we apply EC to the pairing Hamiltonian and show that EC-resummed perturbation theory is in qualitative agreement with the exact solution and that EC-based emulators robustly predict the ground-state energy once the training data are chosen appropriately. In particular the phase transition from the normal to the superfluid regime is quantitatively predicted using a very low number of training points.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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