Quantum Monte Carlo simulations of solids

1,867 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

QuSpin: a Python Package for Dynamics and Exact Diagonalisation of Quantum Many Body Systems part I: spin chains (2016, methodology): “In contrast to the tremendous progress made in studying low-energy phenomena based on well-developed sophisticated techniques, such as Quantum Monte Carlo methods [1, 2, 3], Density Matrix Renormalisation Group [4, 5], Matrix Product States [6], Dynamical Mean-Field Theory [7, 8, 9], etc.”
High-pressure phases of group-IV, III–V, and II–VI compounds (2003, positive): “The idea that the LDA places the diamond phase too high in energy has recently received support from highly accurate quantum Monte Carlo calculations (see Foulkes et al., 2001).”
Computational Physics on Graphics Processing Units (2012, background): “A general overview of QMC can be found from [102].”
Concepts of quantum non-Markovianity: A hierarchy (2017, positive): “Areas where this technique has great application include the quantized motion of atoms undergoing spontaneous emission [131]; analysis of laser cooling schemes [135]; and simulations of many-body quantum systems [136].”
Neural-Network Quantum States, String-Bond States, and Chiral Topological States (2017, methodology): “The Variational Monte Carlo method [59, 60] (VMC) provides a general algorithm for optimizing the energy of such a wave function.”