46 citations · 76 across the 3 of their papers we have counts for
9 papers
High- ternary metal hydrides, YKH and LaKH, discovered by machine learning
Peng Song, Zhufeng Hou, Pedro Baptista de Castro +4
The search for hydride compounds that exhibit high superconductivity has been extensively studied. Within the range of binary hydride compounds, the studies have been develop…
Atomic forces by quantum Monte Carlo: application to phonon dispersion calculation
Kousuke Nakano, Tommaso Morresi, Michele Casula +2
We report the first successful application of the {\it ab initio} quantum Monte Carlo (QMC) framework to a phonon dispersion calculation. A full phonon dispersion of diamond is suc…
TurboRVB: a many-body toolkit for {\it ab initio} electronic simulations by quantum Monte Carlo
Kousuke Nakano, Claudio Attaccalite, Matteo Barborini +9
TurboRVB is a computational package for {\it ab initio} Quantum Monte Carlo (QMC) simulations of both molecular and bulk electronic systems. The code implements two types of well e…
General correlated geminal ansatz for electronic structure calculations: exploiting Pfaffians in place of determinants
Claudio Genovese, Tomonori Shirakawa, Kousuke Nakano +1
We propose here a single Pfaffian correlated variational ansatz, that dramatically improves the accuracy with respect to the single determinant one, while remaining at a similar co…
Quantum annealing approach to Ionic Diffusion in Solid
Keishu Utimula, Tom Ichibha, Genki I. Prayogo +3
We have developed a framework for using quantum annealing computation to evaluate a key quantity in ionic diffusion in solids, the correlation factor. Existing methods can only cal…
Stochastic estimations of a total number of classes for the clusterings with too enormous samples to be accommodate into a clustering engine
Keishu Utimula, Genki I. Prayogo, Kousuke Nakano +2
We considered the problem how to handle the exploding number of possibilities to be sorted into irreducible classes by using a clustering tool when its input capacity cannot accomm…