An application for structure prediction based on the evolutionary algorithm. From an input of the atomic position in a unit cell and possible elements at each atomic position, this application predicts the stable structure and composition from the first-principles calculation and molecular dynamics in combination with the evolutionary algorithm. This application is written in Python, and uses Quantum ESPRESSO and GULP as an external program.
COMmon Bayesian Optimization Library (COMBO) is an open source python library for machine learning techniques. COMBO is amenable to large scale problems, because the computational time grows only linearly as the number of candidates increases. Hyperparameters of a prediction model can be automatically learned from data by maximizing type-II likelihood.
Python library for the design, simulation, and optimization of continuous-variable quantum optical circuits. It has high-level functions for solving problems including graph and network optimization, machine learning, and chemistry, and can perform training and optimization of quantum programs using the TensorFlow backend.
Software package that implements Behler-Parinello type neural network potential. The package provides tools for training and evaluating potentials based on given structure-energy data. It also provides an interface with LAMMPS for performing molecular dynamics calculations.
FORTRAN-based software package developed by the Behler Group for implementing Behler-Parinello neural network potentials. Potentials can be constructed, evaluated, and used for molecular dynamics simulations using LAMMPS. The newest generation of neural network potentials that take into account long-range electrostatic interactions are implemented.
An application for structure prediction based on the genetic algorithm. This application can predict the structure and composition of stable phase of crystals, molecules, atomic clusters, and so on by using first-principles calculation and molecular dynamics. This application implements interfaces with various programs such as VASP, LAMMPS, MOPAC, GULP, JDFTx, etc, and runs efficiently on parallel computing architectures.
Software package that implements moment tensor potentials. Potentials can be trained and used for molecular dynamics calculations using LAMMPS. Active learning combined with molecular dynamics calculations is also available.
An application for prediction of stable and metastable structures from a chemical composition. This application applies the revolutionary algorithm to structure prediction by using various external energy calculators (VASP, GULP, Quantum Espresso, CASTEP).
Software package to implement Behler-Parinello neural network potentials. Potentials can be trained from structure-energy/ interatomic forces/stress data, and molecular dynamics calculations using LAMMPS can also be performed using learned potentials. A prediction uncertainty measure can also be calculated simultaneously.
CrySPY is a crystal structure prediction tool by utilizing first-principles calculations and a classical MD program. Only by inputting chemical composition, crystal structures can be automatically generated and searched. In ver. 0.6.1, random search, Bayesian optimization, and LAQA are available as searching algorithms. CrySPY is interfaced with VASP, Quantum ESPRESSO, and LAMMPS.