A full-state vector simulator of quantum circuits optimized for multi-core and multi-nodes architectures. It provides C++ and Python interfaces. Also known as qHiPSTER (The Quantum High Performance Software Testing Environment).
An open source framework for quantum computation. By using Qiskit, users can generate quantum circuits and run it on simulators and real devices.
A comprehensive online database for materials science. It covers 3,000 kinds of property information (crystal structure, phase diagrams, thermophysical property data, etc.) and 290,000 kinds of material data and provides efficient information search for these data. A variety of analytics tools, including data integration, graphing and customizable data visualization, are also available.
ChemSpider is a free chemical structure database that provides fast access to over 100 million structures, properties, and related information, and is operated by the Royal Society of Chemistry.
By integrating and linking compounds from hundreds of high-quality data sources, ChemSpider makes it easy to find chemical data from diverse data sources that are freely available for online searching. Users can also add and manage data in a wikipedia-like fashion. Meanwhile, manual curation by the Royal Society of Chemistry continuously improves data quality.
Easy-to-use and fast Python library for simulation of quantum information and quantum many-body systems. It provides Tensor module for tensor network simulations and Matrix module for “exact” quantum simulations.
Open source Python package for data mining of materials. It can extract data from more than dozens of databases, perform preprocessing and visualization of extracted data. By combining machine-learning tools such as scikit-learn, users can build machine-learning models with descriptors created from the extracted data.
Open-source software for analyzing scientific data. DAWN can visualize data in various dimensions, from 1D to 3D, and it is also possible to create maps that plot different types of data. It can not only visualize data, but also process data, such as fitting for peak detection. It supports general data formats such as text files and HDF5, as well as data formats such as NeXus, which is used in X-ray experiments.
An AI system for predicting protein conformation. It is possible to predict the three-dimensional structure (folding structure) of a protein from its primary sequence (amino acid sequence). It learns hundreds of thousands of protein structure databases and uses DeepMind-based deep learning techniques to predict the conformation of new proteins from their amino acid sequences.
A tool for generating wavevector paths in band calculations of solids. It identifies high-symmetry points in reciprocal space based on the symmetry of the crystal and provides a standardized “path” connecting them. It supports various crystal structure formats (such as POSCAR and CIF) and is compatible with many electronic structure calculation software (e.g., VASP, Quantum ESPRESSO, ABINIT). A web-based interface is also available.