Quantum Espresso (Quantum opEn-Source Package for Research in Electronic Structure, Simulation, and Optimization) is an integrated suite of packages for atomistic simulations based on the electronic structure. It implements density-functional theory (DFT) in the plane-wave pseudopotential approach, but it also includes more advanced levels of theory. Ground state calculations, structural optimization, ab-initio molecular dynamics are included, together with response functions, spectroscopic properties and quantum transport. It is released under the GNU GPL and runs on a huge variety of architectures.
Ref. Stefano Baroni, SISSA (IT) – email@example.com
Siesta is a DFT code able to perform efficient electronic structure calculations and ab initio molecular dynamics simulations of molecules and solids. Its efficiency stems from the use of strictly localised basis sets and from the implementation of linear-scaling algorithms which can be applied to suitable systems. Its accuracy and cost can be tuned in a wide range, from quick exploratory calculations to highly accurate simulations matching the quality of other approaches, such as plane-wave methods.
Ref. Pablo Ordejon, ICN2 (ES) – firstname.lastname@example.org
Fleur (Full-potential Linearized augmented plane wave in EURope) is a code family to calculate ground- and excited-state properties of solids within DFT. It treats all electrons on the same footing, and is based on the full-potential linearised augmented plane wave method. The FLEUR family includes:
(i) a versatile DFT code for the ground-state properties of multicomponent magnetic one-, two- and three-dimensional solids. A focus of the code is on non-collinear magnetism, determination of exchange parameters, spin-orbit related properties (topological and Chern insulators, Rashba and Dresselhaus effect, magnetic anisotropies, Dzyaloshinskii-Moriya interaction);
(ii) a Green function version of the code to calculate ballistic transport properties through planar junctions; and
(iii) the SPEX code implementing MBPT for electronic excitation properties of solids, with different levels of GW approaches. The code enables the determination of static and frequency dependent Hubbard U parameters by constrained random phase approximation (RPA) and the excitation and lifetime of magnons through the Bethe-Salpeter equation.
Ref. Stefan Blügel, Julich (DE) – email@example.com
Yambo is a code that implements ground-state as well as excited-state properties in an ab initio context. It implements many body perturbation theory (MBPT) and advanced orbital dependent functionals within DFT to allow the calculation of physical properties such as reliable band-gaps, band alignments, defect quasiparticle energies, optical and out-of-equilibrium properties. More specifically, Yambo implements the GW approximation for the self–energy, a linear response time-dependent DFT (TD-DFT) and Bethe–Salpeter formalism for the response function. It is released within the GPL license and is currently interfaced with QUANTUM ESPRESSO and other codes.
Ref. Andrea Marini, Cnr (IT) – firstname.lastname@example.org
Aiida (Automated Interactive Infrastructure and Database for Atomistic simulations) is a Python materials’ informatics framework to manage, store, share, and disseminate the workload of high-throughput computational efforts, while providing an ecosystem for materials simulations where codes are automatically optimised on the relevant hardware platforms, and complex scientific workflows involving different codes and datasets can be seamlessly implemented and shared. AIIDA is designed around the four pillars of materials’ informatics: Automation, Data, Environment, and Sharing. At the low-level, AIIDA takes care of automation and data storage for the management and safeguarding of calculations, data and workflows. At the user-level, it provides an advanced and intuitive research environment for accelerating scientific discoveries, and sharing capabilities to enable collaborative research.
Ref. Nicola Marzari, EPFL (CH) – email@example.com
Palenque (Python Abstraction Layer for Quantum Engines) is developed to delegate the evaluation of increasingly complex properties to an external wrapper written in a high-level language. The target is maximising the inter-operability of different codes, with the final goals of increasing the capabilities of quantum engines (QEs) and enabling their sustainable development by:
i) reducing code duplication by moving common features that require little communication and computational burden outside of the QEs;
ii) facilitating the implementation of new algorithms that are shared by multiple QEs.
Ref. Michele Ceriotti, EPFL (CH) –