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Advanced capabilities for materials modelling with Quantum ESPRESSO.

P Giannozzi1, O Andreussi2,3, T Brumme4

  • 1Department of Mathematics, Computer Science, and Physics, University of Udine, via delle Scienze 206, I-33100 Udine, Italy.

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|October 25, 2017
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Summary
This summary is machine-generated.

Quantum EXPRESSO, a popular open-source quantum simulation software, has been enhanced with new methodologies, improved performance, and expanded interoperability for materials science research.

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Area of Science:

  • Computational Materials Science
  • Quantum Mechanics
  • Condensed Matter Physics

Background:

  • Quantum EXPRESSO is a widely used open-source software suite for quantum simulations of materials.
  • It employs advanced electronic-structure techniques like density-functional theory.
  • Its popularity stems from its versatility, performance, and active research community.

Purpose of the Study:

  • To detail recent extensions and improvements to the Quantum EXPRESSO software suite.
  • To highlight new methodologies, property calculators, and enhanced computational performance.
  • To describe advancements in code modularization and interoperability.

Main Methods:

  • Utilizes plane-wave pseudopotential and projector-augmented-wave approaches.
  • Implements density-functional theory, density-functional perturbation theory, and many-body perturbation theory.
  • Focuses on improving parallelization and code modularity for diverse hardware architectures.

Main Results:

  • Introduction of new methodologies and property calculators for broader simulation capabilities.
  • Significant improvements in parallelization and performance across various hardware platforms.
  • Enhanced interoperability within the Quantum EXPRESSO distribution and with external software.

Conclusions:

  • The recent updates enhance Quantum EXPRESSO's utility as a core open-source development platform.
  • These advancements facilitate the implementation of novel research ideas in quantum simulations.
  • The expanded capabilities and improved performance solidify its position in computational materials science.