TURBOMOLE: Modular program suite for ab initio quantum-chemical and condensed-matter simulations

Journal article

TURBOMOLE is a collaborative, multi-national software development project aiming to provide highly efficient and stable computational tools for quantum chemical simulations of molecules, clusters, periodic systems, and solutions. The TURBOMOLE software suite is optimized for widely available, inexpensive, and resource-efficient hardware such as multi-core workstations and small computer clusters. TURBOMOLE specializes in electronic structure methods with outstanding accuracy-cost ratio, such as density functional theory including local hybrids and the random phase approximation (RPA), GW-Bethe-Salpeter methods, second-order Møller-Plesset theory, and explicitly correlated coupled-cluster methods. TURBOMOLE is based on Gaussian basis sets and has been pivotal for the development of many fast and low-scaling algorithms in the past three decades, such as integral-direct methods, fast multipole methods, the resolution-of-the-identity approximation, imaginary frequency integration, Laplace transform, and pair natural orbital methods. This review focuses on recent additions to TURBOMOLE's functionality, including excited-state methods, RPA and Green's function methods, relativistic approaches, high-order molecular properties, solvation effects, and periodic systems. A variety of illustrative applications along with accuracy and timing data are discussed. Moreover, available interfaces to users as well as other software are summarized. TURBOMOLE's current licensing, distribution, and support model are discussed, and an overview of TURBOMOLE's development workflow is provided. Challenges such as communication and outreach, software infrastructure, and funding are highlighted.

Authors: Balasubramani, SG; Chen, GP; Coriani, S; Diedenhofen, M; Frank, MS

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: AIP Publishing
• Journal: Journal of Chemical Physics
• Volume: 152
• Issue: 18
• Article number: 184107
• Publication date: 2020-05-13
• Acceptance date: 2020-04-01
• DOI: 10.1063/5.0004635
• EISSN: 1089-7690
• ISSN: 0021-9606
• Pmid: 32414256
• Language: English
• Keywords: FFR