QDK/Chemistry: A Modular Toolkit for Quantum Chemistry Applications

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Authors: Nathan Baker, Brian A. Bilodeau, Chi Chen, Yingrong Chen, Marco Eckhoff, Alexandra Efimovskaya, Piero Gasparotto, Puck van Gerwen, Rushi Gong, Kevin Hoang, Zahra Hooshmand, Andrew J. Jenkins
+14 more Conrad S. N. Johnston, Run R. Li, Jiashu Liang, Hongbin Liu, Alexis W. Mills, Maximilian Mörchen, George Maxwell Nishibuchi, Chong Sun, Bill Ticehurst, Matthias Troyer, Jan P. Unsleber, Stefan Wernli, David Williams-Young, Boqin Zhang
Cited by: 1

Abstract

We present QDK/Chemistry, a software toolkit for quantum chemistry workflows targeting quantum computers. The toolkit addresses a key challenge in the field: while quantum algorithms for chemistry have matured considerably, the infrastructure connecting classical electronic structure calculations to quantum circuit execution remains fragmented. QDK/Chemistry provides this infrastructure through a modular architecture that separates data representations from computational methods, enabling researchers to compose workflows from interchangeable components. In addition to providing native implementations of targeted algorithms in the quantum-classical pipeline, the toolkit builds upon and integrates with widely used open-source quantum chemistry packages and quantum computing frameworks through a plugin system, allowing users to combine methods from different sources without modifying workflow logic. This paper describes the design philosophy, current capabilities, and role of QDK/Chemistry as a foundation for reproducible quantum chemistry experiments.

Fields of Study & Subjects

Quantum Computing Algorithms and Architecture Scientific Computing and Data Management Machine Learning in Materials Science

Publication details

Journal / source
arXiv (Cornell University)
Publication date
21 January 2026
Document type
Preprint