QDK/Chemistry: A Modular Toolkit for Quantum Chemistry Applications
Nathan A. Baker, Brian Bilodeau, Chi Chen, Yingrong Chen, Marco Eckhoff, Alexandra Efimovskaya, Piero Gasparotto, Puck van Gerwen, Rushi Gong, Kevin Hoang, Zahra Hooshmand, Andrew J. Jenkins, Conrad S. N. Johnston, Run R. Li, Jiashu Liang, Hongbin Liu, Alexis Mills

TL;DR
QDK/Chemistry is a modular software toolkit that bridges classical and quantum computing for chemistry, enabling flexible, reproducible workflows by integrating various algorithms and existing quantum chemistry tools.
Contribution
It introduces a modular architecture for quantum chemistry workflows that connects classical and quantum computations through interchangeable components and plugin integrations.
Findings
Provides native quantum chemistry algorithms for quantum-classical workflows.
Enables integration with existing quantum chemistry packages and frameworks.
Supports reproducible and flexible quantum chemistry experiments.
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…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Scientific Computing and Data Management · Machine Learning in Materials Science
