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Cited by 2,123

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

QuTiP: An open-source Python framework for the dynamics of open quantum systems

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Johansson, J.R., Nation, P.D., Nori, Franco·2012·Computer Physics Communications
DOI 10.1016/j.cpc.2012.02.021
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Abstract

Article history: We present an object-oriented open-source framework for solving the dynamics of open quantum systems written in Python. Arbitrary Hamiltonians, including time-dependent systems, may be built up from operators and states defined by a quantum object class, and then passed on to a choice of master equation or Monte Carlo solvers. We give an overview of the basic structure for the framework before detailing the numerical simulation of open system dynamics. Several examples are given to illustrate the build up to a complete calculation. Finally, we measure the performance of our library against that of current implementations. The framework described here is particularly well suited to the fields of quantum optics, superconducting circuit devices, nanomechanics, and trapped ions, while also being ideal for use in classroom instruction.

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Metadata

Authors
Johansson, J. R., Nation, P. D., & Nori, F.
Venue
Computer Physics Communications
Publisher
Elsevier BV
Published
2012-08
Volume
183
Issue
8
Pages
1760-1772
ISSN
0010-4655 (ISSN-L)
DOI
10.1016/j.cpc.2012.02.021
OpenAlex
W2118492081
Cited by
2,123
References
11
FWCI
12.30
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: QuTiP: An open-source Python framework for the dynamics of open quantum systems. https://app.cochat.ai/papers/10.1016/j.cpc.2012.02.021
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Johansson, J. R., Nation, P. D., & Nori, F. (2012). QuTiP: An open-source Python framework for the dynamics of open quantum systems. Computer Physics Communications. https://doi.org/10.1016/j.cpc.2012.02.021

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.