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      "citation": "Kalantre, S. S., Zwolak, J. P., Ragole, S., Wu, X., Zimmerman, N. M., Stewart, M. D., & Taylor, J. M. (2019). Machine learning techniques for state recognition and auto-tuning in quantum dots. Npj Quantum Information, 5(1). https://doi.org/10.1038/s41534-018-0118-7\n"
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    "Acknowledgments: This research is sponsored in part by the Army Research Office (ARO), through Grant No. W911NF-17-1-0274. The development and maintenance of the growth facilities used for fabricating samples were supported by the Department of Energy, through Grant No. DE-FG02-03ER46028. We acknowledge the use of clean room facilities supported by The National Science Foundation (NSF) through the UW-Madison MRSEC (DMR-1720415) and electron beam lithography equipment acquired with the support of the NSF MRI program (DMR-1625348). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the ARO or the U.S. Government.  The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright noted herein. Any mention of commercial products is for information only; it does not imply recommendation or endorsement by NIST."
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  "annotated": "2025-03-11T19:36:50.615045",
  "issued": "2022-02-25T16:49:59",
  "rights": "Purchase is not required for data downloading. Users must complete registration form to download data.",
  "revised": "2025-03-11T19:36:50.615045"
}