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Quantum inspire - Qutech's platform for co-development and collaboration in quantum computing

Autor: Last, T., Samkharadze, Nodar, Eendebak, P.T., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K.K.L., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L.M.K., Maturova, K., Veltin, J., Alberts, G.J.N., Sanchez, Martha I., Panning, Eric M.

Publikováno v: Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020, 11324

The mission of QuTech is to bring quantum technology to industry and society by translating fundamental scientific research into applied research. To this end we are developing Quantum Inspire (QI), a full-stack quantum computer prototype for future

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::65eb14e31ac63fe4ff6e2fad520c52d3
http://resolver.tudelft.nl/uuid:196882c3-7860-4966-8004-cfb4f9748f56

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Deep learning and data assimilation for real-time production prediction in natural gas wells

Autor: Loh, K.K.L., Shoeibi Omrani, P.S., Linden, R.J.P. van der

Publikováno v: arXiv pre

The prediction of the gas production from mature gas wells, due to their complex end-of-life behavior, is challenging and crucial for operational decision making. In this paper, we apply a modified deep LSTM model for prediction of the gas flow rates

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::fac45c9d9befd46eea2195f055779faf
http://resolver.tudelft.nl/uuid:5a0ddeb8-729e-42d9-a210-2fa7da207ae6

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