CORDIS provides links to public deliverables and publications of HORIZON projects.
Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .
Deliverables
A range of point defect-based structures will be fabricated. A comprehensive set of experiments will be conducted to determine their behaviour in a wide range of conditions. Results will be systematized, analysed and reported to improve the quantitative defect-based QR model (D1.4).
Project logo and website and social media accounts (opens in new window)A project logo and website will be prepared and made available on the internet. This short report will describe the logo and website structure and main characteristics. Also, social media accounts (Twitter, LinkedIn) will be created to disseminate project news, which will be described in the short report.
Quantitative model of defect-based QR (opens in new window)A mathematical description of a quantum reservoir (QR) structure comprising several defect-based quantum bits will be developed, under realistic assumptions about its design and its environment. Based on this description, a numerical model of the system will be built, which will allow to make quantitative predictions of the behaviour of the QR in the presence of the external signal, controls, and ambient noise. The model will be used to simulate the QR in a wide range of parameters in order to find the optimal design parameters and the regime of its operation (D3.1-3), and to train the software-implemented neural network (D4.1).
Quantitative model of superconducting QR (opens in new window)A mathematical description of a quantum reservoir (QR) structure comprising several superconducting quantum bits will be developed, under realistic assumptions about its design and its environment. Based on this description, a numerical model of the system will be built, which will allow to make quantitative predictions of the behaviour of the QR in the presence of the external signal, controls, and ambient noise. The model will be used to simulate the QR in a wide range of parameters in order to find the optimal design parameters and the regime of its operation (D2.1-4), and to train the software-implemented neural network (D4.1).
Dissemination and communication plan - initial version (opens in new window)A report documenting the Dissemination and Communication Plan over the course of the project.
A 5-qubit superconducting QR will be designed and fabricated, tested and characterised. Results will be analysed and reported to improve the quantitative superconducting QR model (D1.3).
Software implementation of neural network for QRC (opens in new window)A numerical model of a neural network for the processing of a QR output will be developed. Corresponding software will be developed and tested using the inputs from quantitative models as well as from actual experimental QR implementations.
Publications
Author(s):
Didier Felbacq, Emmanuel Rousseau, Emmanuel Kling
Published in:
Active Photonic Platforms (APP), 2024
Publisher:
Active Photonic Platforms (APP)
DOI:
10.1117/12.3027578
Author(s):
Finlay Potter, Alexandre Zagoskin, Sergey Savel'ev, Alexander G. Balanov
Published in:
Physical Review A, Issue 110, 2024, ISSN 2469-9926
Publisher:
American Physical Society (APS)
DOI:
10.1103/PhysRevA.110.042604
Author(s):
Finlay Potter, Alexandre Zagoskin, Sergey Savel'ev, Alexander G. Balanov
Published in:
Physical Review A, Issue 110, 2024, ISSN 2469-9926
Publisher:
American Physical Society (APS)
DOI:
10.1103/PHYSREVA.110.042604
Author(s):
Anton Pershin, András Tárkányi, Vladimir Verkhovlyuk, Viktor Ivády, Adam Gali
Published in:
2025
Publisher:
arXivLabs
DOI:
10.48550/ARXIV.2501.00180
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