Optimizing quantum circuit placement via machine learning-Reference-Cited by-同舟云学术

Optimizing quantum circuit placement via machine learning

Published:2022-07-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 59th ACM/IEEE Design Automation Conference
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Author:

Fan Hongxiang¹,Guo Ce¹,Luk Wayne¹

Affiliation:

1. Imperial College London, London, UK

Funder

Engineering and Physical Sciences Research Council

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3489517.3530403

Reference38 articles.

1. Giovanni Acampora and Roberto Schiattarella . 2021. Deep neural networks for quantum circuit mapping. Neural Computing and Applications ( 2021 ), 1--21. Giovanni Acampora and Roberto Schiattarella. 2021. Deep neural networks for quantum circuit mapping. Neural Computing and Applications (2021), 1--21.

2. 2013. A meet-in-the-middle algorithm for fast synthesis of depth-optimal quantum circuits;Matthew Amy;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems,2013

3. Simulated Quantum Computation of Molecular Energies

4. Debjyoti Bhattacharjee et al. 2019. MUQUT: Multi-constraint quantum circuit mapping on NISQ computers . In 2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD). IEEE, 1--7. Debjyoti Bhattacharjee et al. 2019. MUQUT: Multi-constraint quantum circuit mapping on NISQ computers. In 2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD). IEEE, 1--7.

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