Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Seyed Shakib Vedaie"'
Publikováno v:
Physical Review Research, Vol 5, Iss 2, p 023098 (2023)
Two-qubit gate performance is vital for scaling up ion-trap quantum computing. Optimized quantum control is needed to achieve reductions in gate duration and gate error rate. We describe two-qubit gates with addressed Raman beams within a linear trap
Externí odkaz:
https://doaj.org/article/8bbf7ecb45f84a19b74867cfcd35009c
Two-qubit gate performance is vital for scaling up ion-trap quantum computing. Optimized quantum control is needed to achieve reductions in gate-time and gate error-rate. We describe two-qubit gates with addressed Raman beams within a linear trapped-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17afb8dc36c9e72cd5587c9103a4fec2
Autor:
Inderpreet Singh, Jaspreet S. Oberoi, Ehsan Zahedinejad, Daniel Crawford, Seyed Shakib Vedaie, Barry C. Sanders, Moslem Noori
Publikováno v:
Physical Review Applied. 14
Quantum information processing is likely to have a far-reaching impact in the field of artificial intelligence. Noisy, intermediate-scale quantum devices provide a platform for exploring the possibility of attaining a quantum advantage through hybrid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::42e0b8586cb4b283fda3f716801f49ba
https://doi.org/10.1103/physrevapplied.14.034034
https://doi.org/10.1103/physrevapplied.14.034034
Publikováno v:
2018 IEEE Photonics Society Summer Topical Meeting Series (SUM).
We develop reinforcement learning as a tool for classical and quantum control, which we treat in a unified framework. Our reinforcement-learning approach yields robust quantum metrology policies that beat the standard quantum limit.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1792f76ac38376cf3a218d209634d9e3
https://doi.org/10.1109/phosst.2018.8456754
https://doi.org/10.1109/phosst.2018.8456754
Publikováno v:
Imaging and Applied Optics 2018 (3D, AO, AIO, COSI, DH, IS, LACSEA, LS&C, MATH, pcAOP).
We develop a framework for relating adaptive optical quantum-enhanced metrology, quantum control and reinforcement learning together, and we use these connections to use reinforcement learning methods for determining policies that beat the standard q
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5d04bef7079f246aad08f4b278cd7322
https://doi.org/10.1364/lsc.2018.stu5h.4
https://doi.org/10.1364/lsc.2018.stu5h.4