Grape Algorithm
The GRAPE Algorithm is a quantum optimal control method that iteratively computes control pulses by maximizing a fidelity functional through gradient ascent, distinguishing itself from other control techniques by its explicit discretization of the control fields and efficient evaluation of gradients over the entire time evolution.
31
Publications
1.5K
Citations
99
Authors
60
Institutions
Publications per year
2017–2026
22
Parents
31
Learning robust and high-precision quantum controls
Re-Bing Wu, Haijin Ding, Daoyi Dong et al. · Physical review. A/Physical review, A · 2019 · 122 citations · Full text
Computing, Computer Science, Physics +15
Handling Missing Data with Graph Representation Learning
Jiaxuan You, Xiaobai Ma, Daisy Yi Ding et al. · arXiv (Cornell University) · 2020 · 94 citations · Full text
Georg Jäger, Daniel M. Reich, Michael H. Goerz et al. · Physical Review A · 2014 · 79 citations · Full text
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60
Tsinghua University
Beijing, China
6 h-index
16 publications
983 citations
Princeton University
Princeton, United States
3 h-index
7 publications
233 citations

Aarhus University
Aarhus, Denmark
3 h-index
8 publications
458 citations
Beijing Academy of Quantum Information Sciences
Beijing, China
3 h-index
9 publications
787 citations
University of Southampton
Southampton, United Kingdom
3 h-index
8 publications
497 citations
Hefei National Center for Physical Sciences at Nanoscale
Hefei, China
2 h-index
3 publications
65 citations
University of Science and Technology of China
Hefei, China
2 h-index
9 publications
167 citations
Technical University of Munich
Munich, Germany
2 h-index
6 publications
843 citations
1–8 of 60
PRA · 13 publications · 569 citations
13
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PRA · 4 publications · 381 citations
4
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1 publications · 34 citations
1
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1 publications · 57 citations
1
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Conference · 1 publications · 11 citations
1
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