Analog Quantum Optimization
Analog Quantum Optimization is an analog quantum computation paradigm that leverages continuous-time evolution of quantum states in a programmable energy landscape to solve combinatorial optimization problems by guiding the system toward its ground state.
10
Publications
960
Citations
32
Authors
21
Institutions
Publications per year
2017–2026
7
Parents
10
Adiabatic quantum optimization with the wrong Hamiltonian
Kevin Young, Robin Blume-Kohout, Daniel A. Lidar · Physical Review A · 2013 · 61 citations · Full text
Computing, Computer Science, Physics +15
Embedding Overhead Scaling of Optimization Problems in Quantum Annealing
Mario S. Könz, Wolfgang Lechner, Helmut G. Katzgraber et al. · PRX Quantum · 2021 · 37 citations · Full text
Michel Fabrice Serret, Bertrand Marchand, Thomas Ayral · Physical review. A/Physical review, A · 2020 · 32 citations · Full text
Computing, Computer Science, Physics +17
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32
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21
University of Southern California
Los Angeles, United States
1 h-index
1 publications
61 citations
1QBit
Vancouver, Canada
1 h-index
1 publications
17 citations
Microsoft (United States)
Redmond, United States
1 h-index
1 publications
37 citations
QLT (Canada)
Vancouver, Canada
1 h-index
1 publications
17 citations
Institute of Information Technologies
Sofia, Bulgaria
1 h-index
1 publications
17 citations
Sandia National Laboratories California
Livermore, United States
1 h-index
3 publications
183 citations
ETH Zurich
Zurich, Switzerland
1 h-index
2 publications
74 citations
École Polytechnique
Palaiseau, France
1 h-index
1 publications
32 citations
1–8 of 21
QST · 1 publications · 17 citations
1
h-index
Repository · 1 publications · 11 citations
1
h-index
1 publications · 37 citations
1
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PRA · 1 publications · 32 citations
1
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PRA · 1 publications · 61 citations
1
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1–5