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The preparation of quantum Gibbs state is an essential part of quantum computation and has wide-ranging applications in various areas, including quantum simulation, quantum optimization, and quantum machine learning.
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Joran Van Apeldoorn, András Gilyén, Sander Gribling, and Ronald de Wolf, “Quantum sdp-solvers: Better upper and lower bounds,” Quantum 4
2020
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Carlos Bravo-Prieto, Ryan LaRose, Marco Cerezo, Yigit Subasi, Lukasz Cincio, and Patrick Coles, “Variational quantum linear solver: A hybrid algorithm for linear systems,” Bulletin of the American Physical Society 65
2020
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2020
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Guillaume Verdon, Jacob Marks, Sasha Nanda, Stefan Leichenauer, and Jack Hidary, “Quantum hamiltonian-based models and the variational quantum thermalizer algorithm,” Bulletin of the American Physical Society 65
2020
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Xiaosi Xu, Jinzhao Sun, Suguru Endo, Ying Li, Simon C Benjamin, and Xiao Yuan, “Variational algorithms for linear algebra,” Science Bulletin 66
2021
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G. Li, Z. Song, and X. Wang, “VSQL: Variational shadow quantum learning for classification,” (2021)
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