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We propose an efficient method for simultaneously optimizing both the structure and parameter values of quantum circuits with only a small computational overhead.
Robert. Parrish, Joseph. Iosue, Asier Ozaeta and Peter. McMahon · 1904
Earlier work this paper cites.
“Quantum Computation with Ions in Thermal Motion”
Anders Srensen and Klaus Mlmer · 1971
Earlier work this paper cites.
“Multivariate stochastic approximation using a simultaneous perturbation gradient approximation”
J.. Spall · 1992
Earlier work this paper cites.
“Nonlinear Programming”
D.P. Bertsekas · 1999
Earlier work this paper cites.
“On the Finite Time Convergence of Cyclic Coordinate Descent Methods”, 2010
Ankan Saha and Ambuj Tewari · 2010
Earlier work this paper cites.
“A variational eigenvalue solver on a photonic quantum processor”
Alberto Peruzzo et al · 2014
Earlier work this paper cites.
“Adam: A Method for Stochastic Optimization”, 2014
Diederik. Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
“Coordinate descent algorithms”
Stephen Wright · 2015
Earlier work this paper cites.
“Quantum Algorithms for Fixed Qubit Architectures”, 2017
E. Farhi, J. Goldstone, S. Gutmann and H. Neven · 2017
Earlier work this paper cites.
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