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Variational quantum algorithms are ubiquitous in applications of noisy intermediate-scale quantum computers.
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“Quantum analytic descent” (2020)
Bálint Koczor and Simon C. Benjamin · 2008
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“Variational Hamiltonian diagonalization for dynamical quantum simulation” (2020)
Benjamin Commeau, Marco Cerezo, Zoë Holmes, Lukasz Cincio, Patrick J. Coles, and Andrew Sornborger · 2009
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“A variational eigenvalue solver on a photonic quantum processor”
Alberto Peruzzo, Jarrod McClean, Peter Shadbolt, Man-Hong Yung, Xiao-Qi Zhou, Peter J. Love, Alán Aspuru-Guzik, and Jeremy L. O’Brien · 2014
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“Hybrid quantum-classical approach to quantum optimal control”
Jun Li, Xiaodong Yang, Xinhua Peng, and Chang-Pu Sun · 2017
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“Quantum autoencoders for efficient compression of quantum data”
Jonathan Romero, Jonathan P. Olson, and Alan Aspuru-Guzik · 2017
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“A quantum algorithm to train neural networks using low-depth circuits” (2017)
Guillaume Verdon, Michael Broughton, and Jacob Biamonte · 2017
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“Automatic differentiation in PyTorch”
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
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Ying Li and Simon C. Benjamin · 2017
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“Quantum circuit learning”
Kosuke Mitarai, Makoto Negoro, Masahiro Kitagawa, and Keisuke Fujii · 2018
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“Hierarchical quantum classifiers”
Edward Grant, Marcello Benedetti, Shuxiang Cao, Andrew Hallam, Joshua Lockhart, Vid Stojevic, Andrew G. Green, and Simone Severini · 2018
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“Differentiable learning of quantum circuit Born machines”
Jin-Guo Liu and Lei Wang · 2018
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“Automatic differentiation in machine learning: a survey”
Atılım Güneş Baydin, Barak A. Pearlmutter, Alexey Andreyevich Radul, and Jeffrey Mark Siskind · 2018
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Javier Gil Vidal and Dirk Oliver Theis · 2018
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Seth Lloyd · 2018
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“Quantum approximate optimization algorithm for MaxCut: A fermionic view”
Zhihui Wang, Stuart Hadfield, Zhang Jiang, and Eleanor G. Rieffel · 2018
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“Quantum natural gradient”
James Stokes, Josh Izaac, Nathan Killoran, and Giuseppe Carleo · 2020
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“Avoiding local minima in variational quantum eigensolvers with the natural gradient optimizer”
David Wierichs, Christian Gogolin, and Michael Kastoryano · 2020
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“On the universality of the quantum approximate optimization algorithm”
Mauro E. S. Morales, Jacob D. Biamonte, and Zoltán Zimborás · 2020
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“Quantum approximate optimization algorithm: Performance, mechanism, and implementation on near-term devices”
Leo Zhou, Sheng-Tao Wang, Soonwon Choi, Hannes Pichler, and Mikhail D. Lukin · 2020
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“Quantum circuits with many photons on a programmable nanophotonic chip”
J.M. Arrazola, V. Bergholm, K. Brádler, T.R. Bromley, M.J. Collins, I. Dhand, A. Fumagalli, T. Gerrits, A. Goussev, L.G. Helt, J. Hundal, T. Isacsson, R.B. Israel, J. Izaac, S. Jahangiri, R. Janik, N. Killoran, S.P. Kumar, J. Lavoie, A.E. Lita, D.H. Mahler, M. Menotti, B. Morrison, S.W. Nam, L. Neuhaus, H.Y. Qi, N. Quesada, A. Repingon, K.K. Sabapathy, M. Schuld, D. Su, J. Swinarton, A. Száva, K. Tan, P. Tan, V.D. Vaidya, Z. Vernon, Z. Zabaneh, and Y. Zhang · 2021
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Marcello Benedetti, Erika Lloyd, Stefan Sack, and Mattia Fiorentini · 2019
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Tyson Jones, Suguru Endo, Sam McArdle, Xiao Yuan, and Simon C. Benjamin · 2019
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Harper R. Grimsley, Sophia E. Economou, Edwin Barnes, and Nicholas J. Mayhall · 2019
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Ryan LaRose, Arkin Tikku, Étude O’Neel-Judy, Lukasz Cincio, and Patrick J. Coles · 2019
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code: balintkoczor/quantum-analytic-descent
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