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Quantum machine learning has emerged as a promising utilization of near-term quantum computation devices.
The maximum principle in the theory of optimal processes of control
V.G. Boltyanski, R.V. Gamkrelidze, E.F. Mishchenko, and L.S. Pontryagin · 1960
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Ising model in a transverse field. i. basic theory
R B Stinchcombe · 1973
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Relation between quantum computing and quantum controllability
Viswanath Ramakrishna and Herschel Rabitz · 1996
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Complete controllability of quantum systems
S. G. Schirmer, H. Fu, and A. I. Solomon · 2001
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Optimal control of coupled spin dynamics: design of nmr pulse sequences by gradient ascent algorithms
Navin Khaneja, Timo Reiss, Cindie Kehlet, Thomas Schulte-Herbrüggen, and Steffen J. Glaser · 2005
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A fourier-coefficient based solution of an optimal control problem in quantum chemistry
Katharina Kormann, Sverker Holmgren, and Hans O. Karlsson · 2010
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Permutationally invariant quantum tomography
G. Tóth, W. Wieczorek, D. Gross, R. Krischek, C. Schwemmer, and H. Weinfurter · 2010
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Efficient quantum state tomography
Marcus Cramer, Martin B. Plenio, Steven T. Flammia, Rolando Somma, David Gross, Stephen D. Bartlett, Olivier Landon-Cardinal, David Poulin, and Yi-Kai Liu · 2010
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Optimal control technique for many-body quantum dynamics
Patrick Doria, Tommaso Calarco, and Simone Montangero · 2011
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Chopped random-basis quantum optimization
Tommaso Caneva, Tommaso Calarco, and Simone Montangero · 2011
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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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The quest for a quantum neural network
Maria Schuld, Ilya Sinayskiy, and Francesco Petruccione · 2014
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Information theoretical analysis of quantum optimal control
S. Lloyd and S. Montangero · 2014
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Precise qubit control beyond the rotating wave approximation
Jochen Scheuer, Xi Kong, Ressa S Said, Jeson Chen, Andrea Kurz, Luca Marseglia, Jiangfeng Du, Philip R Hemmer, Simone Montangero, Tommaso Calarco, Boris Naydenov, and Fedor Jelezko · 2014
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Progress towards practical quantum variational algorithms
Dave Wecker, Matthew B. Hastings, and Matthias Troyer · 2015
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Training schrödinger’s cat: quantum optimal control
Steffen J. Glaser, Ugo Boscain, Tommaso Calarco, Christiane P. Koch, Walter Köckenberger, Ronnie Kosloff, Ilya Kuprov, Burkhard Luy, Sophie Schirmer, Thomas Schulte-Herbrüggen, Dominique Sugny, and Frank K. Wilhelm · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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The theory of variational hybrid quantum-classical algorithms
Jarrod R McClean, Jonathan Romero, Ryan Babbush, and Alán Aspuru-Guzik · 2016
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Local random quantum circuits are approximate polynomial-designs
Fernando G. S. L. Brandão, Aram W. Harrow, and Michał Horodecki · 2016
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Quantum machine learning
Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, and Seth Lloyd · 2017
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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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Optimizing variational quantum algorithms using pontryagin’s minimum principle
Zhi-Cheng Yang, Armin Rahmani, Alireza Shabani, Hartmut Neven, and Claudio Chamon · 2017
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Quantum Computing in the NISQ era and beyond
John Preskill · 2018
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Quantum circuit learning
K. Mitarai, M. Negoro, M. Kitagawa, and K. Fujii · 2018
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Tunable, flexible, and efficient optimization of control pulses for practical qubits
Shai Machnes, Elie Assémat, David Tannor, and Frank K. Wilhelm · 2018
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Reinforcement learning in different phases of quantum control
Marin Bukov, Alexandre G. R. Day, Dries Sels, Phillip Weinberg, Anatoli Polkovnikov, and Pankaj Mehta · 2018
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Barren plateaus in quantum neural network training landscapes
Jarrod R. McClean, Sergio Boixo, Vadim N. Smelyanskiy, Ryan Babbush, and Hartmut Neven · 2018
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From the quantum approximate optimization algorithm to a quantum alternating operator ansatz
Stuart Hadfield, Zhihui Wang, Bryan O’Gorman, Eleanor G. Rieffel, Davide Venturelli, and Rupak Biswas · 2019
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Quantum convolutional neural networks
Quantum-optimal-control-inspired ansatz for variational quantum algorithms
Alexandre Choquette, Agustin Di Paolo, Panagiotis Kl. Barkoutsos, David Sénéchal, Ivano Tavernelli, and Alexandre Blais · 2021
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Noise-induced barren plateaus in variational quantum algorithms
Samson Wang, Enrico Fontana, M. Cerezo, Kunal Sharma, Akira Sone, Lukasz Cincio, and Patrick J. Coles · 2021
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Entanglement-induced barren plateaus
Carlos Ortiz Marrero, Mária Kieferová, and Nathan Wiebe · 2021
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Entanglement devised barren plateau mitigation
Taylor L. Patti, Khadijeh Najafi, Xun Gao, and Susanne F. Yelin · 2021
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Large gradients via correlation in random parameterized quantum circuits
Tyler Volkoff and Patrick J Coles · 2021
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Cost function dependent barren plateaus in shallow parametrized quantum circuits
M. Cerezo, Akira Sone, Tyler Volkoff, Lukasz Cincio, and Patrick J. Coles · 2021
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Iris Cong, Soonwon Choi, and Mikhail D. Lukin · 2019
Cited alongside, same era.
Quantum-assisted quantum compiling
Sumeet Khatri, Ryan LaRose, Alexander Poremba, Lukasz Cincio, Andrew T. Sornborger, and Patrick J. Coles · 2019
Cited alongside, same era.
Universal quantum control through deep reinforcement learning
Murphy Yuezhen Niu, Sergio Boixo, Vadim N. Smelyanskiy, and Hartmut Neven · 2019
Cited alongside, same era.
Generalized unitary coupled cluster wave functions for quantum computation
Joonho Lee, William J. Huggins, Martin Head-Gordon, and K. Birgitta Whaley · 2019
Cited alongside, same era.
Variational quantum state diagonalization
Ryan LaRose, Arkin Tikku, Étude O’Neel-Judy, Lukasz Cincio, and Patrick J. Coles · 2019
Cited alongside, same era.
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
Cited alongside, same era.
Training deep quantum neural networks
Kerstin Beer, Dmytro Bondarenko, Terry Farrelly, Tobias J. Osborne, Robert Salzmann, Daniel Scheiermann, and Ramona Wolf · 2020
Cited alongside, same era.
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On barren plateaus and cost function locality in variational quantum algorithms
A V Uvarov and J D Biamonte · 2021
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Classical shadows for quantum process tomography on near-term quantum computers, 2021
Ryan Levy, Di Luo, and Bryan K. Clark · 2021
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Challenges and opportunities in quantum machine learning
M. Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, and Patrick J. Coles · 2022
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Noisy intermediate-scale quantum algorithms
Kishor Bharti, Alba Cervera-Lierta, Thi Ha Kyaw, Tobias Haug, Sumner Alperin-Lea, Abhinav Anand, Matthias Degroote, Hermanni Heimonen, Jakob S. Kottmann, Tim Menke, Wai-Keong Mok, Sukin Sim, Leong-Chuan Kwek, and Alán Aspuru-Guzik · 2022
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Trainability of dissipative perceptron-based quantum neural networks
Kunal Sharma, M. Cerezo, Lukasz Cincio, and Patrick J. Coles · 2022
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Quantum optimal control in quantum technologies. strategic report on current status, visions and goals for research in europe
Christiane P. Koch, Ugo Boscain, Tommaso Calarco, Gunther Dirr, Stefan Filipp, Steffen J. Glaser, Ronnie Kosloff, Simone Montangero, Thomas Schulte-Herbrüggen, Dominique Sugny, and Frank K. Wilhelm · 2022
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Diagnosing Barren Plateaus with Tools from Quantum Optimal Control
Martin Larocca, Piotr Czarnik, Kunal Sharma, Gopikrishnan Muraleedharan, Patrick J. Coles, and M. Cerezo · 2022
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Equivalence of quantum barren plateaus to cost concentration and narrow gorges
Andrew Arrasmith, Zoë Holmes, M Cerezo, and Patrick J Coles · 2022
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Quantum variational algorithms are swamped with traps
Eric R. Anschuetz and Bobak T. Kiani · 2022
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Connecting ansatz expressibility to gradient magnitudes and barren plateaus
Zoë Holmes, Kunal Sharma, M. Cerezo, and Patrick J. Coles · 2022
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Optimizing quantum control pulses with complex constraints and few variables through autodifferentiation
Yao Song, Junning Li, Yong-Ju Hai, Qihao Guo, and Xiu-Hao Deng · 2022
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Performance comparison of optimization methods on variational quantum algorithms
Xavier Bonet-Monroig, Hao Wang, Diederick Vermetten, Bruno Senjean, Charles Moussa, Thomas Bäck, Vedran Dunjko, and Thomas E. O’Brien · 2023
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Critical points in quantum generative models, 2023
Eric R. Anschuetz · 2023
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Reduce&chop: Shallow circuits for deeper problems, 2023
Adrián Pérez-Salinas, Radoica Draškić, Jordi Tura, and Vedran Dunjko · 2023
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Hamiltonian variational ansatz without barren plateaus, 2023
Chae-Yeun Park and Nathan Killoran · 2023
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Out-of-distribution generalization for learning quantum dynamics
Matthias C. Caro, Hsin-Yuan Huang, Nicholas Ezzell, Joe Gibbs, Andrew T. Sornborger, Lukasz Cincio, Patrick J. Coles, and Zoë Holmes · 2023
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