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Quantum computers and simulators may offer significant advantages over their classical counterparts, providing insights into quantum many-body systems and possibly improving performance for solving exponentially hard problems, such as optimization and satisfiability.
Ground-state energy estimation of the water molecule on a trapped ion quantum computer
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Classical and Quantum Bounded Depth Approximation Algorithms
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Quantum annealing: a journey through digitalization, control, and hybrid quantum variational schemes (2019)
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Quantum annealing in the transverse Ising model
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Experimental issues in coherent quantum-state manipulation of trapped atomic ions
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A quantum adiabatic evolution algorithm applied to random instances of an np-complete problem
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Effective Quantum Spin Systems with Trapped Ions
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Arbitrarily accurate composite pulse sequences
Brown, K. R., Harrow, A. W. & Chuang, I. L · 2004
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Manipulation and detection of a trapped yb + {\mathrm{yb}}^{+} hyperfine qubit
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Quantum Computation and Quantum Information: 10th Anniversary Edition (Cambridge University Press, New York, NY, USA, 2011), 10th edn
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Advances in quantum metrology
Giovannetti, V., Lloyd, S. & Maccone, L · 2011
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Entanglement entropy for the long-range ising chain in a transverse field
Koffel, T., Lewenstein, M. & Tagliacozzo, L · 2012
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Obstructions To Classically Simulating The Quantum Adiabatic Algorithm
Hastings, M. B. & Freedman, M. H · 2013
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Experimental performance of a quantum simulator: Optimizing adiabatic evolution and identifying many-body ground states
Richerme, P. et al · 2013
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A Quantum Approximate Optimization Algorithm
Farhi, E., Goldstone, J. & Gutmann, S · 2014
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A Quantum Approximate Optimization Algorithm Applied to a Bounded Occurrence Constraint Problem
Farhi, E., Goldstone, J. & Gutmann, S · 2014
Quantum approximate optimization is computationally universal
Lloyd, S · 2018
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Quantum Computing in the NISQ era and beyond
Preskill, J · 2018
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Zhou, L., Wang, S.-T., Choi, S., Pichler, H. & Lukin, M. D · 2018
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Bang-bang control as a design principle for classical and quantum optimization algorithms
Bapat, A. & Jordan, S · 2018
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A universal training algorithm for quantum deep learning
Verdon, G., Pye, J. & Broughton, M · 2018
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Quantum dynamics of cold trapped ions with application to quantum computation
James, D. F. V · 2014
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The theory of variational hybrid quantum-classical algorithms
McClean, J. R., Romero, J., Babbush, R. & Aspuru-Guzik, A · 2016
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Quantum supremacy through the quantum approximate optimization algorithm
Farhi, E. & Harrow, A. W · 2016
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Nonperturbative calculation of phonon effects on spin squeezing
Dylewsky, D., Freericks, J., Wall, M., Rey, A. & Foss-Feig, M · 2016
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Average-case complexity versus approximate simulation of commuting quantum computations
Bremner, M. J., Montanaro, A. & Shepherd, D. J · 2016
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Certification of Boson Sampling Devices with Coarse-Grained Measurements
Wang, S.-T. & Duan, L.-M · 2016
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Near-optimal quantum circuit for grover’s unstructured search using a transverse field
Jiang, Z., Rieffel, E. G. & Wang, Z · 2017
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Quantum approximate optimization algorithm for maxcut: A fermionic view
Wang, Z., Hadfield, S., Jiang, Z. & Rieffel, E. G · 2018
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Performance of the quantum approximate optimization algorithm on the maximum cut problem
Crooks, G. E · 2018
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Ho, W. W., Jonay, C. & Hsieh, T. H · 2018
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Open source matrix product states: Opening ways to simulate entangled many-body quantum systems in one dimension
Jaschke, D., Wall, M. L. & Carr, L. D · 2018
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Quantum algorithms for scientific computing and approximate optimization
Hadfield, S · 2018
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Quantum chemistry calculations on a trapped-ion quantum simulator
Hempel, C. et al · 2018
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in preparation (2019)
Brady, L., Bapat, A. & Gorshkov, A · 2019
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Efficient variational simulation of non-trivial quantum states
Ho, W. W. & Hsieh, T. H · 2019
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Cryogenic trapped-ion system for large scale quantum simulation
Pagano, G. et al · 2019
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On the complexity and verification of quantum random circuit sampling
Bouland, A., Fefferman, B., Nirkhe, C. & Vazirani, U · 2019
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