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D. Wang, You, X., Li, T., and Childs, A. M., “Quantum exploration algorithms for multi-armed bandits”, Proceedings of the 35th Conference on Artificial Intelligence (AAAI 2021), vol. 35, no. 11, pp. 10102-10110, 2021.
Y. Wang, Gullans, M., Na, X., Whitsitt, S., and Gorshkov, A. V., “Universal scattering with general dispersion relations”, Phys. Rev. Research, vol. 4, 2022.
C. - H. Wang and Taylor, J. M., “Landauer formulation of photon transport in driven systems”, Physical Review B, vol. 94, no. 15, p. 155437, 2016.
Y. Wang, Subhankar, S., Bienias, P., Lacki, M., Tsui, T. - C., Baranov, M. A., Gorshkov, A. V., Zoller, P., Porto, J. V., and Rolston, S. L., “Dark state optical lattice with sub-wavelength spatial structure”, Phys. Rev. Lett., vol. 120, p. 083601, 2018.
Y. Wang, Gullans, M., Na, X., and Gorshkov, A. V., “Universality in one-dimensional scattering with general dispersion relations”, Phys. Rev. Res., vol. 4, 2022.
S. Wang, Fontana, E., Cerezo, M., Sharma, K., Sone, A., Cincio, L., and Coles, P. J., “Noise-induced barren plateaus in variational quantum algorithms”, Nature Communications, vol. 12, p. 6961, 2021.
Q. Wang, Li, M., Monroe, C., and Nam, Y., “Resource-Optimized Fermionic Local-Hamiltonian Simulation on Quantum Computer for Quantum Chemistry”, Quantum, vol. 5, no. 509, 2021.
Q. Wang, Cian, Z. - P., Li, M., Markov, I. L., and Nam, Y., “Ever more optimized simulations of fermionic systems on a quantum computer”, 2023.
C. - H. Wang and Taylor, J. M., “A Quantum Model for an Entropic Spring”, Physical Review B, vol. 93, no. 21, p. 214102, 2016.
C. - H. Wang and Taylor, J. M., “Optomechanical approach to controlling the temperature and chemical potential of light”, Phys. Rev. A 97, 033850, 2018.
X. Wang and Wilde, M. M., “α-Logarithmic negativity”, 2019.
C. - H. Wang, Gullans, M., Porto, J. V., Phillips, W. D., and Taylor, J. M., “Bose Condensation of Photons Thermalized via Laser Cooling of Atoms”, 2018.
C. - H. Wang, Gullans, M., Porto, J. V., Phillips, W. D., and Taylor, J. M., “Photon thermalization via laser cooling of atoms”, Phys. Rev. A 98, 013834, 2018.
Y. Wang, Tran, M. C., and Taylor, J. M., “Quantum simulation of ferromagnetic Heisenberg model”, 2017.
D. Wang, Higgott, O., and Brierley, S., “Accelerated Variational Quantum Eigensolver”, Phys. Rev. Lett. , vol. 122, no. 140504 , 2019.
G. Wang, “Quantum Algorithms for Curve Fitting”, 2014.
X. Wang and Wilde, M. M., “Resource theory of asymmetric distinguishability for quantum channels”, 2019.
G. Wang, “Efficient quantum algorithms for analyzing large sparse electrical networks”, Quantum Information & Computation, vol. 17, no. 11&12, pp. 987-1026, 2017.
D. Wang, “Simulating quantum circuits by classical circuits”, 2019.
X. Wang, Wilde, M. M., and Su, Y., “Quantifying the magic of quantum channels”, New Journal of Physics, vol. 21, no. 103002, 2019.
X. Wang and Wilde, M. M., “Exact entanglement cost of quantum states and channels under PPT-preserving operations”, 2018.
X. Wang, Wilde, M. M., and Su, Y., “Efficiently computable bounds for magic state distillation”, Phys. Rev. Lett. , vol. 124, no. 090505, 2020.
D. Wang, Sundaram, A., Kothari, R., Kapoor, A., and Roetteler, M., “Quantum Algorithms for Reinforcement Learning with a Generative Model”, Proceedings of the 38th International Conference on Machine Learning, PMLR, vol. 139, 2021.
G. Wang, “Quantum Algorithm for Linear Regression”, Physical Review A, vol. 96, p. 012335, 2017.
P. Walther, Eisaman, M. D., Nemiroski, A., Gorshkov, A. V., Zibrov, A. S., Zeilinger, A., and Lukin, M. D., “Multi-photon Entanglement: From Quantum Curiosity to Quantum Computing and Quantum Repeaters”, Proc. SPIE, vol. 6664, p. 66640G, 2007.