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X. Wang, Wilde, M. M., and Su, Y., “Efficiently computable bounds for magic state distillation”, Phys. Rev. Lett. , vol. 124, no. 090505, 2020.
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.
C. - H. Wang and Taylor, J. M., “Optomechanical approach to controlling the temperature and chemical potential of light”, Phys. Rev. A 97, 033850, 2018.
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.
C. - H. Wang and Taylor, J. M., “A Quantum Model for an Entropic Spring”, Physical Review B, vol. 93, no. 21, p. 214102, 2016.
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, Tran, M. C., and Taylor, J. M., “Quantum simulation of ferromagnetic Heisenberg model”, 2017.
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.
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.
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.
G. Wang, “Efficient quantum algorithms for analyzing large sparse electrical networks”, Quantum Information & Computation, vol. 17, no. 11&12, pp. 987-1026, 2017.
X. Wang and Wilde, M. M., “α-Logarithmic negativity”, 2019.
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 Algorithms for Curve Fitting”, 2014.
Y. Wang, Gullans, M., Na, X., Whitsitt, S., and Gorshkov, A. V., “Universal scattering with general dispersion relations”, Phys. Rev. Research, vol. 4, 2022.
D. Wang, Higgott, O., and Brierley, S., “Accelerated Variational Quantum Eigensolver”, Phys. Rev. Lett. , vol. 122, no. 140504 , 2019.
G. Wang, “Quantum Algorithm for Linear Regression”, Physical Review A, vol. 96, p. 012335, 2017.
Y. Wang, Gullans, M., Browaeys, A., Porto, J. V., Chang, D. E., and Gorshkov, A. V., “Single-photon bound states in atomic ensembles”, 2018.
X. Wang and Wilde, M. M., “Resource theory of asymmetric distinguishability for quantum channels”, 2019.
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.
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.
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.
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.