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P
H. Fu, Wang, D., and Zhao, Q., Parallel self-testing of EPR pairs under computational assumptions, 2023.
H. Fu, Wang, D., and Zhao, Q., Parallel self-testing of EPR pairs under computational assumptions, 2023.
T. D. Ellison, Chen, Y. - A., Dua, A., Shirley, W., Tantivasadakarn, N., and Williamson, D. J., Pauli Stabilizer Models of Twisted Quantum Doubles, PRX Quantum, vol. 3, 2022.
T. D. Ellison, Chen, Y. - A., Dua, A., Shirley, W., Tantivasadakarn, N., and Williamson, D. J., Pauli topological subsystem codes from Abelian anyon theories, 2022.
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.
X. -song Ma, Dakic, B., Kropatsche, S., Naylor, W., Chan, Y. -hao, Gong, Z. - X., Duan, L. -ming, Zeilinger, A., and Walther, P., Photonic quantum simulation of ground state configurations of Heisenberg square and checkerboard lattice spin systems , 2012.
S. Zhu, Hung, S. - H., Chakrabarti, S., and Wu, X., On the Principles of Differentiable Quantum Programming Languages, 2020.
A. M. Childs and Wiebe, N., Product Formulas for Exponentials of Commutators, Journal of Mathematical Physics, vol. 54, no. 6, p. 062202, 2013.
E. Waks and Monroe, C., Protocol for Hybrid Entanglement Between a Trapped Atom and a Semiconductor Quantum Dot , Physical Review A, vol. 80, no. 6, 2009.
G. Pupillo, Rey, A. Maria, Williams, C. J., and Clark, C. W., Pseudo-fermionization of 1-D bosons in optical lattices, New Journal of Physics, vol. 8, no. 8, pp. 161 - 161, 2006.
Q
L. Li, Zhu, M., Cleaveland, R., Lee, Y., Chang, L., and Wu, X., Qafny: Quantum Program Verification Through Type-guided Classical Separation Logic, 2023.
J. P. Zwolak, Kalantre, S. S., Wu, X., Ragole, S., and Taylor, J. M., QFlow lite dataset: A machine-learning approach to the charge states in quantum dot experiments, PLOS ONE, vol. 13, no. 10, p. e0205844, 2018.
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, Wilde, M. M., and Su, Y., Quantifying the magic of quantum channels, New Journal of Physics, vol. 21, no. 103002, 2019.
S. - H. Hung, Hietala, K., Zhu, S., Ying, M., Hicks, M., and Wu, X., Quantitative Robustness Analysis of Quantum Programs (Extended Version), Proc. ACM Program. Lang., vol. 3, no. POPL, p. Article 31, 2018.
M. Jarret, Lackey, B., Liu, A., and Wan, K., Quantum adiabatic optimization without heuristics, 2018.
S. Chakrabarti, Childs, A. M., Hung, S. - H., Li, T., Wang, C., and Wu, X., Quantum algorithm for estimating volumes of convex bodies, ACM Transactions on Quantum Computing, 2023.
S. Chakrabarti, Childs, A. M., Hung, S. - H., Li, T., Wang, C., and Wu, X., Quantum algorithm for estimating volumes of convex bodies, ACM Transactions on Quantum Computing, 2023.
D. W. Berry, Childs, A. M., Ostrander, A., and Wang, G., Quantum algorithm for linear differential equations with exponentially improved dependence on precision, Communications in Mathematical Physics, vol. 356, no. 3, pp. 1057-1081, 2017.
G. Wang, Quantum Algorithm for Linear Regression, Physical Review A, vol. 96, p. 012335, 2017.
S. Chakrabarti, Childs, A. M., Li, T., and Wu, X., Quantum algorithms and lower bounds for convex optimization, Quantum, vol. 4, no. 221, 2020.
G. Wang, Quantum Algorithms for Curve Fitting, 2014.
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.
A. M. Childs, Li, T., Liu, J. - P., Wang, C., and Zhang, R., Quantum Algorithms for Sampling Log-Concave Distributions and Estimating Normalizing Constants, 2022.
A. F. Shaw, Lougovski, P., Stryker, J. R., and Wiebe, N., Quantum Algorithms for Simulating the Lattice Schwinger Model, Quantum, vol. 4, no. 306, 2020.