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F
P. C. Maurer, Maze, J. R., Stanwix, P. L., Jiang, L., Gorshkov, A. V., Zibrov, A. A., Harke, B., Hodges, J. S., Zibrov, A. S., Yacoby, A., Twitchen, D., Hell, S. W., Walsworth, R. L., and Lukin, M. D., “Far-field optical imaging and manipulation of individual spins with nanoscale resolution”, Nature Phys., vol. 6, p. 912, 2010.
P. C. Maurer, Maze, J. R., Stanwix, P. L., Jiang, L., Gorshkov, A. V., Zibrov, A. A., Harke, B., Hodges, J. S., Zibrov, A. S., Yacoby, A., Twitchen, D., Hell, S. W., Walsworth, R. L., and Lukin, M. D., “Far-field optical imaging and manipulation of individual spins with nanoscale resolution”, Nature Phys., vol. 6, p. 912, 2010.
J. Zhou, Criswell, J., and Hicks, M., “Fat Pointers for Temporal Memory Safety of C”, Proceedings of the ACM on Programming Languages, vol. 7, no. 1, pp. 316-347, 2023.
L. Egan, Debroy, D. M., Noel, C., Risinger, A., Zhu, D., Biswas, D., Newman, M., Li, M., Brown, K. R., Cetina, M., and Monroe, C., “Fault-Tolerant Operation of a Quantum Error-Correction Code”, 2020.
E. Zeuthen, Schliesser, A., Sørensen, A. S., and Taylor, J. M., “Figures of merit for quantum transducers”, 2016.
J. Chen, Ji, Z., Zeng, B., and Zhou, D. L., “From Ground States to Local Hamiltonians”, Physical Review A, vol. 86, no. 2, 2012.
J. Chen, Ji, Z., Zeng, B., and Zhou, D. L., “From Ground States to Local Hamiltonians”, Physical Review A, vol. 86, no. 2, 2012.
G
M. C. Tran, Zuppardo, M., de Rosier, A., Knips, L., Laskowski, W., Paterek, T., and Weinfurter, H., “Genuine N -partite entanglement without N -partite correlation functions”, Physical Review A, vol. 95, no. 6, p. 062331, 2017.
J. Chen, Ji, Z., Kribs, D., Wei, Z., and Zeng, B., “Ground-State Spaces of Frustration-Free Hamiltonians”, Journal of Mathematical Physics, vol. 53, no. 10, p. 102201, 2012.
H
Q. Zhao, Zhou, Y., Shaw, A. F., Li, T., and Childs, A. M., “Hamiltonian simulation with random inputs”, Phys. Rev. Lett. 129, 270502, vol. 129, no. 270502, 2022.
Q. Zhao, Zhou, Y., Shaw, A. F., Li, T., and Childs, A. M., “Hamiltonian simulation with random inputs”, Phys. Rev. Lett. 129, 270502, vol. 129, no. 270502, 2022.
M. Russ, Zajac, D. M., Sigillito, A. J., Borjans, F., Taylor, J. M., Petta, J. R., and Burkard, G., “High-fidelity quantum gates in Si/SiGe double quantum dots”, Physical Review B, vol. 97, no. 8, p. 085421, 2018.
I
A. Zabalo, Wilson, J. H., Gullans, M., Vasseur, R., Gopalakrishnan, S., Huse, D. A., and Pixley, J. H., “Infinite-randomness criticality in monitored quantum dynamics with static disorder”, 2022.
N. M. Sundaresan, Lundgren, R., Zhu, G., Gorshkov, A. V., and Houck, A. A., “Interacting Qubit-Photon Bound States with Superconducting Circuits”, Phys. Rev. , vol. X 9, no. 011021, 2019.
D. Zhu, Kahanamoku-Meyer, G. D., Lewis, L., Noel, C., Katz, O., Harraz, B., Wang, Q., Risinger, A., Feng, L., Biswas, D., Egan, L., Gheorghiu, A., Nam, Y., Vidick, T., Vazirani, U., Yao, N. Y., Cetina, M., and Monroe, C., “Interactive Protocols for Classically-Verifiable Quantum Advantage”, 2021.
J
J. Chen, Guo, C., Ji, Z., Poon, Y. - T., Yu, N., Zeng, B., and Zhou, J., “Joint product numerical range and geometry of reduced density matrices”, 2016.
J. Chen, Guo, C., Ji, Z., Poon, Y. - T., Yu, N., Zeng, B., and Zhou, J., “Joint product numerical range and geometry of reduced density matrices”, 2016.
L
D. Bluvstein, Evered, S. J., Geim, A. A., Li, S. H., Zhou, H., Manovitz, T., Ebadi, S., Cain, M., Kalinowski, M., Hangleiter, D., J. Ataides, P. Bonilla, Maskara, N., Cong, I., Gao, X., Rodriguez, P. Sales, Karolyshyn, T., Semeghini, G., Gullans, M., Greiner, M., Vuletic, V., and Lukin, M. D., “Logical quantum processor based on reconfigurable atom arrays”, Nature, 2023.
M
W. Zhong, Gold, J. M., Marzen, S., England, J. L., and Halpern, N. Yunger, “Machine learning outperforms thermodynamics in measuring how well a many-body system learns a drive”, Scientific Reports, vol. 11, 2021.
S. S. Kalantre, Zwolak, J. P., Ragole, S., Wu, X., Zimmerman, N. M., Stewart, M. D., and Taylor, J. M., “Machine Learning techniques for state recognition and auto-tuning in quantum dots”, 2017.
S. S. Kalantre, Zwolak, J. P., Ragole, S., Wu, X., Zimmerman, N. M., Stewart, M. D., and Taylor, J. M., “Machine Learning techniques for state recognition and auto-tuning in quantum dots”, 2017.
T. Zolkin, Kharkov, Y., and Nagaitsev, S., “Machine-assisted discovery of integrable symplectic mappings”, 2022.
S. Guo, Fritsch, A. R., Greenberg, C., Spielman, I. B., and Zwolak, J. P., “Machine-learning enhanced dark soliton detection in Bose-Einstein condensates”, Mach. Learn.: Sci. Technol. , vol. 2, p. 035020, 2021.
H. Pichler, Zhu, G., Seif, A., Zoller, P., and Hafezi, M., “Measurement Protocol for the Entanglement Spectrum of Cold Atoms”, Phys. Rev. X , vol. 6(4), no. 041033, 2016.
H. Pichler, Zhu, G., Seif, A., Zoller, P., and Hafezi, M., “Measurement Protocol for the Entanglement Spectrum of Cold Atoms”, Phys. Rev. X , vol. 6(4), no. 041033, 2016.