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D. M. Zajac, Sigillito, A. J., Russ, M., Borjans, F., Taylor, J. M., Burkard, G., and Petta, J. R., Resonantly driven CNOT gate for electron spins, Science, vol. 359, no. 6374, pp. 439-442, 2018.
E. Zeuthen, Schliesser, A., Sørensen, A. S., and Taylor, J. M., Figures of merit for quantum transducers, 2016.
E. Zeuthen, Schliesser, A., Taylor, J. M., and Sørensen, A. S., Electro-optomechanical equivalent circuits for quantum transduction, 2018.
E. Zeuthen, Gullans, M., Maghrebi, M. F., and Gorshkov, A. V., Correlated Photon Dynamics in Dissipative Rydberg Media, Physical Review Letters, vol. 119, no. 4, p. 043602, 2017.
B. Zhan, Kimmel, S., and Hassidim, A., Super-Polynomial Quantum Speed-ups for Boolean Evaluation Trees with Hidden Structure, ITCS '12 Proceedings of the 3rd Innovations in Theoretical Computer Science Conference, pp. 249-265, 2012.
Y. Zhang, Shalm, L. K., Bienfang, J. C., Stevens, M. J., Mazurek, M. D., Nam, S. Woo, Abellán, C., Amaya, W., Mitchell, M. W., Fu, H., Miller, C., Mink, A., and Knill, E., Experimental Low-Latency Device-Independent Quantum Randomness, Phys. Rev. Lett. , vol. 124, no. 010505, 2020.
C. Zhang, Leng, J., and Li, T., Quantum Algorithms for Escaping from Saddle Points, 2020.
Y. Zhang, Fu, H., and Knill, E., Efficient randomness certification by quantum probability estimation, Phys. Rev. Research , vol. 2, no. 013016, 2020.
J. Zhang, Pagano, G., Hess, P. W., Kyprianidis, A., Becker, P., Kaplan, H., Gorshkov, A. V., Gong, Z. - X., and Monroe, C., Observation of a Many-Body Dynamical Phase Transition with a 53-Qubit Quantum Simulator, Nature, vol. 551, pp. 601-604, 2017.
E. Zhao, Bray-Ali, N., Williams, C. J., Spielman, I. B., and Satija, I. I., Chern numbers hiding in time-of-flight images, Physical Review A, vol. 84, no. 6, 2011.
Q. Zhao and Yuan, X., Exploiting anticommutation in Hamiltonian simulation, 2021.
Q. Zhao and Zhou, Y., Constructing Multipartite Bell inequalities from stabilizers, 2020.
T. Zhou, Xu, S., Chen, X., Guo, A., and Swingle, B., The operator Lévy flight: light cones in chaotic long-range interacting systems, Phys. Rev. Lett. , vol. 124, no. 180601, 2020.
B. Zhu, Gadway, B., Foss-Feig, M., Schachenmayer, J., Wall, M., Hazzard, K. R. A., Yan, B., Moses, S. A., Covey, J. P., Jin, D. S., Ye, J., Holland, M., and Rey, A. Maria, Suppressing the loss of ultracold molecules via the continuous quantum Zeno effect , Physical Review Letters, vol. 112, no. 7, 2014.
D. Zhu, Johri, S., Nguyen, N. H., C. Alderete, H., Landsman, K. A., Linke, N. M., Monroe, C., and Matsuura, A. Y., Probing many-body localization on a noisy quantum computer, 2020.
S. Zhu, Hung, S. - H., Chakrabarti, S., and Wu, X., On the Principles of Differentiable Quantum Programming Languages, 2020.
J. P. Zwolak, McJunkin, T., Kalantre, S. S., Dodson, J. P., MacQuarrie, E. R., Savage, D. E., Lagally, M. G., Coppersmith, S. N., Eriksson, M. A., and Taylor, J. M., Auto-tuning of double dot devices in situ with machine learning, Phys. Rev. Applied , vol. 13, no. 034075 , 2020.
J. P. Zwolak, Kalantre, S. S., McJunkin, T., Weber, B. J., and Taylor, J. M., Ray-based classification framework for high-dimensional data, 2020.
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.