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H
T. M. Hanna, Tiesinga, E., and Julienne, P. S., “Creation and manipulation of Feshbach resonances with radio-frequency radiation ”, New Journal of Physics, vol. 12, no. 8, p. 083031, 2010.
T. M. Hanna, Tiesinga, E., and Julienne, P. S., “Prediction of Feshbach resonances from three input parameters”, Physical Review A, vol. 79, no. 4, 2009.
T. M. Hanna, Tiesinga, E., Mitchell, W. F., and Julienne, P. S., “Resonant control of polar molecules in an optical lattice”, Physical Review A, vol. 85, no. 2, 2012.
D. Hangleiter and Gullans, M., “Bell sampling from quantum circuits”, 2023.
D. Hangleiter and Eisert, J., “Computational advantage of quantum random sampling”, 2022.
D. Hangleiter, Carolan, J., and Thébault, K. P. Y., Analogue Quantum Simulation: A New Instrument for Scientific Understanding. Springer Nature, 2022, pp. 83-102.
D. Hangleiter and Gullans, M., “Bell sampling from quantum circuits”, 2023.
D. Hangleiter, Roth, I., Eisert, J., and Roushan, P., “Precise Hamiltonian identification of a superconducting quantum processor”, 2021.
H. Halvorson and Bub, J., “Can quantum cryptography imply quantum mechanics? Reply to Smolin”, 2003.
N. Yunger Halpern, Swingle, B., and Dressel, J., “The quasiprobability behind the out-of-time-ordered correlator”, Phys. Rev. , vol. A, no. 97, 2018.
N. Yunger Halpern, Kothakonda, N. B. T., Haferkamp, J., Munson, A., Eisert, J., and Faist, P., “Resource theory of quantum uncomplexity”, Physical Review A, vol. 106, 2022.
N. Yunger Halpern, Kothakonda, N. B. T., Haferkamp, J., Munson, A., Eisert, J., and Faist, P., “Resource theory of quantum uncomplexity”, 2021.
N. Yunger Halpern and Majidy, S., “How to build Hamiltonians that transport noncommuting charges in quantum thermodynamics”, npj Quantum Inf, vol. 8, no. 10, 2022.
N. Yunger Halpern, Beverland, M. E., and Kalev, A., “Noncommuting conserved charges in quantum many-body thermalization”, Phys. Rev. E , vol. 101, no. 042117, 2020.
N. Yunger Halpern, Beverland, M. E., and Kalev, A., “Equilibration to the non-Abelian thermal state in quantum many-body physics”, 2019.
M. Hafezi, Adhikari, P., and Taylor, J. M., “A chemical potential for light”, Physical Review B, vol. 92, no. 17, p. 174305, 2015.
J. Haferkamp, Faist, P., Kothakonda, N. B. T., Eisert, J., and Halpern, N. Yunger, “Linear growth of quantum circuit complexity”, Nat. Phys., 2022.
G
J. Antonio Ma Guzmán, Erker, P., Gasparinetti, S., Huber, M., and Halpern, N. Yunger, “DiVincenzo-like criteria for autonomous quantum machines”, 2023.
N. Gupta, Katz, J., and Chopra, N., “Statistical Privacy in Distributed Average Consensus on Bounded Real Inputs”, 2019.
N. Gupta, Katz, J., and Chopra, N., “Information-Theoretic Privacy in Distributed Average Consensus”, 2018.
N. Gupta, Katz, J., and Chopra, N., “Information-Theoretic Privacy For Distributed Average Consensus: Bounded Integral Inputs”, 2018.
A. Y. Guo, Deshpande, A., Chu, S. - K., Eldredge, Z., Bienias, P., Devulapalli, D., Su, Y., Childs, A. M., and Gorshkov, A. V., “Implementing a Fast Unbounded Quantum Fanout Gate Using Power-Law Interactions”, Phys. Rev. Research, vol. 4, no. L042016, 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.
A. Y. Guo, Tran, M. C., Childs, A. M., Gorshkov, A. V., and Gong, Z. - X., “Signaling and Scrambling with Strongly Long-Range Interactions”, Physical Review A, vol. 102, no. 010401(R), 2020.
S. Guo, Koh, S. M., Fritsch, A. R., Spielman, I. B., and Zwolak, J. P., “Combining machine learning with physics: A framework for tracking and sorting multiple dark solitons”, Phys. Rev. Research, vol. 4, p. 023163 , 2022.