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Author Title Type [ Year(Desc)]
Filters: Author is Yi-Kai Liu  [Clear All Filters]
2017
V. Dunjko, Liu, Y. - K., Wu, X., and Taylor, J. M., “Exponential improvements for quantum-accessible reinforcement learning”, 2017.
P. Bierhorst, Knill, E., Glancy, S., Mink, A., Jordan, S. P., Rommal, A., Liu, Y. - K., Christensen, B., Nam, S. Woo, and Shalm, L. K., “Experimentally Generated Random Numbers Certified by the Impossibility of Superluminal Signaling”, 2017.
S. Kimmel and Liu, Y. - K., “Phase retrieval using unitary 2-designs”, in SampTA 2017, 2017.
R. Perlner and Liu, Y. - K., “Thermodynamic Analysis of Classical and Quantum Search Algorithms”, 2017.
V. Dunjko, Liu, Y. - K., Wu, X., and Taylor, J. M., “Super-polynomial and exponential improvements for quantum-enhanced reinforcement learning”, 2017.
2018
Z. Ji, Liu, Y. - K., and Song, F., “Pseudorandom States, Non-Cloning Theorems and Quantum Money”, In: Shacham H., Boldyreva A. (eds) Advances in Cryptology – CRYPTO 2018. CRYPTO 2018. Lecture Notes in Computer Science., vol. 10993, 2018.
F. Krahmer and Liu, Y. - K., “Phase Retrieval Without Small-Ball Probability Assumptions”, IEEE Transactions on Information Theory , vol. 64, no. 1, pp. 485-500, 2018.
I. Roth, Kueng, R., Kimmel, S., Liu, Y. - K., Gross, D., Eisert, J., and Kliesch, M., “Recovering quantum gates from few average gate fidelities”, Phys. Rev. Lett. , vol. 121, p. 170502, 2018.
P. Bierhorst, Knill, E., Glancy, S., Zhang, Y., Mink, A., Jordan, S., Rommal, A., Liu, Y. - K., Christensen, B., Nam, S. Woo, Stevens, M. J., and Shalm, L. K., “Experimentally Generated Randomness Certified by the Impossibility of Superluminal Signals”, Nature, vol. 556, pp. 223-226, 2018.
S. P. Jordan and Liu, Y. - K., “Quantum Cryptanalysis: Shor, Grover, and Beyond”, IEEE Security & Privacy , vol. 16, no. 5, pp. 14-21, 2018.
2019
G. Alagic, Alperin-Sheriff, J., Apon, D., Cooper, D., Dang, Q., Miller, C., Moody, D., Peralta, R., Perlner, R., Robinson, A., Smith-Tone, D., and Liu, Y. - K., “Status Report on the First Round of the NIST Post-Quantum Cryptography Standardization Process”, School: National Institute for Standards and Technology , 2019.
T. L. Scholten, Liu, Y. - K., Young, K., and Blume-Kohout, R., “Classifying single-qubit noise using machine learning”, 2019.
2020
G. Alagic, Alperin-Sheriff, J., Apon, D., Cooper, D., Dang, Q., Kelsey, J., Liu, Y. - K., Miller, C., Moody, D., Peralta, R., Perlner, R., Robinson, A., and Smith-Tone, D., “Status Report on the Second Round of the NIST Post-Quantum Cryptography Standardization Process”, NISTIR 8309, 2020.
2021
A. Seif, Hafezi, M., and Liu, Y. - K., “Compressed Sensing Measurement of Long-Range Correlated Noise”, 2021.
2023
Y. - K. Liu, “An Uncertainty Principle for the Curvelet Transform, and the Infeasibility of Quantum Algorithms for Finding Short Lattice Vectors”, 2023.
Y. - K. Liu, “An Uncertainty Principle for the Curvelet Transform, and the Infeasibility of Quantum Algorithms for Finding Short Lattice Vectors”, 2023.
K. Huang, Farfurnik, D., Seif, A., Hafezi, M., and Liu, Y. - K., “Random Pulse Sequences for Qubit Noise Spectroscopy”, 2023.
2024
Z. Liu, Devulapalli, D., Hangleiter, D., Liu, Y. - K., Kollár, A. J., Gorshkov, A. V., and Childs, A. M., “Efficiently verifiable quantum advantage on near-term analog quantum simulators”, 2024.
J. Rajakumar, Watson, J. D., and Liu, Y. - K., “Polynomial-Time Classical Simulation of Noisy IQP Circuits with Constant Depth”, 2024.