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2018
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.
S. Whitsitt, Samajdar, R., and Sachdev, S., “Quantum field theory for the chiral clock transition in one spatial dimension”, Phys. Rev. , vol. B , no. 98, p. 205118 , 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.
A. Gilyen, Su, Y., Low, G. Hao, and Wiebe, N., “Quantum singular value transformation and beyond: exponential improvements for quantum matrix arithmetics”, Proceedings of the 51st ACM Symposium on Theory of Computing , pp. 193-204, 2018.
J. Chen, Childs, A. M., and Hung, S. - H., “Quantum algorithm for multivariate polynomial interpolation”, Proceedings of The Royal Society A, vol. 474, no. 2209, 2018.
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.
N. Yunger Halpern, Swingle, B., and Dressel, J., “The quasiprobability behind the out-of-time-ordered correlator”, Phys. Rev. , vol. A, no. 97, 2018.
M. Jarret, Lackey, B., Liu, A., and Wan, K., “Quantum adiabatic optimization without heuristics”, 2018.
K. Fang, Wang, X., Tomamichel, M., and Berta, M., “Quantum Channel Simulation and the Channel's Smooth Max-Information”, 2018.
S. Gharibian, Santha, M., Sikora, J., Sundaram, A., and Yirka, J., “Quantum generalizations of the polynomial hierarchy with applications to QMA(2)”, Proceedings of 43rd International Symposium on Mathematical Foundations of Computer Science (MFCS 2018), 2018.
F. G. S. L. Brandão, Kalev, A., Li, T., Lin, C. Yen- Yu, Svore, K. M., and Wu, X., “Quantum SDP Solvers: Large Speed-ups, Optimality, and Applications to Quantum Learning”, To appear at the 46th International Colloquium on Automata, Languages and Programming (ICALP 2019), 2018.
A. Bouland, Fefferman, B., Nirkhe, C., and Vazirani, U., “Quantum Supremacy and the Complexity of Random Circuit Sampling”, 2018.
G. Alagic, Majenz, C., Russell, A., and Song, F., “Quantum-secure message authentication via blind-unforgeability”, 2018.
2017
A. M. Childs, Kothari, R., and Somma, R. D., “Quantum algorithm for systems of linear equations with exponentially improved dependence on precision”, SIAM Journal on Computing, vol. 46, no. 6, pp. 1920-1950, 2017.
Y. Wang, Tran, M. C., and Taylor, J. M., “Quantum simulation of ferromagnetic Heisenberg model”, 2017.
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. Alagic, Dulek, Y., Schaffner, C., and Speelman, F., “Quantum Fully Homomorphic Encryption With Verification”, Proceedings of ASIACRYPT 2017, pp. 438-467, 2017.
G. Wang, “Quantum Algorithm for Linear Regression”, Physical Review A, vol. 96, p. 012335, 2017.
S. Jeffery and Kimmel, S., “Quantum Algorithms for Graph Connectivity and Formula Evaluation”, 2017.
T. Xin, Lu, D., Klassen, J., Yu, N., Ji, Z., Chen, J., Ma, X., Long, G., Zeng, B., and Laflamme, R., “Quantum state tomography via reduced density matrices”, Physical Review Letters, vol. 118, p. 020401, 2017.
G. Alagic and Majenz, C., “Quantum Non-malleability and Authentication”, In: Katz J., Shacham H. (eds) Advances in Cryptology – CRYPTO 2017. Lecture Notes in Computer Science. Springer, Cham, vol. 10402, 2017.
G. Alagic and Russell, A., “Quantum-Secure Symmetric-Key Cryptography Based on Hidden Shifts”, In: Coron JS., Nielsen J. (eds) Advances in Cryptology – EUROCRYPT 2017. Lecture Notes in Computer Science, Springer, Cham, vol. 10212, 2017.
2016
X. Xu, Kim, S., Bahl, G., and Taylor, J. M., “A quasi-mode theory of chiral phonons”, 2016.
J. Chen, Johnston, N., Li, C. - K., and Plosker, S., “Quantifying the coherence of pure quantum states”, Physical Review A, vol. 94, no. 4, p. 042313, 2016.
V. Dunjko, Taylor, J. M., and Briegel, H. J., “Quantum-Enhanced Machine Learning”, Physical Review Letters, vol. 117, no. 13, p. 130501, 2016.