Publications

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Q
J. Leng, Zheng, Y., and Wu, X., A quantum-classical performance separation in nonconvex optimization, 2023.
Y. Alexeev, Amsler, M., Baity, P., Barroca, M. Antonio, Bassini, S., Battelle, T., Camps, D., Casanova, D., Choi, Yjai, Chong, F. T., Chung, C., Codella, C., Corcoles, A. D., Cruise, J., Di Meglio, A., Dubois, J., Duran, I., Eckl, T., Economou, S., Eidenbenz, S., Elmegreen, B., Fare, C., Faro, I., Fernández, C. Sanz, Ferreira, R. Neumann Ba, Fuji, K., Fuller, B., Gagliardi, L., Galli, G., Glick, J. R., Gobbi, I., Gokhale, P., Gonzalez, Sde la Puen, Greiner, J., Gropp, B., Grossi, M., Gull, E., Healy, B., Huang, B., Humble, T. S., Ito, N., Izmaylov, A. F., Javadi-Abhari, A., Jennewein, D., Jha, S., Jiang, L., Jones, B., de Jong, W. Albert, Jurcevic, P., Kirby, W., Kister, S., Kitagawa, M., Klassen, J., Klymko, K., Koh, K., Kondo, M., Kurkcuoglu, D. Murat, Kurowski, K., Laino, T., Landfield, R., Leininger, M., Leyton-Ortega, V., Li, A., Lin, M., Liu, J., Lorente, N., Luckow, A., Martiel, S., Martin-Fernandez, F., Martonosi, M., Marvinney, C., Medina, A. Castaneda, Merten, D., Mezzacapo, A., Michielsen, K., Mitra, A., Mittal, T., Moon, K., Moore, J., Motta, M., Na, Y. - H., Nam, Y., Narang, P., Ohnishi, Y. -ya, Ottaviani, D., Otten, M., Pakin, S., Pascuzzi, V. R., Penault, E., Piontek, T., Pitera, J., Rall, P., Ravi, G. Subramania, Robertson, N., Rossi, M., Rydlichowski, P., Ryu, H., Samsonidze, G., Sato, M., Saurabh, N., Sharma, V., Sharma, K., Shin, S., Slessman, G., Steiner, M., Sitdikov, I., Suh, I. - S., Switzer, E., Tang, W., Thompson, J., Todo, S., Tran, M., Trenev, D., Trott, C., Tseng, H. - H., Tureci, E., Valinas, D. García, Vallecorsa, S., Wever, C., Wojciechowski, K., Wu, X., Yoo, S., Yoshioka, N., Yu, V. Wen-zhe, Yunoki, S., Zhuk, S., and Zubarev, D., Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions, 2023.
S. Chakrabarti, Huang, Y., Li, T., Feizi, S., and Wu, X., Quantum Wasserstein Generative Adversarial Networks, Advances in Neural Information Processing Systems (NIPS), vol. 32, 2019.
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.
T. Li and Wu, X., Quantum query complexity of entropy estimation, IEEE Transactions on Information Theory, vol. 65, no. 5, pp. 2899-2921, 2019.
J. Leng, Hickman, E., Li, J., and Wu, X., Quantum Hamiltonian Descent, 2023.
B. Augustino, Leng, J., Nannicini, G., Terlaky, T., and Wu, X., A quantum central path algorithm for linear optimization, 2023.
S. Chakrabarti, Childs, A. M., Li, T., and Wu, X., Quantum algorithms and lower bounds for convex optimization, Quantum, vol. 4, no. 221, 2020.
S. Chakrabarti, Childs, A. M., Hung, S. - H., Li, T., Wang, C., and Wu, X., Quantum algorithm for estimating volumes of convex bodies, ACM Transactions on Quantum Computing, vol. 4, 2023.
L. Li, Chang, L., Cleaveland, R., Zhu, M., and Wu, X., The Quantum Abstract Machine, 2024.
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.
L. Li, Zhu, M., Cleaveland, R., Lee, Y., Chang, L., and Wu, X., Qafny: Quantum Program Verification Through Type-guided Classical Separation Logic, 2023.
L. Li, Zhu, M., Cleaveland, R., Nicolellis, A., Lee, Y., Chang, L., and Wu, X., Qafny: A Quantum-Program Verifier, 2024.
E
X. You and Wu, X., Exponentially Many Local Minima in Quantum Neural Networks, Proceedings of the 38th International Conference on Machine Learning, PMLR, vol. 139, pp. 12144-12155, 2021.