Publications

A

Y. Peng, Ying, M., and Wu, X., “Algebraic Reasoning of Quantum Programs via Non-Idempotent Kleene Algebra”, 2021.

X. You, Chakrabarti, S., Chen, B., and Wu, X., “Analyzing Convergence in Quantum Neural Networks: Deviations from Neural Tangent Kernels”, 2023.

C

Y. - H. Chen, Chung, K. - M., Lai, C. - Y., Vadhan, S. P., and Wu, X., “Computational Notions of Quantum Min-Entropy”, 2017.

K. - M. Chung, Lee, Y., Lin, H. - H., and Wu, X., “Constant-round Blind Classical Verification of Quantum Sampling”, 2020.

X. You, Chakrabarti, S., and Wu, X., “A Convergence Theory for Over-parameterized Variational Quantum Eigensolvers”, 2022.

E

M. Barbosa, Barthe, G., Fan, X., Grégoire, B., Hung, S. - H., Katz, J., Strub, P. - Y., Wu, X., and Zhou, L., “EasyPQC: Verifying Post-Quantum Cryptography”, ACM CCS 2021, 2021.

K. Hietala, Li, L., Gaur, A., Green, A., Rand, R., Wu, X., and Hicks, M., “Expanding the VOQC Toolkit”, in The Second International Workshop on Programming Languages for Quantum Computing (PLanQC 2021), 2021.

F. G. S. L. Brandão, Kalev, A., Li, T., Lin, C. Yen- Yu, Svore, K. M., and Wu, X., “Exponential Quantum Speed-ups for Semidefinite Programming with Applications to Quantum Learning”, 2017.

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.

L

A. W. Harrow, Natarajan, A., and Wu, X., “Limitations of semidefinite programs for separable states and entangled games”, Commun. Math. Phys., vol. 366, no. 2, 2019.

M

A. Senanian, Prabhu, S., Kremenetski, V., Roy, S., Cao, Y., Kline, J., Onodera, T., Wright, L. G., Wu, X., Fatemi, V., and McMahon, P. L., “Microwave signal processing using an analog quantum reservoir computer”, 2023.

P

S. Zhu, Hung, S. - H., Chakrabarti, S., and Wu, X., “On the Principles of Differentiable Quantum Programming Languages”, 2020.

Q

L. Li, Zhu, M., Cleaveland, R., Lee, Y., Chang, L., and Wu, X., “Qafny: Quantum Program Verification Through Type-guided Classical Separation Logic”, 2023.

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, Chang, L., Cleaveland, R., Zhu, M., and Wu, X., “The Quantum Abstract Machine”, 2024.

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.

S. Chakrabarti, Childs, A. M., Li, T., and Wu, X., “Quantum algorithms and lower bounds for convex optimization”, Quantum, vol. 4, no. 221, 2020.

B. Augustino, Leng, J., Nannicini, G., Terlaky, T., and Wu, X., “A quantum central path algorithm for linear optimization”, 2023.

J. Leng, Hickman, E., Li, J., and Wu, X., “Quantum Hamiltonian Descent”, 2023.

T. Li and Wu, X., “Quantum query complexity of entropy estimation”, IEEE Transactions on Information Theory, vol. 65, no. 5, pp. 2899-2921, 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.

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.

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.

J. Leng, Zheng, Y., and Wu, X., “A quantum-classical performance separation in nonconvex optimization”, 2023.

R

X. Wu, Yao, P., and Yuen, H., “Raz-McKenzie simulation with the inner product gadget”, Electronic Colloquium on Computational Complexity (ECCC), 2017.