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Filters: Author is Xiaodi Wu  [Clear All Filters]
2024
S. Kushnir, Leng, J., Peng, Y., Fan, L., and Wu, X., “QHDOPT: A Software for Nonlinear Optimization with Quantum Hamiltonian Descent”, 2024.
L. Li, Chang, L., Cleaveland, R., Zhu, M., and Wu, X., “The Quantum Abstract Machine”, 2024.
L. Li, Zhu, M., Cleaveland, R., Nicolellis, A., Lee, Y., Chang, L., and Wu, X., “Qafny: A Quantum-Program Verifier”, 2024.
J. Leng, Li, J., Peng, Y., and Wu, X., “Expanding Hardware-Efficiently Manipulable Hilbert Space via Hamiltonian Embedding”, 2024.
2023
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. 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.
Y. Peng, Young, J., Liu, P., and Wu, X., “SimuQ: A Domain-Specific Language For Quantum Simulation With Analog Compilation”, 2023.
X. You, Chakrabarti, S., Chen, B., and Wu, X., “Analyzing Convergence in Quantum Neural Networks: Deviations from Neural Tangent Kernels”, 2023.
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.
J. Leng, Zheng, Y., and Wu, X., “A quantum-classical performance separation in nonconvex optimization”, 2023.
2022
X. You, Chakrabarti, S., and Wu, X., “A Convergence Theory for Over-parameterized Variational Quantum Eigensolvers”, 2022.
2021
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.
L. Li, Voichick, F., Hietala, K., Peng, Y., Wu, X., and Hicks, M., “Verified Compilation of Quantum Oracles”, 2021.
K. Hietala, Rand, R., Hung, S. - H., Wu, X., and Hicks, M., “A Verified Optimizer for Quantum Circuits”, Proceedings of the ACM on Programming Languages, vol. 5, no. POPL, 2021.
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.
Y. Peng, Ying, M., and Wu, X., “Algebraic Reasoning of Quantum Programs via Non-Idempotent Kleene Algebra”, 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.
2020
S. Zhu, Hung, S. - H., Chakrabarti, S., and Wu, X., “On the Principles of Differentiable Quantum Programming Languages”, 2020.
K. - M. Chung, Lee, Y., Lin, H. - H., and Wu, X., “Constant-round Blind Classical Verification of Quantum Sampling”, 2020.
T. Peng, Harrow, A., Ozols, M., and Wu, X., “Simulating large quantum circuits on a small quantum computer”, Phys. Rev. Lett., vol. 125, no. 150504, 2020.
S. Chakrabarti, Childs, A. M., Li, T., and Wu, X., “Quantum algorithms and lower bounds for convex optimization”, Quantum, vol. 4, no. 221, 2020.
T. Li, Wang, C., Chakrabarti, S., and Wu, X., “Sublinear classical and quantum algorithms for general matrix games”, To appear in the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021), 2020.
2019
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.
T. Li and Wu, X., “Quantum query complexity of entropy estimation”, IEEE Transactions on Information Theory, vol. 65, no. 5, pp. 2899-2921, 2019.