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A
Y. Peng
,
Ying, M.
, and
Wu, X.
,
“
Algebraic Reasoning of Quantum Programs via Non-Idempotent Kleene Algebra
”
, 2021.
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X. You
,
Chakrabarti, S.
,
Chen, B.
, and
Wu, X.
,
“
Analyzing Convergence in Quantum Neural Networks: Deviations from Neural Tangent Kernels
”
, 2023.
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C
Y. - H. Chen
,
Chung, K. - M.
,
Lai, C. - Y.
,
Vadhan, S. P.
, and
Wu, X.
,
“
Computational Notions of Quantum Min-Entropy
”
, 2017.
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K. - M. Chung
,
Lee, Y.
,
Lin, H. - H.
, and
Wu, X.
,
“
Constant-round Blind Classical Verification of Quantum Sampling
”
, 2020.
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X. You
,
Chakrabarti, S.
, and
Wu, X.
,
“
A Convergence Theory for Over-parameterized Variational Quantum Eigensolvers
”
, 2022.
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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.
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J. Leng
,
Li, J.
,
Peng, Y.
, and
Wu, X.
,
“
Expanding Hardware-Efficiently Manipulable Hilbert Space via Hamiltonian Embedding
”
, 2024.
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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.
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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.
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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.
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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.
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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.
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P
S. Zhu
,
Hung, S. - H.
,
Chakrabarti, S.
, and
Wu, X.
,
“
On the Principles of Differentiable Quantum Programming Languages
”
, 2020.
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Q
L. Li
,
Zhu, M.
,
Cleaveland, R.
,
Nicolellis, A.
,
Lee, Y.
,
Chang, L.
, and
Wu, X.
,
“
Qafny: A Quantum-Program Verifier
”
, 2024.
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L. Li
,
Zhu, M.
,
Cleaveland, R.
,
Lee, Y.
,
Chang, L.
, and
Wu, X.
,
“
Qafny: Quantum Program Verification Through Type-guided Classical Separation Logic
”
, 2023.
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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.
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L. Li
,
Chang, L.
,
Cleaveland, R.
,
Zhu, M.
, and
Wu, X.
,
“
The Quantum Abstract Machine
”
, 2024.
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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.
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S. Chakrabarti
,
Childs, A. M.
,
Li, T.
, and
Wu, X.
,
“
Quantum algorithms and lower bounds for convex optimization
”
,
Quantum
, vol. 4, no. 221, 2020.
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B. Augustino
,
Leng, J.
,
Nannicini, G.
,
Terlaky, T.
, and
Wu, X.
,
“
A quantum central path algorithm for linear optimization
”
, 2023.
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J. Leng
,
Hickman, E.
,
Li, J.
, and
Wu, X.
,
“
Quantum Hamiltonian Descent
”
, 2023.
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T. Li
and
Wu, X.
,
“
Quantum query complexity of entropy estimation
”
,
IEEE Transactions on Information Theory
, vol. 65, no. 5, pp. 2899-2921, 2019.
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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.
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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.
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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.
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