Publications

D. An, Linden, N., Liu, J. - P., Montanaro, A., Shao, C., and Wang, J., “Quantum-accelerated multilevel Monte Carlo methods for stochastic differential equations in mathematical finance”, Quantum 5, 481 (2021), vol. 5, p. 481, 2021.

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.

N. - H. Chia, Li, T., Lin, H. - H., and Wang, C., “Quantum-inspired classical sublinear-time algorithm for solving low-rank semidefinite programming via sampling approaches”, 2019.

Y. Xu, Wang, Y., Kuo, E. - J., and Albert, V. V., “Qubit-Oscillator Concatenated Codes: Decoding Formalism and Code Comparison”, PRX Quantum, vol. 4, p. 020342, 2023.

C. M. Langlett, Yang, Z. - C., Wildeboer, J., Gorshkov, A. V., Iadecola, T., and Xu, S., “Rainbow Scars: From Area to Volume Law”, 2021.

V. Iyer, Jain, S. P., Kovacs-Deak, M., Kumar, V. M., Schaeffer, L., Wang, D., and Whitmeyer, M., “On the Rational Degree of Boolean Functions and Applications”, 2023.

J. P. Zwolak, Kalantre, S. S., McJunkin, T., Weber, B. J., and Taylor, J. M., “Ray-based classification framework for high-dimensional data”, Proceedings of the Machine Learning and the Physical Sciences Workshop at NeurIPS 2020, Vancouver, Canada, 2020.

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

F. Liu, Whitsitt, S., Bienias, P., Lundgren, R., and Gorshkov, A. V., “Realizing and Probing Baryonic Excitations in Rydberg Atom Arrays”, 2020.

R. Verdel, Liu, F., Whitsitt, S., Gorshkov, A. V., and Heyl, M., “Real-time dynamics of string breaking in quantum spin chains”, 2019.

B. Swingle and Wang, Y., “Recovery Map for Fermionic Gaussian Channels”, 2018.

M. S. Safronova, Williams, C. J., and Clark, C. W., “Relativistic many-body calculations of electric-dipole matrix elements, lifetimes and polarizabilities in rubidium ”, Physical Review A, vol. 69, no. 2, 2004.

M. Kalinowski, Wang, Y., Bienias, P., Gullans, M., Ornelas-Huerta, D. P., Craddock, A. N., Rolston, S. L., Porto, J. V., Büchler, H. Peter, and Gorshkov, A. V., “Resonant enhancement of three-body loss between strongly interacting photons”, 2020.

X. Wang and Wilde, M. M., “Resource theory of asymmetric distinguishability for quantum channels”, 2019.

S. Bäuml, Das, S., Wang, X., and Wilde, M. M., “Resource theory of entanglement for bipartite quantum channels”, 2019.

Q. Wang, Li, M., Monroe, C., and Nam, Y., “Resource-Optimized Fermionic Local-Hamiltonian Simulation on Quantum Computer for Quantum Chemistry”, Quantum, vol. 5, no. 509, 2021.

D. Wu, Zhao, Q., Gu, X. - M., Zhong, H. - S., Zhou, Y., Peng, L. - C., Qin, J., Luo, Y. - H., Chen, K., Li, L., Le Liu, N. -, Lu, C. - Y., and Pan, J. - W., “Robust Self-Testing of Multiparticle Entanglement”, Phys. Rev. Lett. , vol. 127, p. 230503, 2021.

N. - H. Chia, Gilyen, A., Li, T., Lin, H. - H., Tang, E., and Wang, C., “Sampling-based sublinear low-rank matrix arithmetic framework for dequantizing quantum machine learning”, to appear in Proceedings of STOC 2020, 2020.

G. Pupillo, Rey, A. Maria, Brennen, G., Williams, C. J., and Clark, C. W., “Scalable quantum computation in systems with Bose-Hubbard dynamics”, Journal of Modern Optics, vol. 51, no. 16-18, pp. 2395 - 2404, 2004.