Papers

Publications:

[1] I. Cong, S. Choi, M. D. Lukin. Quantum Convolutional Neural Networks. Nature Physics (2019). doi:10.1038/s41567-019-0648-8

[2] I. Cong, Z. Wang. “Topological quantum computation with gapped boundaries and boundary defects.” Topological Phases of Matter and Quantum Computation 747 (2020): 153. doi:10.1090/conm/747/15043

[3] I. Cong, M. Cheng, Z. Wang. Universal Quantum Computation with Gapped Boundaries. Phys. Rev. Lett. 119, 170504 (2017). doi:10.1103/PhysRevLett.119.170504

[4] I. Cong, M. Cheng, Z. Wang. On Defects Between Gapped Boundaries in Two-Dimensional Topological Phases of Matter. Phys. Rev. B. 96, 195129 (2017). doi:10.1103/PhysRevB.96.195129

[5] I. Cong, M. Cheng, Z. Wang. Hamiltonian and Algebraic Theories of Gapped Boundaries in Topological Phases of Matter. Comm. Math. Phys. (2017) 355: 645. doi:/10.1007/s00220-017-2960-4

[6] I. Cong, L.-M. Duan. Quantum Discriminant Analysis for Dimensionality Reduction and Classification. New J. Phys. 18, 073011 (2016). doi:10.1088/1367-2630/18/7/073011

Pre-prints:

[1] I. Cong, S.-T. Wang, H. Levine, A. Keesling, M. D. Lukin. Hardware-Efficient, Fault-Tolerant Quantum Computation with Rydberg Atoms. arXiv:2105.13501 (2021).

[2] I. Cong, M. Cheng, Z. Wang. Topological Quantum Computation with Gapped Boundaries. arXiv:1609.02037  (2016).