Publications

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2022
A. Bapat, Childs, A. M., Gorshkov, A. V., and Schoute, E., Advantages and limitations of quantum routing, 2022.
C. - L. Hong, Tsai, T., Chou, J. - P., Chen, P. - J., Tsai, P. - K., Chen, Y. - C., Kuo, E. - J., Srolovitz, D., Hu, A., Cheng, Y. - C., and Goan, H. - S., Accurate and Efficient Quantum Computations of Molecular Properties Using Daubechies Wavelet Molecular Orbitals: A Benchmark Study against Experimental Data, PRX Quantum, vol. 3, p. 020360, 2022.
S. Dontha, Tan, S. Jie Samuel, Smith, S., Choi, S., and Coudron, M., Approximating Output Probabilities of Shallow Quantum Circuits which are Geometrically-local in any Fixed Dimension, Leibniz International Proceedings in Informatics (LIPIcs), vol. 232, p. 9:1--9:17, 2022.
Y. Kharkov, Ivanova, A., Mikhantiev, E., and Kotelnikov, A., Arline Benchmarks: Automated Benchmarking Platform for Quantum Compilers, 2022.
D. H. Wu and Albert, V. V., Approximating the two-mode two-photon Rabi model, Physics Letters A, vol. 422, 2022.
D. Hangleiter, Carolan, J., and Thébault, K. P. Y., Analogue Quantum Simulation: A New Instrument for Scientific Understanding. Springer Nature, 2022, pp. 83-102.
2020
A. Bapat and Jordan, S. P., Approximate optimization of MAXCUT with a local spin algorithm, 2020.
J. T. Young, Bienias, P., Belyansky, R., Kaufman, A. M., and Gorshkov, A. V., Asymmetric blockade and multi-qubit gates via dipole-dipole interactions, 2020.
T. Faulkner, Hollands, S., Swingle, B., and Wang, Y., Approximate recovery and relative entropy I. general von Neumann subalgebras, 2020.
T. Faulkner, Hollands, S., Swingle, B., and Wang, Y., Approximate recovery and relative entropy I. general von Neumann subalgebras, 2020.
J. P. Zwolak, McJunkin, T., Kalantre, S. S., Dodson, J. P., MacQuarrie, E. R., Savage, D. E., Lagally, M. G., Coppersmith, S. N., Eriksson, M. A., and Taylor, J. M., Auto-tuning of double dot devices in situ with machine learning, Phys. Rev. Applied , vol. 13, no. 034075 , 2020.
Y. Nam, Su, Y., and Maslov, D., Approximate Quantum Fourier Transform with O(nlog(n)) T gates, npj Quantum Information , vol. 6, no. 26, 2020.
S. Xu and Swingle, B., Accessing scrambling using matrix product operators, Nature Physics , vol. 16, no. 2, pp. 199-204, 2020.
R. Yousefzadeh and O'Leary, D. P., Auditing and Debugging Deep Learning Models via Decision Boundaries: Individual-level and Group-level Analysis, 2020.