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Journal Article
M. Ringbauer, Hinsche, M., Feldker, T., Faehrmann, P. K., Bermejo-Vega, J., Edmunds, C., Postler, L., Stricker, R., Marciniak, C. D., Meth, M., Pogorelov, I., Blatt, R., Schindler, P., Eisert, J., Monz, T., and Hangleiter, D., “Verifiable measurement-based quantum random sampling with trapped ions”, 2023.
M. Hinsche, Ioannou, M., Nietner, A., Haferkamp, J., Quek, Y., Hangleiter, D., Seifert, J. - P., Eisert, J., and Sweke, R., “A single T-gate makes distribution learning hard”, 2022.
A. Deshpande, Mehta, A., Vincent, T., Quesada, N., Hinsche, M., Ioannou, M., Madsen, L., Lavoie, J., Qi, H., Eisert, J., Hangleiter, D., Fefferman, B., and Dhand, I., “Quantum Computational Supremacy via High-Dimensional Gaussian Boson Sampling”, 2021.
A. Deshpande, Mehta, A., Vincent, T., Quesada, N., Hinsche, M., Ioannou, M., Madsen, L., Lavoie, J., Qi, H., Eisert, J., Hangleiter, D., Fefferman, B., and Dhand, I., “Quantum computational advantage via high-dimensional Gaussian boson sampling”, Science Advances, vol. 8, p. eabi7894, 2022.
M. Hinsche, Ioannou, M., Nietner, A., Haferkamp, J., Quek, Y., Hangleiter, D., Seifert, J. - P., Eisert, J., and Sweke, R., “Learnability of the output distributions of local quantum circuits”, 2021.