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  1. 2021

  2. Advances in the development of a vacuum insulated tandem accelerator and its applications

    Taskaev, S. Y., Bykov, T. A., Ivanov, A. A., Kasatov, D. A., Kolesnikov, I. A., Koshkarev, A. M., Makarov, A. N., Ostreinov, G. M., Schudlo, I. M., Sokolova, E. O. & Sorokin, I. N., 2021, 27th Russian Particle Accelerator Conference, RuPAC 2021. Kuzin, M. & Schaa, V. R. W. (eds.). CERN, p. 108-110 3 p. FRB01. (CERN-Proceedings; vol. 2021-September).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

  3. Alternative implementation of atomic form factors

    Alizzi, A., Sen, A. & Silagadze, Z. K., 2021, In: Acta Physica Polonica B. 52, 10, p. 1209-1231 23 p.

    Research output: Contribution to journal › Article › peer-review

  4. Assessment of single-shot temperature measurements by thermally-assisted OH PLIF using excitation in the A2Σ+-X2π (1-0) band

    Dulin, V., Sharaborin, D., Tolstoguzov, R., Lobasov, A., Chikishev, L., Markovich, D., Wang, S., Fu, C., Liu, X., Li, Y. & Gao, Y., 2021, In: Proceedings of the Combustion Institute. 38, 1, p. 1877-1883 7 p.

    Research output: Contribution to journal › Conference article › peer-review

  5. Complex fully connected neural networks for nonlinearity compensation in long-haul transmission systems

    Bogdanov, S. & Sidelnikov, O., 2021, The European Conference on Lasers and Electro-Optics, CLEO/Europe 2021. The Optical Society, ci_p_7. (Optics InfoBase Conference Papers).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

  6. Computing continuous nonlinear fourier spectrum of optical signal with artificial neural networks

    Sedov, E., Prilepsky, J., Chekhovskoy, I. & Turitsyn, S., 2021, European Quantum Electronics Conference, EQEC 2021. The Optical Society, ej_1_4. (Optics InfoBase Conference Papers).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

  7. Computing continuous nonlinear Fourier spectrum of optical signal with artificial neural networks

    Sedov, E., Prylepskiy, J., Chekhovskoy, I. & Turitsyn, S., 2021, Applications of Machine Learning 2021. Zelinski, M. E., Taha, T. M. & Howe, J. (eds.). SPIE, 118430J. (Proceedings of SPIE - The International Society for Optical Engineering; vol. 11843).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

  8. Computing Environmental for the Super-Charm-Tau factory detector project

    Belozyorova, M., Maksimov, D., Razuvaev, G., Sukharev, A., Vorobyev, V., Zhadan, A. & Zhadan, D., 2021, In: CEUR Workshop Proceedings. 3041, p. 375-380 6 p.

    Research output: Contribution to journal › Conference article › peer-review

  9. Control of multi-soliton generation in fiber 8-figure laser by tunable spectral filtering

    Kokhanovskiy, A., Kuprikov, E., Serebrennikov, K. & Turitsyn, S., 2021, The European Conference on Lasers and Electro-Optics, CLEO/Europe 2021. The Optical Society, cj_p_7. (Optics InfoBase Conference Papers).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

  10. Deep neural networks with time-domain synthetic photonic lattices

    Pankov, A. V., Sidelnikov, O. S., Vatnik, I. D., Churkin, D. V. & Sukhorukov, A. A., 2021, European Quantum Electronics Conference, EQEC 2021. The Optical Society, jsiv_p_3. (Optics InfoBase Conference Papers).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

  11. Deep reinforcement learning algorithm for self-tuning 8-figure fiber laser

    Kokhanovskiy, A., Kuprikov, E., Serebrennikov, K. & Turitsyn, S., 2021, The European Conference on Lasers and Electro-Optics, CLEO/Europe 2021. The Optical Society, cj_4_3. (Optics InfoBase Conference Papers).

    Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

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ID: 3088911