High Power Laser Science and Engineering, Volume. 7, Issue 4, 04000e59(2019)
Deep-learning-based phase control method for tiled aperture coherent beam combining systems On the Cover
Fig. 1. Experimental setup for implementing the DL-based phase control method for CBC. (SL: seed laser; PA: pre-amplifier; FS: fiber splitter; FPM: fiber phase modulator; FA: fiber amplifier; HRM: highly reflective mirror; FL: focus lens; BS: beam splitter.)
Fig. 2. Illustration of the CNN for estimating the phase error in CBC systems.
Fig. 3. Intensity profiles of the beam arrays consisting of (a) 7 elements and (b) 19 elements.
Fig. 4. Average MSE of the CNN as a function of the number of training epochs.
Fig. 5. Performances of the trained CNN for phase control. Far-field intensity profiles (a1)–(a5) without phase error compensation, and with phase error compensation using CNNs trained at (b1)–(b5) the focal plane and (c1)–(c5) the non-focal-plane.
Fig. 6. Far-field intensity profiles of the (a) incoherently combined beam, (b) DL-based coherently combined beam and (c) ideal coherently combined beam, for the case of the 7-element hexagonal array. (d) Far-field intensity profiles along the
Fig. 7. Far-field intensity profiles of the (a) incoherently combined beam, (b) DL-based coherently combined beam and (c) ideal coherently combined beam, for the case of the 19-element hexagonal array. (d) Far-field intensity profiles along the
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Tianyue Hou, Yi An, Qi Chang, Pengfei Ma, Jun Li, Dong Zhi, Liangjin Huang, Rongtao Su, Jian Wu, Yanxing Ma, Pu Zhou. Deep-learning-based phase control method for tiled aperture coherent beam combining systems[J]. High Power Laser Science and Engineering, 2019, 7(4): 04000e59
Category: Research Articles
Received: Jun. 16, 2019
Accepted: Sep. 20, 2019
Published Online: Nov. 12, 2019
The Author Email: Pengfei Ma (shandapengfei@126.com), Pu Zhou (zhoupu203@163.com)