Optical vortex beam with orbital angular momentum (OAM) has great potential to increase the capacity of optical communication and information processing in classical and quantum regimes. Nevertheless, important challenges that influence the optical data transmission in free space is the existence of diffusers along the optical path, which causes inevitable information loss during the wave propagation. Numerous algorithms have been proposed successively for identifying the modes of vortex beams propagating through scattering media. However, these methods all require completion on a computer, which is energy-intensive and energy consuming. Here, we propose an all-optical regime for identifying the modes of vortex light fields propagating through scattering media. After training by deep learning, our model can recognize the mode of vortex beam through unknown phase diffusers, demonstrating generalization to new random diffusers that have never been encountered before. Once physically deployed, the entire setup will rapidly identify the modes of vortex light propagating through scattering media at the speed of light, and the entire inference process will consume zero energy except for illumination source. Our research represents a significant step towards highly accurate recognition of vortex light modes propagating through complex scattering media, providing significant guidance for the application of optical communication in complex environments.
Wavefront sensing is a technique for measuring wavefront aberrations in optical beams, playing a crucial role in various optical systems used for astronomical observations, laser communications, and inertial confinement fusion. As optical systems are being employed in increasingly extreme scenarios, wavefront aberrations have become more pronounced, often exhibiting high temporal variations, which demands more elevated rates of wavefront sensing. This paper introduces a novel wavefront sensing method based on cascaded phase modulation layers capable of achieving ultra-high wavefront sensing speed while maintaining satisfactory accuracy.
We incorporate neural networks into the optical design of off-axis three-mirror reflective system, enabling us to achieve design outcomes without relying on iteration or ray tracing methods. Our approach involves combining analytical relations with neural networks during the design process, which yields results covering the entire parameter space with a single user input, and each design is scored simultaneously. Our results demonstrate that neural networks can simulate the complex relationship between performance requirements and structural parameters of an optical system. As such, the structural parameters can be directly obtained from the performance requirements, replacing the iterative optimization process traditionally used. This approach leads to relatively efficient and straightforward optical design. We anticipate that this method can be extended to various optical systems, reducing the experience threshold and difficulty of optical design.
Tight control of the output energy is required in high-power laser devices. The main amplifier provides the most dominant energy gain, whose output needs to be predicted accurately. However, due to its complex structure and time-varying performance, the prediction results using traditional physical model-fitting methods are biased. In this paper, we propose a physical knowledge-based neural network, with an analytical model as the backbone and multidimensional influencing factors introduced by neural networks as input, to achieve accurate prediction. The method combines the powerful characterization ability of neural networks and the interpretability of physical models, which significantly improves the accuracy by considering the coupling effects of several factors and measurement errors. The relative deviation of the method's prediction results improves 65.9% compared to the traditional physical model and 57.9% compared to the pure neural network. The model provides a correction approach for similar problems of oversimplified physical models and can be exploited to aid model development of other measurable processes in physical science.
The energy accuracy of laser beams is an essential property of inertial confinement fusion (ICF). However, the energy gain is difficult to be predicted and controlled precisely due to the dramatically-increasing complexity of huge optical systems. Artificial neural network is a numerical algorithm with valuable flexibility that maps inputs to output values, which provides an approach to figure out this issue. In the study, a novel method combining deep neural networks and the Frantz- Nodvik equations is proposed to predict the output energy of the main amplifier in the high-power ICF laser system. To improve the prediction performance, the artificial neural network counts in more related factors that are neglected in traditional configurations. Dynamic state parameters describing amplification capacity are output by neural network and constrained by physical prior knowledge. The experimental results show that the proposed method provides a more accurate prediction of output energy than the conventional fitting approaches, from 6.5% to 4.2% on relative deviation. The study investigates the methodology of combining neural networks with physical models to reproduce a complex energy gain process and to represent a nonlinear unresolvable model, which can be exploited to aid model development of other measurable processes in physical science.
We presented a novel scheme to improve the stability of the orbital angular momentum (OAM) modes transmission by adding a dip at the edge of the annular high-index region of the air-core fiber. The simulation indicated a larger effective index difference of the vector modes that composed OAM modes in the same order, promising a stable transmission of the OAM modes. The intensity of the modes was concentrated better in this scheme decreasing the crosstalk between adjacent fibers. The propagation properties of the OAM modes in bent fiber were investigated.
The polarization smoothing (PS) of the focal spot on target is a key technology for inertial confinement fusion (ICF) laser. A mathematical model is presented to analyze the polarization smoothing in a convergent beam. The relation between the separations (both transverse and longitudinal) of focal spots and the parameters of the crystal are established. Via numerical simulation, the three-dimensional distributions of the far-field with and without PS are demonstrated. The relation between the property of the focal spot and the crystal’s thickness and tilt angle are obtained. Best smoothing can be achieved with the optimized thickness and tilt angle of the PS crystal.
The laser pulse should be shaped to satisfy the ICF physical requirement and the profile should be flattened to increase the extraction efficiency of the disk amplifiers and to ensure system safety in ICF laser facility. The spatial-temporal distribution of the laser pulse is affected by the gain saturation, uniformity gain profile of the amplifiers, and the frequency conversion process. The pulse spatial-temporal distribution can’t be described by simply analytic expression, so new iteration algorithms are needed. We propose new inversion method and iteration algorithms in this paper. All of these algorithms have been integrated in SG99 software and the validity has been demonstrated. The result could guide the design of the ICF laser facility in the future.
Physical model was established to describe the pulse superposition in multi-pass amplification process when the pulse reflected from the cavity mirror and the front and the end of the pulse encountered. Theoretical analysis indicates that pulse superposition will consume more inversion population than that consumed without superposition. The standing wave field will be formed when the front and the end of the pulse is coherent overlapped. The inversion population density is spatial hole-burning by the standing wave field. The pulse gain and pulse are affected by superposition. Based on this physical model, three conditions, without superposition, coherent superposition and incoherent superposition were compared. This study will give instructions for high power solid laser design.
For better performance of laser coupling in inertial confinement fusion (ICF), beam shaping of the focus spot is
required. Among all the beam smoothing methods, the multi frequency modulation smoothing by spectral dispersion
(MultiFM-SSD) proposed by LLE has the advantages of the faster smoothing and better operability. Strong
frequency modulation to amplitude modulation conversion(FM-to-AM) will take place because of the complex
spectrum imposed by the multi frequency modulators applied in the Multi FM-SSD method. The FM-to-AM effect is
studied with numerical simulation including the polarization mode dispersion and group velocity dispersion. The
results reveal that the modulation frequencies and bandwidths of multi modulators will influence the contrast degree
of the FM-to-AM effect. The compensation of the FM-to-AM with arbitrary waveform generator (AWG) is also
numerically simulated. The FM-to-AM effect is effectively suppressed, i.e. the non-uniformity of the pulse decreases
substantially, by applying multiple intensity and phase compensation (the compensation function is obtained via G-S
algorithm).
optical propagation simulation by SG99 code and invert algorithm has been made for two typical laser architecture,
namely the National Ignition Facility (model A) and SG-III laser facility (model B) based on measured 400mm aperture
Nd:glass slab gain distribution data on ITB system. When the gain nonuniformity is about 5%, 7%, and 9% respectively
within 395x395mm2 aperture and output beam aperture is 360x360mm2, and output energy is about 16kJ/5ns(square)
with B-integral limited, 1ω(1053nm) nearfield modulation is about 1.10, 1.15, and 1.30 respectively for model A (11+7
slab configuration), and 1.07, 1.08, and 1.17 respectively for model B (9+9 slab configuration) without spatial gain
compensation. With the above three gain nonuniformity and slab configuration unchanged, to achieve flat-in-top output
near field, the compensation depth of the input near field is about 1.5:1, 2.0:1, and 6.0:1 respectively for model A, and
1.3:1, 1.4:1, and 3.5:1 respectively for model B. Compared with model A (the beam aperture unchanged in multi-pass
amplification), the influence of slab gain nonuniformity on model B (beam aperture changed) is smaller. All the above
simulation results deserve further experiment study in the future.
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