ABSTRACT
Wavefront aberration describes the deviation of a wavefront in an imaging system from a desired perfect shape, such as a plane or a sphere, which may be caused by a variety of factors, such as imperfections in optical equipment, atmospheric turbulence, and the physical properties of imaging subjects and medium. Measuring the wavefront aberration of an imaging system is a crucial part of modern optics and optical engineering, with a variety of applications such as adaptive optics, optical testing, microscopy, laser system design, and ophthalmology. While there are dedicated wavefront sensors that aim to measure the phase of light, they often exhibit some drawbacks, such as higher cost and limited spatial resolution compared to regular intensity measurement. In this paper, we introduce a lightweight and practical learning-based method, named LWNet, to recover the wavefront aberration for an imaging system from a single intensity measurement. Specifically, LWNet takes a measured point spread function (PSF) as input and recovers the wavefront aberration with a two-stage network. The first stage network estimates an initial wavefront aberration via supervised learning, and the second stage network further optimizes the wavefront aberration via self-supervised learning by enforcing the statistical priors and physical constraints of wavefront aberrations via Zernike decomposition. For supervised learning, we created a synthetic PSF-wavefront aberration dataset via ray tracing of 88 lenses. Experimental results show that even trained with simulated data, LWNet works well for wavefront aberration estimation of real imaging systems and consistently outperforms prior learning-based methods.
ABSTRACT
The performance of the underwater optical communication (UWOC) systems was primarily limited by the low optical transmission efficiency due to the beam divergence and water interference. It has been proved in our previous works that holographic beam shaping can effectively increase the optical transmission efficiency and therefore the communication distances and speed. The conventional hologram optimisation method treated each pixel as an independent variable, leading to a large search space and a slow process. In this work, we proposed to use a small set of parameters to describe the beam shaping holograms that were able to limit the beam divergence and compensate for the wavefront distortion. This significantly reduced the number of variables to be optimised and enabled the optimisation to be more efficient and effective. In a proof-of-concept experiment based on the off-the-shelf components, the proposed method was able to generate the optimal hologram within 20 iterations while achieving a tenfold increase in the optical transmission efficiency for a 30 m link at 100 Mbps.
ABSTRACT
In this paper, we proposed and experimentally verified a diffraction-based optical beam shaping technique for underwater optical communication (UWOC) applications. The proposed method aimed to address the key issue in UWOC links, i.e., the high propagation loss experienced by the launched optical beam. It enabled a significantly higher portion of the launched signal to be collected by the receiver. The optimal transmission distance could also be fine-tuned by the software configuration. In a proof-of-concept demonstration based on the off-the-shelf components, 100 Mbps transmission was achieved over 15-meter distance and a significant enhancement in the transmission quality was observed. There is a huge scope for further improvement in the transmission distance and data rate when the proposed technique was used with purpose-built optical components and advanced coding schemes.
ABSTRACT
The phase flicker in digital liquid crystal on silicon (LCOS) device introduces temporal phase noise to the phase pattern displayed on the device. Such temporal phase noise could elevate the power of unwanted diffraction orders and ultimately cause crosstalk in optical switches based on the LCOS technology. Building on our previous work, this paper demonstrated an automated phase flicker optimisation process by using the genetic algorithm. The method developed in this work further shortened the optimisation process by 10x. It was also demonstrated that the optimised digital driving waveform set was able to reduce the crosstalk level in the optical switches by at least 3â dB.