Photorefractive two-wave mixing for image amplification in digital holography

Koukourakis, Nektarios; Abdelwahab, Tarek; Li, Ming Yuan; Höpfner, Henning; Lai, Yiu Wai; Darakis, Emmanouil; Brenner, Carsten; Gerhardt, Nils C.; Hofmann, Martin R.

doi:10.1364/oe.19.022004

Cited by 40 publications

(10 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The resulting output fields are imaged on the CMOS camera, where they are recorded holographically. Amplitude and phase distributions are reconstructed by using the Angular Spectrum method [36]. Both amplitude and phase distributions are used for the holographic MD and thus the complex weights are calculated directly.…”

Section: Experimental Investigationsmentioning

confidence: 99%

Intensity-Only Mode Decomposition on Multimode Fibers Using a Densely Connected Convolutional Network

Rothe

Zhang

Koukourakis

et al. 2021

J. Lightwave Technol.

Self Cite

View full text Add to dashboard Cite

Section: Experimental Investigationsmentioning

confidence: 99%

Intensity-Only Mode Decomposition on Multimode Fibers Using a Densely Connected Convolutional Network

Rothe

Zhang

Koukourakis

et al. 2021

J. Lightwave Technol.

Self Cite

View full text Add to dashboard Cite

“…ROI is the whole 2D region of interest (in most cases, the MMF's core area), and E * i is the complex conjugated field distribution of an LP mode. To perform the MD, holograms are recorded with a CMOS camera and reconstructed numerically using the Angular Spectrum method [25]. In recent work, this approach was used for inverse precoding within a novel MMF communication system, enabling mode division multiplexing, and exploiting physical layer security [18].…”

Section: Digital Holography-based Modal Decompositionmentioning

confidence: 99%

Deep Learning for Computational Mode Decomposition in Optical Fibers

et al. 2020

Self Cite

View full text Add to dashboard Cite

Multimode fibers are regarded as the key technology for the steady increase in data rates in optical communication. However, light propagation in multimode fibers is complex and can lead to distortions in the transmission of information. Therefore, strategies to control the propagation of light should be developed. These strategies include the measurement of the amplitude and phase of the light field after propagation through the fiber. This is usually done with holographic approaches. In this paper, we discuss the use of a deep neural network to determine the amplitude and phase information from simple intensity-only camera images. A new type of training was developed, which is much more robust and precise than conventional training data designs. We show that the performance of the deep neural network is comparable to digital holography, but requires significantly smaller efforts. The fast characterization of multimode fibers is particularly suitable for high-performance applications like cyberphysical systems in the internet of things.

show abstract

“…Therefore, the MMF output signal is superimposed with the reference beam on CMOS2, as shown in Figure 1. The resulting hologram is captured with the camera and numerically reconstructed with the angular spectrum method [27].…”

Section: Holographic Decomposition Of Light Into the Fiber's Mode Domainmentioning

confidence: 99%

Transmission Matrix Measurement of Multimode Optical Fibers by Mode-Selective Excitation Using One Spatial Light Modulator

et al. 2019

Self Cite

View full text Add to dashboard Cite

Multimode fibers (MMF) are promising candidates to increase the data rate while reducing the space required for optical fiber networks. However, their use is hampered by mode mixing and other effects, leading to speckled output patterns. This can be overcome by measuring the transmission matrix (TM) of a multimode fiber. In this contribution, a mode-selective excitation of complex amplitudes is performed with only one phase-only spatial light modulator. The light field propagating through the fiber is measured holographically and is analyzed by a rapid decomposition method. This technique requires a small amount of measurements N, which corresponds to the degree of freedom of the fiber. The TM determines the amplitude and phase relationships of the modes, which allows us to understand the mode scrambling processes in the MMF and can be used for mode division multiplexing.

show abstract

Photorefractive two-wave mixing for image amplification in digital holography

Cited by 40 publications

References 45 publications

Intensity-Only Mode Decomposition on Multimode Fibers Using a Densely Connected Convolutional Network

Intensity-Only Mode Decomposition on Multimode Fibers Using a Densely Connected Convolutional Network

Deep Learning for Computational Mode Decomposition in Optical Fibers

Transmission Matrix Measurement of Multimode Optical Fibers by Mode-Selective Excitation Using One Spatial Light Modulator

Contact Info

Product

Resources

About