Statistics and control of waves in disordered media

Shi, Z.B.; Davy, Matthieu; Genack, Azriel Z.

doi:10.1364/oe.23.012293

Cited by 18 publications

(16 citation statements)

References 165 publications

(281 reference statements)

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“…Subsequent investigations have been extended from the traditional subject of global transport behavior (e.g., transmission from the input to output edge) to the new realm of the eigenchannel structure (see Ref. 17 for a review).…”

Section: Introductionmentioning

confidence: 99%

Controlling transmission eigenchannels in random media by edge reflection

et al. 2015

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Transmission eigenchannels and associated eigenvalues, that give a full account of wave propagation in random media, have recently emerged as a major theme in theoretical and applied optics. Here we demonstrate, both analytically and numerically, that in quasi one-dimensional (1D) diffusive samples, their behavior is governed mostly by the asymmetry in the reflections of the sample edges rather than by the absolute values of the reflection coefficients themselves. We show that there exists a threshold value of the asymmetry parameter, below which high transmission eigenchannels exist, giving rise to a singularity in the distribution of the transmission eigenvalues, ρ(T → 1) ∼ (1−T )At the threshold, ρ(T ) exhibits critical statistics with a distinct singularity ∼ (1 − T ) − 1 3 ; above it the high transmission eigenchannels disappear and ρ(T ) vanishes for T exceeding a maximal transmission eigenvalue. We show that such statistical behavior of the transmission eigenvalues can be explained in terms of effective cavities (resonators), analogous to those in which the states are trapped in 1D strong Anderson localization. In particular, the ρ(T )-transition can be mapped onto the shuffling of the resonator with perfect transmittance from the sample center to the edge with stronger reflection. We also find a similar transition in the distribution of resonant transmittances in 1D layered samples. These results reveal a physical connection between high transmission eigenchannels in diffusive systems and 1D strong Anderson localization. They open up a fresh opportunity for practically useful application: controlling the transparency of opaque media by tuning their coupling to the environment.

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Section: Introductionmentioning

confidence: 99%

Controlling transmission eigenchannels in random media by edge reflection

et al. 2015

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“…Meanwhile, AOPC has other advantages, e.g., a large photosensitive area and a large number of pixels and is able to complete more integrated phase conjugation. The number of controllable optical modes for AOPC is as high as 10 11 . As a result, a higher PBR will be obtained with the same focus size.…”

Section: The Relation Between Decorrelation Time and Motionmentioning

confidence: 99%

“…A series of breakthroughs have been made in this¯eld in aspects of theoretical basis, new techniques and experimental validation. Several review articles (those written by Mosk, Judkewitz, Horstmeyer, Kamali, Park, Kim et al) have illustrated the important progress in WFE, including the theories of optical transmission inside scattering media, [11][12][13][14][15][16] memory e®ects, 17 feedback guided mechanisms, [18][19][20] controlling approaches of optical waves, [21][22][23] biological applications, [24][25][26][27] etc.…”

Section: Introductionmentioning

confidence: 99%

Fast optical wavefront engineering for controlling light propagation in dynamic turbid media

Xia

Wang

2019

J. Innov. Opt. Health Sci.

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While propagating inside the strongly scattering biological tissue, photons lose their incident directions beyond one transport mean free path (TMFP, [Formula: see text]1 millimeter (mm)), which makes it challenging to achieve optical focusing or clear imaging deep inside tissue. By manipulating many degrees of the incident optical wavefront, the latest optical wavefront engineering (WFE) technology compensates the wavefront distortions caused by the scattering media and thus is toward breaking this physical limit, bringing bright perspective to many applications deep inside tissue, e.g., high resolution functional/molecular imaging, optical excitation (optogenetics) and optical tweezers. However, inside the dynamic turbid media such as the biological tissue, the wavefront distortion is a fast and continuously changing process whose decorrelation rate is on timescales from milliseconds (ms) to microseconds ([Formula: see text]s), or even faster. This requires that the WFE technology should be capable of beating this rapid process. In this review, we discuss the major challenges faced by the WFE technology due to the fast decorrelation of dynamic turbid media such as living tissue when achieving light focusing/imaging and summarize the research progress achieved to date to overcome these challenges.

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“…Note that the performance of modulation (e.g., focusing) in this way sees some limitations while the iterative method modi¯es the wavefront in a real-time manner. 29 Nevertheless, the TM physically describes the interaction between the medium and the random optical process, where features like polarization, 29 spectrum, 30,31 as well as eigenchannels [32][33][34][35][36] of the transmission can be extracted. Furthermore, the measured TM can be used to derive the desired modulation for raster scanning 37 and image transmission.…”

Section: Introductionmentioning

confidence: 99%

Artificial intelligence-assisted light control and computational imaging through scattering media

Cheng

Luo

et al. 2019

J. Innov. Opt. Health Sci.

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Coherent optical control within or through scattering media via wavefront shaping has seen broad applications since its invention around 2007. Wavefront shaping is aimed at overcoming the strong scattering, featured by random interference, namely speckle patterns. This randomness occurs due to the refractive index inhomogeneity in complex media like biological tissue or the modal dispersion in multimode fiber, yet this randomness is actually deterministic and potentially can be time reversal or precompensated. Various wavefront shaping approaches, such as optical phase conjugation, iterative optimization, and transmission matrix measurement, have been developed to generate tight and intense optical delivery or high-resolution image of an optical object behind or within a scattering medium. The performance of these modulations, however, is far from satisfaction. Most recently, artificial intelligence has brought new inspirations to this field, providing exciting hopes to tackle the challenges by mapping the input and output optical patterns and building a neuron network that inherently links them. In this paper, we survey the developments to date on this topic and briefly discuss our views on how to harness machine learning (deep learning in particular) for further advancements in the field.

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Statistics and control of waves in disordered media

Cited by 18 publications

References 165 publications

Controlling transmission eigenchannels in random media by edge reflection

Controlling transmission eigenchannels in random media by edge reflection

Fast optical wavefront engineering for controlling light propagation in dynamic turbid media

Artificial intelligence-assisted light control and computational imaging through scattering media

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