Invariance Property of the Fisher Information in Scattering Media

Horodynski, Michael; Bouchet, Dorian; Kühmayer, Matthias; Rotter, Stefan

doi:10.1103/physrevlett.127.233201

Cited by 4 publications

(3 citation statements)

References 54 publications

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“…A related observation was subsequently also reported in Ref. 211 which numerically studied systems without any absorption: if the average dwell time is constant, so is the average precision with which a particle's property can be estimated, as long as the scattering regime is ballistic or diffusive (but not Anderson localized). The physics of the underlying RCA mechanisms extends of course to more complex tasks, such as the recognition of sub-wavelength object shapes or materials inside an RCA without any manipulation in the extreme proximity of the scene.…”

Section: B Meta-programmable Reverberation-coded Aperturessupporting

confidence: 53%

Intelligent meta-imagers: From compressed to learned sensing

Saigre-Tardif

Faqiri

Zhao

et al. 2022

Applied Physics Reviews

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Computational meta-imagers synergize metamaterial hardware with advanced signal processing approaches such as compressed sensing. Recent advances in artificial intelligence (AI) are gradually reshaping the landscape of meta-imaging. Most recent works use AI for data analysis, but some also use it to program the physical meta-hardware. The role of “intelligence” in the measurement process and its implications for critical metrics like latency are often not immediately clear. Here, we comprehensively review the evolution of computational meta-imaging from the earliest frequency-diverse compressive systems to modern programmable intelligent meta-imagers. We introduce a clear taxonomy in terms of the flow of task-relevant information that has direct links to information theory: compressive meta-imagers indiscriminately acquire all scene information in a task-agnostic measurement process that aims at a near-isometric embedding; intelligent meta-imagers highlight task-relevant information in a task-aware measurement process that is purposefully non-isometric. The measurement process of intelligent meta-imagers is, thus, simultaneously an analog wave processor that implements a first task-specific inference step “over-the-air.” We provide explicit design tutorials for the integration of programmable meta-atoms as trainable physical weights into an intelligent end-to-end sensing pipeline. This merging of the physical world of metamaterial engineering and the digital world of AI enables the remarkable latency gains of intelligent meta-imagers. We further outline emerging opportunities for cognitive meta-imagers with reverberation-enhanced resolution, and we point out how the meta-imaging community can reap recent advances in the vibrant field of metamaterial wave processors to reach the holy grail of low-energy ultra-fast all-analog intelligent meta-sensors.

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Section: B Meta-programmable Reverberation-coded Aperturessupporting

confidence: 53%

Intelligent meta-imagers: From compressed to learned sensing

Saigre-Tardif

Faqiri

Zhao

et al. 2022

Applied Physics Reviews

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“…To acquire the information states, a great challenge lies in the random scattering caused by the disorder of complex systems, which causes signal attenuation and weakens the observable wave field features 15,16 . Over the years, many operators or matrices based on physical features of wave field properties have been derived, including transmission matrix engineering 17 , the energy deposition matrix 18 , the crosscorrelations operator 19 , the generalized Wigner-Smith (GWS) operator 20,21 , the Floquet scattering matrix 22 , the acousto-optical transmission matrix 23 , the deposition matrix 24 , the random matrix theory for the coherent perfect absorption 25,26 , and Fisher information operator 27 . They all provide useful mathematical tools for studying the interaction mechanism between wave field and scattering spaces.…”

Section: Introductionmentioning

confidence: 99%

Non-invasive self-adaptive information states acquisition inside dynamic scattering spaces

Li,

et al. 2023

Preprint

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Pushing the information states acquisition efficiency has been a long-held goal to reach the measurement precision limit inside scattering spaces. Recent studies point out that the maximum information states can be achieved by engineered modes with specific matrices and operators, however, they typically necessitate time-consuming iterations or partial intrusion for multi-targets. Whereas non-invasive designs have been substantially explored across various physical scenarios, acquiring information states non-invasively inside dynamic scattering spaces remains challenging as it involves intractable non-unique mapping problem. Here, we first demonstrate that non-invasive information states acquisition is feasible and propose a tandem-generated adversarial network framework that can perform self-adaptive wavefield control inside dynamic scattering spaces. As an example, we have carried out a proof-of-principle experiment in the microwave regime, and prove that by using only the external scattering matrix of the system, information states acquisition for multi-targets can achieve the Fisher information limit efficiently. Our work demonstrates the unprecedented potential for real-time, efficient, and complex wave manipulation, providing explicable perspectives for precise measurements inside dynamic complex systems, such as medical micro-manipulation, optical Internet of Things, and intelligent communications.

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“…To demonstrate our approach for constructing optimal tractor beam states, we first compute a unitary scattering matrix (for which the GWS operator is Hermitian, hence the eigenstate corresponding to the most positive eigenvalue then describes the input field of the optimal tractor beam). Since procedures for how to set up this scattering matrix in an appropriate basis (in free space) don't seem to be available in the literature, we present a comprehensive description of our solution in the following, with the details being available in Appendix A and the code being published alongside this work [39]. Restricting our analysis to two spatial dimensions, our starting point is the scalar Helmholtz equation in polar coordinates, [∆ + k 2 ε( r)]ψ( r) = 0, in a circular region (see Fig.…”

mentioning

confidence: 99%

Implementing Optimal Field Configurations for Micromanipulation

Horodynski¹,

Kühmayer²,

Brandstötter³

et al. 2019

Conference on Lasers and Electro-Optics

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Moving objects with optical or acoustical waves is a topic both of fundamental interest and of importance for a range of practical applications. One particularly intriguing example is the tractor beam, which pulls an object toward the wave's source, in opposition to the wave's momentum. In this study, we introduce a protocol that enables the identification of wave states that produce the optimal tractor force for arbitrary objects. Our method relies solely on the solution of a simple eigenvalue problem involving the system's measurable scattering matrix. Using numerical simulations, we demonstrate the efficacy of this wavefront shaping protocol for a representative set of different targets. Moreover, we show that the diffractive nature of waves enables the possibility of a tractor beam, that works even for targets where a geometric optics approach fails to explain the pulling forces.

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Invariance Property of the Fisher Information in Scattering Media

Cited by 4 publications

References 54 publications

Intelligent meta-imagers: From compressed to learned sensing

Intelligent meta-imagers: From compressed to learned sensing

Non-invasive self-adaptive information states acquisition inside dynamic scattering spaces

Implementing Optimal Field Configurations for Micromanipulation

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