arXiv subjects

Philipp del Hougne

Publications and source records attributed to Philipp del Hougne.

85 records · Page 5Linked to original sources

arXiv2020

Implementing Non-Universal Features with a Random Matrix Theory Approach: Application to Space-to-Configuration Multiplexing

We consider the efficiency of multiplexing spatially encoded information across random configurations of a metasurface-programmable chaotic cavity in the microwave domain. The distribution of the effective rank of the channel matrix is studied to quantify the channel diversity and to assess a specific system's performance. System-specific features such as unstirred field components give rise to nontrivial inter-channel correlations and need to be properly accounted for in modelling based on random matrix theory. To address this challenge, we propose a two-step hybrid approach. Based on an ensemble of experimentally measured scattering matrices for different random metasurface configurations, we first learn a system-specific pair of coupling matrix and unstirred contribution to the Hamiltonian, and then add an appropriately weighted stirred contribution. We verify that our method is capable of reproducing the experimentally found distribution of the effective rank with good accuracy. The approach can also be applied to other wave phenomena in complex media.

physics.app-ph↗

arXiv2020

Robust Position Sensing with Wave Fingerprints in Dynamic Complex Environments

Irregular propagation environments with complex scattering effects challenge traditional ray-tracing-based localization. However, the environment's complexity enables solutions based on wave fingerprints (WFPs). Yet, since WFPs rely on the extreme sensitivity of the chaotic wave field to geometrical details, it is not clear how viable WFP techniques may be in a realistic dynamically evolving environment. Here, we reveal that environmental perturbations reduce both the diversity of the WFP dictionary and the effective signal-to-noise ratio (SNR), such that the amount of information that can be obtained per measurement is reduced. This unfavorable effect can, however, be fully compensated by taking more measurements. We show in simulations and experiments with a low-cost software-defined radio that WFP localization of non-cooperative objects is possible even when the scattering strength of the environmental perturbation significantly exceeds that of the object to be localized. Our results underline that diversity is only one important ingredient to achieve high sensing accuracy in compressed sensing, the other two being SNR and the choice of decoding method. We find that sacrificing diversity for SNR may be worthwhile and observe that artificial neural networks outperform traditional decoding methods in terms of the achieved sensing accuracy, especially at low SNR.

physics.app-ph↗

arXiv2020

Metasurface-Assisted Passive Wireless Communication with Commodity Wi-Fi Signals

Wireless communication has become a standard solution to address ever-increasing demands for information transfer in our modern society. Conventional systems work in an active way in the sense that an active carrier signal is mandatorily required to transfer information from Alice to Bob. Especially in the era of 5G6G and with the advent of the Internet of Things (IoT), an exponential growth of users and connectivity confronts conventional systems with important challenges including limited spectrum resources, information security, energy consumption and cost efficiency. Here, we introduce the fundamentally different concept of passive wireless communication (PWC) which has the potential to resolve the above-mentioned issues. PWC transfers digital information by modulating demodulating already existing omnipresent ambient stray electromagnetic waves using a programmable metasurface. We provide a theoretical framework for encoding decoding and modulating demodulating in PWC and build a proof-of-principle prototype system leveraging existing commodity 2.4GHz Wi-Fi signals. We demonstrate information transfer from Alice to Bob with data rates on the order of hundreds of Kbps using distinguishable information-carrying control coding patterns of metasurface, neither necessitating an active carrier signal and its associated radio-frequency chain nor affecting the background active wireless communication. The presented strategy is particularly appealing for green IoT connectivity. At the same time, the concept is applicable to all types of wave phenomena and provides a fundamentally new perspective on the design of future wireless communication architectures.

physics.app-ph↗

arXiv2020

Experimental realization of optimal energy storage in resonators embedded in scattering media

The ability to enhance light-matter interactions by increasing the energy stored in optical resonators is inherently dependent on their coupling to the incident wavefront. In practice, weak coupling may result from resonators' irregular shapes and/or the scrambling of waves in the surrounding scattering environment. Here, we present a non-invasive wavefront shaping technique providing optimal coupling to resonators. The coherent control of the incident wavefront relies on the lengthening of delay times of waves efficiently exciting the resonator. We demonstrate our concept in microwave experiments by injecting in-situ optimal wavefronts that maximize the energy stored in multiple high-permittivity dielectric scatterers and extended leaky cavities embedded in a complex environment. We expect our framework to find important applications in the enhancement of light-matter interactions in photonic materials as well as to enhance energy harvesting.

physics.optics↗

arXiv2019

Optimized Analog Information Multiplexing Across Custom-Tailored MetaCavity Configurations

Combining tunable metasurfaces with chaotic cavities opens new avenues for finely tailored dynamic control of microwaves with programmable coding metacavities (PCMs). There is currently a strong interest in utilizing PCMs to overcome the notorious difficulty of coherent measurements across large apertures at radiofrequencies, with important applications in imaging and sensing for security screening, medical diagnosis and human-computer interaction. Such approaches rely on multiplexing spatially encoded information across a random sequence of PCM coding patterns for single-port single-frequency acquisition. Here, it is shown that a judiciously tailored rather than random coding sequence is necessary to unlock the full potential of PCMs for analog multiplexing. Specifically, the singular value spectrum of the multiplexing channel matrix is tailored to be perfectly flat - as opposed to downward sloping. In-situ experiments show that thereby the number of necessary measurements to achieve a given reconstruction quality is lowered by a factor of 2.5. Computational imaging and other microwave metrology applications are expected to benefit from the resulting reduction in acquisition time, processing burden and latency. The proposed approach and platform also set the stage for future studies in the emerging field of wave control through engineered wave chaos.

physics.app-ph↗

arXiv2019

Artificial Neural Network with Physical Dynamic Metasurface Layer for Optimal Sensing

We address the fundamental question of how to optimally probe a scene with electromagnetic (EM) radiation to yield a maximum amount of information relevant to a particular task. Machine learning (ML) techniques have emerged as powerful tools to extract task-relevant information from a wide variety of EM measurements, ranging from optics to the microwave domain. However, given the ability to actively illuminate a particular scene with a programmable EM wavefront, it is often not clear what wavefronts optimally encode information for the task at hand (e.g., object detection, classification). Here, we show that by integrating a physical model of scene illumination and detection into a ML pipeline, we can jointly learn optimal sampling and measurement processing strategies for a given task. We consider in simulation the example of classifying objects using microwave radiation produced by dynamic metasurfaces. By integrating an analytical forward model describing the metamaterial elements as coupled dipoles into the ML pipeline, we jointly train analog model weights with digital neural network weights. The learned non-intuitive illumination settings yield a higher classification accuracy using fewer measurements. On the practical level, these results are highly relevant to emerging context-aware systems such as autonomous vehicles, touchless human-interactive devices or within smart health care, where strict time constraints place severe limits on measurement strategies. On the conceptual level, our work serves as a bridge between wavefront shaping and tunable metasurface design on the physical layer and ML techniques on the processing layer.

physics.app-ph↗

arXiv2019

Wave Chaos in a Cavity of Regular Geometry with Tunable Boundaries

Wave chaotic systems underpin a wide range of research activities, from fundamental studies of quantum chaos via electromagnetic compatibility up to more recently emerging applications like microwave imaging for security screening, antenna characterisation or wave-based analog computation. To implement a wave chaotic system experimentally, traditionally cavities of elaborate geometries (bowtie shapes, truncated circles, parallelepipeds with hemispheres) are employed because the geometry dictates the wave field's characteristics. Here, we propose and experimentally verify a radically different paradigm: a cavity of regular geometry but with tunable boundary conditions, experimentally implemented by leveraging a reconfigurable metasurface. Our results set new foundations for the use and the study of chaos in wave physics.

physics.app-ph↗

arXiv2018

Turning Optical Complex Media into Universal Reconfigurable Linear Operators by Wavefront Shaping

Performing linear operations using optical devices is a crucial building block in many fields ranging from telecommunication to optical analogue computation and machine learning. For many of these applications, key requirements are robustness to fabrication inaccuracies and reconfigurability. Current designs of custom-tailored photonic devices or coherent photonic circuits only partially satisfy these needs. Here, we propose a way to perform linear operations by using complex optical media such as multimode fibers or thin scattering layers as a computational platform driven by wavefront shaping. Given a large random transmission matrix (TM) representing light propagation in such a medium, we can extract a desired smaller linear operator by finding suitable input and output projectors. We discuss fundamental upper bounds on the size of the linear transformations our approach can achieve and provide an experimental demonstration. For the latter, first we retrieve the complex medium's TM with a non-interferometric phase retrieval method. Then, we take advantage of the large number of degrees of freedom to find input wavefronts using a Spatial Light Modulator (SLM) that cause the system, composed of the SLM and the complex medium, to act as a desired complex-valued linear operator on the optical field. We experimentally build several $16\times16$ complex-valued operators, and are able to switch from one to another at will. Our technique offers the prospect of reconfigurable, robust and easy-to-fabricate linear optical analogue computation units.

physics.optics↗

arXiv2018

Optimal Communication Channels in a Disordered World with Tamed Randomness

Multi-channel wireless systems have become a standard solution to address our information society's ever-increasing demand for more information transfer. The ultimate bound on the capacity such systems can achieve is the limited channel diversity in a given propagation medium, and countless proposals to reduce channel cross-talk by engineering software or hardware details of the signals and antenna arrays have been proposed. Here we demonstrate the physical shaping of the propagation medium itself to achieve optimal channel diversity. Using a reconfigurable metasurface placed inside a random environment, we tune the disorder and impose perfect orthogonality of wireless channels. We present experiments in the microwave domain in which we impose equal weights of the channel matrix eigenvalues for up to 4x4 systems, and almost equal weights in larger systems. We further describe one example of wireless image transmission in an office room in which we augmented the 3x3 system's number of effectively independent channels from 2 to the optimum of 3.

physics.app-ph↗

arXiv2018

Leveraging Chaos for Wave-Based Analog Computation: Demonstration with Indoor Wireless Communication Signals

In sight of fundamental thermal limits on further substantial performance improvements of modern digital computational processing units, wave-based analog computation is becoming an enticing alternative. A wave, as it propagates through a carefully tailored medium, performs the desired computational operation. Yet, the necessary designs are so intricate that experimental demonstrations will necessitate further technological advances. Here, we show that, counterintuitively, the carefully tailored medium can be replaced with a random medium, subject to an appropriate shaping of the incident wave front. Using tunable metasurface reflect-arrays, we demonstrate our concept experimentally in a chaotic microwave cavity. We conclude that off-the-shelf wireless communication infrastructure in combination with a simple reflect-array suffices to perform analog computation with Wi-Fi waves reverberating in a room.

physics.class-ph↗

arXiv2017

Shaping Microwave Fields using Non-Linear Unsolicited Feedback: Application to Enhanced Energy Harvesting

Wavefront Shaping has emerged over the past decade as a powerful tool to control wave propagation through complex media, initially in optics and more recently also in the microwave domain with important applications in telecommunication, imaging and energy transfer. The crux of implementing wavefront shaping concepts in real life is often its need for (direct) feedback, requiring access to the target to focus on. Here, we present the shaping of a microwave field based on indirect, unsolicited and blind feedback which may be the pivotal step towards practical implementations. With the example of a radiofrequency harvester in a metallic cavity, we demonstrate tenfold enhancement of the harvested power by wavefront shaping based on non-linear signals detected at an arbitrary position away from the harvesting device.

physics.app-ph↗

arXiv2016

Spatio-temporal wavefront shaping in a microwave cavity

Controlling waves in complex media has become a major topic of interest, notably through the concepts of time reversal and wavefront shaping. Recently, it was shown that spatial light modulators can counter-intuitively focus waves both in space and time through multiple scattering media when illuminated with optical pulses. In this letter we transpose the concept to a microwave cavity using flat arrays of electronically tunable resonators. We prove that maximizing the Green's function between two antennas at a chosen time yields diffraction limited spatio-temporal focusing. Then, changing the photons' dwell time inside the cavity, we modify the relative distribution of the spatial and temporal degrees of freedom (DoF), and we demonstrate that it has no impact on the field enhancement: wavefront shaping makes use of all available DoF, irrespective of their spatial or temporal nature. Our results prove that wavefront shaping using simple electronically reconfigurable arrays of reflectors is a viable approach to the spatio-temporal control of microwaves, with potential applications in medical imaging, therapy, telecommunications, radar or sensing. They also offer new fundamental insights regarding the coupling of spatial and temporal DoF in complex media.

physics.class-ph↗

arXiv2016

Intensity-only measurement of partially uncontrollable transmission matrix: demonstration with wave-field shaping in a microwave cavity

Transmission matrices (TMs) have become a powerful and widely used tool to describe and control wave propagation in complex media. In certain scenarios the TM is partially uncontrollable, complicating its identification and use. In standard optical wavefront shaping experiments, uncontrollable reflections or additional sources may be the cause; in reverberating cavities, uncontrollable reflections off the walls have that effect. Here we employ phase retrieval techniques to identify such a partially uncontrollable system's TM solely based on random intensity-only reference measurements. We demonstrate the feasibility of our method by focusing both on a single target as well as on multiple targets in a microwave cavity, using a phase-binary Spatial-Microwave-Modulator.

physics.class-ph↗