arXiv subjects

Sylvain Gigan

Publications and source records attributed to Sylvain Gigan.

At least 55 records · Page 3Linked to original sources

arXiv2023

Single-pixel transmission matrix recovery via 2-photon fluorescence

Imaging at depth in opaque materials has long been a challenge. Recently, wavefront shaping has enabled significant advance for deep imaging. Nevertheless, most non-invasive wavefront shaping methods require cameras, lack the sensitivity for deep imaging under weak optical signals, or can only focus on a single "guidestar". Here, we retrieve the transmission matrix (TM) non-invasively using two-photon fluorescence exploiting a general single-pixel detection framework, allowing to achieve single-target focus on multiple guidestars spread beyond the memory effect range. In addition, if we assume memory effect correlations exist in the transmission matrix, we are able to significantly reduce the number of measurements needed.

physics.optics↗

arXiv2023

Functional imaging through scattering medium via fluorescence speckle demixing and localization

Recently, fluorescence-based optical techniques have emerged as a powerful tool to probe information in the mammalian brain. However, tissue heterogeneities prevent clear imaging of deep neuron bodies due to light scattering. While several up-to-date approaches based on ballistic light allow to retrieve information at shallow depths inside the brain, non-invasive localization and functional imaging at depth still remains a challenge. It was recently shown that functional signals from time-varying fluorescent emitters located behind scattering samples could be retrieved by using a matrix factorization algorithm. Here we show that the seemingly information-less, low-contrast fluorescent speckle patterns recovered by the algorithm can be used to locate each individual emitter, even in the presence of background fluorescence. We test our approach by imaging the temporal activity of large groups of fluorescent sources behind different scattering phantoms mimicking biological tissues, and through a brain slice with a thickness of ~200 micron.

physics.optics↗

arXiv2023

Quantifying high-dimensional spatial entanglement with a single-photon-sensitive time-stamping camera

High-dimensional entanglement is a promising resource for quantum technologies. Being able to certify it for any quantum state is essential. However, to date, experimental entanglement certification methods are imperfect and leave some loopholes open. Using a single-photon sensitive time-stamping camera, we quantify high-dimensional spatial entanglement by collecting all output modes and without background subtraction, two critical steps on the route towards assumptions-free entanglement certification. We show position-momentum Einstein-Podolsky-Rosen (EPR) correlations and quantify the entanglement of formation of our source to be larger than 2.8 along both transverse spatial axes, indicating a dimension higher than 14. Our work overcomes important challenges in photonic entanglement quantification and paves the way towards the development of practical quantum information processing protocols based on high-dimensional entanglement.

quant-ph↗

arXiv2023

Manipulation and certification of high-dimensional entanglement through a scattering medium

High-dimensional entangled quantum states improve the performance of quantum technologies compared to qubit-based approaches. In particular, they enable quantum communications with higher information capacities or enhanced imaging protocols. However, the presence of optical disorder such as atmospheric turbulence or biological tissue perturb quantum state propagation and hinder their practical use. Here, we demonstrate a wavefront shaping approach to transmit high-dimensional spatially entangled photon pairs through scattering media. Using a transmission matrix approach, we perform wavefront correction in the classical domain using an intense classical beam as a beacon to compensate for the disturbances suffered by a co propagating beam of entangled photons. Through violation of an Einstein-Podolski-Rosen criterion by $988$ sigma, we show the presence of entanglement after the medium. Furthermore, we certify an entanglement dimensionality of $17$. This work paves the way towards manipulation and transport of entanglement through scattering media, with potential applications in quantum microscopy and quantum key distribution.

quant-ph↗

arXiv2022

Intelligent Computing: The Latest Advances, Challenges and Future

Computing is a critical driving force in the development of human civilization. In recent years, we have witnessed the emergence of intelligent computing, a new computing paradigm that is reshaping traditional computing and promoting digital revolution in the era of big data, artificial intelligence and internet-of-things with new computing theories, architectures, methods, systems, and applications. Intelligent computing has greatly broadened the scope of computing, extending it from traditional computing on data to increasingly diverse computing paradigms such as perceptual intelligence, cognitive intelligence, autonomous intelligence, and human-computer fusion intelligence. Intelligence and computing have undergone paths of different evolution and development for a long time but have become increasingly intertwined in recent years: intelligent computing is not only intelligence-oriented but also intelligence-driven. Such cross-fertilization has prompted the emergence and rapid advancement of intelligent computing. Intelligent computing is still in its infancy and an abundance of innovations in the theories, systems, and applications of intelligent computing are expected to occur soon. We present the first comprehensive survey of literature on intelligent computing, covering its theory fundamentals, the technological fusion of intelligence and computing, important applications, challenges, and future perspectives. We believe that this survey is highly timely and will provide a comprehensive reference and cast valuable insights into intelligent computing for academic and industrial researchers and practitioners.

cs.AI↗

arXiv2022

Phase Retrieval: From Computational Imaging to Machine Learning

Phase retrieval consists in the recovery of a complex-valued signal from intensity-only measurements. As it pervades a broad variety of applications, many researchers have striven to develop phase-retrieval algorithms. Classical approaches involve techniques as varied as generic gradient-descent routines or specialized spectral methods, to name a few. Yet, the phase-recovery problem remains a challenge to this day. Recently, however, advances in machine learning have revitalized the study of phase retrieval in two ways: significant theoretical advances have emerged from the analogy between phase retrieval and single-layer neural networks; practical breakthroughs have been obtained thanks to deep-learning regularization. In this tutorial, we review phase retrieval under a unifying framework that encompasses classical and machine-learning methods. We focus on three key elements: applications, overview of recent reconstruction algorithms, and the latest theoretical results.

physics.optics↗

arXiv2022

Competing oxygen evolution reaction mechanisms revealed by high-speed compressive Raman imaging

Transition metal oxides are state-of-the-art materials for catalysing the oxygen evolution reaction (OER), whose slow kinetics currently limit the efficiency of water electrolysis. However, microscale physicochemical heterogeneity between particles, dynamic reactions both in the bulk and at the surface, and an interplay between particle reactivity and electrolyte makes probing the OER challenging. Here, we overcome these limitations by applying state-of-the-art compressive Raman imaging to uncover competing bias-dependent mechanisms for the OER in a solid electrocatalyst, α-Li2IrO3. By spatially and temporally tracking changes in the in- and out-of-plane Ir-O stretching modes - identified by density functional theory calculations - we follow catalytic activation and charge accumulation following ion exchange under a variety of electrolytes, particle compositions and cycling conditions. We extract velocities of phase fronts and demonstrate that at low overpotentials oxygen is evolved by the combination of an electrochemical-chemical mechanism and a classical electrocatalytic adsorbate mechanism, whereas at high overpotentials only the latter occurs. These results provide strategies to promote mechanisms for enhanced OER performances, and highlight the power of compressive Raman imaging for low-cost, chemically specific tracking of microscale reaction dynamics in a broad range of systems where ion and electron exchange can be coupled to structural changes, i.e. catalysts, battery materials, memristors, etc.

cond-mat.mtrl-sci↗

arXiv2022

Online learning of the transfer matrix of dynamic scattering media: wavefront shaping meets multidimensional time series

Thanks to the latest advancements in wavefront shaping, optical methods have proven crucial to achieve imaging and control light in multiply scattering media, like biological tissues. However, the stability times of living biological specimens often prevent such methods from gaining insights into relevant functioning mechanisms in cellular and organ systems. Here we present a recursive and online optimization routine, borrowed from time series analysis, to optimally track the transfer matrix of dynamic scattering media over arbitrarily long timescales. While preserving the advantages of both optimization-based routines and transfer-matrix measurements, it operates in a memory-efficient manner. Because it can be readily implemented in existing wavefront shaping setups, featuring amplitude and/or phase modulation and phase-resolved or intensity-only acquisition, it paves the way for efficient optical investigations of living biological specimens.

physics.optics↗

arXiv2022

Three-dimensional operando optical imaging of single particle and electrolyte heterogeneities inside Li-ion batteries

Understanding (de)lithiation heterogeneities in battery materials is key to ensuring optimal electrochemical performance and developing better energy storage devices. However, this remains challenging due to the complex three dimensional morphology of microscopic electrode particles, the involvement of both solid and liquid phase reactants, and range of relevant timescales (seconds to hours). Here, we overcome this problem and demonstrate the use of bench-top laser scanning confocal microscopy for simultaneous three-dimensional operando measurement of lithium ion dynamics in single particles, and the electrolyte, in batteries. We examine two technologically important cathode materials that are known to suffer from intercalation heterogeneities: LixCoO2 and LixNi0.8Mn0.1Co0.1O2. The single-particle surface-to-core transport velocity of Li-phase fronts, and volume changes - as well as their inter-particle heterogeneity - are captured as a function of C-rate, and benchmarked to previous ensemble measurements. Additionally, we visualise heterogeneities in the bulk and at the surface of particles during cycling, and image the formation of spatially non-uniform concentration gradients within the liquid electrolyte. Importantly, the conditions under which optical imaging can be performed inside absorbing and multiply scattering materials such as battery intercalation compounds are outlined.

cond-mat.mtrl-sci↗

arXiv2022

Scattering correcting wavefront shaping for three-photon microscopy

Three-photon (3P) microscopy is getting traction due to its superior performance in deep tissues. Yet, aberrations and light scattering still pose one of the main limitations in the attainable depth ranges for high-resolution imaging. Here, we show scattering correcting wavefront shaping with a simple continuous optimization algorithm, guided by the integrated 3P fluorescence signal. We demonstrate focusing and imaging behind scattering layers and investigate convergence trajectories for different sample geometries and feedback non-linearities. Furthermore, we show imaging through a mouse skull and demonstrate a novel fast phase estimation scheme that substantially increases the speed at which the optimal correction can be found.

physics.optics↗

arXiv2022

Physics-based neural network for non-invasive control of coherent light in scattering media

Optical imaging through complex media, such as biological tissues or fog, is challenging due to light scattering. In the multiple scattering regime, wavefront shaping provides an effective method to retrieve information; it relies on measuring how the propagation of different optical wavefronts are impacted by scattering. Based on this principle, several wavefront shaping techniques were successfully developed, but most of them are highly invasive and limited to proof-of-principle experiments. Here, we propose to use a neural network approach to non-invasively characterize and control light scattering inside the medium and also to retrieve information of hidden objects buried within it. Unlike most of the recently-proposed approaches, the architecture of our neural network with its layers, connected nodes and activation functions has a true physical meaning as it mimics the propagation of light in our optical system. It is trained with an experimentally-measured input/output dataset built from a series of incident light patterns and corresponding camera snapshots. We apply our physics-based neural network to a fluorescence microscope in epi-configuration and demonstrate its performance through numerical simulations and experiments. This flexible method can include physical priors and we show that it can be applied to other systems as, for example, non-linear or coherent contrast mechanisms.

physics.optics↗

arXiv2022

Tuneable spin-glass optical simulator based on multiple light scattering

The race to heuristically solve non-deterministic polynomial-time (NP) problems through efficient methods is ongoing. Recently, optics was demonstrated as a promising tool to find the ground state of a spin-glass Ising Hamiltonian, which represents an archetypal NP problem. However, achieving completely programmable spin couplings in these large-scale optical Ising simulators remains an open challenge. Here, by exploiting the knowledge of the transmission matrix of a random medium, we experimentally demonstrate the possibility of controlling the couplings of a fully connected Ising spin system. By further tailoring the input wavefront we showcase the possibility of modifying the Ising Hamiltonian both by accounting for an external magnetic field and by controlling the number of degenerate ground states and their properties and probabilities. Our results represent a relevant step toward the realisation of fully-programmable Ising machines on thin optical platforms, capable of solving complex spin-glass Hamiltonians on a large scale.

cond-mat.dis-nn↗

arXiv2022

Non-invasive chemically selective energy delivery and focusing inside a scattering medium guided by Raman scattering

Raman scattering is a chemically selective probing mechanism with diverse applications in industry and clinical settings. Yet, most samples are optically opaque limiting the applicability of Raman probing at depth. Here, we demonstrate chemically selective energy deposition behind a scattering medium by combining prior information on the chemical's spectrum with the measurement of a spectrally resolved Raman speckle as a feedback mechanism for wavefront shaping. We demonstrate unprecedented six-fold signal enhancement in an epi-geometry, realizing targeted energy deposition and focusing on selected Raman active particles.

physics.optics↗

arXiv2022

Temporal light control in complex media through the singular value decomposition of the time-gated transmission matrix

The complex temporal behavior of an ultrashort pulse of light propagating through a multiply scattering medium can be characterized experimentally through a time-gated transmission matrix. Using a spatial light modulator, we demonstrate here, that injecting singular vectors of this matrix allows us to optimally control energy deposition at any controllable delay time. Our approach provides insights into fundamental aspects of multi-spectral light scattering and could find applications in imaging or coherent control.

physics.optics↗

arXiv2022

Single-shot diffraction-limited imaging through scattering layers via bispectrum analysis

Recently introduced speckle-correlations based techniques enable noninvasive imaging of objects hidden behind scattering layers. In these techniques the hidden object Fourier amplitude is retrieved from the scattered light autocorrelation, and the lost Fourier phase is recovered via iterative phase-retrieval algorithms, which suffer from convergence to wrong local-minima solutions and cannot solve ambiguities in object-orientation. Here, inspired by notions used in astronomy, we experimentally demonstrate that in addition to Fourier amplitude, the object phase information is naturally and inherently encoded in scattered light bispectrum (the Fourier transform of triple-correlation), and can also be extracted from a single high-resolution speckle pattern, based on which we present a single-shot imaging scheme to deterministically and unambiguously retrieve diffraction-limited images of objects hidden behind scattering layers.

physics.optics↗

arXiv2022

Speckle engineering through singular value decomposition of the transmission matrix

Speckle patterns are ubiquitous in optics and have multiple applications for which the control of their spatial correlations is essential. Here, we report on a method to engineer speckle correlations behind a scattering medium through the singular value decomposition of the transmission matrix. We not only demonstrate control over the speckle grain size and shape but also realize patterns with non-local correlations. Moreover, we show that the reach of our method extends also along the axial dimension, allowing volumetric speckle engineering behind scattering layers.

physics.optics↗

arXiv2021

Roadmap on Wavefront Shaping and deep imaging in complex media

The last decade has seen the development of a wide set of tools, such as wavefront shaping, computational or fundamental methods, that allow to understand and control light propagation in a complex medium, such as biological tissues or multimode fibers. A vibrant and diverse community is now working on this field, that has revolutionized the prospect of diffraction-limited imaging at depth in tissues. This roadmap highlights several key aspects of this fast developing field, and some of the challenges and opportunities ahead.

physics.optics↗

arXiv2021

Controlling spatial coherence with an optical complex medium

Control over optical spatial coherence is a key requirement in diverse applications including imaging, optical trapping, and communications. Current approaches to controlling spatial coherence are constrained by speed or limited to a single pair of optical fields. Here, we propose a method to achieve single-shot control of the spatial coherence between an arbitrary number of fields. Our method employs a multi-port linear optical device, which we realize by shaping the wavefront of the input light fields and transmitting them through a complex medium. To demonstrate the capabilities of our method, we experimentally realize a 3x3-port system and use it to generate three output beams with desired mutual correlations.

physics.optics↗