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Scattering Media as a Resource Towards Information Processing and Sensing

Objective

Scattering of light in complex environments has long been considered a nuisance and an inescapable limitation to imaging and sensing alike, ranging from astronomical observation, biomedical imaging, spectroscopy, etc. In the last decade, wavefront shaping techniques have revolutionized this view, by allowing light focusing and imaging even deep in the multiple scattering regime. This principle is embodied in the possibility—that I pioneered—to access the transmission matrix of a complex medium.
In SMARTIES, I will go one major conceptual step further, by exploiting directly the inherent property of a complex medium to mix perfectly and deterministically the information carried by the light. This mixing is actually a processing step. Along this general idea, SMARTIES will explore two synergistic directions:
—Classical and quantum optical computing: Thanks to the highly multimode nature and the strong mixing properties of complex material, I will aim at demonstrating high performance classical computing tasks in the context of randomized algorithms. As a platform for quantum information processing, this will be relevant for high dimension quantum computing algorithms, and quantum machine learning.
—Generalized imaging and sensing: Rather than tediously focusing and imaging through a scattering material, computational approaches can significantly improve and simplify the imaging process. I also aim to show that the relevant information can be directly and optimally extracted from the scattered light without imaging, using machine-learning algorithms.
From a methodological standpoint, SMARTIES will require bridging knowledge from mesoscopic physics, light-matter interaction, linear and non-linear optics, with algorithms and signal processing concepts. It will deliver a whole new class of optical methods and devices, based on disorder. Its applications range from big data analysis, quantum technologies, to sensors and deep imaging for biology and neuroscience.

Field of science

  • /engineering and technology/electrical engineering, electronic engineering, information engineering/electronic engineering/computer hardware/quantum computer
  • /engineering and technology/electrical engineering, electronic engineering, information engineering/electronic engineering/signal processing
  • /natural sciences/computer and information sciences/data science/big data
  • /natural sciences/computer and information sciences/data science/data processing
  • /natural sciences/physical sciences/condensed matter physics/mesoscopic physics
  • /natural sciences/computer and information sciences/artificial intelligence/machine learning
  • /natural sciences/computer and information sciences/data science/data analysis

Call for proposal

ERC-2016-COG
See other projects for this call

Funding Scheme

ERC-COG - Consolidator Grant

Host institution

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Address
Rue Michel Ange 3
75794 Paris
France
Activity type
Research Organisations
EU contribution
€ 1 999 891

Beneficiaries (1)

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
France
EU contribution
€ 1 999 891
Address
Rue Michel Ange 3
75794 Paris
Activity type
Research Organisations