1: He-Ne laser speckle
2: Interference fringes in a soap bubble
3: Fractal electron tree or Lichtenberg figure

About us

We are a theoretical research group forming part of the Photonics Division located at the Blackett Laboratory of Imperial College London. The group is lead by Dr. Matthew R. Foreman who currently holds a Royal Society University Research Fellowship.

Our research focuses on optical and plasmonic sensing, polarisation sensitive imaging, disordered media and electromagnetic theory. More information on some of our past and present projects can be found by visiting our Research pages.

Recent news

Random matrix theory of polarized light scattering in disordered media

14 Dec 2022: Our latest paper in Waves in Random and Complex Media has just gone live online. In it we describe a new random matrix modelling technique to describe propagation of polarized light through a random scattering medium. It is open access, so please check it out now!

PhD positions available

21 Oct 2022: We have funding available for a number of PhD positions based at NTU Singapore. A list of currently available projects can be found here. Contact Matthew Foreman if you are interested in joining the team or want more information.

Move to NTU Singapore

21 Oct 2022: After 7.5 years at Imperial College, the group is moving! As of March 2023, Matthew will take up an Assistant Professor position at Nanyang Technological University in Singapore. Matthew's appointment is in the School of Electrical and Electronic Engineering (EEE) and he will be working closely with the Institute for Digital Molecular Analytics and Science (IDMxS).

Recent publications

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N. Byrnes and M. R. Foreman, "Random matrix theory of polarized light scattering in disordered media" Waves Random Complex Media in press (2022).

Abstract : In this work we present a method for generating random matrices describing electromagnetic scattering from disordered media containing dielectric particles with prescribed single particle scattering characteristics. Resulting scattering matrices automatically satisfy the physical constraints of unitarity, reciprocity and time reversal, whilst also incorporating the polarization properties of electromagnetic waves and scattering anisotropy. Our technique therefore enables statistical study of a variety of polarization phenomena, including depolarization rates and polarization-dependent scattering by chiral particles. In this vein, we perform numerical simulations for media containing isotropic and chiral spherical particles of different sizes for thicknesses ranging from the single to multiple scattering regime and discuss our results, drawing comparisons to established theory.

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H. Lee, J. Berk, A. Webster, D. Kim and M. R. Foreman, "Label-free detection of single nanoparticles with disordered nanoisland surface plasmon sensor" Nanotechnology 33, 165502 (2022).

Abstract : We report sensing of single nanoparticles using disordered metallic nanoisland substrates supporting surface plasmon polaritons (SPPs). Speckle patterns arising from leakage radiation of elastically scattered SPPs provides a unique fingerprint of the scattering microstructure at the sensor surface. Experimental measurements of the speckle decorrelation are presented and shown to enable detection of sorption of individual gold nanoparticles and polystyrene beads. Our approach is verified through bright-field and fluorescence imaging of particles adhering to the nanoisland substrate.

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N. Byrnes and M. R. Foreman, "Polarisation statistics of vector scattering matrices from the circular orthogonal ensemble" Opt. Commun. 503, 127462 (2022).

Abstract : We study the polarisation properties of random N × N scattering matrices distributed according to the circular orthogonal ensemble. We interpret 2 × 2 sub-blocks of the scattering matrix as Jones matrices and study their statistical properties. Using the polar decomposition, we derive probability density functions for retardance and diattenuation from scattering matrices of arbitrary size and in the limit N → ∞.

Funding

Our research is supported by generous funding from:

The Royal Society
Microsoft Research
EPSRC