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Sylvain Gigan

4 papers hereh-index 3222 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • physics.optics2
  • cs.ET1
  • physics.app-ph1
same name
  • Sylvain Gigan — 7 papers, h 2
  • Sylvain Gigan — 5 papers, h 5
  • Sylvain Gigan — 4 papers, h 4
  • Sylvain Gigan — 3 papers, h 2
  • Sylvain Gigan — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedLow Photon Number Non-Invasive Imaging Through Time-Varying Diffusers

1 citations · 1 across the 2 of their papers we have counts for

collaborators

4 papers

physics.optics2026

Real-time Calibration-free Imaging Through Dynamic and Distinct Multimode Fibers via Spatial Harmonic Invariant Nonlinear Encoding (SHINE)

Zhiyuan Wang, Haoran Li, Songjie Luo +8

Multimode fibers (MMFs) provide a compact, high-throughput platform for minimally invasive imaging and information transmission. However, their utility is fundamentally constrained…

physics.optics2026★ 1 cited

Low Photon Number Non-Invasive Imaging Through Time-Varying Diffusers

Adrian Makowski, Wojciech Zwolinski, Pawel Szczypkowski +3

Optical imaging plays a crucial role in advancing science and technology, enabling applications in fields ranging from biomedicine to astronomy. However, imaging through scattering…

cs.ET2025

Roadmap on Neuromorphic Photonics

Daniel Brunner, Bhavin J. Shastri, Mohammed A. Al Qadasi +147

This roadmap consolidates recent advances while exploring emerging applications, reflecting the remarkable diversity of hardware platforms, neuromorphic concepts, and implementatio…

physics.app-ph2024

Training of Physical Neural Networks

Ali Momeni, Babak Rahmani, Benjamin Scellier +25

Physical neural networks (PNNs) are a class of neural-like networks that leverage the properties of physical systems to perform computation. While PNNs are so far a niche research…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.