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researcher

S. Reitzenstein

53 papers hereh-index 5412.6k citations423 works total

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

author position
  • middle author25
  • last author24

Across the 49 of 53 papers where every author was matched, so the position is known.

fields
  • cond-mat.mes-hall23
  • physics.optics8
  • quant-ph8
  • physics.app-ph5
  • cs.ET4
  • cond-mat.mtrl-sci2
same name
  • S. Reitzenstein — 31 papers, h 22
  • S. Reitzenstein — 1 paper, h 12
  • S. Reitzenstein — 1 paper

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
20102026
most citedQuantum dots for photonic quantum information technology

173 citations · 577 across the 35 of their papers we have counts for

collaborators
Showing cs.ETShow all

4 papers · 1 filter

cs.ET2026

Power law scaling for classification accuracy in physical neural networks

Andrei V. Ermolaev, Mathilde Hary, Anas Skalli +7

Physical neural networks (PNNs) harness the intrinsic complexity of physical systems to perform neural computation, potentially at speeds and energy efficiencies inaccessible to co…

cs.ET2025

High Clockrate Free-space Optical In-Memory Computing

Yuanhao Liang, James Wang, Kaiwen Xue +12

The ability to process and act on data in real time is increasingly critical for applications ranging from autonomous vehicles, three-dimensional environmental sensing and remote r…

cs.ET2024★ 20 cited

Experimental reservoir computing with diffractively coupled VCSELs

Moritz Pflüger, Daniel Brunner, Tobias Heuser +3

We present experiments on reservoir computing (RC) using a network of vertical-cavity surface-emitting lasers (VCSELs) that we diffractively couple via an external cavity. Our opti…

cs.ET2020

Developing of a photonic hardware platform for brain-inspired computing based on 5×5 VCSEL arrays

T. Heuser, M. Pflüger, I. Fischer +3

Brain-inspired computing concepts like artificial neural networks have become promising alternatives to classical von Neumann computer architectures. Photonic neural networks targe…

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