Topology optimization for nano‐photonics

By Jakob S. Jensen, Ole Sigmund. 2011

735 citations recorded by the source corpus.

Subfields: Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering, Surfaces, Coatings and Films

View Paper: https://www.semanticscholar.org/paper/6cd60bd6885c2e048110398e6050303b58a31e5d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atomic and Molecular Physics, and Optics

In Electrical and Electronic Engineering

In Surfaces, Coatings and Films

Citations in the corpus

Deep learning in nano-photonics: inverse design and beyond (2020, methodology): “A more systematic alternative was the combination of numerical simulation methods with gradient-based or heuristic optimization algorithms, such as stimulated annealing, topology optimization, and genetic algorithms [32,41 – 44].”
Inverse design and demonstration of a compact and broadband on-chip wavelength demultiplexer (2015, background): “These complex, aperiodic structures can provide previously unattainable functionality, or higher performance and smaller footprints than traditional devices, due to the greatly expanded design space [5, 8, 9, 10, 11, 12, 13, 14].”
Physics-informed neural networks with hard constraints for inverse design (2021, methodology): “As a comparison, we also solve this problem by using the method for PDE-constrained inverse design discussed in [34], and here we have considered two numerical PDE solvers: FDFD [7] and FEM [1, 3, 16] (details in Appendices B and C, respectively).”
Topology optimisation for natural convection problems (2014, methodology): “Although the topology optimisation method originated and gained maturity within structural mechanics, the method has since been extended to a wide range of physics, such as acoustics [10], photonics [11], fluidics [12] and many more.”
Intelligent nanophotonics: merging photonics and artificial intelligence at the nanoscale (2018, methodology): “igmund and coworkers conducted a systematic study using the tool of topology optimization, which was originally developed for structural design [36,37] but has been applied to many other applications [25]. In topology optimization, the entire design domain is discretized into pixels, each being a de”
A survey of structural and multidisciplinary continuum topology optimization: post 2000 (2014, background): “Similarly, other works have focused on the optimal material distribution in photonic crystal waveguides, which transmit electromagnetic waves for a variety of objectives (Jensen and Sigmund 2011).”
Cavity-enhanced second-harmonic generation via nonlinear-overlap optimization (2015, methodology): “The scattering framework makes it straightforward to calculate the derivatives of f (and possible functional constraints) with respective to ǭα via the adjoint variable method [39–41].”
Design of manufacturable 3D extremal elastic microstructure (2014, background): “It is utilized in a broad range of problems varying from pure mechanical designs (e.g., aerospace structures (Krog et al., 2004)) to designs in electromagnetics and photonics (e.g., Jensen and Sigmund, 2011).”