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High-performance multimode/multiwavelength (de)multiplexer is one of the most pivotal photonic devices for advanced on-chip interconnect systems. Traditional on-chip photonic (de)multiplexing requires large device footprint for maintaining…

Optics · Physics 2025-09-03 Faqian Chong , Yulun Wu , Bingtao Gao , Shilong Li , Hongsheng Chen , Song Han

The field of magnonics offers a new type of low-power information processing, in which magnons, the quanta of spin waves, carry and process data instead of electrons. Many magnonic devices were demonstrated recently, but the development of…

Applied Physics · Physics 2021-06-09 Qi Wang , Andrii V. Chumak , Philipp Pirro

Optical devices lie at the heart of most of the technology we see around us. When one actually wants to make such an optical device, one can predict its optical behavior using computational simulations of Maxwell's equations. If one then…

Machine Learning · Computer Science 2022-02-09 Joeri Lenaerts , Hannah Pinson , Vincent Ginis

Nanophotonic technologies inherently rely on tailoring light-matter interactions through the excitation and interference of deeply confined optical resonances. However, existing concepts in optical mode engineering remain heuristic and are…

In this paper, we introduce the design approach of integrated photonic devices by employing reinforcement learning known as attractor selection. Here, we combined three-dimensional finite-difference time-domain method with attractor…

The fusion of artificial intelligence (AI) with physics-guided frameworks has opened transformative avenues for advancing the design and optimization of electromagnetic and nanophotonic systems. Innovations in deep neural networks (DNNs)…

Deep learning has emerged as a key tool for designing nanophotonic structures that manipulate light at sub-wavelength scales. We investigate how to inversely design plasmonic nanostructures using conditional generative adversarial networks.…

Optics · Physics 2026-05-21 Petter Persson , Nils Henriksson , Nicolò Maccaferri

Previously proposed designs of integrated photonic devices have used the intuitive brute force approach or optimization methods that employ parameter search algorithms. However, a small parameter space and poor exploitation of the…

Applied Physics · Physics 2019-02-28 Yusuf A. Yilmaz , Ahmet M. Alpkilic , Aydan Yeltik , Hamza Kurt

Electromagnetic metasurfaces have attracted significant interest recently due to their low profile and advantageous applications. Practically, many metasurface designs start with a set of constraints for the radiated far-field, such as…

Materials Science · Physics 2022-04-04 Stewart Pearson , Parinaz Naseri , Sean V. Hum

The design of metamaterials which support unique optical responses is the basis for most thin-film nanophotonics applications. In practice this inverse design problem can be difficult to solve systematically due to the large design…

Computational Physics · Physics 2026-05-25 Andrew Lininger , Michael Hinczewski , Giuseppe Strangi

Inverse design (ID) is a computational method that systematically explores a design space to find optimal device geometries based on specific performance criteria. In silicon photonics, ID often leads to devices with design features that…

Systems and Control · Electrical Eng. & Systems 2024-10-11 Shaheer Khan , Mustafa Hammood , Nicolas A. F. Jaeger , Lukas Chrostowski

Inverse design is a powerful tool in wave-physics and in particular in photonics for compact, high-performance devices. To date, applications have mostly been limited to linear systems and it has rarely been investigated or demonstrated in…

Metasurfaces is an emerging field that enables the manipulation of light by an ultra-thin structure composed of sub-wavelength antennae and fulfills an important requirement for miniaturized optical elements. Finding a new design for a…

Machine learning-based compact models provide a rapid and efficient approach for estimating device behavior across multiple input parameter variations. In this study, we introduce two reverse-design algorithms that utilize these compact…

Emerging Technologies · Computer Science 2025-08-29 Diego Ferrer , Jack Hutchins , Revanth Koduru , Sumeet Kumar Gupta , Admedullah Aziz

Machine learning (ML) is emerging as a transformative tool for the design of architected materials, offering properties that far surpass those achievable through lab-based trial-and-error methods. However, a major challenge in current…

Electromagnetic metasurface design based on far-field constraints without the complete knowledge of the fields on both sides of the metasurface is typically a time consuming and iterative process, which relies heavily on heuristics and ad…

Optics · Physics 2022-08-17 Parinaz Naseri , Stewart Pearson , Zhengzheng Wang , Sean V. Hum

Metasurfaces are an emerging technology that may supplant many of the conventional optics found in imaging devices, displays, and precision scientific instruments. Here, we develop a method for designing optical systems composed of multiple…

Optics · Physics 2019-10-23 Adam S. Backer

One emerging approach for the fabrication of complex architectures on the nanoscale is to utilize particles customized to intrinsically self-assemble into a desired structure. Inverse methods of statistical mechanics have proven…

Materials Science · Physics 2017-09-08 R. B. Jadrich , B. A. Lindquist , T. M. Truskett

The inverse design of optical metasurfaces is a rapidly emerging field that has already shown great promise in miniaturizing conventional optics as well as developing completely new optical functionalities. Such a design process relies on…

Optics · Physics 2020-08-26 Maksym V. Zhelyeznyakov , Steven L. Brunton , Arka Majumdar

Integrated photonics is increasingly demanded in applications such as large-scale data centers, intelligent sensing, and next-generation wireless communications, where compact, multifunctional, and energy-efficient components are essential.…

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