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Deep-learning enabled generalized inverse design of multi-port radio-frequency and sub-terahertz passives and integrated circuits

Author

Listed:
  • Emir Ali Karahan

    (Princeton University)

  • Zheng Liu

    (Princeton University)

  • Aggraj Gupta

    (Indian Institute of Technology Madras)

  • Zijian Shao

    (Princeton University)

  • Jonathan Zhou

    (Princeton University)

  • Uday Khankhoje

    (Indian Institute of Technology Madras)

  • Kaushik Sengupta

    (Princeton University)

Abstract

Millimeter-wave and terahertz integrated circuits and chips are expected to serve as the backbone for future wireless networks and high resolution sensing. However, design of these integrated circuits and chips can be quite complex, requiring years of human expertise, careful tailoring of hand crafted circuit topologies and co-design with parameterized and pre-selected templates of electromagnetic structures. These structures (radiative and non-radiative, single-port and multi-ports) are subsequently optimized through ad-hoc methods and parameter sweeps. Such bottom-up approaches with pre-selected regular topologies also fundamentally limit the design space. Here, we demonstrate a universal inverse design approach for arbitrary-shaped complex multi-port electromagnetic structures with designer radiative and scattering properties, co-designed with active circuits. To allow such universalization, we employ deep learning based models, and demonstrate synthesis with several examples of complex mm-Wave passive structures and end-to-end integrated mm-Wave broadband circuits. The presented inverse design methodology, that produces the designs in minutes, can be transformative in opening up a new, previously inaccessible design space.

Suggested Citation

  • Emir Ali Karahan & Zheng Liu & Aggraj Gupta & Zijian Shao & Jonathan Zhou & Uday Khankhoje & Kaushik Sengupta, 2024. "Deep-learning enabled generalized inverse design of multi-port radio-frequency and sub-terahertz passives and integrated circuits," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-54178-1
    DOI: 10.1038/s41467-024-54178-1
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    References listed on IDEAS

    as
    1. Jianjun Ma & Rabi Shrestha & Jacob Adelberg & Chia-Yi Yeh & Zahed Hossain & Edward Knightly & Josep Miquel Jornet & Daniel M. Mittleman, 2018. "Security and eavesdropping in terahertz wireless links," Nature, Nature, vol. 563(7729), pages 89-93, November.
    2. Xue Wu & Huaixi Lu & Kaushik Sengupta, 2019. "Programmable terahertz chip-scale sensing interface with direct digital reconfiguration at sub-wavelength scales," Nature Communications, Nature, vol. 10(1), pages 1-13, December.
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