Inverse design of multiresonance filters via quasi-normal mode theory
arXiv:2504.10219 · doi:10.1364/OE.579219
Abstract
We present a practical methodology for inverse design of compact high-order/multiresonance filters in linear passive 2-port wave-scattering systems, targeting any desired transmission spectrum (such as standard pass/stop-band filters). Our formulation allows for both large-scale topology optimization and few-variable parametrized-geometry optimization. It is an extension of a quasi-normal mode theory and analytical filter-design criteria (on the system resonances and background response) derived in our previous work. Our new optimization-oriented formulation relies solely on a scattering solver and imposes these design criteria as equality constraints with easily calculated (via the adjoint method) derivatives, so that our algorithm is numerically tractable, robust, and well-suited for large-scale inverse design. We demonstrate its effectiveness by designing 3rd- and 4th-order elliptic and Chebyshev filters for photonic metasurfaces, multilayer films, and electrical LC-ladder circuits.
arXiv comment16 pages, 7 figures
References in corpus (11)
- Outlook for inverse design in nanophotonics
- Coherent Perfect Absorbers: Time-reversed Lasers
- High-NA Achromatic Metalenses by Inverse Design
- Topology Optimized Multi-layered Meta-optics
- Maximizing the quality factor to mode volume ratio for ultra-small photonic crystal cavities
- Fullwave Maxwell inverse design of axisymmetric, tunable, and multi-scale multi-wavelength metalenses
- Band Gap Optimization of Two-Dimensional Photonic Crystals Using Semidefinite Programming and Subspace Methods
- How to calculate the pole expansion of the optical scattering matrix from the resonant states
- Quasi-normal mode theory of the scattering matrix, enforcing fundamental constraints for truncated expansions
- Analytical criteria for designing multiresonance filters in scattering systems, with application to microwave metasurfaces
- Designing Structures that Maximize Spatially Averaged Surface-Enhanced Raman Spectra