Reconfigurable Curved Beams at Terahertz Frequencies Using Inverse-Designed Bilayer Diffractive Structures

Curved electromagnetic beams at terahertz (THz) frequencies have recently emerged as a powerful example of wavefront engineering, with applications in imaging and high-capacity wireless communications. Unlike canonical self-accelerating solutions such as Airy beams, general curved-beam propagation enables arbitrary, application-specific trajectories that are not constrained by analytic beam families. Here, we demonstrate a passive and reconfigurable approach for generating trajectory-engineered THz curved beams using inverse-designed bilayer diffractive optical elements (DOEs). Two phase-only diffractive layers are optimized using gradient-based inverse design to produce predetermined curved propagation paths. Reconfiguration is achieved by a 180° rotation of the second layer, which modifies the effective phase profile of the cascaded structure without altering the incident wave or individual layer designs. The proposed system can produce distinct curved trajectories with controlled transverse displacement and beam confinement, as confirmed by scalar diffraction simulations and experimental measurements. Overall, this work establishes inverse-designed cascaded DOEs as a compact and scalable platform for reconfigurable trajectory control of THz beams, providing a flexible alternative to analytic self-accelerating beams for radiative near-field THz communications.

💡 Research Summary

This paper presents a passive, reconfigurable method for generating arbitrarily curved terahertz (THz) beams by employing two phase‑only diffractive optical elements (DOEs) that are jointly inverse‑designed. Unlike conventional self‑accelerating beams such as Airy beams, which are limited to parabolic trajectories defined by analytic solutions, the authors directly optimize the phase profiles of two cascaded diffractive layers to produce two predetermined curved trajectories with distinct transverse displacements (3.6 mm and 17.8 mm) over a propagation range of 45 mm to 155 mm at a design frequency of 0.3 THz (λ ≈ 1 mm).

Design and Optimization:
Each DOE measures 80 mm × 80 mm and is discretized into 800 × 800 pixels of 0.1 mm size, providing sub‑wavelength control. The inverse‑design problem is formulated in PyTorch, where the phase values of both layers are treated as learnable tensors. A loss function based on the mean‑squared error between simulated intensity distributions (computed via scalar angular‑spectrum propagation) and target intensity patterns at multiple z‑planes is minimized using the Adam optimizer. Symmetry along the y‑axis reduces the number of independent parameters to 800 × 400 per layer, and zero‑padding expands the computational window to 1600 × 1600 to suppress FFT edge artifacts. Optimization converges within ~1000 iterations (≈4 min on an NVIDIA RTX A2000 GPU).

Conversion of phase to physical height profiles uses the relation h(x,y)=λ φ(x,y)/(2π