On-chip wavefront shaping with dielectric metasurface

Chang

et al. 2021

Preprint

Self Cite

Miniaturized image classifiers are potential for revolutionizing their applications in optical communication, autonomous vehicles, and healthcare. With deep diffractive neuron networks trained subwavelength structures, we demonstrate image recognitions by a passive silicon photonic metasystem. The metasystem implements high-throughput vector-by-matrix multiplications, enabled by 103 passive subwavelength phase shifters as weight elements in 1 mm2 footprint. The large weight matrix size incorporates the fabrication variation related uncertainties, and thus the pre-trained metasystem can perform machine learning tasks without post-tuning. A 15-pixel spatial pattern classifier reaches near 90% accuracy with femtosecond inputs. The metasystem’s superior parallelism (1015 bit/s) dramatically expand data processing capability of photonic integrated circuits, towards next generation low latency and low power photonic accelerators compatible with complementary metal-oxide-semiconductor manufacturing.

Section: Resultsmentioning

confidence: 99%

Integrated photonic metasystem for image classifications at telecommunication wavelength

Chang

et al. 2021

Preprint

Self Cite

“…This paper considers 1D rectangular etched slot arrays defined in the silicon-on-insulator (SOI) substrate as 1Dmetasurfaces [45], termed as metalines (Fig. 1(a)).…”

Section: B Silicon Metalinesmentioning

confidence: 99%

“…By recent proposal of on-chip diffractive optical elements using high contrast transmitarray (HCTA) metasurfaces, with ultra-compact dimensions, good tolerance to fabrication variation, minimized scattering loss and broadband operation, new directions for silicon photonic computational chips operating at the speed of light with applications in areas of imaging, sensing and quantum information processing has been opened [45]. Cascaded layers of HCTAs for demonstration of meta-system functionalities such as Fourier transformation and differentiation have been implemented in [45]. Also, an onchip optical meta-neural-network based on cascaded layers of HCTAs has been proposed and benchmarked on the classification of handwritten digit images in [46].…”

Section: Introductionmentioning

confidence: 99%

Inverse Design of On-Chip Thermally Tunable Varifocal Metalens Based on Silicon Metalines

Zarei

Khavasi

2021

IEEE Access

High-contrast transmitarray (HCTA) metasurfaces, named as metalines in this article, a category of lithographically defined on-chip diffractive elements with minimized scattering loss, enables parallel on-chip optical signal processing. While high-performance devices with different functionalities are reported, most of them are static, and their optical functions are fixed after fabrication. However, dynamically tunable metasurfaces are of essential need in many modern optical systems. Here, we employ an inverse design method, combining FDTD parameter sweep with Fourier-optics simulations, to design thermally-controlled varifocal metalenses. Thermal tunability is accomplished through the thermo-optical effect of silicon. Maximum focal length tunability of 12% and 24% are demonstrated for 400µm and 200µm aperture varifocal metalens doublets at the wavelength of 1.55µm, respectively. The focusing efficiency is more than 74% for the whole temperature range. The 400µm and 200µm aperture metalenses are able to concentrate the input beam to spot sizes less than one wavelength and two wavelengths, respectively. This paves the way for dynamically controlled silicon photonics computational chips.

“…Metasurfaces are defined as arrays of spatially varying geometries used to generate desirable electromagnetic wavefronts [10]- [13]. The target frequency response can be achieved using metasurfaces with subwavelength thickness, enabling the development of conformal arrays [12], [13]. The metasurface-based spatial filter design has come to occupy an important position in mm-wave 5G mobile communications.…”

Section: Introductionmentioning

confidence: 99%

Design of Single-Layer Metasurface Filter by Conformational Space Annealing Algorithm for 5G mm-Wave Communications

et al. 2021

In this paper, we first demonstrate a metasurface that offers spectral filter performances not yet reported for a single-layer metasurface because of the limited number of geometric parameters. The configuration of the metasurface is determined by a conformational space annealing algorithm, which is a key toward being able to design for a desired frequency, bandwidth, and response type for various wireless communication devices, including the fifth-generation (5G) millimeter-wave communication devices. As a proof-of-concept, we fabricate a very thin (50 µm) single-layer metasurface combined with a 5G antenna array to experimentally demonstrate high frequency-selectivity with stable frequency responses with oblique incidences and polarizations. The gain of the 4 × 4 patch antenna array with the metasurface bandpass filter was reduced by only 0.48 dB compared with that of the 4 × 4 patch antenna array itself at 27.5 GHz, whereas the gain of the 4 × 4 patch antenna array with the metasurface bandstop was reduced by 20 dB compared with that of the 4 × 4 patch antenna array itself at 28.5 GHz.