Search for: All records

On-chip ultraviolet (UV) sources are of great interest for building compact and scalable atomic clocks, quantum computers, and spectrometers. However, few material platforms are suitable for integrated UV light generation and manipulation. Of these materials, thin-film lithium niobate offers unique advantages such as sub-micron modal confinement, strong nonlinearity, and quasi-phase matching. Despite these characteristics, its utilization in the UV has remained elusive because of the substantial sensitivity of standard quasi-phase matching to fabrication imperfections, the photorefractive effect, and relatively large losses in this range. Here, we present efficient (197 ± 5%/W/cm²) second harmonic generation of UV-A light in a periodically poled lithium niobate nanophotonic waveguide. We achieve on-chip UV powers of ∼30 µW and linear wavelength tunability using temperature. These results are enabled with large cross section waveguides, which leads to first-order UV quasi-phase-matching with relatively long poling periods (>1.5 µm). By varying the poling period, we have achieved the shortest reported wavelength (355 nm) generated through frequency doubling in thin-film lithium niobate. Our results open up new avenues for UV on-chip sources and chip-scale photonics through compact frequency-doubling of common near-IR laser diodes.

 

A lithium niobate–based platform can generate and measure squeezed states of light on a chip. 

We demonstrate broadly-tunable synchronously-pumped optical parametric oscillators in nanophotonic lithium niobate. A picosecond 1-µm pump generates subpicosecond signal/idler frequency combs tunable between 1.5 and 3.3µm with up-conversion to the visible on the same chip.

 

Abstract In recent years, the computational demands of deep learning applications have necessitated the introduction of energy-efficient hardware accelerators. Optical neural networks are a promising option; however, thus far they have been largely limited by the lack of energy-efficient nonlinear optical functions. Here, we experimentally demonstrate an all-optical Rectified Linear Unit (ReLU), which is the most widely used nonlinear activation function for deep learning, using a periodically-poled thin-film lithium niobate nanophotonic waveguide and achieve ultra-low energies in the regime of femtojoules per activation with near-instantaneous operation. Our results provide a clear and practical path towards truly all-optical, energy-efficient nanophotonic deep learning. 

Strong amplification in integrated photonics is one of the most desired optical functionalities for computing, communications, sensing, and quantum information processing. Semiconductor gain and cubic nonlinearities, such as four-wave mixing and stimulated Raman and Brillouin scattering, have been among the most studied amplification mechanisms on chip. Alternatively, material platforms with strong quadratic nonlinearities promise numerous advantages with respect to gain and bandwidth, among which nanophotonic lithium niobate is one of the most promising candidates. Here, we combine quasi-phase matching with dispersion engineering in nanophotonic lithium niobate waveguides and achieve intense optical parametric amplification. We measure a broadband phase-sensitive on-chip amplification larger than 50 dB/cm in a 6-mm-long waveguide. We further confirm high gain operation in the degenerate and nondegenerate regimes by amplifying vacuum fluctuations to macroscopic levels, with on-chip gains exceeding 100 dB/cm over 600 nm of bandwidth around 2 µm. Our results unlock new possibilities for on-chip few-cycle nonlinear optics, mid-infrared photonics, and quantum photonics.