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We develop a thermally tunable hybrid photonic platform comprising gallium arsenide (GaAs) photonic crystal cavities, silicon nitride (SiN$_x$) grating couplers and waveguides, and chromium (Cr) microheaters on an integrated photonic chip. The GaAs photonic crystal cavities are evanescently connected to a common bus waveguide, separating the computation and communication layers. The microheaters are designed to continuously and reversibly tune distant photonic crystal cavities to a common resonance. This architecture can be implemented in a coherent optical network for dedicated optical computing and machine learning.
We integrate about 100 single Cadmium Selenide semiconductor nanowires in self-standing Silicon Nitride photonic crystal cavities in a single processing run. Room temperature measurements reveal a single narrow emission linewidth, corresponding to a
A novel technique is presented for realising programmable silicon photonic circuits. Once the proposed photonic circuit is programmed, its routing is retained without the need for additional power consumption. This technology enables a uniform multi-
Efficient numeric algorithm is the key for accurate evaluation of density of states (DOS) in band theory. Gilat-Raubenheimer (GR) method proposed in 1966 is an efficient linear extrapolation method which was limited in specific lattices. Here, using
Photonic crystal-based biosensors hold great promise as valid and low-cost devices for real-time monitoring of a variety of biotargets. Given the high processability and easiness of read-out even for unskilled operators, these systems can be highly a
Development of scalable quantum photonic technologies requires on-chip integration of components such as photonic crystal cavities and waveguides with nonclassical light sources. Recently, hexagonal boron nitride (hBN) has emerged as a promising plat