Intra-cavity coherent combining of DBR lasers on an InP generic foundry platform.

We report an intra-cavity coherent combining of two distributed Bragg reflector (DBR) lasers with a combining efficiency of ∼84% on an InP generic foundry platform. The on-chip power of the intra-cavity combined DBR lasers is ∼9.5 mW at the injection current of 42 mA in both gain sections simultaneously. The combined DBR laser operates in a single-mode regime with a side-mode suppression ratio of 38 dB. This monolithic approach paves the way toward high-power and compact lasers, which is useful in scaling integrated photonic technologies.

A 10-kHz intrinsic linewidth coupled extended-cavity DBR laser monolithically integrated on an InP platform.

We report a monolithically integrated coupled extended-cavity distributed Bragg reflector laser with, to our knowledge, the lowest reported intrinsic linewidth of ∼10 kHz, which is extracted from a corresponding frequency-noise level of ∼3200 Hz2/Hz, realized on an InP generic foundry platform. Using the delayed self-heterodyne method, the experimentally measured linewidth was 45 kHz. The laser has an on-chip optical output power of 18 mW around 1550 nm at an injection current of 95 mA. The laser operates in a single-mode regime with a side-mode suppression ratio of 54 dB. Our monolithic approach paves the way toward further integration, such as integrated quantum key distribution transceivers.

High-extinction CROW filters for scalable quantum photonics.

We report an integrated tunable-bandwidth optical filter with a passband to stop-band ratio of over 96 dB using a single silicon chip with an ultra-compact footprint. The integrated filter is used in filtering out the pump photons in non-degenerate spontaneous four-wave mixing (SFWM), which is used for producing correlated photon pairs at different wavelengths. SFWM occurs in a long silicon waveguide, and two cascaded second-order coupled-resonator optical waveguide (CROW) filters were used to spectrally remove the pump photons. The tunable bandwidth of the filter is useful to adjust the coherence time of the quantum correlated photons and may find applications in large-scale integrated quantum photonic circuits.

Compact high-extinction tunable CROW filters for integrated quantum photonic circuits.

We describe the use of cascaded second-order coupled-resonator optical waveguide (CROW) tunable filters to achieve one of the highest reported measured extinction ratios of $ {\gt} {110}\;{\rm dB}$>110dB. The CROW filters were used to remove the pump photons in spontaneous four-wave mixing (SFWM) in a silicon waveguide. The SFWM generated quantum-correlated photons that could be measured after the cascaded CROW filters. The CROW filters offer a compact footprint for use in monolithic quantum photonic circuits.

Crossover from photodarkening to photobleaching in a-Ge(x)Se(100-x) thin films.

In this Letter, we present the interesting results of photodarkening (PD), transition toward photostability, and a slow crossover from PD to photobleaching when composition of the chalcogenide glassy thin film changes from Ge-deficient to rich. A subsequent Raman analysis on these as-prepared and irradiated samples provide the direct evidence of photoinduced structural rearrangement, i.e., photocrystallization of Se and the removal of edge-sharing GeSe4 tetrahedra. Further, our experimental results clearly demonstrate that light-induced effects can be effectively controlled by choosing the right composition and provide valuable information on synthesizing photostable/sensitive glasses.

OPTCLOUD: An Optimal Cloud Service Selection Framework Using QoS Correlation Lens.

Cloud computing has grown as a computing paradigm in the last few years. Due to the explosive increase in the number of cloud services, QoS (quality of service) becomes an important factor in service filtering. Moreover, it becomes a nontrivial problem when comparing the functionality of cloud services with different performance metrics. Therefore, optimal cloud service selection is quite challenging and extremely important for users. In the existing approaches of cloud service selection, the user's preferences are offered by the user in a quantitative form. With fuzziness and subjectivity, it is a hurdle task for users to express clear preferences. Moreover, many QoS attributes are not independent but interrelated; therefore, the existing weighted summation method cannot accommodate correlations among QoS attributes and produces inaccurate results. To resolve this problem, we propose a cloud service framework that takes the user's preferences and chooses the optimal cloud service based on the user's QoS constraints. We propose a cloud service selection algorithm, based on principal component analysis (PCA) and the best-worst method (BWM), which eliminates the correlations between QoS and provides the best cloud services with the best QoS values for users. In the end, a numerical example is shown to validate the effectiveness and feasibility of the proposed methodology.