Electrically-Driven, On-Demand, High-Speed Generation of Telecom-Band, Indistinguishable Single Photons and Entangled Photon Pairs

Photonic quantum computers with photons as qubits promise to realize scalable quantum computers with its long coherent time. Cluster states with time-bin entangled photons realize large-scale measurement-based quantum computers. Quantum interconnects transfer quantum states and enable large-scale integration of quantum processors.

Single photon and entangled photon pair sources are essential. And electrically-driven, on-demand high-speed generation of wavelength indistinguishable photons is crucial. Telecom-band photons are required to be compatible to Si-photonics-based quantum circuits and optical fiber transmission. Polarization control is essential for entangled photon pair generation. We develop intracavity-contact, quantum-dot vertical microcavities with resonant tunneling injection to meet all these requirements.

Photonic Nanodevices for Trapped-Ion Quantum Computers

Trapped ions are a promising platform for implementing quantum computers because of their exceptional quantum properties. One of the most active recent research trends is the amalgamation of optical functionalities into compact chip-based configurations to facilitate the scalability of these systems. Beyond merely shining light onto individual ions for manipulation, the ability to finely tailor optical attributes, such as polarization states, assumes paramount importance for enabling universal quantum operations. The on-chip integration of such optical functionalities, particularly within the near-ultraviolet to visible wavelength range corresponding to the typical transition wavelengths of ions, poses a significant challenge. Our objective is to embody on-chip ion trap devices capable
of executing sophisticated quantum computations by harnessing state-of-the-art optical
technologies/physics such as topological photonics.

Scalable and Universal Reservoir Computing with 2D Active Photonic Cavities

With wide proliferation of IoTs including software-driven automobiles and drones, increasing amount of dynamic data is easily captured with less cost, which promises to predict highly-expected values or risks. Reservoir computing realizes dynamic AI, high-speed training with small amount of dynamic information, and enables quick prediction. Physical reservoir computing exploits physical systems and utilizes their features.

Photonic reservoir computing employing photonics as physical system enables high-speed and energy-efficient data analysis. Scalable and universal hardware is essential for evolving reservoir computing for dynamic AI, and continuous media is the most suitable for physical reservoir. We develop 2D active photonic cavities implemented by high-Q 2D photonic cavity and active region with quantum wells to realize scalable and universal reservoir computing with continuous-media photonic reservoir.