Abstract : Photons play a central role in many areas of quantum information processing and quantum sensing, ranging from linear optics quantum computing and quantum simulation to quantum communications. A central problem in many of these applications is the need to control many spatial and temporal modes with high efficiency and precision. Photonic integrated circuits can contain closely-spaced and extremely phase-stable components that enable precision control of many spatial and temporal modes in dielectric waveguides. This program developed photonic integrated circuits (PICs) based on the silicon-on-insulator platform. We developed large-scale PICs with cascaded Mach-Zehnder interferometers (MZI) with precision electro-optic modulators. These PICs have very low internal losses (0.1 dB/MZI) and achieve exceptionally high contrast interference ( 80 dB) over tens of spatial modes. These fully programmable mode transformers have driven experimental and theoretical advances in quantum simulation, cluster-state quantum computing, all-optical quantum repeaters, neuromorphic computing, and other applications. In addition, we developed new schemes for ballistic quantum computation, new methods for high-efficiency single photon sources, a new approach for 3-photon cluster state generation that forms the essential ingredient for percolation-based generation of scalable cluster states, and quantum logic gates based on weak optical nonlinearities.
Abstract : Photons play a central role in many areas of quantum information processing and quantum sensing, ranging from linear optics quantum computing and quantum simulation to quantum communications. A central problem in many of these applications is the need to control many spatial and temporal modes with high efficiency and precision. Photonic integrated circuits can contain closely-spaced and extremely phase-stable components that enable precision control of many spatial and temporal modes in dielectric waveguides. This program developed photonic integrated circuits (PICs) based on the silicon-on-insulator platform. We developed large-scale PICs with cascaded Mach-Zehnder interferometers (MZI) with precision electro-optic modulators. These PICs have very low internal losses (0.1 dB/MZI) and achieve exceptionally high contrast interference ( 80 dB) over tens of spatial modes. These fully programmable mode transformers have driven experimental and theoretical advances in quantum simulation, cluster-state quantum computing, all-optical quantum repeaters, neuromorphic computing, and other applications. In addition, we developed new schemes for ballistic quantum computation, new methods for high-efficiency single photon sources, a new approach for 3-photon cluster state generation that forms the essential ingredient for percolation-based generation of scalable cluster states, and quantum logic gates based on weak optical nonlinearities.
There has been a strong interest to translate optical quantum technologies into photonic integrated circuits (PICs) as they could provide a stable, compact, and potentially scalable architecture for generating, manipulating, and measuring optical quantum states. Among the various PIC technologies that are being developed, silicon-on-insulator (SOI) PICs have several advantages, including technologically mature foundry fabrication, CMOS-process integration, and high-performance switches, modulators, polarization control, filters, and other essential optical components. However, several components are missing that are needed for quantum information processing tasks. Here, we describe recent progress on augmenting SOI PICs with essential capabilities for photonic quantum technologies — entangled photon sources, single photon detectors, and reconfigurable linear optics unitary transformations — and focus on two central application areas: quantum communications and quantum simulation.
Silicon-on-insulator (SOI) wafers have been developed for electronic integrated circuits, but are also one of the most promising platforms in photonic integrated circuits due to its low loss, high refractive index, ability to fast phase modulation, and well-developed fabrication technologies. With advantages to handle light with a small volume and high modulation speed, silicon photonics has been intensively investigated as the next generation platform of signal processing, interconnection, and communication devices. Recently, silicon photonics has been attracted great interests in quantum optics communities as optical quantum systems for linear optical quantum computing are achievable using silicon photonic components including beam splitters, phase modulators, and filters and the small footprint of a silicon photonic quantum system has unprecedented performances of high stability and scalability. Here we show our recent results on the fabrication of silicon photonic elements for quantum applications. We fabricated low-loss optical waveguides, efficient fiber-to-waveguide grating couplers, resonator-based optical filters, and tunable beam splitters and tested their performances. A micro-sized heater is attached on a Mach-Zehnder interferometer, showing stable operation as a slow phase modulator. In addition, phase modulators using plasma dispersion effects are under investigation. Finally, the quantum characteristics of photon pairs generated by spontaneous four-wave mixing in silicon waveguides are investigated. These results will be an essential cornerstone for the realization of quantum optical computing and quantum communication devices.
Photonics integration is a key technology for realizing large-scale photonic quantum information processing. We demonstrate state-of-art reconfigurable photonic processors based on low-loss silicon nitride waveguide networks. We present the science behind such a processor, which consists of a large mesh of integrated reconfigurable Mach Zehnder interferometers. In this talk, we will present the newest results of the current generation of our programmable quantum photonic processors obtained by classical as well as quantum optical characterization. Furthermore, we show the challenges of scaling up quantum photonic processors and the range of potential applications of large-scale quantum information processing those will enable.
Photonics integration is a key technology for realizing large-scale photonic quantum information processing. We demonstrate state-of-art reconfigurable photonic processors based on low-loss silicon nitride waveguide networks. We present the science behind such a processor, which consists of a large mesh of integrated reconfigurable Mach Zehnder interferometers. In this talk, we will present the newest results of the current generation of our programmable quantum photonic processors obtained by classical as well as quantum optical characterization. Furthermore, we show the challenges of scaling up quantum photonic processors and the range of potential applications of large-scale quantum information processing those will enable.
In recent years, quantum information has rapidly evolved as a field with transformative potential in science and technology. It provides secure encryption for communication, accurate emulation of practical physical systems, streamlined and accelerated machine learning models, and advanced computational powers that outperform classical supercomputers in solving complex problems. These advancements are all reliant on the superposition and entanglement properties of qubits. While various candidates such as trapped ions or superconducting qubits have been proposed to realize quantum technologies, photons have demonstrated a prominent advantage due to their robustness against decoherence and noise, high clock cycle rate, fast and easy measurement, and room temperature working environment. In addition, photonic integrated chip (PIC) technology has developed rapidly since the beginning of the 21st century. The number of devices integrated on a single chip has increased rapidly, and its complexity has also increased. Quantum computing combined with integrated photonics is expected to solve bottleneck problems in practical situations. In this thesis, based on the silicon-on-insulator (SOI) platform, an optical computing chip and a large-scale quantum computing chip with various practical applications are specifically studied. In the first part of the thesis, a novel integrated diffractive optical network is studied, and a scheme is designed to realize parallel Fourier transform, convolution operations, and application-specific optical computing. Due to the utilization of on-chip compact diffractive cells (slab waveguides), the footprint and power consumption of the proposed architecture is reduced from quadratic scaling in the input data dimensions required for Mach-Zehnder interferometer (MZI)-based optical neural network (ONN) architectures to linear scaling for the improved deep neural networks. A 10-fold reduction in both footprint and energy consumption and equal high accuracy with previous MZI-based ONNs was experimentally achieved for computations performed on the Modified National Institute of Standards and Technology (MNIST) and Fashion-MNIST datasets. This reduction in the resource scaling from quadratic to linear has a profound impact on the realization of large-scale silicon-photonics computing circuits with current fabrication technologies. A quantum photonic microprocessor based on Gaussian Boson sampling (GBS) that offers dynamic programmability to solve various graph-related NP-complete problems is then demonstrated. The system with optical, electrical, and thermal packaging implements a GBS with 16 modes of single-mode squeezed vacuum states, a universal programmable 16-mode interferometer, and a single photon readout on all outputs with high accuracy, generality, and controllability. The developed system is applied to demonstrate applications in solving NP-complete problems, manifesting the ability of photonic quantum computing to realize practical applications for conventionally intractable computations. The GBS-based quantum photonic microprocessor is applied to solve task assignment, Boolean satisfiability, graph clique, max cut, and vertex cover. These demonstrations suggest an excellent benchmarking platform, paving the way toward large-scale combinatorial optimization. Finally, this thesis explores the application possibility of large-scale PICs in molecular simulation. A new algorithm utilizing states with zero displacements (vacuum-squeezed states) coupling to a linear network is proposed to calculate molecular vibronic spectra. With a large-scale PIC, molecular vibronic spectra are accurately simulated for formic acid and thymine with high reconstructed fidelity (>91%) and for naphthalene, phenanthrene, and benzene under the non-Condon regime. Our experimental demonstration will open pathways toward conducting large-scale molecular quantum simulations, a task surpassing classical computers’ capabilities.