Optical analog computing has natural advantages of parallel computation, high speed and low energy consumption over traditional digital computing. To date, research in the field of on-chip optical analog computing has mainly focused on classical mathematical operations. Despite the advantages of quantum computing, on-chip quantum analog devices based on metasurfaces have not been demonstrated so far. In this work, based on a silicon-on-insulator (SOI) platform, we illustrated an on-chip quantum searcher with a characteristic size of 60 × 20 μm2. We applied classical waves to simulate the quantum search algorithm based on the superposition principle and interference effect, while combining it with an on-chip metasurface to realize modulation capability. The marked items are found when the incident waves are focused on the marked positions, which is precisely the same as the efficiency of the quantum search algorithm. The proposed on-chip quantum searcher facilitates the miniaturization and integration of wave-based signal processing systems.
Optical analog computing has natural advantages of parallel computation, high speed and low energy consumption over traditional digital computing. To date, research in the field of on-chip optical analog computing has mainly focused on classical mathematical operations. Despite the advantages of quantum computing, on-chip quantum analog devices based on metasurfaces have not been demonstrated so far. In this work, based on a silicon-on-insulator (SOI) platform, we illustrated an on-chip quantum searcher with a characteristic size of 60 × 20 μm2. We applied classical waves to simulate the quantum search algorithm based on the superposition principle and interference effect, while combining it with an on-chip metasurface to realize modulation capability. The marked items are found when the incident waves are focused on the marked positions, which is precisely the same as the efficiency of the quantum search algorithm. The proposed on-chip quantum searcher facilitates the miniaturization and integration of wave-based signal processing systems.
Metamaterials, artificially structured electromagnetic (EM) materials, have enabled the realization of many unconventional EM properties not found in nature, such as negative refractive index, magnetic response, invisibility cloaking, and so on. Based on these man-made materials with novel EM properties, various devices are designed and realized. However, quantum analog devices based on metamaterials have not been achieved so far. Here, metamaterials are designed and printed to perform quantum search algorithm. The structures, comprising of an array of 2D subwavelength air holes with different radii perforated on the dielectric layer, are fabricated using a 3D-printing technique. When an incident wave enters in the designed metamaterials, the profile of beam wavefront is processed iteratively as it propagates through the metamaterial periodically. After ≈N roundtrips, precisely the same as the efficiency of quantum search algorithm, searched items will be found with the incident wave all focusing on the marked positions. Such a metamaterial-based quantum searching simulator may lead to remarkable achievements in wave-based signal processors.
Owing to the inherent advantages of parallelism, rapid processing speed, and minimal energy consumption, optical analog computing has witnessed a progressive development. Quantum optical computing exceeds the capabilities of classical computing in terms of computational speed in numerous tasks. However, existing metamaterial-based quantum Deutsch-Jozsa (DJ) algorithm devices have large structural dimensions and are not suitable for miniaturized optical computing systems. Furthermore, most reported on-chip metasurface devices, rendered monofunctional after fabrication, do not possess sophisticated optical systems. In this work, we develop an electrically tunable on-chip DJ algorithm device on a lithium-niobate-on-insulator (LNOI) platform. The on-chip device consists of various etched slots, each with carefully designed size. By applying different external voltages to each individual unit, precise phase redistribution across the device is attainable, enabling the realization of tunable DJ algorithm. Notably, we can determine whether the oracle metasurface yields a constant or balance function by measuring the output electric field. The on-chip device is miniaturized and easy to integrate while enabling functional reconfiguration, which paves the way for numerous applications in optical computing.
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.
Riding a different wave: This study shows that an acoustic metasurface can be a platform to implement airborne surface acoustic waves (SAWs) for analog computing based on a quantum algorithm. The authors' gradient-index acoustic system can be used to perform the Grover search algorithm, with quadratic speedup over classical searches. Such a SAW-based computing system would offer---in the foreseeable future---a flexible platform for analog simulation of quantum algorithms, which could find application in on-chip integrated acoustic and phononic devices.
The capability of realizing quantum photonics implementations on-chip will have a strong impact on several aspects of quantum computation and information processing. The implementation of large scale integrated quantum photonic technologies requires on-chip reconfigurable waveguide circuits as well as single-photon sources and detectors. Many successes have been made in recent years to demonstrate complex quantum circuits in many material platforms. Among all these platforms, the Silicon-on-Insulator (SOI) platform is outstanding as it is well developed for classical applications and therefore deploys a high component density, mature fabrication techniques and compatibility with the telecom regime and the complementary metal-oxide-semiconductor (CMOS) technology. However, the lack of on-demand non-classical light sources, directly incorporated in silicon chips, forces the use of nonlinear processes to generate non-classical light states: the probabilistic nature of the emission process sets a limit in the maximally achievable experimental complexity. The use of on-demand sources will have a strong impact on the device’s scalability.
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.