Multi-plane diffraction (MPD) systems with classical sources and conventional intensity detection are recently proposed for scalable quantum computing (QC) and communications (QComm) with time domain entanglement resources and by exploiting the energy efficient interference of exponentially increasing number of propagation paths. MPD provides unique advantages for the challenges of scalability of qubits and complex set-ups including single photon generation and detection mechanisms in state-of-the-art linear optics implementations. However, MPD based QC architectures denoted by quantum path computing (QPC) are theoretically modeled for only electron based system set-up with Gaussian sources while proposed classical communication architectures are defined for free space propagation without modeling for arbitrary Fourier optical set-ups being mathematically equivalent to linear canonical transforms (LCTs). In this article, MPD architectures are defined, theoretically modeled and numerically analyzed for Fourier optics with arbitrary LCTs between diffraction planes while utilizing both Gaussian and Hermite-Gaussian laser modes. Photonic MPD proposes QC and QComm based on the mature science of Fourier optics significantly developed since the last century with globally available resources for fast and wide spread development of the proposed design. It promises the simplest linear optical system with important QC applications while promising novel resources for classical and quantum communications.
Multi-plane diffraction (MPD) systems with classical sources and conventional intensity detection are recently proposed for scalable quantum computing (QC) and communications (QComm) with time domain entanglement resources and by exploiting the energy efficient interference of exponentially increasing number of propagation paths. MPD provides unique advantages for the challenges of scalability of qubits and complex set-ups including single photon generation and detection mechanisms in state-of-the-art linear optics implementations. However, MPD based QC architectures denoted by quantum path computing (QPC) are theoretically modeled for only electron based system set-up with Gaussian sources while proposed classical communication architectures are defined for free space propagation without modeling for arbitrary Fourier optical set-ups being mathematically equivalent to linear canonical transforms (LCTs). In this article, MPD architectures are defined, theoretically modeled and numerically analyzed for Fourier optics with arbitrary LCTs between diffraction planes while utilizing both Gaussian and Hermite-Gaussian laser modes. Photonic MPD proposes QC and QComm based on the mature science of Fourier optics significantly developed since the last century with globally available resources for fast and wide spread development of the proposed design. It promises the simplest linear optical system with important QC applications while promising novel resources for classical and quantum communications.
The scalability, error correction and practical problem solving are important challenges for quantum computing (QC) as more emphasized by quantum supremacy (QS) experiments. Quantum path computing (QPC), recently introduced for linear optic based QCs as an unconventional design, targets to obtain scalability and practical problem solving. It samples the intensity from the interference of exponentially increasing number of propagation paths obtained in multi-plane diffraction (MPD) of classical particle sources. QPC exploits MPD based quantum temporal correlations of the paths and freely entangled projections at different time instants, for the first time, with the classical light source and intensity measurement while not requiring photon interactions or single photon sources and receivers. In this article, photonic QPC is defined, theoretically modeled and numerically analyzed for arbitrary Fourier optical or quadratic phase set-ups while utilizing both Gaussian and Hermite-Gaussian source laser modes. Problem solving capabilities already including partial sum of Riemann theta functions are extended. Important future applications, implementation challenges and open issues such as universal computation and quantum circuit implementations determining the scope of QC capabilities are discussed. The applications include QS experiments reaching more than [Formula: see text] Feynman paths, quantum neuron implementations and solutions of nonlinear Schrödinger equation.
Quantum history states were recently formulated by extending the consistent histories approach of Griffiths to the entangled superposition of evolution paths and were then experimented with Greenberger-Horne-Zeilinger states. Tensor product structure of history-dependent correlations was also recently exploited as a quantum computing resource in simple linear optical setups performing multiplane diffraction (MPD) of fermionic and bosonic particles with remarkable promises. This significantly motivates the definition of quantum histories of MPD as entanglement resources with the inherent capability of generating an exponentially increasing number of Feynman paths through diffraction planes in a scalable manner and experimental low complexity combining the utilization of coherent light sources and photon-counting detection. In this article, quantum temporal correlation and interference among MPD paths are denoted with quantum path entanglement (QPE) and interference (QPI), respectively, as novel quantum resources. Operator theory modeling of QPE and counterintuitive properties of QPI are presented by combining history-based formulations with Feynman's path integral approach. Leggett-Garg inequality as temporal analog of Bell's inequality is violated for MPD with all signaling constraints in the ambiguous form recently formulated by Emary. The proposed theory for MPD-based histories is highly promising for exploiting QPE and QPI as important resources for quantum computation and communications in future architectures.
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.
Compared with other physical platforms for Quantum Information Processing (QIP), photons have the unique advantages of travelling over free-space links or optical fiber with relatively low decoherence and of propagating with minimal coupling to the environment, while also being easily coupled to existing telecommunications technology. The R&D of various single photon and entangled photon generation technologies and the linear-optical implementations of quantum computation and communication are now surveyed and analyzed in a structured manner. We discuss photonic qubit degrees of freedom (polarization, time-bin, path, frequency and Orbital angular momentum), determine sources such as deterministic quantum-dot based sources and probabilistic sources based on spontaneous parametric down conversion (SPDC), and review architectures for Linear Optical Quantum Computation (LOQC), such as the Knill–Laflamme–Milburn (KLM) protocol and measurement-based quantum computation. Building on the density-matrix treatment of biexciton–exciton coherent dynamics in semiconductor quantum dots, we recapitulate the development of two-pulse coherent control schemes for generation and readout of photonic qubits in these systems and how they have been stretched towards optical control of logic gates. A comparative performance framework is established along the lines of source brightness, entanglement fidelity, photon indistinguishability, channel loss and scalability, which is illustrated by simulated performance plots and tabulated against literature numbers. Remaining hurdles in the field regarding issues of photon loss, scalable multiplexing, deterministic two-qubit interaction, and its integration with a quantum memory are highlighted and a perspective is provided on hybrid photonic–matter architectures for fault-tolerant quantum networks.
High-dimensional entangled photons are a key resource for advanced quantum information processing. Efficient processing of high-dimensional entangled photons requires the ability to synthesize their state using general unitary transformations. The leading technology for processing photons in high-dimensions is integrated multiport interferometers. However, such devices are incompatible with free-space and fiber-based systems, and their architecture poses significant scaling challenges. Here we unlock these limitations by demonstrating a reconfigurable processor of entangled photons that is based on multi-plane light conversion (MPLC), a technology that was recently developed for multiplexing hundreds of spatial modes for classical free-space and fiber communication. To demonstrate the flexibility of MPLC, we perform four key tasks of quantum information processing using the same MPLC hardware: entanglement certification, tailored two-photon interference, arbitrary state transformations, and mode conversion. Based on the high degree of control we obtain, we expect MPLC will become a leading platform for future quantum technologies.
Quantum information processing (QIP) is an interdisciplinary field concerned with the development of computers and information processing systems that utilize quantum mechanical properties of nature to carry out their function. QIP systems have become vastly more practical since the turn of the century. Today, QIP applications span imaging, cryptographic security, computation, and simulation (quantum systems that mimic other quantum systems). \nMany important strategies improve quantum versions of classical information system hardware, such as single photon detectors and quantum repeaters. Another more abstract strategy engineers high-dimensional quantum state spaces, so that each successful event carries more information than traditional two-level systems allow. Photonic states in particular bring the added advantages of weak environmental coupling and data transmission near the speed of light, allowing for simpler control and lower system design complexity. \n \nIn this dissertation, numerous novel, scalable designs for practical high-dimensional linear-optical QIP systems are presented. First, a correlated photon imaging scheme using orbital angular momentum (OAM) states to detect rotational symmetries in objects using measurements, as well as building images out of those interactions is reported. Then, a statistical detection method using chains of OAM superpositions distributed according to the Fibonacci sequence is established and expanded upon. It is shown that the approach gives rise to schemes for sorting, detecting, and generating the recursively defined high-dimensional states on which some quantum cryptographic protocols depend. \n \nFinally, an ongoing study based on a generalization of the standard optical multiport for applications in quantum computation and simulation is reported upon. The architecture allows photons to reverse momentum inside the device. This in turn enables realistic implementation of controllable linear-optical scattering vertices for carrying out quantum walks on arbitrary graph structures, a powerful tool for any quantum computer. It is shown that the novel architecture provides new, efficient capabilities for the optical quantum simulation of Hamiltonians and topologically protected states. Further, these simulations use exponentially fewer resources than feedforward techniques, scale linearly to higher-dimensional systems, and use only linear optics, thus offering a concrete experimentally achievable implementation of graphical models of discrete-time quantum systems.