Many practical applications of Quantum Computing (Quacomp) require communication between quantum nodes and Quantum Computers (QCs). This chapter covers some of the basic physical technologies that have applications to Quantum Communications (Quacom) and Quantum Networking/Networks (Quanet[s]); it covers: Sources of nonclassical light (e.g., entangled light, squeezed light) Single-photon detectors (e.g., trapped ions techniques) Quantum memory and repeaters (e.g., Single Photon Avalanche Diodes) Transducers (e.g., Electro-Optic E0 transducers) Simulators
Many practical applications of Quantum Computing (Quacomp) require communication between quantum nodes and Quantum Computers (QCs). This chapter covers some of the basic physical technologies that have applications to Quantum Communications (Quacom) and Quantum Networking/Networks (Quanet[s]); it covers: Sources of nonclassical light (e.g., entangled light, squeezed light) Single-photon detectors (e.g., trapped ions techniques) Quantum memory and repeaters (e.g., Single Photon Avalanche Diodes) Transducers (e.g., Electro-Optic E0 transducers) Simulators
In this section we provide a broad overview of the basic principles of quantum mechanics and how they enable modern quantum technologies. The starting point is the concept of superposition, which allows quantum systems to be in multiple states at the same time and forms the basis of quantum computation using qubits and parallel processing of information. The conversation then turns to quantum entanglement, a non-classical effect that creates strong correlations between particles, and has applications in secure communication and quantum teleportation. Also mentioned is the quantum coherence, which preserves phase relations between quantum states and makes it possible for quantum systems to function correctly. But it is also emphasized that quantum coherence is fragile to environmental perturbations. This chapter also covers quantum measurement, taking into account the probabilistic nature of quantum mechanics, and how the act of observation results in the collapse of a quantum state to a definite outcome. These principles together constitute the theoretical basis of quantum computing, where quantum gates and algorithms and qubits take advantage of superposition, entanglement and interference to offer computational benefits over classical systems. The most important algorithms like Shor’s and Grover’s algorithms that demonstrate a considerable speed-up in solving the problem are discussed along with different models of quantum computing, such as gate, adiabatic and measurement-based models. Furthermore, the section reviews some physical realizations of quantum systems, such as superconducting qubits, trapped ions, photonic systems and topological qubits, with their advantages and difficulties. Overall, this discussion shows how the basic principles of quantum mechanics are the foundation for the development of advanced quantum technologies, while also dealing with the practical difficulties that arise in their implementation.
This chapter provides a basic overview of Quantum Computers (QCs) used in Quantum Computing (Quacomp) applications. Classical computers utilize silicon-based semiconductor devices. In recent years integrated circuit lateral feature sizes have been reduced to 10 nm, increasing chip density; however, as these sizes progress to be reduced to 5 nm and smaller, silicon-based circuits become impractical. QCs make use of quantum phenomena such as entanglement and superposition to increase and improve the computation speed as compared to classical computers, enabling them to solve some computationally complex problems in practical time windows. At this juncture QCs are not able to act as replacements for general- purpose computers, but they can outperform classical computers in a set of specific computational problems, such as optimization problems or for identifying the best solution from a set of feasible solutions. This chapter covers three QC approaches: the circuit model (or gate model), the adiabatic quantum computation model, and the categorical quantum model. Quacomp has experienced relatively rapid development in recent years, starting with the basic ideation in the early 1980s, then continuing with early proof of concepts for hardware in the next two decades, and now, in the 2020s, with QC hardware that can implement over one-thousand qubits (e.g., [ TIL22 ], [ FEY82 ], [ LEU00 ], [ NEG06 ], [ PLA07 ], [ MON11 ], [ MON16 ], [ CAS23 ]). Figure 5.1 (courtesy of IBM) depicts recent illustrative achievements in practical QC development at IBM, a key player in this arena (in the fall of 2023, IBM® announced the Condor prototype, the world’s first universal QC with 1,121 qubits 1 ). The generation of QCs at the time of this writing is known as Noisy-Intermediate Scale Quantum (NISQ) devices (some proponents cite this as being the third generation). These NISQ QCs are typically cooled to cryogenic temperatures (around −273° C) in order to operate efficiently; these environmental conditions are challenging to maintain in other than laboratory settings. In practical terms, QCs remain of somewhat limited and specialized functionality and are prone to computational errors. Considering these limitations, Hybrid QC (HQC) 170 171 172 arrangements and Hybrid Quantum Applications (HQApps) endeavor to combine classical and QC systems in order to undertake calculations directed at various (but specific) optimization or related use cases; tasks such as preparing inputs for quantum algorithms, storing data, or interacting with the user are typically still performed using classical computers. The number of operations in a QC typically equates with the number of quantum gates and the number of qubits supported; however, the larger the number of gates, the more likely it is that errors, including decoherence, are introduced into the quantum state. NISQ entails a somewhat limited number of logical qubits and associated physical qubits to support error correction schemes. Fortunately, a category of algorithms running on NISQ devices can proceed with only a small number of qubits and exhibit some degree of noise resilience; typically, they are hybrid algorithms, with a portion of the computational steps performed on a quantum device and with other computational steps running on a conventional computer. The bottom line is that with NISQ devices, the number of operations is typically moderate at this juncture, thus the scope and type of algorithms that can be implemented is relatively limited. However, there is research that shows that even these QCs can outperform conventional computers on a set of mathematical problems (e.g., [ PRE18 ], [ BRO19 ], [ MAD22 ]). The next step in the evolution is the interconnection of QCs over a distance network, as discussed in Chapter 6 . A classification of fundamental QC technologies has been proposed the European standards body CEN-CENELEC, specifically the Focus Group on Quantum Technologies (FGQT), which was established in June 2020 to coordinate and support the development of standards relevant for European industry and research [ OVA22 ]. See Table 5.1 .
A number of optical technologies remain to be developed and optimized for various applications in quantum information processing, especially quantum communication. We will give an overview of our approach to some of these, including periodic heralded single-photon sources based on spontaneous parametric down-conversion, ultrabright sources of tunable entangled photons, near unit efficiency single- and multi-photon detectors based on an atomic vapor interaction, quantum state transducers based on high efficiency frequency up-conversion, and low-loss optical quantum memories.
Single-photon detectors (SPDs) are the most sensitive instruments for light detection. In the near-infrared range, SPDs based on III–V compound semiconductor avalanche photodiodes have been extensively used during the past two decades for diverse applications due to their advantages in practicality including small size, low cost and easy operation. In the past decade, the rapid developments and increasing demands in quantum information science have served as key drivers to improve the device performance of single-photon avalanche diodes and to invent new avalanche quenching techniques. This Review aims to introduce the technology advances of InGaAs/InP single-photon detector systems in the telecom wavelengths and the relevant quantum communication applications, and particularly to highlight recent emerging techniques such as high-frequency gating at GHz rates and free-running operation using negative-feedback avalanche diodes. Future perspectives of both the devices and quenching techniques are summarized. Recent progress in single-photon detectors for quantum communication based on III–V compound semiconductor avalanche photodiodes is reviewed. Specifically, Jun Zhang and Jian-Wei Pan at the University of Science and Technology of China and their colleagues in the USA and Switzerland introduce technological advances for InGaAs/InP single-photon detector systems in the telecommunication band along with their associated applications in quantum communication. III–V single-photon avalanche diodes are the most practical tools available for detecting ultraweak near-infrared light. The scientists overview important parameters for evaluating the performance of detector systems based on single-photon avalanche diodes and describe the experimental characterization of these parameters. They also consider emerging techniques, including high-frequency gating at gigahertz rates and free-running operation using negative-feedback avalanche diodes. Finally, the future prospects of these devices are considered.
In this tutorial we review basic ideas of quantum computing, from quantum bits and state entanglement to quantum gates and quantum networks [1]. In addition, we give an overview over possible physical implementations of quantum gates[2-6], with emphasis on quantum optical systems: this includes ion traps [2,3], and cavity QED in the optical and microwave domain [4-6], Fundamental problems of building quantum computers, in particular the decoherence problem, and error correction schemes for quantum memory elements [7] and quantum gates [8] will be discussed. We conclude with a critical evaluation what should be expected from quantum computing ideas in terms of applications in physics (quantum optics) and mathematics within the nest few years.
Epitaxially grown quantum dots (QDs) are promising sources of nonclassical states of light such as single photons and entangled photons. However, in order for them to be used as a resource for long-distance quantum communication, distributed quantum computation, or linear optics quantum computing, these photons must be coupled efficiently to long-lived quantum memories as part of a quantum repeater network. Here, we theoretically examine the prospects for efficient storage and retrieval of a QD-generated single photon with a 1-ns lifetime in a multilevel atomic system. We calculate using an experimentally demonstrated optical depth of 150 that the storage (total) efficiency can exceed 46 (28) in a dense, ultracold ensemble of 87Rb atoms. Furthermore, we find that the optimal control pulse required for storage and retrieval can be obtained using a diode laser and an electro-optic modulator rather than a mode-locked, pulsed laser source. Increasing the optical depth, for example, by using Bose-condensed ensembles or an optical cavity, can increase the efficiencies to near unity. Aside from enabling a high-speed quantum network based on QDs, such an efficient optical interface between an atomic ensemble and a QD can also lead to entanglement between collective spin-wave excitations of atoms and the spin of an electron or hole confined in the QD.