Computational Quantum Electromagnetics: Basic Concepts and Emerging Trends

In this paper we discuss two potential areas of intersection between Quantum Information Technologies and Information Fusion. The first area we call Quantum (Data Fusion) and refers to the use of quantum computers to perform data fusion algorithms with classical data generated by quantum and classical sensors. As we discuss, we expect that these quantum fusion algorithms will have a better computational complexity than traditional fusion algorithms. This means that quantum computers could allow the efficient fusion of large data sets for complex multi-target tracking. On the other hand, (Quantum Data) Fusion refers to the fusion of quantum data that is being generated by quantum sensors. The output of the quantum sensors is considered in the form of qubits, and a quantum computer performs data fusion algorithms. Our theoretical models suggest that we expect that these algorithms can increase the sensitivity of the quantum sensor network.

The marriage of quantum physics and information technology has the potential to generate radically new information processing devices. Examples are quantum cryptosystems, which provide guaranteed secure communication, and quantum computers, which manipulate data quantum mechanically and could thus solve some problems currently intractable to conventional (classical) computation. This introductory chapter serves two purposes. Firstly, I discuss some of the basic aspects of quantum physics which underpin quantum information technology (QIT). These will be used (and in somes cases further expanded upon) in subsequent chapters. Secondly, and as a lead into the whole book, I outline some of the ideas of QIT and its possible uses. To appear as Chapter 1 of Introduction to Quantum Computation and Information, eds. H.-K. Lo, S. Popescu and T. P. Spiller, (World Scienti c Press 1998), http://www.wspc.com.sg/.

Diamond is a material with a number of outstanding mechanical, optical, electrical and chemical properties. In the last decade it has additionally attracted the attention of scientists due to the promising properties of the color centers in its crystal lattice which can find applications in quantum information technology or quantum sensing on a nanometer scale. In this contribution we present the most prominent color centers in diamond, namely the nitrogen-vacancy (NV) and the silicon-vacancy (SiV) centers, and the possibilities to create them in diamond. In order to increase the collection efficiency of the photons emitted by the color centers they should be incorporated in photonic structures. We demonstrate the fabrication of nanopillars with diameters down to 50 nm in nanocrystalline diamond (NCD) films and monocrystalline diamond. In order to reduce the photon scattering from the rough NCD surfaces we developed a planarization technique which significantly reduced the surface roughness.

Interference with or without entanglement has been recognized as a key resource for quantum computing and quantum communications systems, as for example discussed by Nielsen and Chuang¹ and numerous other works. Multiple paths between sources and detectors require an understanding of the underpinning wave-particle duality issue in the interference effects. Recently a new axiom (particle and its wave function φ(r, t) cannot be coincident or co-located at space-time point (r_k, t_k) unless φ(r, t) = δ(r-r_k, t-t_k) the Dirac delta function) has been suggested² and justified, which explains duality without Niels Bohr’s complementarity principle, thus eliminating the role of the observer, avoiding complicated “which way” (welcher-weg) considerations and observer subjectivity. This greatly simplifies analysis and design of multi-path quantum systems and restores objectivity. The same paper also suggested in the context of entanglement new concepts of (a) “total causality” that includes entanglement as a cause to locally and causally explain “action at a distance”, and (b) “partial causality” that excludes entanglement as a cause and thereby introduces the perception of strange phenomena of non-locality, retro-causality and quantum erasure, which are nevertheless very important. This paper reviews and then applies the axiom to bring much needed clarity to certain confusing and much debated aspects of developments in non-interaction measurements, counterfactual communications and quantum computers. These potential clarifications and simplifications of analysis and design of multi path systems may help developers of future quantum communication and quantum computer systems.

Quantum information is a new subject produced by the cross integration of quantum physics and information technology, mainly including quantum communication, quantum computing and quantum metrology. In recent years, quantum information technologies such as quantum cryptography and quantum computing have developed rapidly. Under this background, some universities have set up a professional elective course of quantum information for undergraduates majoring in cyberspace security. This course mainly introduces students to quantum information related to cyberspace security, such as quantum key distribution, quantum cryptographic algorithm, quantum computing algorithm and quantum computer. This paper combs and summarizes the teaching experience of quantum information course group from the perspectives of teaching and learning. On the one hand, it discusses how teachers organize teaching effectively. According to the characteristics of undergraduates majoring in cyberspace security, teacher need to set clear teaching objectives, carefully choose teaching contents, compile appropriate teaching materials, select appropriate teaching methods and make exquisite teaching slides. At the same time, when implementing classroom teaching, teacher need to pay attention to teach the course from the perspective of cyberspace security and integrate the latest research results of quantum information into classroom teaching in real time. On the other hand, it discusses how teachers help students learn quantum information course well. Teachers should focus on visualizing the abstract theory, helping students build their own quantum information knowledge system and improve their learning enthusiasm. The teaching experience has certain reference significance for the teaching and curriculum construction of quantum information.

Quantum circuits are an abstract framework to represent quantum dynamics. They are used to formally describe and reason about processes within quantum information technology. They are primarily used in quantum computation, quantum communication, and quantum cryptography—for which they provide a machine code–level description of quantum algorithms and protocols. The quantum circuit model is an abstract representation of these technologies based on the use of quantum circuits, with which algorithms and protocols can be concretely developed and studied. Quantum circuits are typically based on the concept of qubits: two-level quantum systems that serve as a fundamental unit of quantum hardware. In their simplest form, circuits take a set of qubits initialized in a simple known state, apply a set of discrete single- and two-qubit evolutions known as “gates,” and then finally measure all qubits. Any quantum computation can be expressed in this form through a suitable choice of gates, in a quantum analogy of the Boolean circuit model of conventional digital computation. More complex versions of quantum circuits can include features such as qudits, which are higher level quantum systems, as well as the ability to reset and measure qubits or qudits throughout the circuit. However, even the simplest form of the model can be used to emulate such behavior, making it fully sufficient to describe quantum information technology. It is possible to use the quantum circuit model to emulate other models of quantum computing, such as the adiabatic and measurement-based models, which formalize quantum algorithms in a very different way. As well as being a theoretical model to reason about quantum information technology, quantum circuits can also provide a blueprint for quantum hardware development. Corresponding hardware is based on the concept of building physical systems that can be controlled in the way required for qubits or qudits, including applying gates on them in sequence and performing measurements.

This issue's SIGEST paper, from the SIAM Journal on Computing (SICOMP), takes SIAM readers into the world of quantum computing, a world with its roots in physics that still probably is better known to many physicists and theoretical computer scientists than to a good portion of SIAM readers. Quantum computation is a form of computing based upon quantum mechanics, rather than the classical physics that conventional computers utilize. The distinction between conventional and quantum computers starts to become apparent at the most basic level of bits: whereas standard computers utilize binary bits that may have either the state 0 or 1, quantum computers are based upon “qubits” (quantum binary digits) that may have the state 0, 1, or a superposition of these two states with a complex number that specifies the probability for being in each state. Mathematically, the state of a quantum computer can change through a sequence of unitary transformations to the initial state. One reason for the great interest in quantum computation is that it has been shown that quantum computers can solve some important problems, such as the factorization of very large integers (which has important implications for cryptography), far more efficiently than we currently are able to solve these problems on conventional computers. The selected paper, “Adiabatic Quantum Computation Is Equivalent to Standard Quantum Computation” by Dorit Aharonov, Wim van Dam, Julia Kempe, Zeph Landau, Seth Lloyd, and Oded Regev, which was originally published in SICOMP in 2007, establishes an important theoretical result in the field of quantum computation. As the title indicates, it involves adiabatic quantum computation, a form of quantum computing that has attracted interest in recent years in part because it may offer promise in the effort to build effective quantum computers. Adiabatic quantum computation is distinctly different from standard quantum computation. In the standard model, computations are represented similarly to classical circuits, except that the circuits carry qubits instead of bits. In contrast, the adiabatic model is inspired by the adiabatic theorem in quantum mechanics which states that a system in its lowest energy or ground state will remain in that state if it is subjected to conditions that change sufficiently slowly. It already was known that standard quantum computers can efficiently simulate adiabatic quantum computers. The key contribution of this paper is to show the reverse: that adiabatic quantum computation can efficiently simulate standard quantum computation. In the words of the SICOMP editorial board in nominating this paper, “This is a surprising result that continues to be very influential.” It established that the two forms of quantum computation are theoretically equivalent, one implication of which is to bolster the potential practical importance of adiabatic quantum computation. The paper by Aharonov et al. is very nicely suited to SIGEST—it is important in its field, it is nicely and accessibly written, it offers a glimpse into an area of applied mathematics and computation that is of growing importance, and it touches on many areas of applied mathematics, including linear algebra, Markov chains, and optimization. We hope it will provide SIAM readers a glimpse of current theoretical research that may, some day, help lead to a brave new world of practical computation.

A professor of physics at Harvard University, Mikhail D. Lukin was elected to the National Academy of Sciences in 2018 for his work in quantum optics and quantum information science. Lukin has explored a variety of topics during his career, from quantum manipulation of atomic and nanoscale systems to nanophotonics and quantum metrology. He has developed several techniques, with applications including the realization of quantum computers and quantum networks and quantum sensors that can be used in materials science research and biological imaging. In his Inaugural Article (1), Lukin and colleagues used quantum temperature sensors and local laser heating to manipulate cell cycle timing in embryos of the nematode worm Caenorhabditis elegans , a model organism for cell and molecular biology research. Lukin recently spoke to PNAS about his findings. Image credit: Mikhail Lukin. > PNAS:How did you become interested in using quantum sensors to study biological systems? > Lukin:I’m a quantum physicist, and my “day job” involves building quantum machines, such as quantum computers, quantum simulators, and quantum communication systems. Over the past two decades our community has developed very sophisticated and unique tools to study and control quantum systems. We have learned how to look at atoms one at …

Recent discoveries in quantum information processing have brought a variety of deep, important and exciting challenges which need to be faced by physics, informatics and mathematics. The impact of these discoveries is broad and is reflected in new important relationships between the foundations of computing and physics. (a) The foundations of computing (information processing and communication) have to be built on the basis of the laws and limitations of quantum physics rather than classical physics. (b) Quantum physics offers powerful methods of encoding, processing and transmitting information that are not available in the classical world. Consequently, quantum information processing and communication systems seem to have the potential to be more efficient than their classical counterparts, while quantum communication systems seem to have the potential to be both more efficient and more secure than classical systems. (c) Quantum computing represents the area through which the fundamental physics is expected to have the most important technological impact in the foreseeable future. (d) Quantum information processing paradigms, concepts and methods seem to have the potential to contribute to a better understanding of quantum phenomena and, thereby, to a better comprehension of the laws and limitations of Nature; this, in turn, may have far-reaching implications for science and technology.

The quantum computer, is a "supercomputer" that relies on the phenomena of quantum mechanics to perform operations on data. Object of suppositions, sometimes farfetched, quantum mechanics gave birth to the quantum computer, a machine capable of processing data tens of millions of times faster than a conventional computer. A quantum computer doesn't use the same memory as a conventional computer. Rather than a sequence of 0 and 1, it works with qubits or quantum bits. The quantum computer is a combination of two major scientific fields: quantum mechanics and computer science. Quantum mechanics, on which this computer is based, governs the movement of bodies in the atomic, molecular and corpuscular domains, is a theory whose logic is totally contrary to intuition and it is essential to use mathematics to fully grasp it. Quantum computing is the sub-domain of computer science that deals with quantum computers using quantum mechanical phenomena, as opposed to those of electricity exclusively, for so-called "classical" computing. The quantum phenomena used are quantum entanglement and superposition. The article examines some aspects related to the development, operation, advantages and difficulties, applications and future of the quantum computer.

Quantum physics has a growing influence on sensor technology; particularly, in the areas of quantum computer science, quantum communications, and quantum sensing based on recent insights from atomic, molecular and optical physics. These quantum contributions have the potential to impact information fusion techniques. Quantum information technology (QIT) methods of interest suggest benefits for information fusion, so a panel was organized to articulate methods of importance for the community. The panel discussion presented many ideas from which the leading impact for information fusion is directly related to the sub-Rayleigh sensing that reduces uncertainty for object assessment through enhanced resolution. The second areas of importance is in the cyber security of data that supports data, sensor, and information fusion. Some elements of QIT that require further analysis is in quantum computing for which only a limited set of information fusion techniques can harness the methods associated with quantum computer architectures. The panel reviewed various aspects of QIT for information fusion which provides a foundation to identify future alignment between quantum and information fusion techniques.

In this article, aspects of quantum electromagnetics (QEM) are discussed with a view toward illustrating basic concepts and making some connections with classical EM. The similarities and differences between the mathematical representations as well as the physical interpretations in the quantum and classical cases are reviewed, and a brief discussion of the different objectives and quantities to be measured/computed in quantum and classical regimes is provided. The role of the classical Green function in rigorous, fully quantum electrodynamics (QED) is highlighted, and an example of quantum state evolution in a graphene environment is presented.

This study aims to leverage the advanced capabilities of quantum computing to construct an efficient framework for processing large-scale health data, uncover potential higher-order correlations in medicine, and enhance the accuracy of smart healthcare diagnosis and treatment. A data processing framework is developed using quantum annealing algorithms and quantum circuits. We call it the quantum medical data simulation computational model (Q-MDSC). A unique encoding method based on quantum bits is employed for health data features, such as encoding symptom information from electronic health records into different quantum bits and representing different alleles of genetic data through superposition states of quantum bits. The properties of quantum entanglement are utilized to relate different data types, and quantum parallelism is harnessed to process multiple data combinations simultaneously. Additionally, this quantum computing framework is compared with traditional data mining methods using the same datasets, which include the Cochrane Systematic Review Database (https://www.cochranelibrary.com), the BioASQ Dataset (https://participants-area.bioasq.org), the PubMed Central Dataset (https://www.ncbi.nlm.nih.gov/pmc), and the Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov). The datasets are divided into training and testing sets in a 7:3 ratio during the experiments. Tests are conducted on association mining tasks of varying data scales and complexities, ranging from simple symptom-disease associations to complex gene-symptom-disease higher-order associations. The results indicate that, when processing large-scale data, the quantum computing framework improves overall computational speed by approximately 45% compared to traditional algorithms. Regarding uncovering higher-order correlations, the quantum computing framework enhances accuracy by about 30% relative to traditional algorithms. For early disease prediction, the accuracy achieved with the new framework is approximately 25% higher than that of conventional methods. Furthermore, for personalized treatment plan matching, the matching accuracy of the quantum computing framework surpasses traditional approaches by about 35%. These findings demonstrate the significant potential of the quantum computing-based smart healthcare framework for processing large-scale health data in the context of higher-order correlation mining, paving new pathways for the development of smart healthcare. This study utilizes multiple public datasets to achieve breakthroughs in computational speed, higher-order correlation mining, early disease prediction, and personalized treatment plan matching, thus opening new avenues for advancing smart healthcare.

Entanglement is an essential feature of quantum theory and the core of the majority of quantum information science and technologies. Quantum computing is one of the most important fruits of quantum entanglement and requires not only a bipartite entangled state but also more complicated multipartite entanglement. In previous experimental works to demonstrate various entanglement-based quantum information processing, light has been extensively used. Experiments utilizing such a complicated state need highly complex optical circuits to propagate optical beams and a high level of spatial interference between different light beams to generate quantum entanglement or to efficiently perform balanced homodyne measurement. Current experiments have been performed in conventional free-space optics with large numbers of optical components and a relatively large-sized optical setup. Therefore, they are limited in stability and scalability. Integrated photonics offer new tools and additional capabilities for manipulating light in quantum information technology. Owing to integrated waveguide circuits, it is possible to stabilize and miniaturize complex optical circuits and achieve high interference of light beams. The integrated circuits have been firstly developed for discrete-variable systems and then applied to continuous-variable systems. In this article, we review the currently developed scheme for generation and verification of continuous-variable quantum entanglement such as Einstein-Podolsky-Rosen beams using a photonic chip where waveguide circuits are integrated. This includes balanced homodyne measurement of a squeezed state of light. As a simple example, we also review an experiment for generating discrete-variable quantum entanglement using integrated waveguide circuits.

Quantum computing and industrial information integration: A review