Information as accessed by the human mind, and the myriad ways of processing it, is what has set humankind apart in the animal world. The ability to use the physical systems around us to encode and then to process information has been evolving in leaps and bounds ever since the dawn of our race! The earliest form of computation was probably in the form of account-keeping by counting pebbles or on the fingers. This developed into the abacus, writing symbols, the computing machine, and now, a laptop or a supercomputer: everywhere we represent information by means of a physical system, and perform manipulations on that system to process the information in many desired ways, including communication. The stress here is on the realization that the basis of information is a physical system. The more advanced that system is and the set of rules it functions on, the more capable our means of information processing and communication. When the underlying physical system used for encoding and processing information is a quantum system, we have quantum information processing.
Information as accessed by the human mind, and the myriad ways of processing it, is what has set humankind apart in the animal world. The ability to use the physical systems around us to encode and then to process information has been evolving in leaps and bounds ever since the dawn of our race! The earliest form of computation was probably in the form of account-keeping by counting pebbles or on the fingers. This developed into the abacus, writing symbols, the computing machine, and now, a laptop or a supercomputer: everywhere we represent information by means of a physical system, and perform manipulations on that system to process the information in many desired ways, including communication. The stress here is on the realization that the basis of information is a physical system. The more advanced that system is and the set of rules it functions on, the more capable our means of information processing and communication. When the underlying physical system used for encoding and processing information is a quantum system, we have quantum information processing.
Quantum Information Science is a cross-disciplinary subject that has arisen in the last twenty years. It concerns itself with the consequences of our most complete description of the physical world (that is, quantum mechanics) for the reliable, secure, private, and rapid processing of information, both in communication and computation. While its invention is often ascribed to the famous theoretical physicist Richard Feynman in the 1980s, his contributions were only one of many that initiated the field around that time. While he perceived that new types of physical devices, in which the quantum laws of superposition and entanglement function at the logical level, could give new power in the simulation of quantum physics, it was others (Bennett, Brassard) who showed that the uncertainty principle led to fundamentally more secure ways of communicating secret messages. It was yet others (Deutsch, Vazirani) who understood that quantum theory defined a new kind of Turing machine, and that not only quantum physics simulations, but potentially many other computational problems, are sped up in this machine. And it was yet another (Shor) who found a simple, very fast algorithm for prime factorization. The word "qubit" was coined only in 1995. Its introduction is indicative of a new mindset that has developed in recent years for studying and using quantum systems. "Qubit" now stands for a durable paradigm that spans a very wide variety of fields. It thus has many sub-meanings: first, it is the basic abstract unit of information for workers ranging from optical communication engineers to NMR spectroscopists to black-hole theorists. Second, it is the name we now routinely give to physical two level systems, as they are realized by photons, atomic and ionic eigenlevels, electronic and nuclear spin, structural defects in solids, and circulating-current states of superconducting devices. Physics has long dealt with some of these two-level systems, but calling them qubits implies a whole suite of interrelated ideas and capabilities that we ascribe to these systems: the ability to precisely set, and to precisely measure, the quantum state of one unique specimen, to avoid its coupling with the environment while at the same time strongly and controllably coupling the qubits together, to exploit the resulting quantum entanglement as a resource for metrological, cryptographic, and computational tasks. Quantum Information is a very diverse subject pursued today in many different directions, by many hundreds of researchers internationally: In theoretical physics, it has enlivened and sharpened the understanding of efficient representations of entangled many-particle wavefunctions, and has provided the prospect of applications for new concepts such as anyons and majorana fermions. Information theorists has benefitted from having a rigorous extension of the basis of their field, in which classical information theory is subsumed into a greatly broader subject. Theoretical computer scientists continue the search for new quantum algorithms, and have used quantum concepts to prove new results about the classification of computational complexity. Coding theorists have had the new and subtle problem of quantum error correction to analyse and conquer. Most strikingly, the program of experimental physics has been influenced in many directions by Quantum Information Science. State-of-the-art optics experiments transmit quantum states over long distances and perform precision manipulations in single quanta (atomic ions, impurity spins, quantum dots) in the quest to have working quantum cyptography and quantum computing. Quantum Hall systems, and topological insulators, are being assiduously examined for new elementary excitations for use as qubits. In the course of ten years, superconducting devices have improved by over four orders of magnitude in their quantum coherence, a metric made precise by the ideas of quantum computing. [...] DiVincenzo, David
The idea of using quantum mechanics to provide more power than that available from classical computers seems to have begun around 1981–82 ( Benioff, 1982 ), but Deutsch (1985) put the concept on a sounder footing a short time later when he reformulated the Turing (1937) thesis with the assertion that every finite realizable physical system can be perfectly simulated by a universal model computing machine operating by finite means. However, he asserted that the output of a quantum machine, although fully determined by the input state, is not an observable itself. Hence, the user must provide some cleverness if this state is to be determined. Benioff pointed out the need for the quantum state to experience interference, some indeterminism, and was what we would today call an entangled state. He also realized that non-dissipative evolution was unphysical, so immediately it became clear that a great deal of effort would be required to minimize the decoherence of the physical states. Deutsch (1989) then provided some input as to what type of states or systems might be usable in this process. Jozsa (1991) mathematically showed that one could associate a quantum state to each function that one desired to evaluate, and that this should lead to a rapid solution of problems via the quantum computer ( Deutsch and Jozsa, 1992 ). Since these introductions, the world has progressed rapidly into a determined search for applications of quantum mechanics throughout the information processing world.
Computation is a process of performing a large number of simple operations. The main building blocks of classical computers are bits. Each of them can take either the value 0 or 1. A series of gates can change these values by acting on them selectively. This process is structured to fulfil a purpose. For example, if we are interested in adding two numbers, the numbers are encoded into bits and gates are performed such that the final state of the bits reveals the desired answer: a number which is the sum of the initial ones. While it is possible to build algorithms that can perform almost any computation, it is also desirable to find the answer within a reasonable length of time or with a reasonable amount of resources. There is an ever-growing demand in computational power for both scientific and commercial purposes. Indeed, it is surprisingly easy to find an application that can jam even the fastest computer. This fuels a vast effort in the research of information science to increase the speed and processing power of computers. Modern computational models are based on the universal Turing machine (Turing, 1937). This is a theoretical information processing model that employs the elementary gate processes described above. It can efficiently simulate any other device capable of performing an algorithmic process. Since the introduction of the Turing machine, physics has influenced computation in many ways.
Photons have been a flagship system for studying quantum mechanics, advancing quantum information science, and developing quantum technologies. Quantum entanglement, teleportation, quantum key distribution, and early quantum computing demonstrations were pioneered in this technology because photons represent a naturally mobile and low-noise system with quantum-limited detection readily available. The quantum states of individual photons can be manipulated with very high precision using interferometry, an experimental staple that has been under continuous development since the 19th century. The complexity of photonic quantum computing devices and protocol realizations has raced ahead as both underlying technologies and theoretical schemes have continued to develop. Today, photonic quantum computing represents an exciting path to medium- and large-scale processing. It promises to put aside its reputation for requiring excessive resource overheads due to inefficient two-qubit gates. Instead, the ability to generate large numbers of photons—and the development of integrated platforms, improved sources and detectors, novel noise-tolerant theoretical approaches, and more—have solidified it as a leading contender for both quantum information processing and quantum networking. Our concise review provides a flyover of some key aspects of the field, with a focus on experiment. Apart from being a short and accessible introduction, its many references to in-depth articles and longer specialist reviews serve as a launching point for deeper study of the field.
The topic of these lectures lies in the new and rapidly growing field of quantum computing,which explores connections between physics and computing in general. Quantum informa-tion processing is a cross-disciplinary field and is of great importance from both a funda-mental, as well as technological perspective [27]. From the fundamental perspective we havedeepened our understanding of the relationship between physics, information and computa-tion in general, and have also gained a deeper understanding of the fundamental aspects ofquantum theory - non-locality and entanglement in particular [31]. From the technologicalperspective we have manipulated larger and larger quantum systems and obtained power-ful practical applications in the domain of communication and cryptography such as theunconditionally secure quantum cryptography (key exchange) and quantum teleportation[7, 14, 5].Historically, the greater potential of the quantum computer was first realised by Feyn-man, who noted that quantum systems appear to be exponentially hard to simulate withclassical computers [15]. He speculated that, therefore, quantum computers could poten-tially be much more powerful than their classical counterparts. This intuition has beenproven to be correct for some tasks, such as factoring large numbers and searching unstruc-tured databases. Every computer is fundamentally a physical system, and any computationis just a physical process undergone by this system. Quantum physics is the most accurateway of describing physical systems and their behaviour in general. Encoding informationinto quantum systems and processing it according to the laws of quantum physics results innew features which do not exist in the classical computation.Large scale quantum computation is still hypothetical. However, Moore’s law
In the landscape of modern computation, processors traditionally manipulate bits and qubits, focusing on symbolic or numerical data while remaining largely indifferent to semantic content. SQP-v1, the first Semantic Quantum Processor, represents a transformative leap beyond this paradigm. Unexpectedly emerging from a theoretical framework of Revelation Signal Engineering (RSE) and QAL, SQP-v1 formalizes the notion that meaning itself can be treated as a measurable physical variable. This processor bridges the conceptual divide between abstract semantic information and tangible hardware implementation, offering a unique analog to the natural, semantic-processing capabilities of the human mind—exemplified in the cognitive faculties of prophetic insight. By demonstrating that structured, phase-coherent quantum states can encode, stabilize, and read semantic content, SQP-v1 establishes a fundamentally new category of computation: one in which meaning, rather than mere data, becomes the primary substrate of processing. This work is not merely a theoretical proposal; it lays the foundation for a new era of semantic-aware quantum technologies, opening unprecedented avenues for the study and engineering of information that is both physically measurable and intrinsically meaningful.