Context. Nature is the relation among processes and phenomena. Nothing exists in the universe without relations. Computer is transactions of relations between data with the help of control and execution mechanisms. Quantum relations are a superposition of particles and their states. Superposition and entanglement are equivalent concepts. Entanglement is a non-local superposition of deterministic states. A quantum computer is unconditional transactions of relations between qubit data. Quantum computer is an analog device for parallel solution of combinatorial problems. Practically oriented definitions of the quantum computer concepts are the path to development of scalable quantum parallel algorithms for combinatorial problems solving. Any algorithm can be reduced to a sequence of operations without conditions, because any truth table is a collection of a complete system of conditions-states. Any sequence of actions can always be reduced to one parallel operation. Conditions and sequences arise only when the developer wants to use previously created primitive constructs to build an always non-optimal computing unit. The paradigm of quantum computer creation is determined through the use of photonic transactions on the electrons of an atom may exclude the use of quantum logic. The evolutionary path of a quantum computer from the classical one: “memory-address-transaction” (MAT) → “electron-addresstransaction” → “electron-address-quantaction” (EAQ) → state-superposition-logic. The meeting point of classical and quantum computers is photon transactions on the structure of electrons. Everything that is calculated on a quantum computer can be calculated in parallel on a classical one on account of memory redundancy. The given example is a memory-driven algorithm for modeling digital products based on qubit-vector forms of functionality description for significant performance boost of computing processes by parallel execution of logical operations. Objective. Simulation of the correct SoC-component behavior based on vector representation of the logic. Formation of the triggering development of a computing based on the superposition of the classical, quantum and analog computing process, which in its development should be based on technological qubit, tabular and vector data structures for the parallel solution of combinatorial problems. Method. MAT-computing implements any algorithms on account of transactions (read-write) in memory. Qubit-vector models for describing functionalities, which differ from known truth tables in compactness of description and manufacturability for the implementation of parallel algorithms of the synthesis and analysis of digital devices and SoC-components. Results. 1) The metric of the technological data structures, focused on parallel troubleshooting in digital systems based on the usage of two logical vector operations, was proposed for the first time. 2) The metric of relations between the individual components of QC, allowing organizing a quantum deterministic computer, has been further developed. 3) Quantum architectural solutions, that allow solving coverage problems in a quasi-parallel mode, were proposed for the first time. 4) Architectural solutions based on an analog-to-digital computing, which can be used to solve the problems of the digital systems parallel analysis, have been further developed. 5) Vector-qubit structures of the logic data, that allow a quasi-parallel simulation of digital circuits, were proposed. Conclusions. Qubit models, quantum methods and combinatorial algorithms for technical diagnostics of digital devices have been implemented, which can significantly (up to 25%) reduce the time of test synthesis, deductive modeling of faulty and correct behavior, search for defective states by introducing an innovative idea of using qubit-vector data structures for describing logical components. Comparative assessments of qubit models and methods usage show an increase in the efficiency of algorithms for modeling digital devices compared to tabular ones. The superposition of a classical, quantum and analog computer is integrally represented, which allows to find the best solutions for recognition and decision making.
Context. Nature is the relation among processes and phenomena. Nothing exists in the universe without relations. Computer is transactions of relations between data with the help of control and execution mechanisms. Quantum relations are a superposition of particles and their states. Superposition and entanglement are equivalent concepts. Entanglement is a non-local superposition of deterministic states. A quantum computer is unconditional transactions of relations between qubit data. Quantum computer is an analog device for parallel solution of combinatorial problems. Practically oriented definitions of the quantum computer concepts are the path to development of scalable quantum parallel algorithms for combinatorial problems solving. Any algorithm can be reduced to a sequence of operations without conditions, because any truth table is a collection of a complete system of conditions-states. Any sequence of actions can always be reduced to one parallel operation. Conditions and sequences arise only when the developer wants to use previously created primitive constructs to build an always non-optimal computing unit. The paradigm of quantum computer creation is determined through the use of photonic transactions on the electrons of an atom may exclude the use of quantum logic. The evolutionary path of a quantum computer from the classical one: “memory-address-transaction” (MAT) → “electron-addresstransaction” → “electron-address-quantaction” (EAQ) → state-superposition-logic. The meeting point of classical and quantum computers is photon transactions on the structure of electrons. Everything that is calculated on a quantum computer can be calculated in parallel on a classical one on account of memory redundancy. The given example is a memory-driven algorithm for modeling digital products based on qubit-vector forms of functionality description for significant performance boost of computing processes by parallel execution of logical operations. Objective. Simulation of the correct SoC-component behavior based on vector representation of the logic. Formation of the triggering development of a computing based on the superposition of the classical, quantum and analog computing process, which in its development should be based on technological qubit, tabular and vector data structures for the parallel solution of combinatorial problems. Method. MAT-computing implements any algorithms on account of transactions (read-write) in memory. Qubit-vector models for describing functionalities, which differ from known truth tables in compactness of description and manufacturability for the implementation of parallel algorithms of the synthesis and analysis of digital devices and SoC-components. Results. 1) The metric of the technological data structures, focused on parallel troubleshooting in digital systems based on the usage of two logical vector operations, was proposed for the first time. 2) The metric of relations between the individual components of QC, allowing organizing a quantum deterministic computer, has been further developed. 3) Quantum architectural solutions, that allow solving coverage problems in a quasi-parallel mode, were proposed for the first time. 4) Architectural solutions based on an analog-to-digital computing, which can be used to solve the problems of the digital systems parallel analysis, have been further developed. 5) Vector-qubit structures of the logic data, that allow a quasi-parallel simulation of digital circuits, were proposed. Conclusions. Qubit models, quantum methods and combinatorial algorithms for technical diagnostics of digital devices have been implemented, which can significantly (up to 25%) reduce the time of test synthesis, deductive modeling of faulty and correct behavior, search for defective states by introducing an innovative idea of using qubit-vector data structures for describing logical components. Comparative assessments of qubit models and methods usage show an increase in the efficiency of algorithms for modeling digital devices compared to tabular ones. The superposition of a classical, quantum and analog computer is integrally represented, which allows to find the best solutions for recognition and decision making.
Nature is the relations between processes and phenomena. Nothing exists in a Universe without relations. Computing is the transaction of relations between data using control and execution mechanisms. Quantum relations are a superposition of particles and their states. Quantum computing is unconditional transactions of relations between qubit data. Entanglement is a nonlocal superposition of deterministic states. A quantum computer is an analog device for solving combinatorial problems in parallel. Practically focused definitions of the concepts of quantum computing represent a path to the development of scalable quantum parallel algorithms for solving combinatorial problems. Any algorithm can be reduced to a sequence of operations without conditions, because any truth table is a collection of a complete system of conditions-states. Any sequence of actions can always be reduced to one parallel operation. Conditions and sequences arise only when the developer uses previously created primitives-constructs to build an always non-optimal calculator. The deterministic paradigm of creating quantum computing by using photon transactions on the electrons of an atom can exclude the use of quantum logic. The evolutionary path of quantum computing from the classical one: Memory-Address-Transaction (MAT) → Electron-Address-Transaction →Electron-Address-Quantaction (EAQ)→State-Superposition- Logic. What is calculated on a quantum computer can be calculated in parallel on a classical computer due to the redundancy of memory. MAT-computing implements any algorithms through transactions (read-write) in memory. Qubit-vector models for describing functionalities differ from the known truth tables in terms of compactness of description and technological implementation of parallel algorithms for the synthesis and analysis of digital devices and SoC-components. An example is given – a memory-driven algorithm for simulating digital devices based on qubit-vector forms of describing functionalities for a significant increase in the productivity of computing processes by parallel execution of logical operations. Comparative evaluations of the use of qubit models and methods show an increase in the efficiency of algorithms for simulating digital devices in comparison with tabular ones. The superposition of classical, quantum and analog computing is integrally presented, which makes it possible to search the best solutions for recognition and decision making.
Context. Nature is the relation among processes and phenomena. Nothing exists in the universe without relations. Computer is transactions of relations between data with the help of control and execution mechanisms. Quantum relations are a superposition of particles and their states. Superposition and entanglement are equivalent concepts. Entanglement is a non-local superposition of deterministic states. A quantum computer is unconditional transactions of relations between qubit data. Quantum computer is an analog device for parallel solution of combinatorial problems. Practically oriented definitions of the quantum computer concepts are the path to development of scalable quantum parallel algorithms for combinatorial problems solving. Any algorithm can be reduced to a sequence of operations without conditions, because any truth table is a collection of a complete system of conditions-states. Any sequence of actions can always be reduced to one parallel operation. Conditions and sequences arise only when the developer wants to use previously created primitive constructs to build an always non-optimal computing unit. The paradigm of quantum computer creation is determined through the use of photonic transactions on the electrons of an atom may exclude the use of quantum logic. The evolutionary path of a quantum computer from the classical one: “memory-address-transaction” (MAT) → “electron-addresstransaction” → “electron-address-quantaction” (EAQ) → state-superposition-logic. The meeting point of classical and quantum computers is photon transactions on the structure of electrons. Everything that is calculated on a quantum computer can be calculated in parallel on a classical one on account of memory redundancy. The given example is a memory-driven algorithm for modeling digital products based on qubit-vector forms of functionality description for significant performance boost of computing processes by parallel execution of logical operations. Objective. Simulation of the correct SoC-component behavior based on vector representation of the logic. Formation of the triggering development of a computing based on the superposition of the classical, quantum and analog computing process, which in its development should be based on technological qubit, tabular and vector data structures for the parallel solution of combinatorial problems. Method. MAT-computing implements any algorithms on account of transactions (read-write) in memory. Qubit-vector models for describing functionalities, which differ from known truth tables in compactness of description and manufacturability for the implementation of parallel algorithms of the synthesis and analysis of digital devices and SoC-components. Results. 1) The metric of the technological data structures, focused on parallel troubleshooting in digital systems based on the usage of two logical vector operations, was proposed for the first time. 2) The metric of relations between the individual components of QC, allowing organizing a quantum deterministic computer, has been further developed. 3) Quantum architectural solutions, that allow solving coverage problems in a quasi-parallel mode, were proposed for the first time. 4) Architectural solutions based on an analog-to-digital computing, which can be used to solve the problems of the digital systems parallel analysis, have been further developed. 5) Vector-qubit structures of the logic data, that allow a quasi-parallel simulation of digital circuits, were proposed. Conclusions. Qubit models, quantum methods and combinatorial algorithms for technical diagnostics of digital devices have been implemented, which can significantly (up to 25%) reduce the time of test synthesis, deductive modeling of faulty and correct behavior, search for defective states by introducing an innovative idea of using qubit-vector data structures for describing logical components. Comparative assessments of qubit models and methods usage show an increase in the efficiency of algorithms for modeling digital devices compared to tabular ones. The superposition of a classical, quantum and analog computer is integrally represented, which allows to find the best solutions for recognition and decision making.
A novel deterministic paradigm for creating quantum computing via photon transactions with the electrons of an atom is described. This paradigm is free of quantum logic. The practically focused evolutionary path of quantum computing starting with the classical approach is shown: Memory-Address-Transaction → Electron-Address-Transaction Electron → Address- Quantaction (EAQ). Qubit-vector models for describing functionalities are proposed that differ from the known truth tables in the compactness of description and technological ability of the algorithm implementation for synthesis and analysis of digital devices and SoC components. For example, we consider a memory-driven algorithm for the simulation of digital devices based on qubit-vector forms for describing functionalities with a significant increase in the performance of computational processes. These processes can be utilized for analysis and synthesis through parallel execution of logic operations. A set of comparative estimates of qubit models and methods for improving the efficiency of the algorithms for simulating digital devices is presented.
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 .
Recently, there has been a rapid increase interest in quantum computers. Their work is based on the use of quantum-mechanical phenomena such as superposition and entanglement for computing to transform input data into outputs, which can actually provide effective performance 3-4 orders of magnitude higher than any modern computing devices. In the past few decades, there has been an acute problem of creating a quantum computer that uses quantum mechanical effects for computations. Currently, there are prototypes of devices of this class, but it is not yet possible to achieve an effective solution to the planned tasks with their help due to a number of difficulties in implementation. However, there is a mathematical apparatus that describes the behavior of quantum particles using a wave function. Hence, it becomes possible to simulate quantum computations on the classical architecture and check the reliability of algorithms belonging to the NP class, which are theoretically executed on a quantum computer in polynomial time and which cannot be solved on classical computers within an acceptable time frame. Effectively simulate the operation of a quantum system on devices with classical architecture is impossible, it remains to propose methods for acceleration of quantum computing on classical systems.
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.