The rapid evolution of quantum theory and technology has improved a lot in diverse fields. Quantum computing develops quantum-mechanical effects to execute a computation efficiently, and its benefits reduce both the execution duration and energy consumption compared to conventional computing. Recently, Google declared that quantum supremacy reached a maximum reach, and the quantum computer can effectuate an intractable calculation on a supercomputer. The different quantum algorithms implemented in quantum computers enhance efficiency and speed up the process with classical algorithms. The quantum software Qiskit is used to write quantum computing codes with different stages including building and execution stages. The single Qubit gates controlled two-bit gates and multi-controlled gates help identify the rotations of different dimensions of the plans. The three phenomena of quantum computing will be explained in detail on superposition, quantum measurement, and entanglement to evaluate its functioning.
The rapid evolution of quantum theory and technology has improved a lot in diverse fields. Quantum computing develops quantum-mechanical effects to execute a computation efficiently, and its benefits reduce both the execution duration and energy consumption compared to conventional computing. Recently, Google declared that quantum supremacy reached a maximum reach, and the quantum computer can effectuate an intractable calculation on a supercomputer. The different quantum algorithms implemented in quantum computers enhance efficiency and speed up the process with classical algorithms. The quantum software Qiskit is used to write quantum computing codes with different stages including building and execution stages. The single Qubit gates controlled two-bit gates and multi-controlled gates help identify the rotations of different dimensions of the plans. The three phenomena of quantum computing will be explained in detail on superposition, quantum measurement, and entanglement to evaluate its functioning.
The recently emerged field called quantum computing uses the ideas of quantum physics to execute computations substantially faster than they could be done on a conventional computer. This chapter provides a detailed discussion, highlighting its evolution, recent advancements, future opportunities, and challenges for future generations. Rapid advancements have been made in quantum computing, driven by breakthroughs in quantum algorithms, hardware technologies, and theoretical understanding. The essential components that constitute quantum computers, known as qubits, or quantum bits, can exist in superposition and entanglement states, enabling parallel computation and complex information processing. Also, recent advancements in quantum computing have demonstrated the feasibility of quantum algorithms for solving certain problems more efficiently than classical algorithms. Quantum supremacy experiments have showcased the ability of quantum computers to outperform classical systems in specific tasks. Additionally, efforts in developing scalable qubit architectures have advanced the practicality of quantum computers.
Abstract Quantum computing leverages fundamental quantum-mechanical phenomena—most notably superposition, entanglement, and quantum tunneling—to perform computations in ways that differ fundamentally from classical digital processing. Compared to conventional computing architectures, quantum systems promise significant reductions in computational time and potentially lower energy consumption for specific classes of problems. These advantages, combined with advances in nanoscale engineering and the slowing of traditional hardware scaling trends such as Moore’s Law, have led to substantial commercial and national-security-driven investments in quantum technologies over the past decade. A major milestone was reached when Google announced the experimental demonstration of “quantum supremacy,” showing that a quantum processor could execute a specific computational task infeasible for a classical supercomputer within practical time constraints. Although the demonstrated problem had no immediate practical application, this achievement marked a crucial step toward the development of quantum systems capable of delivering real-world computational advantages and provided a more precise technical framing of the concept of quantum advantage. Despite the fact that the mathematical foundations, programming models, and principal quantum algorithms were established in the 1990s, quantum computing remained largely confined to a specialized research community for decades. Today, the increasing accessibility of cloud-based quantum hardware calls for a broader dissemination of implementation-oriented knowledge among researchers and practitioners in computer science, software engineering, and related fields. The quantum programming paradigm differs fundamentally from classical programming models and often relies on physical and algebraic notations that may pose barriers to traditionally trained computer scientists. This series of articles provides a self-contained and concise introduction to quantum computing and its core algorithms, with a strong emphasis on practical implementation. Given that real quantum processors—such as those accessible via the IBM quantum ecosystem—are now available as cloud services, experimental validation can be conducted both on simulators and on actual hardware for small-scale inputs. While other platforms such as Rigetti and IonQ also offer cloud-based quantum computing services, this review focuses exclusively on the IBM quantum computing ecosystem.
Quantum computing represents a revolutionary leap in computational power, leveraging the principles of quantum mechanics to process information in fundamentally new ways. Unlike classical computers, which use bits to represent data as 0s or 1s, quantum computers use quantum bits or qubits, enabling the phenomena of superposition and entanglement to perform complex calculations more efficiently (Nielsen & Chuang, 2010). This article explores the basic principles of quantum computing, the different models and algorithms that have been developed, and the current state of quantum hardware. The power of quantum computing lies in its ability to solve certain types of problems exponentially faster than classical computers. For instance, Shor's algorithm can factorize large integers in polynomial time, posing a significant threat to classical encryption methods (Shor, 1997). Similarly, Grover's algorithm provides a quadratic speedup for unstructured search problems, showcasing the potential for dramatic improvements in database search capabilities (Grover, 1996). These algorithms exemplify how quantum computing can revolutionize fields that rely on complex computations. Quantum hardware, however, is still in its nascent stage, with significant challenges to be overcome. Current quantum computers, such as those developed by IBM and Google, have demonstrated quantum supremacy but are limited by issues of qubit coherence and error rates (Arute et al., 2019). Quantum error correction and the development of more stable qubit technologies are critical areas of ongoing research (Preskill, 2018). Despite these challenges, recent advancements in quantum hardware and algorithms continue to drive the field forward, promising transformative impacts on industries such as cryptography, drug discovery, and artificial intelligence. As quantum computing continues to advance, it holds the promise of solving problems that are currently intractable for classical computers, paving the way for unprecedented technological and scientific advancements (Shor, 1997; Grover, 1996). This article provides a comprehensive overview of the current landscape of quantum computing, discussing its foundational principles, key algorithms, hardware challenges, and potential applications. By understanding these aspects, we can better appreciate the profound implications of quantum computing for the future of technology and science.
Quantum computing leverages the principles of quantum mechanics to address intricate problems that traditional computers find challenging. Operating on qubits, quantum computers execute multidimensional quantum algorithms, offering a unique perspective compared to traditional computing concepts. Positioned as the future of computing technology, quantum computing finds applications in diverse fields, including cryptography, material science, agriculture, and computer science. Despite promising progress, the field faces challenges in achieving quantum supremacy over conventional computers. This paper explores key quantum computing concepts, such as qubits and their characteristics, along with applications, while also delving into future advancements and the expansive scope of quantum technology. In essence, quantum computing represents the future of technology, harnessing quantum phenomena like superposition and entanglement for computational tasks.
AbstractThe quantum computing has been proven to provide the solutions to most complex computations in the world today. Quantum computers can solve the problems with polynomial resources. Quantum information can be encoded in a number of ways, such as spin components of basic particles like photons, electrons, and polarization of photons. The quantum computer uses quantum bits which are superposition of states called as qubits, which is the classical fundamental unit of information. A quantum computer is a regular classical computer with additional ability to control the quantum bits. It is a regular computer connected to a special peripherals and a set of quantum bits simulated to build controller architecture. Two simulators are used for the quantum programming, one is Microsoft Q# and other is IBM Qiskit. Classical language Q # is used to program the quantum controller and its operations such that initializing a qubit, applying a gate on a qubit and measuring a qubit. IBM Qiskit programs simulates the functionality of quantum circuit and creates it’s drawing using a graphical interface with qubits, gates, and measurements. Qiskit provides simulators that run quantum circuits using visualization tools that help to understand the effect of our quantum circuits on the quantum states. The teleportation technique allows the quantum information to be communicated at a distance. An unbreakable encryption protocol is built for polarizing photons through the quantum channel. The combination of quantum computing and AI has the potential to drive significant advances across many sectors.
Quantum computing has in recent years evolved from a purely theoretical field to an active area in both academia and industry. As a result, Quantum Software Engineering has emerged as an area that aims to organize the process of building, testing, and running quantum software. However, writing quantum software still requires programming with quantum gates and qubits, as well as knowledge specific to quantum software frameworks such as Qiskit, Cirq, Qrisp, pyQuil and PennyLane, each of which reaches quantum hardware through its own toolchain. We present Quanifi, which packages the high-level routines of these frameworks as components on the Apache NiFi dataflow canvas. The components exchange circuits as OpenQASM 2.0, so a circuit built by one framework can be executed by another. This allows for two types of redundancy: several frameworks implement the same algorithm, and several engines (simulators or real hardware) execute the same circuit. We describe N×M program execution, which crosses the two: a single NiFi flow runs each of the N implementations on each of the M engines, and because every result is labelled with its implementation and its engine, a disagreement can be linked to an implementation, to an engine, or to a single implementation-engine pair. We ran Grover's algorithm built by three frameworks on three quantum computers from IBM, IQM and Quantum Inspire, and a matrix of three adder builders on one IQM device reached through two routes. N×M execution helped us discover three real defects: an incorrect gate-set declaration in the Quantum Inspire adapter, execution consistent with negated Rx angles on Tuna-17, and circuit modification through Open Quantum. The latter two returned wrong answers without reporting an error. We reported all three defects and Open Quantum's provider confirmed and fixed its QASM parsing defect.