Abstract This practical guide introduces hands-on quantum computing, based on IBM Q learning resources. The exercises were completed by the author on April 28, 2024, using IBM Q cloud resources. The course provides a practical framework for understanding and experimenting with modern quantum computers, covering realistic use cases, circuit execution, and best practices for operating quantum processors with 100 or more qubits. Participants explore the concept of quantum usefulness, which refers to the practical utility of quantum computers in solving real-world problems, distinguishing it from quantum advantage, which is the point where quantum systems outperform classical computers on meaningful tasks. The course emphasizes that while classical computers remain highly powerful and adaptive, the evolving capabilities of quantum processors offer unique opportunities in computation that can complement classical methods. Hands-on exercises guide participants through practical aspects of designing and executing quantum circuits, running experiments on simulators and cloud-accessible quantum hardware, and interpreting results. This approach bridges theoretical knowledge with applied skills, enabling students and researchers to explore the current potential and limitations of quantum computing. The guide also contextualizes quantum computing within decades of classical computational development, highlighting how quantum devices may transform computational paradigms in fields such as optimization, chemistry, cryptography, and machine learning.
Abstract This practical guide introduces hands-on quantum computing, based on IBM Q learning resources. The exercises were completed by the author on April 28, 2024, using IBM Q cloud resources. The course provides a practical framework for understanding and experimenting with modern quantum computers, covering realistic use cases, circuit execution, and best practices for operating quantum processors with 100 or more qubits. Participants explore the concept of quantum usefulness, which refers to the practical utility of quantum computers in solving real-world problems, distinguishing it from quantum advantage, which is the point where quantum systems outperform classical computers on meaningful tasks. The course emphasizes that while classical computers remain highly powerful and adaptive, the evolving capabilities of quantum processors offer unique opportunities in computation that can complement classical methods. Hands-on exercises guide participants through practical aspects of designing and executing quantum circuits, running experiments on simulators and cloud-accessible quantum hardware, and interpreting results. This approach bridges theoretical knowledge with applied skills, enabling students and researchers to explore the current potential and limitations of quantum computing. The guide also contextualizes quantum computing within decades of classical computational development, highlighting how quantum devices may transform computational paradigms in fields such as optimization, chemistry, cryptography, and machine learning.
Abstract This practical guide presents hands-on laboratory exercises on variational quantum algorithms (VQAs) and hybrid quantum-classical workflows, based on the IBM Q learning platform. The work was performed by the author on April 28, 2024, using IBM Q cloud resources. Variational algorithms leverage the variational principle of quantum mechanics to optimize quantum circuits for specific tasks, making them particularly suitable for current noisy intermediate-scale quantum (NISQ) devices and offering a practical route toward achieving quantum advantage. The guide explores the full workflow for designing and implementing variational algorithms, highlighting the trade-offs inherent at each stage, including circuit design, parameter initialization, optimization strategies, and measurement post-processing. It also demonstrates the use of Qiskit Runtime primitives to enhance both the speed and accuracy of computations. Through these exercises, participants gain experience in constructing hybrid quantum-classical algorithms, performing parameter optimization, and interpreting results within the context of near-term quantum devices. While this guide focuses on practical implementation, it also encourages exploration of the underlying theoretical foundations of quantum information and computation, connecting applied algorithmic practice with fundamental principles. The course and exercises provide a structured starting point for researchers, developers, and students aiming to explore the utility of quantum computers for real-world problem solving, particularly in optimization, quantum chemistry, and machine learning applications.
Abstract This methodological guide provides a practical framework for performing laboratory work using quantum computers, adapted and translated from the laboratory exercises developed by the International Quantum Center at CERN, Switzerland. It represents the first set of quantum laboratory exercises fully adapted for Russian-speaking students and researchers. The guide is designed to support hands-on learning during the ongoing second quantum revolution, offering insight into quantum computing technologies with applications in both fundamental research and cybersecurity, particularly in the context of heightened geopolitical and cyber threats exploiting emerging quantum capabilities. The laboratory manual consists of eight exercises covering fundamental and advanced quantum protocols, including qubit manipulation, entanglement, quantum teleportation, Grover and Deutsch–Jozsa algorithms, BB84 quantum key distribution, CHSH game, and statistical sampling from random quantum circuits. Each exercise is structured to provide both theoretical understanding and practical implementation. To perform the laboratory exercises, the following prerequisites are required: Internet access on the student-user side. Creation of an account and registration with a cloud-based quantum computing service, such as IBM Quantum or the Russian Quantum Center platform. The methodology for completing the exercises follows a structured workflow: Preparatory stage – study the content, goals, and theoretical background of the laboratory work. Cloud connection – log in to the quantum computing cloud service using the personal account. Simulation stage – execute the laboratory circuit on a quantum computer simulator in the cloud service. Real hardware execution – run the equivalent circuit on an actual quantum processor. Data analysis – compare simulation and hardware results, analyze measurement outcomes, and identify deviations. Conclusion stage – summarize findings, verify learning objectives, and draw insights from experimental results. This guide provides a comprehensive, hands-on approach for students, researchers, and specialists in information security to gain practical experience with quantum computing, bridging theoretical concepts with experimental implementation.
Abstract This laboratory work provides a practical introduction to the use of a quantum computer, based on educational materials developed by the International Quantum Center at CERN (Switzerland). The objective of the first laboratory session is to familiarize users with the quantum computing environment, fundamental circuit construction, and the interaction between quantum and classical registers. In Laboratory Work No. 1, a basic quantum circuit is configured using the IBM Quantum cloud platform. The system consists of a single quantum bit (qubit), denoted as q0, and a single classical bit, denoted as c4. The experiment demonstrates the initialization of a qubit, the construction of a simple quantum circuit, and the measurement process that maps a quantum state onto a classical bit. Through this hands-on implementation, participants gain an operational understanding of quantum state preparation, measurement postulates, and the hybrid quantum-classical computational workflow. The guide emphasizes practical interaction with real quantum hardware and simulators, allowing users to observe probabilistic measurement outcomes and understand the physical interpretation of quantum superposition and state collapse. By bridging theoretical quantum mechanics and executable quantum circuits, this laboratory work lowers the barrier to entry for students and researchers transitioning from classical programming paradigms to quantum computation.
Abstract This practical guide focuses on the preparation and use of reference states in variational quantum algorithms (VQAs), based on IBM Q learning resources. The exercises were completed by the author on April 28, 2024, using IBM Q cloud resources. Reference states serve as an initial configuration of the quantum system that can improve convergence speed and stability in variational algorithms by providing a physically meaningful starting point for optimization. In this lesson, participants first learn to construct reference states manually, understanding how specific gate sequences and initializations encode desired quantum states. Subsequently, standard reference state configurations commonly used in VQAs are explored, demonstrating best practices for initializing circuits in practical hybrid quantum-classical workflows. The guide emphasizes how proper selection and implementation of reference states can reduce the number of optimization iterations and improve algorithmic performance on noisy intermediate-scale quantum (NISQ) devices. By combining theoretical explanation with hands-on exercises in Qiskit, participants gain practical experience in reference state design, initialization of quantum registers, and integration with variational circuits. This work provides foundational skills for building efficient variational algorithms applicable in quantum chemistry, combinatorial optimization, and machine learning tasks.
Abstract This practical guide explores the construction and application of ansätze and variational forms in variational quantum algorithms (VQAs), based on IBM Q learning resources. The exercises were performed by the author on May 1, 2024, using IBM Q cloud resources. Ansatz-based methods form the core of all variational algorithms, enabling the systematic exploration of parameterized quantum states to optimize a given objective function. In this lesson, participants first learn how to construct parameterized quantum circuits manually, defining the variational form that generates a family of quantum states suitable for optimization. These parameterized circuits are then applied to a previously prepared reference state, forming the ansatz that serves as the foundation for the variational algorithm. The guide emphasizes practical strategies for balancing computational speed and solution accuracy when exploring the parameter space, highlighting the trade-offs involved in designing efficient variational circuits. Through hands-on exercises in Qiskit, participants gain experience in circuit parameterization, application of ansätze to reference states, and iterative optimization. This approach demonstrates how variational forms enable flexible and scalable representations of quantum states, facilitating practical implementation of hybrid quantum-classical algorithms on noisy intermediate-scale quantum (NISQ) devices. The lesson provides foundational skills for constructing effective variational algorithms in quantum chemistry, combinatorial optimization, and machine learning applications, while reinforcing the conceptual understanding of parameterized quantum state spaces.
Abstract This practical guide provides an introduction to quantum-safe cryptography using IBM Q, based on the course Practical Introduction to Quantum-Safe Cryptography. It offers hands-on experience in applying quantum computing concepts to modern cryptographic challenges. The guide covers four key areas of cryptography: Cryptographic hash functions Symmetric-key cryptography Asymmetric-key cryptography Quantum-safe cryptography Through interactive examples and live coding exercises, developers gain insight into the evolving cybersecurity landscape in the quantum era, understanding how quantum computing impacts existing cryptographic schemes. The guide emphasizes practical steps to mitigate cryptographic risks and implement security strategies resilient against future quantum attacks. This resource bridges theoretical foundations with practical experimentation, equipping practitioners with the tools to design quantum-resilient applications and integrate quantum-safe practices into their software development workflows.