Entanglement, a phenomenon that has puzzled scientists since its discovery, has been extensively studied by many researchers through both theoretical and experimental aspect of both quantum information processing (QIP) and quantum mechanics (QM). But how can entanglement be most effectively taught to computer science students compared to applied physics students?. in this educational pursuit, we propose using Yao.jl, a quantum computing framework written in Julia for teaching entanglement to graduate computer science students attending a quantum computing class at Johns Hopkins University. David Mermin's just enough QM for them to understand and develop algorithms in quantum computation [Mer98, Mer03] idea aligns with the purpose of this work. Additionally, the authors of the study Improving students understanding of QM via the Stern-Gerlach experiment (SGE) argue that this experiment should be a key part of any QM education. Here, we explore the concept of entanglement and it's quantification in various quantum information processing experiments, including one inequality-free form of Bell's theorem: (1) Superposition via the Hadamard, (2) Bell-state generation and (3) GHZ state generation. The utilisation of circuit diagrams and code fragmentsis a central theme in this work's philosophy.
Entanglement, a phenomenon that has puzzled scientists since its discovery, has been extensively studied by many researchers through both theoretical and experimental aspect of both quantum information processing (QIP) and quantum mechanics (QM). But how can entanglement be most effectively taught to computer science students compared to applied physics students?. in this educational pursuit, we propose using Yao.jl, a quantum computing framework written in Julia for teaching entanglement to graduate computer science students attending a quantum computing class at Johns Hopkins University. David Mermin's just enough QM for them to understand and develop algorithms in quantum computation [Mer98, Mer03] idea aligns with the purpose of this work. Additionally, the authors of the study Improving students understanding of QM via the Stern-Gerlach experiment (SGE) argue that this experiment should be a key part of any QM education. Here, we explore the concept of entanglement and it's quantification in various quantum information processing experiments, including one inequality-free form of Bell's theorem: (1) Superposition via the Hadamard, (2) Bell-state generation and (3) GHZ state generation. The utilisation of circuit diagrams and code fragmentsis a central theme in this work's philosophy.
Abstract This laboratory work presents a practical introduction to the preparation and analysis of entangled quantum states (Bell pairs) using the Qiskit framework. The material is based on educational resources developed by the International Quantum Center at CERN (Switzerland) and is designed to provide hands-on experience with multi-qubit quantum circuits and entanglement generation. In Laboratory Work No. 3, participants construct and simulate a quantum circuit that prepares an entangled two-qubit state. As a representative example of multi-qubit operations in Qiskit, the circuit generates a Bell state by applying a Hadamard (H) gate to the first qubit q[0]q[0]q[0], followed by a controlled-NOT (CNOT) gate with q[0]q[0]q[0] as the control qubit and q[1]q[1]q[1] as the target qubit. This sequence creates a maximally entangled state, demonstrating the fundamental non-classical correlations characteristic of quantum systems. The laboratory exercise includes measurement operations applied to both qubits, illustrating how entanglement manifests in correlated classical outcomes. When the measurement operator is applied to the first qubit q[0]q[0]q[0], the corresponding classical bit records a definite value, and subsequent measurement of the second qubit q[1]q[1]q[1] yields a correlated result consistent with the structure of the Bell state. The probabilistic yet correlated outcomes provide direct evidence of quantum entanglement. The guide emphasizes the conceptual understanding of entanglement, circuit implementation in Qiskit, and the hybrid quantum-classical workflow underlying quantum computation. By bridging theoretical quantum mechanics with executable quantum circuits, this laboratory work enables students and researchers to experimentally explore one of the central phenomena of quantum information science using cloud-based quantum computing resources.
We present a practical course targeting graduate students with prior knowledge of the basics of quantum computing. The practical aims to deepen students' understanding of fundamental concepts in quantum computing by implementing quantum circuit simulators. Through hands-on experience, students learn about different methods to simulate quantum computing, including state vectors, density matrices, the stabilizer formalism, and matrix product states. By implementing the simulation methods themselves, students develop a more in-depth understanding of fundamental concepts in quantum computing, including superposition, entanglement, and the effects of noise on quantum systems. This hands-on experience prepares students to do research in the field of quantum computing and equips them with the knowledge and skills necessary to tackle complex research projects in the field. In this work, we describe our teaching approach and the structure of our practical, and we discuss evaluations and lessons learned.
Quantum computing education requires students to move beyond classical programming intuitions related to state, determinism, and debugging, and to develop reasoning skills grounded in probability, measurement, and interference. This paper reports on the design and delivery of a combined undergraduate and graduate course at Louisiana State University that employed a lab-integrated learning model to support conceptual change and progressive understanding. The course paired lectures with weekly programming labs that served as environments for experimentation and reflection. These labs enabled students to confront misconceptions and refine their mental models through direct observation and evidence-based reasoning. Instruction began with Quantum Without Linear Algebra (QWLA), which introduced core concepts such as superposition and entanglement through intuitive, dictionary representations. The course then transitioned to IBM Qiskit, which provided a professional framework for circuit design, noise simulation, and algorithm implementation. Analysis of student work and feedback indicated that hands-on experimentation improved confidence, conceptual clarity, and fluency across representations. At the same time, it revealed persistent challenges in debugging, reasoning about measurement, and understanding probabilistic outcomes. This paper presents the course structure, instructional strategies, and lessons learned, and argues that lab-integrated learning offers an effective and accessible approach to teaching quantum computing in computer science education.
Quantum computing will likely change our world as we know it today. In bringing together fields such as quantum mechanics, mathematics, and computer science in their construction and application, quantum computers hold a promise of tremendous increase in processing power when compared to present day technology. For an educator, teaching this topic requires that consideration be given to the fact that quantum computing is not only based on hard-to-teach aspects of physics, math, and computing, but that quantum computing itself is still in the early stages of its development. What is certain is that concepts such as Shor’s and Grover’s algorithms have already been developed specifically for use with quantum computing. Both algorithms are the beneficiaries of quantum properties such as superposition and entanglement which are at the core of the new technology. This paper is presented in a bottom up structure starting with the explanation of the basic component, the qubit, before moving to superposition and entanglement and ending with a lucid explanation of both of the algorithms. Due to the complex nature of the topic, teaching this subject requires that certain measures be taken to teach all students at all levels and have them feel comfortable within themselves about the topic. The course is meant for anyone who wants to learn quantum computing. It is furthermore recommended that those attending have a blank slate so we start with new students. We would like to see a variety of students taking and passing the course, with that in mind, the explanations of the topics are done without employing an excessive amount of math common to other courses in quantum computing. The recommended approach for teaching is through the use of videos and a curriculum which is broken down so topics are made more general and the discussion of that effort is the main focus
Quantum entanglement has gained significant attention in recent years owing to its diverse application in quantum informatics. Its nonlocal nature makes it a crucial resource in quantum information, especially in quantum communication and networking. Entanglement plays a vital role in advancing quantum computation and technology.This study discusses the creation of entangled quantum states using photon pairs and the measurement of entanglement, utilizing the IBM Q Experience the first industrial initiative to develop universal quantum computers and provide widespread access to these technologies through cloud platforms. The introduction of the Qiskit tool has enabled researchers, educators, developers, and enthusiasts to write code and conduct experiments on quantum machines. In this study, we implemented and tested circuits on the IBM Q quantum computing platform using Qiskit to execute quantum computing programs such as the Bell Inequality, CHSH Inequality, and Five-Qubit GHZ States, with two successful programming presented, these tools, along with the associated Jupyter Notebook pages, serve as additional resources for users of the IBM Q Experience. We present the results which will help evaluate these prototypes’ performance. Where quantum computers are designed to process information units that go beyond mere abstract mathematical entities, as suggested by Shannon’s theory; instead, they represent real physical objects defined by one of the two fundamental physical theories—quantum mechanics.
QUANTUM ENTANGLEMENT: THEORY, APPLICATIONS AND EMERGING TECHNOLOGIES provides a comprehensive introduction to one of the most fascinating and fundamental phenomena of quantum mechanics. The book explains the theoretical foundations of quantum entanglement, including quantum states, superposition, measurement, non-local correlations, Bell’s theorem, and the principles underlying entangled systems. It further examines important applications of entanglement in quantum computing, quantum communication, quantum cryptography, quantum teleportation, quantum sensing, and information processing. Special attention is given to emerging technologies and current research directions that are shaping the development of next-generation quantum systems. By connecting fundamental concepts with practical applications, the book helps readers understand both the scientific significance and technological potential of quantum entanglement. It is intended as a useful reference for students, researchers, educators, and readers interested in quantum science, information technology, and emerging quantum technologies.