Abstract The use of quantum entanglement has garnered increasing attention among researchers in recent years due to its wide range of applications, not only revolutionizing the field of information processing but also enhancing quantum-safe communications. Identifying the degree of entanglement present in quantum states is a crucial focus, and designing an algorithm capable of feasibly measuring entanglement is imperative. While theoretical calculations hold high regard, the ease of implementing these algorithms in a laboratory setting is essential to gauge their efficiency.In this context, IBM quantum computers stand out as discrete value NISQ (Noisy Intermediate-Scale Quantum) platforms These platforms are based on superconducting qubits, providing an opportunity to test our algorithms without the need for extravagant laboratory equipment. This paper proposes an algorithm designed to measure entanglement in a bipartite system. We will execute the algorithm on IBM’s 127-qubit backends to compare our calculations with real-world results. Furthermore, we aim to address and mitigate errors inherent in these devices by utilizing local mitigation technique available in the IBM Experiments Python package, aiming for more accurate and reliable outcomes.
Abstract The use of quantum entanglement has garnered increasing attention among researchers in recent years due to its wide range of applications, not only revolutionizing the field of information processing but also enhancing quantum-safe communications. Identifying the degree of entanglement present in quantum states is a crucial focus, and designing an algorithm capable of feasibly measuring entanglement is imperative. While theoretical calculations hold high regard, the ease of implementing these algorithms in a laboratory setting is essential to gauge their efficiency.In this context, IBM quantum computers stand out as discrete value NISQ (Noisy Intermediate-Scale Quantum) platforms These platforms are based on superconducting qubits, providing an opportunity to test our algorithms without the need for extravagant laboratory equipment. This paper proposes an algorithm designed to measure entanglement in a bipartite system. We will execute the algorithm on IBM’s 127-qubit backends to compare our calculations with real-world results. Furthermore, we aim to address and mitigate errors inherent in these devices by utilizing local mitigation technique available in the IBM Experiments Python package, aiming for more accurate and reliable outcomes.
Abstract As quantum computing technology slowly matures and the number of available qubits on a QPU gradually increases, interest in assessing the capabilities of quantum computing hardware in a scalable manner is growing. One of the key properties for quantum computing is the ability to generate multipartite entangled states. In this study, aspects of benchmarking entanglement generation capabilities of noisy intermediate‐scale quantum (NISQ) devices are discussed based on the preparation of graph states and the verification of entanglement in the prepared states. Thereby, entanglement witnesses that are specifically suited for a scalable experiment design are used. This choice of entanglement witnesses can detect A) bipartite entanglement and B) genuine multipartite entanglement for graph states with constant two measurement settings if the prepared graph state is based on a two‐colorable graph, e.g., a square grid graph or one of its subgraphs. With this, it is experimentally verified that a bipartite entangled state comprising all qubits can be prepared on a 127‐qubit IBM Quantum superconducting QPU, and genuine multipartite entanglement can be detected for states of up to 23 qubits with quantum readout error mitigation.
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.
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.
This paper investigates the critical role of entanglement entropy measurement in advancing quantum computing. We propose a novel methodology for precisely quantifying entanglement entropy within quantum systems, recognizing its significance as a key performance indicator for assessing both the quality and scalability of quantum algorithms and hardware. The core of the work focuses on developing a high-precision and efficient measurement technique, addressing the current limitations in entanglement entropy characterization. Specifically, we explore methods for minimizing measurement errors and maximizing the information obtained from entanglement entropy measurements. The theoretical framework presented allows for a deeper understanding of how entanglement entropy relates to computational complexity and provides a basis for optimizing quantum algorithms and designing more robust quantum computing architectures. Ultimately, this research contributes to overcoming a significant bottleneck in the field and paves the way for practical, fault-tolerant quantum computation.
Abstract The practical application of Noisy Intermediate-Scale Quantum (NISQ) hardware is fundamentally limited by gate-level noise, which corrupts computational results. This research addresses this challenge through the development and validation of a modular software framework for Quantum Error Mitigation (QEM). We implement and compare two leading QEM strategies: Zero-Noise Extrapolation (ZNE) and Probabilistic Error Cancellation (PEC). The framework is built using the Qiskit library and is validated using a realistic, hardware-calibrated noisy simulator that mimics the error characteristics of a real IBM Quantum device. Our methodology focuses on a robust implementation of ZNE via unitary folding and a proof-of-concept demonstration of the PEC algorithm. The framework's effectiveness is demonstrated on a simulated noisy backend where, for a 3-qubit Greenberger-Horne-Zeilinger (GHZ) state, the baseline state fidelity was increased from 93.5% to 97.3% via ZNE, corresponding to a 59% reduction in the state's infidelity. This work provides a practical demonstration of how software-based error mitigation can enhance the reliability of quantum computations on current noisy hardware.
The paper is an elaborate comparative assessment of the most relevant entropy-based quantities to be applied in quantifying quantum entanglement in pure, mixed, bipartite, and multipartite quantum systems. The study fills the existing gap in the literature in which most of the previous literature examines individual measures, but a lot of knowledge is lacking on what these measures are regarding their strengths, weaknesses, and the operational usefulness against each other. The study can prove the behaviour of each measure under noise, decoherence, dimensional scaling, and variation of state-type by analysing von Neumann entropy, the Tsallis entropy, entropy of entanglement of formation, concurrence and logarithmic negativity. Numerical studies with pure two-qubit states, Werner states, GHZ states, W states and mixed random states demonstrate specific sensitivity properties and computational limitations which ensure that no single measure can be a universal quantifier. The paper goes on to say that entropy-only measures do not work in mixed regimes because of a dominance in classical correlations. The results have several important implications to quantum communication, quantum simulation, and quantum computing in the NISQ-era, where the choice of measurement has a direct impact on benchmarking, error-correction scheme, and protocol performance based on entanglement. The paper ends with a recommendation of contextual, purpose-based scheme of selecting entanglement measures and suggests a further study on scalable benchmarking, hybrid quantifiers, and operational performance-based entanglement measurements. These observations reinforce the theoretical premise of entanglement studies and enable the advancement of more effective quantum technologies in the field of practice.