Abstract: We present an information-theoretic approach to quantum state classification based on sequential Bayesian inference. In each measurement step, the algorithm updates a probability distribution over candidate states by applying Bayes’ rule to the observed outcome. For each measurement shot on an unknown quantum state, the algorithm selects the observable with the highest expected information […]
Abstract: The process of reconstructing quantum states from experimental measurements, accomplished through quantum state tomography (QST), plays a crucial role in verifying and benchmarking quantum devices. A key challenge of QST is to find out how the accuracy of the reconstruction depends on the number of state copies used in the measurements. When multiple measurement […]
Abstract: Currently, the development of quantum computers is active; however, large-scale machines remain limited and noisy. Furthermore, such quantum computers do not allow direct access to state vectors, posing challenges for quantum algorithm development. Quantum circuit simulators on classical computers offer a solution, with decision diagram (DD)-based simulators being particularly memory-efficient for representing quantum states. […]
Abstract: The all-photonic quantum repeater scheme based on repeater graph states (RGSs) offers a promising approach for constructing quantum networks without relying on long-coherence-time quantum memories, which remain a significant technological challenge. Despite substantial progress in defining new schemes for generating RGSs, and in analyzing their performance for the task of secret key generation, the […]
Abstract: Stabilizer states, along with Clifford manipulations (unitary transformations and measurements) thereof—despite being efficiently simulable on a classical computer—are an important tool in quantum information processing, with applications to quantum computing, error correction, and networking. Graph states, defined on a graph, are a special class of stabilizer states that are central to measurement-based quantum computing, […]
Abstract: In this article, a robust output feedback reference quantum trajectory tracking control design is proposed through the simultaneous continuous weak measurement of noncommuting observables. Using the robust H∞ uncertainties-tolerant observer-based reference quantum trajectory tracking control (UTOBRQTTC) design strategy, the proposed method can robustly estimate the quantum trajectory and robustly track a sequence of any […]
Abstract: Image processing is one of the most promising applications for quantum machine learning. Quanvolutional neural networks with nontrainable parameters are the preferred solution to run on current and near future quantum devices. The typical input preprocessing pipeline for quanvolutional layers comprises of four steps: optional input binary quantization, encoding classical data into quantum states, […]
Abstract: Traditional many-body teleportation relies on the strong interaction property of a quantum many-body system, which usually requires numerous qubits and entanglement resources, making it difficult to realize experimentally. A natural scheme is to use a 1-D spin chain with simple structure to realize many-body teleportation. In this article, we analyze the conditions for general […]
Abstract: Quantum computing has emerged as an innovative computational paradigm with great potential in various domains. As quantum computing advances, the development of high-quality quantum programs has become crucial, making it essential to ensure their reliability. Software testing plays a vital role in achieving the reliability and quality of software systems. Various testing strategies and […]
Abstract: In quantum state discrimination, the design of measurement operators and probe states is typically formulated under the assumption that the set of possible states is perfectly known, but this may yield designs that are sensitive to deviations in the realized set of states. For example, the channel through which a transmitted state is sent […]