Quantum Information Processing最新文献

We propose the scheme realizing the two-level control over the unitary operators (U_k) creating the required quantum state of the system S. These operators are controlled by the superposition state of the auxiliary subsystem R which is governed by two control centers. The first-level control center (main control) creates the equal-probability pure state of R with certain distribution of phase factors that, in turn, govern the power of the second-level control center C that applies the special V-operators to the same subsystem R changing its state and thus controlling the applicability of (U_k). In addition, the above phases are responsible for the entanglement in the subsystem R. We find the direct relation between this entanglement and the number of operators (U_k) that can be controlled by C. The simple example of a two-level control system governing the creation of entangled state of the two-qubit system S is presented.

In the 1970s, Wiesner introduced the concept of quantum money, where quantum states serve as currency, offering physical-level unforgeability through quantum mechanics. Yet, traditional proposals often unrealistically assume personal quantum computing access for each user. To address these issues, we propose a cloud-based semi-quantum money (CSQM) scheme. This approach only requires semi-honest third-party quantum clouds, while the rest of the system, including transactions and banks, remains fully classical. We also estimate the computational power required by the quantum cloud and provide a thorough security analysis. Our approach significantly reduces the quantum resource demands on local users and facilitates seamless integration with current classical systems.

The rapid advancement of quantum neural networks has led to the application of a range of quantum machine learning algorithms, such as the hybrid quantum convolutional neural network (HQCNN), in various data processing tasks. To further enhance the convergence rate and accuracy of learning from a small number of samples, we introduce a novel model called quantum residual attention neural network (QRANN), which incorporates a quantum residual attention layer (QRAL) to reduce the depth of the quantum circuit and the number of trained parameters. The benefits of this new model are demonstrated through its application to the efficient prediction of material properties based on component optimization. Specifically, we conducted numerical experiments using publicly available alloy material datasets from a hackathon competition to predict the properties of alloy materials based on their composition. The results indicate that the proposed QRANN algorithm exhibits superior performance in terms of training convergence speed, prediction accuracy, and generalization ability compared to HQCNN, QSANN, variational quantum regression (VQR) algorithm, and classical multilayer perceptron. This suggests that QRANN is particularly well-suited for learning from limited datasets. Notably, by introducing a fully parameterized QRAL, QRANN can be implemented with fewer parameters and a lower circuit depth compared to HQCNN, using approximately only 74% and 58% of the parameters and circuit depth used in HQCNN experiments, respectively. Therefore, the proposed algorithm can be feasibly realized using current noisy intermediate-scale quantum devices.

Feistel structure is a fundamental symmetric cryptographic primitive. In this paper, we investigate the security of 5-round Feistel structure and generalized Feistel scheme (GFS) in a quantum environment and propose a family of quantum claw-finding attacks in both Q1 and Q2 models. The quantum attack uses claw-finding algorithm with the period function’s approximate promise. By employing the constructed functions g and h as inputs for claw-finding algorithm, secret information can be extracted. The attack on 5-round Feistel structure in Q1 model, which is easier to implement than Q2 model, enriched the diversity of the attack scenarios. The attacks on 5-round Feistel structure, Type-I, Type-II, and Type-III GFS in Q2 model, exhibit an exponentially lower product indicator for quantum and classical query complexity. The strongest reduction occurs in attacks on Type-I and Type-II GFS, decreasing from (2^{4n}) to (2^{2n}).

In this paper, we show how to construct XX Hamiltonians that realize perfect quantum state transfer and also have the property that the overlap of the time evolved state with the initial state is zero for some time before the transfer time. If the latter takes place, we call it an early exclusion state. We also show that in some cases, early state exclusion is impossible. The proofs rely on properties of Krawtchouk and Chebyshev polynomials.

We present how the mechanisms of quantum Darwinism allow for information leakage in the standard BB84 quantum key distribution protocol, a paradigmatic prepare-and-measure quantum cryptography scenario. We work within the decoherence theory framework and employ the model of measurements provided by quantum Darwinism. We investigate how much of the information about the results crucial for the cryptographic key to be kept secret is leaked during the quantum measurement process and subsequently how much of that information might be later obtained by an eavesdropper using a type of so-called Van Eck side-channel wiretapping. We also show how security can be affected by different ways of organizing the surrounding environment into layers, e.g., rooms or other divisions affecting the spread of quantum information in the environment and its interaction, paving a venue for potential enhancements, and insight into proper engineering of shieldings for cryptographical devices.

Trotter product formulas constitute a cornerstone quantum Hamiltonian simulation technique. However, the efficient implementation of Hamiltonian evolution of nested commutators remains an under explored area. In this work, we construct optimized product formulas of orders 3–6 approximating the exponential of a commutator of two arbitrary operators in terms of the exponentials of the operators involved. The new schemes require a reduced number of exponentials and thus provide more efficient approximations than other previously published alternatives. They can also be used as basic methods in recursive procedures to increase the order of approximation. We expect this research will improve the efficiency of quantum control protocols, as well as quantum algorithms such as the Zassenhaus-based product formula, Magnus operator-based time-dependent simulation, and product formula schemes with modified potentials.

Let (R_{q,v}={mathbb {F}}_q+v{mathbb {F}}_q+ v^2{mathbb {F}}_q) where q is an odd prime power and (v^3=v). In this paper, we first provide structures of the Euclidean sums and hulls of cyclic codes of length n over (R_{q,v}). Then, we exhibit a method of constructing new quantum error-correcting (abbreviated to QEC) codes via the Euclidean sums of cyclic codes over (R_{q,v}) and CSS constructions. Finally, we construct two new classes of entanglement-assisted quantum error-correcting (abbreviated to EAQEC) codes by means of the Euclidean hulls of cyclic codes of length n over (R_{q,v}). In addition, to enrich the variety of available QEC and EAQEC codes, many new QEC and EAQEC codes are constructed to illustrate our results.

In recent years, variational quantum circuits (VQCs) have been widely explored to advance quantum circuits against classic models on various domains, such as quantum chemistry and quantum machine learning. Similar to classic machine-learning models, VQCs can be trained through various optimization approaches, such as gradient-based or gradient-free methods. However, when employing gradient-based methods, the gradient variance of VQCs may dramatically vanish as the number of qubits or layers increases. This issue, a.k.a. barren plateaus (BPs), seriously hinders the scaling of VQCs on large datasets. To mitigate the barren plateaus, extensive efforts have been devoted to tackling this issue through diverse strategies. In this survey, we conduct a systematic literature review of recent works from both investigation and mitigation perspectives. Furthermore, we propose a new taxonomy to categorize most existing mitigation strategies into five groups and introduce them in detail. Also, we compare the concurrent survey papers about BPs. Finally, we provide insightful discussion on future directions for BPs.

Continuous variable-based quantum cryptography (CV-QKD) is an emerging field in quantum information science, offering unprecedented security for communication protocols by harnessing the principles of quantum mechanics. However, ocean environments pose unique challenges to quantum communication due to their distinct properties and characteristics. This work investigates the impact of turbulence on the transmission of Gaussian light beams used in a continuous variable-based quantum key distribution system for underwater quantum communication. The objective is to quantitatively analyze the induced losses and propose methodologies to mitigate their effects. To achieve this, we adopt the widely accepted ABCD matrix formalism, which provides a comprehensive framework for characterizing the propagation of optical beams through different media. Moreover, a numerical simulation framework is developed to assess the resulting losses and evaluate the performance of the proposed system. The implications of these numerical simulation frameworks for the design and optimization of quantum communication systems for oceanic environments are thoroughly discussed.