Quantum Information Processing最新文献

Reference-frame-independent quantum key distribution (RFI-QKD) can generate secure keys between two remote peers with an unknown and slowly drifted reference frame. As an intrinsic characteristic of single-photon avalanche detectors, the afterpulse effect is often ignored in the simulation of the analytical model, which leads to a large deviation from the data obtained in practical RFI-QKD systems. Therefore, an afterpulse-compatible model should be adopted to fix this deviation. However, the afterpulse-compatible model results in a decline in the performance of RFI-QKD systems. To mitigate the performance decline of RFI-QKD under the afterpulse effect, we apply the advantage distillation (AD) method to enhance the secret key rate and the maximum transmission distance. Simulation results demonstrate that, without changing the optical hardware of RFI-QKD systems, the AD method can substantially improve the performance of RFI-QKD under the afterpulse effect.

In previous research on ghost imaging encoding transmission schemes, the influence of real transmission channels on the communication quality was weakened to some extent. Simultaneously, to ensure the imaging quality of the algorithm, it is often performed under full sampling or even supersampling, which undoubtedly requires a long sampling time. This paper proposes a ghost imaging reconstruction method that uses a generative adversarial network and Rayleigh fading channel. By introducing the channel transmission model (Rayleigh fading channel) in real scenes and the generative adversarial neural network model, the image is reconstructed under under-sampling and the imaging time is saved. To further explore how to improve the image transmission quality and reduce the channel interference as much as possible, this scheme provides a new imaging technology for the research of the image transmission field, which has good theoretical significance.

In many quantum algorithms, including Hamiltonian simulation, efficient quantum circuit implementation of diagonal unitary matrices is an important issue. For small unitary diagonal matrices, a method based on Walsh operators is known and allows an exact implementation. Whereas, as the matrix size increases, the required resources increase linearly regarding the matrix size, so an efficient approximate implementation is indispensable. In this study, we specify the approximation using piecewise polynomials when the diagonal unitary matrix is generated by a known underlying function. It accelerates the implementation by an exponential factor compared to the exact one. In more detail, we modify a previous method, which we call PPP (phase gate for piecewise-defined polynomial), and propose a novel one called LIU (linearly interpolated unitary diagonal matrix). By introducing a coarse-graining parameter, calculated from the underlying function and the desired error bound, we evaluate the explicit gate counts for different methods as functions of some norms of the given function, the grid parameter, and the allowable error. It helps us to figure out the efficient quantum circuits in practical settings of different grid parameters and error bounds, in addition to an asymptotic speedup when the grid parameter goes to infinity. As an application, we apply our method to the first-quantized Hamiltonian simulation and estimate the quantum resources (gate count and ancillary qubits). It reveals that the error coming from the approximation of the potential function is not negligible compared to the error from the Trotter-Suzuki formula.

The establishment of the global quantum communication network relies on the effective integration of free-space links and optical fiber networks. Mode-pairing quantum key distribution (MP-QKD) represents an advancement in measurement device-independent quantum key distribution (MDI-QKD). By eliminating the need for a complex light-field setup, it breaks the rate–distance limit and can be theoretically applied to the light-field setup of free-space MDI-QKD. In this work, we propose a mode-pairing quantum key distribution model that integrates satellite-based links and fiber links, and its performance is analyzed by simulating the probability distribution of atmospheric transmittance (PDT) between satellites and ground stations. Additionally, the effects of pairing interval and misalignment error are discussed. This work may provide some important references for the future widespread application of satellite-to-ground multipath quantum key distribution.

In this paper, we propose a lightweight quantum key distribution (QKD) protocol for two participants within a unidirectional quantum channel environment that inherently prevents Trojan horse attacks. Our protocol features a novel chain method for encoding and decoding single-photon sequences, thus addressing the common limitations of the traditional QKD protocol, which treats photons independently. A notable advantage of our approach is the simplification achieved by requiring only the disclosure of the first photon basis. Furthermore, our method significantly improves the detection rate of measure-resend attacks. When a single photon of a sequence of photons is attacked by an eavesdropper, the detection rate can reach nearly 16.67% if half of them are decoy photons, offering a 3% enhancement compared to protocols without the chain method. In cases where the entire sequence is attacked, checking just twelves photons can achieve a detection rate of 99%, which is five photons fewer than that required by traditional protocols without the chain method. In addition, a privacy amplification method is introduced for the QKD protocol by sharing a hash function, to maintain high efficiency while enhancing security, as a practical solution for quantum communication.

Twists are defects that are used to encode and process quantum information in topological codes like surface and color codes. Color codes can host three basic types of twists, namely charge-permuting, color-permuting, and domino twists. In this paper, we study domino twists from the viewpoint of computation. Specifically, we give a systematic construction for domino twists in qubit color codes. We also present protocols for measurement of logical qubits. Finally, we show that all Clifford gates can be implemented by braiding twists.

This review delves into quantum sensing from its foundational principles to transformative applications across various fields, encompassing a range of qubit systems such as spin chains, superconducting qubits, and NV centre ensembles. The complex interplay between quantum mechanics and macroscopic systems is explored, highlighting phenomena like quantum entanglement and Bell states. Key challenges, including decoherence and measurement noise, are addressed, providing insights into enhancing quantum sensing capabilities. A comparison of critical attributes for evaluating qubit performance across various quantum technologies and discussion on quantum noise mitigation techniques are provided.

Absolute separable (AS) quantum states are those states from which it is impossible to create entanglement, even under global unitary operations. It is known from the resource theory of non-absolute separability that the set of absolute separable states forms a convex and compact set, and global unitaries are free operations. We show that the action of a quantum switch controlled by an ancilla qubit over the global unitaries can break this robustness of AS states and produce ordinary separable states. First, we consider bipartite qubit systems and find the effect of quantum switch starting from the states sitting on the boundary of the set of absolute separable states . As particular examples, we illustrate what happens to modified Werner states and Bell diagonal (BD) states. For the Bell diagonal states, we provide the structure for the set of AS BD states and show how the structure changes under the influence of a switch. Further, we consider numerical generalization of the global unitary operations and show that it is always possible to take AS states out of the convex set under switching operations. We also generalized our results in higher dimensions.

A popular machine-learning model for regression tasks, including stock-market prediction, weather forecasting and real-estate pricing, is the classical support vector regression (SVR). However, a practically realisable quantum SVR remains to be formulated. We devise annealing-based algorithms, namely simulated and quantum-classical hybrid, for training two SVR models and compare their empirical performances against the SVR implementation of Python’s scikit-learn package for facial-landmark detection (FLD), a particular use case for SVR. Our method is to derive a quadratic-unconstrained-binary formulation for the optimisation problem used for training a SVR model and solve this problem using annealing. Using D-Wave’s hybrid solver, we construct a quantum-assisted SVR model, thereby demonstrating a slight advantage over classical models regarding FLD accuracy. Furthermore, we observe that annealing-based SVR models predict landmarks with lower variances compared to the SVR models trained by gradient-based methods. Our work is a proof-of-concept example for applying quantum-assisted SVR to a supervised-learning task with a small training dataset.

Quantum discord is an important measure of quantum correlations that goes beyond the paradigm of quantum entanglement. However, calculating quantum discord involves optimization over measurements, which is computationally challenging and often infeasible. This raises the intriguing question of Gaussian extremality—whether the quantum discord of a reference Gaussian state can provide a meaningful bound to the quantum discord of the original state. In this paper, we investigate this question by comparing the Gaussian discord of a reference Gaussian state with the quantum discord.