Quantum Information Processing最新文献

The U-Net architecture is widely recognized as one of the most prominent models for medical image segmentation, comprising an encoder and a decoder. The encoder is crucial for extracting image features to enhance segmentation accuracy, typically incorporating convolutional and pooling layers. However, standard encoder structures often miss some classical features and struggle to extract high-level features effectively. In this paper, a hybrid quantum-classical neural network (QC-Net) model with a novel encoder is proposed, aiming to capture more representative features. Our encoder features a residual convolutional block (RCB) to primarily extract some missed features, and then, efficient channel attention (ECA) is employed into the output feature maps after the RCB and pooling operations to handle more complex and noisy information. Consequently, a two-qubit parameterized circuit is devised to capture the final output features of the encoder, aiming to further capture the hidden high-level features from the quantum dimension. The decoder incorporates a joint attention mechanism and deconvolution operations to recover the spatial resolution and detail information of the original input image. To validate its efficacy, we conduct skin lesion segmentation experiments utilizing the ISIC2018 dataset. Notably, our QC-Net model outperforms both U-Net and CA-Net, achieving an average Dice coefficient of 93.2%, indicating improvements of 5.43% and 1.12%, respectively. These results underscore the outstanding performance of our proposed QC-Net model.

The states of a three-mode bosonic system with the restricted Hilbert space are discussed in the context of quantum entanglement and squeezing of quantum fluctuations. The states exhibiting nonzero tripartite entanglement are considered. Mutual relations between the two- and three-mode entanglement quantified by the corresponding negativities and the squeezing described by the corresponding principal squeeze variances are revealed. Entangled three-qubit states exhibiting squeezing are identified.

Quantum annealers are presented as quantum computers that can, with a high probability, optimize certain quadratic functions on Boolean variables in constant time. These functions are basically the Hamiltonian of Ising models that reach the ground energy state with a high probability after an annealing process. In some preliminary works, they have been proposed as a way to solve SAT. These Hamiltonians can be seen as Max2XOR problems, i.e., as the problem of finding an assignment that maximizes the number of XOR clauses of at most two variables that are satisfied. In this paper, we focus on introducing several gadgets to reduce SAT to Max2XOR. We show how they can be used to translate SAT instances to initial configurations of a quantum annealer.

The ability to implement arbitrary unitary operations is essential for quantum information processing, since the evolution of closed quantum systems is governed by unitary dynamics. Conventional methods typically approximate the target evolution by optimizing sequences of fixed single- and two-qubit gates, which often leads to deep circuits and the accumulation of approximation errors. Here, we propose an exact and analytical method for implementing arbitrary unitary operations using discrete-time quantum walks. Specifically, an arbitrary N-dimensional unitary operation U(N) is constructed through a sequence of position-dependent U(2) coin operations and conditional shift operators, requiring only N steps (or (N+1) for odd dimensions) for exact realization. We further present a feasible photonic implementation, where coin and position states are encoded in the polarization and spatial modes of single photons. Numerical simulations confirm the scalability and noise resilience of the approach, demonstrating its advantages for realization of arbitrary unitary operations. Our results thus provide a practical route to realizing arbitrary unitary transformations with reduced resource requirements and enhanced robustness against optical losses and phase instability.

In this paper, the CHSH quantum game is extended to four players. This is achieved by exploring all possible 4-variable Boolean functions to identify those that yield a game scenario with a quantum advantage using a specific entangled state. Notably, two new four-player quantum games are presented. In one game, the optimal quantum strategy is achieved when players share a (vert {GHZ_4} rangle =dfrac{1}{sqrt{2}}(vert {0000} rangle +vert {1111} rangle )) state, breaking the traditional 10% gain observed in 2- and 3-qubit CHSH games and achieving a 22.5% gap. In the other game, players gain a greater advantage using a (vert {W_4} rangle =dfrac{1}{2}(vert {0001} rangle +vert {0010} rangle +vert {0100} rangle +vert {1000} rangle )) state as their quantum resource. Quantum games with other four-qubit entangled states are also explored. To demonstrate the results, these game scenarios are implemented on an online quantum computer, and the advantage of the respective quantum resource for each game is experimentally verified.

Authentication is a crucial service for securing communication, ensuring the authenticity of the parties by verifying their identities. With the rapid development of quantum computing, traditional quantum two-party authentication protocols are more likely to allow eavesdropper attacks to succeed, mainly because they rely solely on the security of the quantum channel and the integrity of the pre-shared key. This study presents a new identity authentication scheme based on single-photon semi-quantum authentication. Unlike traditional tree structures, the scheme adopts a structure and introduces a trusted third party, who holds the keys of all participants. Participants encrypt information from the third party using their own keys combined with bubble operations, and the third party decrypts it to complete the authentication process. This scheme supports authentication for n participants, improves efficiency by simplifying the process, and leverages the unique properties of single-photon technology to protect semi-quantum key distribution and secret sharing. Compared to existing schemes, our scheme offers higher security against simulation, man-in-the-middle, and eavesdropping attacks. Additionally, as it does not rely on complex quantum technologies, it required minimal quantum resources and reduced participant capabilities, enhancing its practical implement ability.

To understand the properties and interactions of materials, determining the ground-state energies is one of the important challenges in quantum chemistry, materials science, and quantum mechanics, where quantum computing can play an important role for studying the properties of materials. In this study, we have explored the quantum processor application to compute the He atom ground-state energy which utilizes the Variational Quantum Eigensolver (VQE) algorithm. In here, we have developed and tested a VQE algorithm tailored for a photonic quantum processor, optimizing a parameterized quantum circuit to minimize the energy expectation value of the He atom’s Hamiltonian on the four-qubit processor by using the Qiskit Aer simulator. The obtained results of this work show a significant improvement in accuracy compared to classical computational methods, such as Hartree–Fock and density functional theory, which demonstrate the compute potential of quantum algorithms in quantum many-body problems. Thus, these results demonstrate the advantages of quantum computing in achieving high accuracy in simulations of molecular and material properties and pave the way for future applications in more complex systems. This work highlights the potential of quantum processors in the fields of quantum chemistry, computational physics, and data science.

Quantum communication is evolving as the next generation of secret sharing technology. Compared to the rapid development in bipartite quantum communications, multipartite quantum network still awaits significant improvements in transmission distances, covering areas, and number of users. Current fiber-based quantum networks are challenged by preparing multi-particle entangled states and the high loss of fiber links. Inspired by the source-independent quantum conference key agreement based on Bell states and the satellite-to-ground transmission links, we proposed two satellite-based quantum network architectures, including up-links and down-links. The simulated key rates are maintained when the number of users increases for both two proposed architectures. The down-link architecture ensures a secure key rate exceeding (10^{-7}) bit/pulse even over a distance of 1000 km. Our work offers viable solutions and quantitative references toward realizing scalable satellite-based secure quantum communication networks.

To reduce the number of basis gates after quantum circuit decomposition, enhance overall fidelity, and improve the expressivity of complex quantum programs, this paper proposes a quantum circuit parameterized decomposition method based on local synthesis (PDBLS). Prior to decomposition, local synthesis is applied to analyze and optimize the circuit structure by formally defining and automatically collecting “compressible blocks”, while also generating new compressible blocks through gate-exchange reordering, thereby reducing the number of basis gates requiring decomposition. At the theoretical level, within the Weyl chamber framework, we provide a rigorous proof showing that the optimal number of basis gates required for decomposing a two-qubit gate (2Q) corresponds exactly to the coverage layer in which its Weyl chamber coordinate lies. In the decomposition stage, we introduce a parameterized decomposition template alternating basis gates with U3 gates, combined with a cost function defined by decomposition fidelity and hardware fidelity, as well as a layer-by-layer deepening strategy with L-BFGS optimization, ensuring minimum basis gate usage while maintaining target fidelity. Experimental results demonstrate that PDBLS significantly reduces the number of 2Q basis gates across various benchmark circuits and gate sets, showing advantages under both exact and approximate decomposition conditions, and exhibiting strong scalability on large-scale circuits.

The problem of quantum state estimation is crucial in the development of quantum technologies. In particular, the use of symmetric quantum states is useful in many relevant applications. In this work, we analyze the task of reconstructing the density matrices of symmetric quantum states generated by a quantum processor. For this purpose, we take advantage of an estimation technique that results to be equivalent to the quantum maximum entropy (MaxEnt) estimation, and which was recently adapted to quantum states with arbitrary symmetries. The smart use of prior knowledge of the quantum state symmetries allows for a reduction in both, the number of measurements that need to be made on the system, and the size of the computational problem to store and process the data, resulting in a better overall performance of the estimator as well. After performing numerical simulations, we implement some examples of symmetric states in IonQ quantum processors, and estimate them using the proposed technique. The results are in good agreement with numerical simulations, showing that the proposed method is a good estimator that allows to save both, experimental and computational resources.