EPJ Quantum Technology最新文献

Quantum information hiding, as an extension of classical information hiding techniques into the realm of quantum information, currently focuses on embedding classical bits (0/1) within quantum carriers. This includes methods such as disguising classical secret information as channel noise and embedding it within quantum error correction codes. However, the embedding mechanism for arbitrary quantum states (alpha |0rangle + beta |1rangle ) is still in the exploratory stage. This paper proposes an innovative framework that leverages the redundant space of quantum error correction codes to construct a nonlinear decoding architecture with quantum neural networks. This approach simultaneously achieves both carrier state error correction and secret state embedding and extraction functions. Specifically, the [5,1,3] stabilizer code is used as the carrier, with secret state embedding achieved through single-qubit substitution, and a quantum autoencoder is designed for steganographic state information decoding. The proposed framework features fully quantum-based input/output systems, overcoming the limitations of traditional variational quantum circuits that rely on probabilistic measurements for output generation. By performing full ground-state measurements at the autoencoder bottleneck layer and optimizing the parallel sub-network architecture, the network achieves efficient convergence and effective extraction of single-copy quantum states. Experimental results show that under the conditions of optimized parameters and data size of 20, the training losses for the carrier and secret states are 0.03 and 0.08, respectively, with test fidelities of 0.92 and 0.93. For a data size of 50, the secret states recovery fidelity exceeds 0.87. KS test analysis indicates that the full ground-state measurement and parallel sub-network are key strategies for achieving network performance. Equivalent error analysis shows that this approach successfully utilizes the potential redundant space of quantum error correction codes, providing new research directions for quantum state information hiding.

Two sets of quantum entangled states that are equivalent under local unitary transformations may exhibit identical effectiveness and versatility in various quantum information processing tasks. Consequently, classification under local unitary transformations has become a fundamental issue in the theory of quantum entanglement. The primary objective of this work is to establish a practical LU-classification for all sets of (l (geq 2)) generalized Bell states (GBSs), high-dimensional generalizations of Bell states, in a bipartite system (mathbb{C}^{d}otimes mathbb{C}^{d}) with (dgeq 3). Based on this classification, we determine the minimal cardinality of indistinguishable GBS sets in (mathbb{C}^{6}otimes mathbb{C}^{6}) under one-way local operations and classical communication (one-way LOCC). We first propose two classification methods based on LU-equivalence for all sets of l GBSs (l-GBS sets). We then establish LU-classification for all 2-GBS, 3-GBS, 4-GBS and 5-GBS sets in (mathbb{C}^{6}otimes mathbb{C}^{6}). Since LU-equivalent sets share identical local distinguishability, it suffices to examine representative GBS sets from equivalent classes. Notably, we identify a one-way LOCC indistinguishable 4-GBS set among these representatives, thereby resolving the case of (d = 6) for the problem of determining the minimum cardinality of one-way LOCC indistinguishable GBS sets in (Yuan et al. in Quantum Inf Process. 18:145, 2019) or (Zhang et al. in Phys Rev A 91:012329, 2015).

Photoluminescent point defects, such as nitrogen vacancy (NV) color centers in diamond, have attracted much attention as solid-state qubits. In recent years, a method has been developed to dope ions one-by-one into a solid substrate with Ångström position accuracy using a Paul trap. However, the dopant atoms must be laser-cooled, and the atoms that are promising dopants for solid-state quantum devices, such as nitrogen, cannot be directly applied. In the previous studies, the cooling of the dopant ions has been achieved using a sympathetic cooling technique, in which the laser-cooled atoms are sandwiched, but this method has several problems such as the need for a mechanism to remove the laser-cooled atoms and the inability to distinguish between the dopant atoms and contaminations. We show that these problems can be overcome by directly cooling the hydrogenated ions instead of sympathetically cooling the ions, and the position accuracy can be improved.

The quantum measurement of the microwave electric field based on Rydberg atoms developed in recent years has shown promise for enhancing accuracy, sensitivity and stability. However, the study of ultra-low frequency electric field measurements in power systems is still in its early stages, presenting new challenges for Rydberg-based measurement techniques. In this work, a ladder-type two-photon three-level structure of Cs atoms is selected, and the corresponding experimental system is constructed. Two kinds of laser control schemes, which are referred to as mismatch and match measurement schemes, are then proposed, and the quantum effect’s optical spectrum is obtained by using the two measurement schemes. After these measured spectral properties are compared, the match measurement scheme is chosen for real-time measurement of ultra-low frequency electric fields. Additionally, dynamic models of the interactions among the laser field, ultra-low frequency electric field and atoms are derived, on the basis of which theoretical simulations are being conducted to study the effects of the input parameters of the electric field and laser power on the optical spectrum. On the basis of the optical spectral features, an inversion method for the excitation electric field in real time is proposed, and its effectiveness is demonstrated.

AC susceptometry, unlike static susceptometry, offers a deeper insight into magnetic materials. By employing AC susceptibility measurements, one can glean into crucial details regarding magnetic dynamics. Nevertheless, traditional AC susceptometers are constrained to measuring changes in magnetic moments within the range of a few nano-joules per tesla. Additionally, their spatial resolution is severely limited, confining their application to bulk samples only. In this study, we introduce the utilization of a Nitrogen Vacancy (NV) center-based quantum diamond microscope for mapping the magnetic fields resulting from micron-scale ferromagnetic samples under an AC drive field, which can be used for determining AC susceptibility with sufficient additional information about the sample. By employing coherent pulse sequences, we extract the in-phase component of the sample magnetic field from samples within a field of view spanning 70 micro-meters while achieving a resolution of 1 micro-meter. Furthermore, we quantify changes in dipole moment on the order of a femto-joules per tesla induced by excitations at frequencies reaching several hundred kilohertz.

Advancements in quantum computing pose a significant threat to most of the cryptography currently deployed in our communication networks. Fortunately, cryptographic building blocks to mitigate this threat are already available; mostly based on Post-Quantum Cryptography (PQC) and Quantum Key Distribution (QKD), but also on symmetric cryptography techniques. Notably, those building blocks must be deployed as soon as possible in communication networks due to the “harvest-now decrypt-later” attack scenario, which is already challenging our sensitive and encrypted data today.

Following an agile and defense-in-depth approach, Hybrid Authenticated Key-Exchange (HAKE) protocols have recently been gaining significant attention. Such protocols have the benefit of modularly combining classical (symmetric) cryptography, PQC, and QKD to achieve strong confidentiality, authenticity, and integrity guarantees for network channels. Unfortunately, only a few protocols have yet been proposed (mainly Muckle and Muckle+) with different flexibility guarantees.

Looking at available standards in the network domain – especially at the Media Access Control Security (MACsec) standard – we believe that HAKE protocols could already bring strong security benefits to MACsec today. MACsec is a standard designed to secure communication at the data link layer in Ethernet networks by providing confidentiality, authenticity, and integrity for all traffic between trusted nodes. In addition, it establishes secure channels within a Local Area Network (LAN), ensuring that data remain protected from eavesdropping, tampering, and unauthorized access, while operating transparently to higher layer protocols. Currently, MACsec does not offer enough protection against the aforementioned threats.

In this work, we tackle the challenge and propose a new versatile HAKE protocol, dubbed VMuckle, which is sufficiently flexible for use in MACsec. The use of VMuckle in MACsec provides LAN participants with quantum-safe hybrid key material to ensure secure communication even in the event of cryptographically relevant quantum computers.

While adders are required for many classical and quantum algorithms, nowadays’ single quantum computer implementations cannot handle the large qubit counts required in practical applications. Implementing a distributed approach is currently the only solution, but it poses the challenge of communication latency. This paper introduces a quantum distributed adder algorithm (QUDA) as a solution for many applications that require large qubit counts. QUDA offers a logarithmic number of instances of quantum data transfer for the addition of two numbers in comparison with existing solutions which are generally either based on ripple carry adders with a linear number of transmission rounds or attempt to distribute an existing monolithic circuit without specializing their techniques to adders. We include implementation details and the used testing methodology, showcasing the correctness and efficiency of the proposed algorithm.

In recent years, in the context of the rapid development of quantum computing technology, quantum attack methods such as Shor’s algorithm pose a serious threat to the traditional public key encryption system based on number-theoretic puzzles. Using the characteristics of quantum bits, this paper proposes a quantum grey-scale image encryption method based on alternating quantum random walk. Firstly, the quantum representation model is used to transform the image into a quantum state, and then the quantum key is generated by the alternating quantum random walk algorithm, and combined with the quantum gate operation for encrypting the grey-scale image data, which not only inherits the advantage of the anti-attack of the quantum computation, but also, through the quantum parallelism and the non-clonability, which solves the security and efficiency bottleneck of traditional image encryption in the quantum era and significantly improves the security of grey-scale image encryption. The algorithm proposed in this paper has been verified by simulation experiments, and the experimental results show that the method is excellent in encryption and decryption effects, and for the encrypted image, a number of performance analyses have been carried out, and the analysis results show that the proposed encryption method has a high degree of security, and it can effectively resist the statistical attack, noise attack, etc., and the distribution of the histogram of encrypted image is more uniform, the pixel correlation analysis is close to 1, and the information entropy is close to 7.999.

Various architectures have been proposed using a large array of semiconductor spin qubits with high-fidelity and high-speed gate operation. However, no quantum algorithm compilers have been developed which can compile quantum algorithms in a consistent manner for the various architectures, limiting the discussion on evaluating the efficiency of quantum algorithm implementation. Here, we propose Qubit Operation Orchestrator considering qubit Connectivity and Addressability Implementation (QOOCAI), a first quantum algorithm compiler designed for various architectures with semiconductor spin qubits. QOOCAI can compile quantum algorithms to various architectures with different qubit connectivity and addressability, which are important features that affect the efficiency of quantum algorithm implementation. Furthermore, we compile multiple quantum algorithms on different architectures with QOOCAI, showing that higher qubit connectivity and addressability make the algorithm implementation quantitatively more efficient. These findings are crucial for developing semiconductor spin qubit devices, highlighting QOOCAI’s potential for improving quantum algorithm implementation efficiency across diverse architectures.

Accurate amine property prediction is essential for optimizing CO₂ capture efficiency in post-combustion processes. Quantum machine learning (QML) can enhance predictive modeling by leveraging superposition, entanglement, and interference to capture complex correlations. In this study, we developed hybrid quantum neural networks (HQNN) to improve quantitative structure-property relationship (QSPR) modeling for CO₂-capturing amines. By integrating variational quantum regressors with classical multi-layer perceptrons and graph neural networks, quantum-enhanced performance was explored in physicochemical property prediction under noiseless conditions and robustness was evaluated against quantum hardware noise using IBM quantum systems. Our results showed that HQNNs improve predictive accuracy for key solvent properties, including basicity, viscosity, boiling point, melting point, and vapor pressure. The fine-tuned and frozen pre-trained HQNN models with 9 qubits consistently achieved the highest rankings, highlighting the benefits of integrating quantum layers with pre-trained classical models. Furthermore, simulations under hardware noise confirmed the robustness of HQNNs, maintaining predictive performance. Overall, these findings emphasize the potential of hybrid quantum-classical architectures in molecular modeling. As quantum hardware and QML algorithms continue to advance, practical quantum benefits in QSPR modeling and materials discovery are expected to become increasingly attainable, driven by improvements in quantum circuit design, noise mitigation, and scalable architectures.