With the development of quantum computing technology, the threat of quantum computing to classical cryptography has been significantly enhanced. Studying the impact of quantum computing on the security of classical cryptosystems is a research focus in the cryptographic community. Pseudorandom functions are fundamental building blocks in numerous cryptosystems and play a critical role in post-quantum cryptography. To the best of our knowledge, research on effective quantum attacks on pseudorandom functions remains limited in the noisy intermediate-scale quantum era. This paper proposes a distributed quantum key recovery attack on pseudorandom functions and designs the corresponding quantum circuit based on distributed quantum computing technology, Bernstein-Vazirani’s and Grover’s algorithms. The proposed attack is applied to two pseudorandom functions, pEDM and SoKAC. Compared with the existing attacks, the proposed attack has lower complexity and stronger robustness to circuit noise. The proposed attack can realize effective quantum key recovery and provide theoretical support for designing quantum secure pseudorandom functions.

Information reconciliation is a significant stage in continuous-variable quantum key distribution (CV-QKD) systems as it directly affects the performance of the CV-QKD systems including secret key rate and secure transmission distance. This paper proposes a multidimensional reconciliation scheme using deep learning in CV-QKD systems. Firstly, different neural networks are constructed to obtain the norm information. Secondly, a multidimensional reconciliation scheme with deep learning assisted norm information is proposed which no longer needs to transmit the norm information through the authenticated classical public channel. Finally, simulation results and performance analysis show that, compared with the traditional multidimensional reconciliation scheme, the multidimensional reconciliation scheme with deep learning assisted norm information can decrease the communication traffic to a certain extent.

In the conventional post-processing phase of Gaussian-modulated coherent state (GMCS) quantum key distribution (QKD) systems, the processes of information reconciliation (IR) and privacy amplification (PA) are typically carried out sequentially and separately. This approach incurs substantial computational complexity and may introduce potential security risks, such as key storage risks. In this paper, we propose a more efficient and secure post-processing scheme that integrates IR and PA into a single process by utilizing well-designed spinal codes. The proposed scheme significantly reduces computational complexity by employing the linear-complexity hash function instead of the superlinear complexity Toeplitz matrices used in conventional PA schemes, and effectively mitigates potential security risks associated with conducting IR and PA as separate processes. Experimental results show that the final secret key throughput of the proposed scheme is at least 250 times higher than that of the conventional PA scheme, with the improvement in throughput becoming even greater as the block lengths increase. More importantly, owing to the rateless property and the capacity-approaching performance of spinal codes, the GMCS QKD systems can achieve reconciliation efficiencies of higher than 97% across a broad range of signal-to-noise ratios from -22.5641 to 0.122 dB.

Photon subtraction (PS) can enhance entanglement, which, for pure states, induces a decrease in the purity of reduced states. In contrast, by analyzing the purities of Gaussian states before and after subtracting or adding a single photon, we prove that the purity of a Gaussian state can be increased by less than 20%. On the one hand, it reveals that PS and photon addition (PA) can reduce entanglement, and on the other hand, it shows that PS or PA can achieve a limited amount of Gaussian state purification. Through the analysis of several examples, we demonstrate the inherent mechanism and applicable scope of photon-subtraction-based purification. We further compare the performance between PS and PA for purifying single-mode Gaussian states, and analyze their capabilities in generating Wigner negativity within purification regimes. In a multimode system, we find that PS can simultaneously increase entanglement and purify some of the reduced states. These findings demonstrate the new application potential of PS and PA, specifically their capability to directly suppress Gaussian noise.

>Secret key rate(SKR) and transmission distance are critical performance metrics for continuous-variable quantum key distribution(CV-QKD) systems [1]. Reconciliation efficiency, a key parameter of the information reconciliation [2]procedure using error correction codes in CV-QKD postprocessing, directly impacts these two performance metrics.Specifically, higher reconciliation efficiency leads to a greater SKR and longer transmission distance. However, fluctuating signal-to-noise ratio(SNR) conditions in practical channels may degrade the reconciliation efficiency or impair the error correction performance [3].

Quantum watermarking can be used for image ownership protection. This paper proposes a quantum watermarking scheme based on Novel Enhanced Quantum Representation (NEQR), DNA encoding, and quantum error correction (QEC). First, XOR operations are performed between the watermark image and a DNA key sequence. Then, performing DNA addition between the resulting image and DNA key image, the encrypted watermark image is obtained. Using the quantum parity determination (QPD) method, the encrypted quantum watermark image is embedded into the least significant bit (LSB) of the carrier image. The quantum circuits for the scheme are also provided. In order to evaluate the effect of the scheme, the watermarking scheme is simulated using MATLAB. The simulation results show that the embedded watermark has good visual quality, and the PSNR of watermarked image is about 51 dB. When ‘salt and pepper’ noise with a density of 0.10 is added to the watermarked image, the PSNR for extracted watermark is 20.38 dB. When the cropping proportion is 50

In the continuous-variable quantum key distribution (CV-QKD) system, the secret key rate (SKR) and transmission distance are important factors to evaluate the quality of system. Numerical methods are commonly employed to compute SKR of QKD systems in practice, but it is difficult to find the optimal parameter to enhance SKR. In this paper, we propose a machine learning-based parameter optimization scheme of CV-QKD. The proposed scheme applies the genetic algorithm-back propagation neural network (GA-BPNN) to CV-QKD to learn the mapping relationship between SKR and modulation variance. According to the property that the mapping relationship is a concave function, the optimal modulation variance can be determined by bisection, and then SKR can be enhanced. Simulation results demonstrate that the proposed scheme can enhance SKR and transmission distance.

Quantum computing solutions are increasingly deployed in commercial environments through delegated computing, especially one of the most critical issues is to guarantee the confidentiality and proprietary of quantum implementations. Since the proposal of general-purpose indistinguishability obfuscation (iO) and functional encryption schemes, iO has emerged as a seemingly versatile cryptography primitive. Existing research on quantum indistinguishable obfuscation (QiO) primarily focuses on task-oriented, lacking solutions to general quantum computing. In this paper, we propose a scheme for constructing QiO via the equivalence of quantum circuits. It introduces the concept of quantum subpath sum equivalence, demonstrating that indistinguishability between two quantum circuits can be achieved by incremental changes in quantum subpaths. The restriction of security loss is solved by reducing the distinguisher to polynomial probability test. The scheme obfuscates the quantum implementation of classical functions in a path-sum specification, ensuring the indistinguishability between different quantum implementations. The results demonstrate the feasibility of indistinguishability obfuscation for general circuits and provide novel insights on intellectual property protection and secure delegated quantum computing.

Non-Hermitian skin effect (NHSE) is one of the most fundamental phenomena in non-Hermitian physics. It is established that 1D NHSE originates from the nontrivial spectral winding topology. However, the topological origin behind the higher-dimensional NHSE remains unclear, which poses a substantial challenge in constructing and manipulating high-dimensional NHSEs. Here, an intuitive bottom-to-top scheme to construct high-dimensional NHSEs is proposed, through assembling multiple independent 1D NHSEs. Not only the elusive high-dimensional NHSEs can be effectively predicted from the well-defined 1D spectral winding topologies, but also the high-dimensional generalized Brillouin zones can be directly synthesized from the 1D counterparts. As examples, two 2D nonreciprocal acoustic metamaterials are experimentally implemented to demonstrate highly controllable multi-polar NHSEs and hybrid skin-topological effects, where the sound fields can be frequency-selectively localized at any desired corners and boundaries. These results offer a practicable strategy for engineering high-dimensional NHSEs, which can boost advanced applications such as selective filters and directional amplifiers.

Information spreads in time. For example, correlations dissipate when the correlated system locally couples to a third party, such as the environment. This simple but important fact forms the known quantum data-processing inequality. Here we theoretically uncover the quantum fluctuation theorem behind the quantum informational inequality. The fluctuation theorem quantitatively predicts the statistics of the underlying stochastic quantum process. To fully capture the quantum nature, the fluctuation theorem established here is extended to the quasiprobability regime. We also experimentally apply an interference-based method to measure the amplitudes composing the quasiprobability and verify our established fluctuation theorem by the IBM quantum computer.

In distributed systems, Byzantine consensus serves as a practical approach to addressing the Byzantine general problem. Previous research has exploited quantum resources to develop quantum detectable Byzantine consensus protocols, aiming to surpass the 1/3 fault tolerance bound. However, these consensus protocols are designed under the assumption of secure channel. They ignored malicious participants’ attacks on the communication process. In this paper, we introduce a new quantum protocol for quantum Byzantine consensus utilizing the full quantum one-way function, which is the foundation for generating verification state in list distribution phase and secure message in agreement phase. By relying on the quantum circuit of the full quantum one-way function, the honest participants are able to reach consensus, while the malicious participants are effectively detected. In order to enhance the scalability of the proposed quantum Byzantine consensus protocol, we categorize the participants into three-member groups when the number of participants is n>3 . Meanwhile, the election of commander is introduced in agreement phase. In the proposed multi-party quantum Byzantine consensus protocol, the full quantum one-way function verifies the honesty of the participants in both list distribution phase and agreement phase. Security analysis demonstrates that the proposed multi-party quantum Byzantine consensus protocol is secure against quantum attacks and the dishonest behaviors of participants.

Electromyography (EMG) generated by human hand movements is usually used to decode different action types with high accuracy. However, the classifications of the gestures rarely consider the impact of force, and the estimation of the grasp force when performing natural grasping movements is so far overlooked. Decoding natural grasping movements and estimating the force generated by the associated movements can help patients to improve the accuracy of prosthesis control. This study mainly focused on two aspects: the classification of four natural grasping movements and the force estimation of these actions. For this purpose, we designed an experimental platform where subjects could perform four common natural grasping movements in daily life, including pinch, palmar, twist, and plug grasp, to complete target profiles. On the one hand, the results showed that, for natural grasping movements with different levels of force (three levels at 20, 50, and 80%), the average accuracy could reach from 91.43 to 97.33% under five classification schemes. On the other hand, the feasibility of force estimation for natural grasping movements was demonstrated. Furthermore, in the process of force estimation, we confirmed that the regression performance about plug grasp was the best, and the average R2 could reach 0.9082. Besides, we found that the regression results were affected by the speed of force application. These findings contribute to the natural control of myoelectric prosthesis and the EMG-based rehabilitation training system, improving the user’s experience and acceptance.

The well-known multidimensional reconciliation is a significant stage of a continuous-variable quantum key distribution (CVQKD) system, which uses $d$-dimensional rotations to build a virtual channel between authenticated parties, Alice and Bob. Generally, a block low-density parity-check code with a belief-propagation (BP) iterative decoding algorithm, which is optimized for an additive white Gaussian noise channel, is always used in multidimensional reconciliation for the CVQKD system. In this paper, we study the signal-to-noise ratio (SNR) of the virtual channel of multidimensional reconciliation in CVQKD and prove that the noise of the virtual channel follows the Student's $t$-distribution. Therefore, we propose a $t$-BP decoding algorithm, which can be better applied to multidimensional reconciliation. Simulation results show that the frame error rate (FER) with the proposed $t$-BP decoding algorithm is superior to that with the conventional BP decoding algorithm applied to multidimensional reconciliation. Subsequently, the FER improvement results in significant influence on reconciliation efficiency and secret key rate of the CVQKD system.

Kun Zhang, Jietai Jing1,3,4,5,∗ Nicolas Treps, and Mattia Walschaers2† State Key Laboratory of Precision Spectroscopy, Joint Institute of Advanced Science and Technology, School of Physics and Electronic Science, East China Normal University, Shanghai 200062, China Laboratoire Kastler Brossel, Sorbonne Université, CNRS, ENS-Université PSL, Collège de France, 4 place Jussieu, F-75252 Paris, France CAS Center for Excellence in Ultra-intense Laser Science, Shanghai 201800, China Department of Physics, Zhejiang University, Hangzhou 310027, China and Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, Shanxi 030006, China (Dated: March 17, 2021)

Due to the rapid development of quantum computing technology, encryption systems based on computational complexity are facing serious threats. Based on the fundamental theorem of quantum mechanics, continuous-variable quantum key distribution (CVQKD) has the property of physical absolute security and can effectively overcome the dependence of the current encryption system on the computational complexity. In this paper, we construct the spatially coupled (SC)-low-density parity-check (LDPC) codes and quasi-cyclic (QC)-LDPC codes by adopting the parity-check matrices of LDPC codes in the Advanced Television Systems Committee (ATSC) 3.0 standard as base matrices and introduce these codes for information reconciliation in the CVQKD system in order to improve the performance of reconciliation efficiency, and then make further improvements to final secret key rate and transmission distance. Simulation results show that the proposed LDPC codes can achieve reconciliation efficiency of higher than 0.96. Moreover, we can obtain a high final secret key rate and a long transmission distance through using our proposed LDPC codes for information reconciliation.

In this paper, we investigate the relationship of quantum teleportation in quantum information science and the Birman---Murakami---Wenzl (BMW) algebra in low-dimensional topology. For simplicity, we focus on the two spin-1/2 representation of the BMW algebra, which is generated by both the Temperley---Lieb projector and the Yang---Baxter gate. We describe quantum teleportation using the Temperley---Lieb projector and the Yang---Baxter gate, respectively, and study teleportation-based quantum computation using the Yang---Baxter gate. On the other hand, we exploit the extended Temperley---Lieb diagrammatical approach to clearly show that the tangle relations of the BMW algebra have a natural interpretation of quantum teleportation. Inspired by this interpretation, we construct a general representation of the tangle relations of the BMW algebra and obtain interesting representations of the BMW algebra. Therefore, our research sheds a light on a link between quantum information science and low-dimensional topology.

This paper focuses on the study of topological features in teleportation-based quantum computation and aims at presenting a detailed review on teleportation-based quantum computation (Gottesman and Chuang in Nature 402: 390, 1999 ). In the extended Temperley–Lieb diagrammatical approach, we clearly show that such topological features bring about the fault-tolerant construction of both universal quantum gates and four-partite entangled states more intuitive and simpler. Furthermore, we describe the Yang–Baxter gate by its extended Temperley–Lieb configuration and then study teleportation-based quantum circuit models using the Yang–Baxter gate. Moreover, we discuss the relationship between the extended Temperley–Lieb diagrammatical approach and the Yang–Baxter gate approach. With these research results, we propose a worthwhile subject, the extended Temperley–Lieb diagrammatical approach, for physicists in quantum information and quantum computation.