arXiv subjects

Shengmei Zhao

Publications and source records attributed to Shengmei Zhao.

At least 19 recordsLinked to original sources

arXiv2026

Quantum-enhanced ghost imaging recognition via joint optimization of speckle patterns and quantum network parameters

Ghost imaging enables nonlocal image reconstruction and exhibits strong robustness against interference, but achieving high-fidelity recognition at ultra-low sampling rates remains challenging. Quantum machine learning offers a novel approach for efficient feature extraction on noisy medium-scale quantum devices; however, existing methods generally suffer from low recognition accuracy and weak noise resistance. This paper proposes a ghost imaging recognition method based on the simultaneous optimization of speckle patterns and quantum network parameters. By leveraging the mathematical equivalence between classical convolution and speckle-object dot product operations in ghost imaging, a speckle consistency regularization mechanism is introduced to achieve end-to-end joint optimization of optical coding and quantum feature extractors. A parallel 8-qubit quantum circuit employing block coding and a star-shaped entanglement structure is designed to extract higher-order features from bucket signals. Simulation results on the MNIST and Fashion-MNIST datasets show that at an ultra-low sampling rate of 1.5625%, the proposed framework achieves recognition accuracies of 90.1% and 81.7%, respectively, representing a 2.6% improvement over classical convolutional neural networks and a maximum improvement of 14.2% over traditional hybrid quantum machine learning models. This method also exhibits strong robustness to quantum noise and has been validated on a real optical ghost imaging system, achieving an average recognition accuracy of 84.8%. These results confirm that the joint optimization of speckle patterns and quantum network parameters provides a reliable and practical solution for low-sampling ghost imaging recognition.

quant-ph↗

arXiv2026

Hierarchical Progressive Optimization for Multi-Qubit Pauli Noise Modeling

Quantum Noise Characterization (QNC) is indispensable for benchmarking and mitigating errors in Noisy Intermediate-Scale Quantum (NISQ) devices. However, traditional Quantum Process Tomography (QPT) suffers from an exponential parameter explosion, severely hindering its scalability. In this paper, we propose a Hierarchical Progressive Optimization (HPO) framework to efficiently extract high-order spatial crosstalk in multi-qubit systems. The complexity analysis shows that the combinatorial projection mask reduces the required number of Pauli transfer matrix (PTM) elements from O($16^N$) to O($N^2 3^N$). Numerical simulations on a 10-qubit HHL circuit achieve a fidelity of 0.9381 with the HPO method, compared to 0.7431 obtained using global depolarizing-noise mitigation.

quant-ph↗

arXiv2026

PdrQC: Pauli-space Discriminative Representations based Quantum Classifier

Quantum classification faces two key challenges. First, the difficulty of distinguishing between different classes varies: some class pairs are easy to separate, while others are more challenging. Second, practical execution is affected by noise, finite sampling, and measurement overhead. To address these issues, we propose the Pauli-Space Discriminative-Representation based Quantum Classifier (PdrQC), a framework for task-adaptive multiclass quantum classification. The method evaluates candidate upload circuits using low-weight Pauli features and formulates upload design as a structured model selection problem based on discriminative representations. By progressively selecting upload structures and compact Pauli readout features for the target multiclass task, the framework achieves a better balance between classification accuracy and resource efficiency. Numerical simulations were conducted on the MNIST and Fashion-MNIST datasets with $K\in\{2,3,5,7,10\}$. The results demonstrate that PdrQC, through its task-adaptive Pauli representation, achieves an effective balance among multiclass classification accuracy, quantum-circuit complexity, and measurement overhead, making it suitable for multiclass quantum classification under limited hardware resources.

quant-ph↗

arXiv2023

Variational Quantum Domain Adaptation

Quantum machine learning is an important application of quantum computing in the era of noisy intermediate-scale quantum devices. Domain adaptation is an effective method for addressing the distribution discrepancy problem between the training data and the real data when the neural network model is deployed. In this paper, a variational quantum domain adaptation method is proposed by using a quantum convolutional neural network, together with a gradient reversal module, and two quantum fully connected layers, named variational quantum domain adaptation(VQDA). The simulations on the local computer and IBM Quantum Experience (IBM Q) platform by Qiskit show the effectiveness of the proposed method. The results demonstrate that, compared to its classical corresponding domain adaptation method, VQDA achieves an average improvement of 4% on the accuracy for MNIST to USPS domain transfer under the same parameter scales. Similarly, for SYNDigits to SVHN domain transfer, VQDA achieves an average improvement of 2% on the accuracy under the same parameter scales.

quant-ph↗

arXiv2022

Evolutionary-based quantum architecture search

Quantum architecture search (QAS) is desired to construct a powerful and general QAS platform which can significantly accelerate quantum advantages in error-prone and depth limited quantum circuits in today Noisy Intermediate-Scale Quantum (NISQ) era. In this paper, we propose an evolutionary-based quantum architecture search (EQAS) scheme for the optimal layout to balance the higher expressive power and the trainable ability. In EQAS, each layout of quantum circuits, i.e quantum circuit architecture(QCA), is first encoded into a binary string, which is called quantum genes later. Then, an algorithm to remove the redundant parameters in QCA is performed according to the eigenvalues of the corresponding quantum Fisher information matrix (QFIM). Later, each QCA is evaluated by the normalized fitness, so that the sampling rate could be obtained to sample the parent generation by the Roulette Wheel selection strategy. Thereafter, the mutation and crossover are applied to get the next generation. EQAS is verified by the classification task in quantum machine learning for three datasets. The results show that the proposed EQAS can search for the optimal QCA with less parameterized gates, and the higher accuracies are obtained by adopting EQAS for the classification tasks over three dataset.

quant-ph↗

arXiv2022

Gradient-Free optimization algorithm for single-qubit quantum classifier

In the paper, a gradient-free optimization algorithm for single-qubit quantum classifier is proposed to overcome the effects of barren plateau caused by quantum devices. A rotation gate RX(ϕ) is applied on a single-qubit binary quantum classifier, and the training data and parameters are loaded into ϕ with the form of vector-multiplication. The cost function is decreased by finding the value of each parameter that yield the minimum expectation value of measuring the quantum circuit. The algorithm is performed iteratively for all parameters one by one, until the cost function satisfies the stop condition. The proposed algorithm is demonstrated for a classification task and is compared with that using Adam optimizer. Furthermore, the performance of the single-qubit quantum classifier with the proposed gradient-free optimization algorithm is discussed when the rotation gate in quantum device is under different noise. The simulation results show that the single-qubit quantum classifier with proposed gradient-free optimization algorithm can reach a high accuracy faster than that using Adam optimizer. Moreover, the proposed gradient-free optimization algorithm can quickly completes the training process of the single-qubit classifier. Additionally, the single-qubit quantum classifier with proposed gradient-free optimization algorithm has a good performance in noisy environments.

quant-ph↗

arXiv2022

Quantum algorithm for neural network enhanced multi-class parallel classification

Using the properties of quantum superposition, we propose a quantum classification algorithm to efficiently perform multi-class classification tasks, where the training data are loaded into parameterized operators which are applied to the basis of the quantum state in quantum circuit composed by \emph{sample register} and \emph{label register}, and the parameters of quantum gates are optimized by a hybrid quantum-classical method, which is composed of a trainable quantum circuit and a gradient-based classical optimizer. After several quantum-to-class repetitions, the quantum state is optimal that the state in \emph{sample register} is the same as that in \emph{label register}. %A structure of loading data many times is performed as a quantum version of neural network to improve the expression ability of quantum circuit. For a classification task of $L$-class, the analysis shows that the space and time complexity of the quantum circuit are $O(L*logL)$ and $O(logL)$, respectively. The numerical simulation results of 2-class task and 5-class task show that the proposed algorithm has a higher classification accuracy, faster convergence and higher expression ability. The classification accuracy and the speed of converging can also be improved by increasing the number times of applying multi-qubit controlled operators on the quantum circuit, especially for multiple classes classification.

quant-ph↗

arXiv2022

Diffractive deep neural network based adaptive optics scheme for vortex beam in oceanic turbulence

Vortex beam carrying orbital angular momentum (OAM) is disturbed by oceanic turbulence (OT) when propagating in underwater wireless optical communication (UWOC) system. Adaptive optics (AO) is used to compensate for distortion and improve the performance of the UWOC system. In this work, we propose a diffractive deep neural network (DDNN) based AO scheme to compensate for the distortion caused by OT, where the DDNN is trained to obtain the mapping between the distortion intensity distribution of the vortex beam and its corresponding phase screen representating OT. The intensity pattern of the distorted vortex beam obtained in the experiment is input to the DDNN model, and the predicted phase screen can be used to compensate the distortion in real time. The experiment results show that the proposed scheme can extract quickly the characteristics of the intensity pattern of the distorted vortex beam, and output accurately the predicted phase screen. The mode purity of the compensated vortex beam is significantly improved, even with a strong OT. Our scheme may provide a new avenue for AO techniques, and is expected to promote the communication quality of UWOC system.

eess.IV↗

arXiv2021

The optimal positive operator-valued measure for state discrimination

Evaluating the amount of information obtained from non-orthogonal quantum states is an important topic in the field of quantum information. The commonly used evaluation method is Holevo bound, which only provides a loose upper bound for quantum measurement. In this paper, we provide a theoretical study of the positive operator-valued measure (POVM) for discriminating nonorthogonal states. We construct a generalized POVM measurement operation, and derive the optimal one for state discrimination by Lagrange multiplier method. With simulation, we find that the optimal POVM measurement provides a tight upper bound for state discrimination, which is significantly lower than that predicted by Holevo bound. The derivation of optimal POVM measurement will play an important role in the security research of quantum key distribution.

quant-ph↗

arXiv2021

Privacy amplification scheme based on composite coding

Privacy amplification is an indispensable step in the post-processing of quantum key distribution, which can be used to compress the redundancy of shared key and improve the security level of the key. The commonly used privacy amplification is based on the random selection of universal hash functions, which needs the help of an additional random source, while it does not exist in general. In this paper, we propose a privacy amplification scheme based on composite coding, which is an extension of quantum CSS codes to classical linear codes. Compared with the universal hashing function, the proposed scheme does not need other random sources, and the randomness can be completely provided by the qubit string. Furthermore, the information-theoretic bound for the extraction of the key is obvious in composite coding.

quant-ph↗

arXiv2021

Ghost Handwritten Digit Recognition based on Deep Learning

We present a ghost handwritten digit recognition method for the unknown handwritten digits based on ghost imaging (GI) with deep neural network, where a few detection signals from the bucket detector, generated by the Cosine Transform speckle, are used as the characteristic information and the input of the designed deep neural network (DNN), and the classification is designed as the output of the DNN. The results show that the proposed scheme has a higher recognition accuracy (as high as 98.14% for the simulations, and 92.9% for the experiments ) with a smaller sampling ratio (say 12.76%). With the increase of the sampling ratio, the recognition accuracy is enhanced greatly. Compared with the traditional recognition scheme using the same DNN structure, the proposed scheme has a little better performance with a lower complexity and non-locality property. The proposed scheme provides a promising way for remote sensing.

eess.IV↗

arXiv2020

Influence of oceanic turbulence on propagation of autofocusing Airy beam with power exponential phase vortex

According to Rytov approximation theory, we derive the analytical expression of the detection probability of the autofocusing Airy beam (AAB) with powerexponent-phase carrying orbital angular momentum (OAM) mode, AAB-PEPV. We analyze the influence of oceanic turbulence on the propagation characteristics of the AAB-PEPV. The results show that the AAB-PEPV beam has a higher detection probability at the receiver when the anisotropic ocean turbulence has a larger unit mass fluid dynamic energy dissipation rate, a larger internal ratio factor, and a higher anisotropy factor. At the same time, the detection probability decreases with the temperature change dissipation rate, the temperature and salinity contribution to the refractive index spectrum. In addition, the larger power exponential phase and the longer wavelength the AAB-PEPV beam has, the better anti-interference the AAB-PEPV beam has.

physics.optics↗

arXiv2019

Upper Bound of Collective Attacks on Quantum Key Distribution

Evaluating the theoretical limit of the amount of information Eve can steal from a quantum key distribution protocol under given conditions is one of the most important things that need to be done in security proof. In addition to source loopholes and detection loopholes, channel attacks are considered to be the main ways of information leakage, while collective attacks are considered to be the most powerful active channel attacks. Here we deduce in detail the capability limit of Eve's collective attack in non-entangled quantum key distribution, like BB84 and measurement-device-independent protocols, and entangled quantum key distribution, like device-independent protocol, in which collective attack is composed of quantum weak measurement and quantum unambiguous state discrimination detection. The theoretical results show that collective attacks are equivalent in entangled and non-entangled quantum key distribution protocols. We also find that compared with the security proof based on entanglement purification, the security proof based on collective attack not only improves the system's tolerable bit error rate, but also improves the key rate.

cs.CR↗

arXiv2019

Phase Matching Quantum Key Distribution based on Single-Photon Entanglement

Two time-reversal quantum key distribution (QKD) schemes are the quantum entanglement based device-independent (DI)-QKD and measurement-device-independent (MDI)-QKD. The recently proposed twin field (TF)-QKD, also known as phase-matching (PM)-QKD, has improved the key rate bound from $O\left( η\right )$ to $O\left( \sqrt η \right )$ with $η$ the channel transmittance. In fact, TF-QKD is a kind of MDI-QKD but based on single-photon detection. In this paper, we propose a different PM-QKD based on single-photon entanglement, referred to as single-photon entanglement-based phase-matching (SEPM)-QKD, which can be viewed as a time-reversed version of the TF-QKD. Detection loopholes of the standard Bell test, which often occur in DI-QKD over long transmission distances, are not present in this protocol because the measurement settings and key information are the same quantity which is encoded in the local weak coherent state. We give a security proof of SEPM-QKD and demonstrate in theory that it is secure against all collective attacks and beam-splitting attacks. The simulation results show that the key rate enjoys a bound of $O\left( \sqrt η \right )$ with respect to the transmittance. SEPM-QKD not only helps us understand TF-QKD more deeply, but also hints at a feasible approach to eliminate detection loopholes in DI-QKD for long-distance communications.

quant-ph↗

arXiv2019

Wave-Particle duality in Single-Photon Entanglement

The simplest single-photon entanglement is the entanglement of the vacuum state and the single-photon state between two path modes. The verification of the existence of single-photon entanglement has attracted extensive research interests. Here, based on the construction of Bell's inequality in wave space, we propose a new method to verify single photon entanglement. Meanwhile, we define the wave state in two-dimensional space relative to the photon number state, and propose a method to measure it. Strong violation of Bell inequality based on joint measurement of wave states indicates the existence of single photon entanglement with certainty. Wave state entanglement obtained from Fourier transform of single photon entanglement and the corresponding measurement protocols will provide us with more information-carrying schemes in the field of quantum information. The difference in the representation in photon-number space and wave space implies the wave-particle duality of single photon entanglement.

quant-ph↗

arXiv2019

Multiple Pulses Phase-matching Quantum Key Distribution

We propose a multiple pulses phase-matching quantum key distribution protocol (MPPM-QKD) to exceed the linear key rate bound and to achieve higher error tolerance. In our protocol, Alice and Bob generate at first their own train pulses (each train should contain L pulses) as well as random bit sequences, and also encode each pulse of their trains with a randomized phase and a modulation phase. As the next step, both encoded trains are simultaneously sent to Charlie, who performs an interference detection and may be also an eavesdropper. After a successful detection is announced by Charlie, Alice and Bob open the randomized phase of each pulse and keep only communications when the summation of the difference randomized phases at two success detection's time-stamps for Alice and Bob are equal to 0 or pi. Thereafter, Alice and Bob compute the sifted key with the time-stamps. The above procedure is repeated until both Alice and Bob achieve sufficiently long sifted keys. We can also show that the secret key rate of the proposed QKD protocol can beat the rate-loss limit of so far known QKD protocols when the transmission distance is greater than 250 km. Moreover, the proposed protocol has a higher error tolerance, approximately 24%, when the transmission distance is 50 km and L = 128. The secret key rate and the transmission distance of our protocol are superior to that of the round-robin differential-phase-shift quantum key distribution protocol [6], and also of the measurement-device-independent quantum key distribution protocol [4], and the secret key rate performance is better in both cases than that of phase-matching quantum key distribution when bit train length is greater than 32.

quant-ph↗

arXiv2019

Compressed ghost edge imaging

In this paper, we propose an advanced framework of ghost edge imaging, named compressed ghost edge imaging (CGEI). In the scheme, a set of structured speckle patterns with pixel shifting are illuminated on an unknown object, and the output is collected by a bucket detector without any spatial resolution. By using compressed sensing algorithm, we obtain the horizontal and vertical edge information of the unknown object with the bucket detector detection results and the known structured speckle patterns. The edge is finally constructed by the two-dimentional edge information. The experimental and numerical simulations results show that the proposed scheme has a higher quality and reduces the number of measurements, in comparison with the existed edge detection schemes based on ghost imaging.

eess.IV↗

arXiv2018

Thermal effects of the quantum states generated from the isomorphs of PPKTP crystal

We theoretically and numerically investigate the temperature-dependent properties of the biphotons generated from four isomorphs of periodically poled $\mathrm{KTiOPO_4}$ (PPKTP): i.e., PPRTP, PPKTA, PPRTA and PPCTA. It is discovered that the first type of group-velocity-matched (GVM) wavelength is decreased by 6.4, 1.2, 8.9, 25.6 and 6.3 nm, while the phase-matched wavelength is decreased by 4.4, -0.4, -1.2, 29.1 and 59.5 nm for PPKTP, PPRTP, PPKTA, PPRTA and PPCTA, respectively, when the temperature is increased from 20$\,^{\circ}\mathrm{C}$ to 120$\,^{\circ}\mathrm{C}$. Although the maximal spectral purity of the heralded single photons is not changed at different temperature, the Hong-Ou-Mandel (HOM) interference shows different patterns due to a shift of the joint spectral amplitude. These thermal effects are very important for precise control of the quantum state for the future applications in quantum information processing, for example, in quantum interference or spectroscopy.

quant-ph↗