Nonlinear optical metasurfaces,which relax the phase-matching constraints of bulk nonlinear crystals and allow for precise engineering,are opening new possibilities in the field of quantum photonics.Recent advancement...Nonlinear optical metasurfaces,which relax the phase-matching constraints of bulk nonlinear crystals and allow for precise engineering,are opening new possibilities in the field of quantum photonics.Recent advancements have experimentally demonstrated high-resolution 2D imaging using a 1D detector array by combining quantum ghost imaging and all-optical scanning with spatially entangled photon pairs generated from a nonlinear metasurface.These findings establish metasurfaces as a promising platform for quantum imaging,communications,and sensing applications.展开更多
Background:Quantum-enhanced medical imaging algorithms–quantum entanglement reconstruction,quantum noise suppression,and quantum beamforming–propose possible remedies for significant constraints in traditional diagn...Background:Quantum-enhanced medical imaging algorithms–quantum entanglement reconstruction,quantum noise suppression,and quantum beamforming–propose possible remedies for significant constraints in traditional diagnostic imaging,such as resolution,radiation efficiency,and real-time processing.Methods:This work used a mixed-methods strategy,including controlled phantom experiments,retrospective multi-center clinical data analysis,and quantum-classical hybrid processing to assess enhancements in resolution,dosage efficiency,and diagnostic confidence.Statistical validation included analysis of variance(ANOVA)and receiver-operating characteristic curve analysis,juxtaposing quantum-enhanced methodologies with conventional and deep learning approaches.Results:Quantum entanglement reconstruction enhanced magnetic resonance imaging spatial resolution by 33.2%(P<0.01),quantum noise suppression facilitated computed tomography scans with a 60%reduction in radiation,and quantum beamforming improved ultrasound contrast by 27%while preserving real-time processing(<2 ms delay).Inter-reader variability(12%in Diagnostic Confidence Scores)showed that systematic training is needed,even if the performance was better.The research presented(1)a reusable clinical quantum imaging framework,(2)enhanced hardware processes(field-programmable gate array/graphics processing unit acceleration),and(3)cost-benefit analyses demonstrating a 22-month return on investment breakeven point.Conclusion:Quantum-enhanced imaging has a lot of promise for use in medicine,especially in neurology and cancer.Future research should focus on multi-modal integration(e.g.,positron emission tomography–magnetic resonance imaging),cloud-based quantum simulations for enhanced accessibility,and extensive trials to confirm long-term diagnostic accuracy.This breakthrough gives healthcare systems a technology roadmap and a reason to spend money on quantum-enhanced diagnostics.展开更多
Performance assessment of an imaging system is important for the optimization design with various technologies.The information-theoretic viewpoint based on communication theory or statistical inference theory can prov...Performance assessment of an imaging system is important for the optimization design with various technologies.The information-theoretic viewpoint based on communication theory or statistical inference theory can provide objective and operational measures on imaging performance. These approaches can be further developed by combining with the quantum statistical inference theory for optimizing imaging performance over measurements and analyze its quantum limits, which is demanded in order to improve an imaging system when the photon shot noise in the measurement is the dominant noise source. The aim of this review is to discuss and analyze the recent developments in this branch of quantum imaging.展开更多
Ensuring information security in the quantum era is a growing challenge due to advancements in cryptographic attacks and the emergence of quantum computing.To address these concerns,this paper presents the mathematica...Ensuring information security in the quantum era is a growing challenge due to advancements in cryptographic attacks and the emergence of quantum computing.To address these concerns,this paper presents the mathematical and computer modeling of a novel two-dimensional(2D)chaotic system for secure key generation in quantum image encryption(QIE).The proposed map employs trigonometric perturbations in conjunction with rational-saturation functions and hence,named as Trigonometric-Rational-Saturation(TRS)map.Through rigorous mathematical analysis and computational simulations,the map is extensively evaluated for bifurcation behaviour,chaotic trajectories,and Lyapunov exponents.The security evaluation validates the map’s non-linearity,unpredictability,and sensitive dependence on initial conditions.In addition,the proposed TRS map has further been tested by integrating it in a QIE scheme.The QIE scheme first quantum-encodes the classic image using the Novel Enhanced Quantum Representation(NEQR)technique,the TRS map is used for the generation of secure diffusion key,which is XOR-ed with the quantum-ready image to obtain the encrypted images.The security evaluation of the QIE scheme demonstrates superior security of the encrypted images in terms of statistical security attacks and also against Differential attacks.The encrypted images exhibit zero correlation and maximum entropy with demonstrating strong resilience due to 99.62%and 33.47%results for Number of Pixels Change Rate(NPCR)and Unified Average Changing Intensity(UACI).The results validate the effectiveness of TRS-based quantum encryption scheme in securing digital images against emerging quantum threats,making it suitable for secure image encryption in IoT and edge-based applications.展开更多
Quantum machine learning is an important application of quantum computing in the era of noisy intermediate-scale quantum devices.Domain adaptation(DA)is an effective method for addressing the distribution discrepancy ...Quantum machine learning is an important application of quantum computing in the era of noisy intermediate-scale quantum devices.Domain adaptation(DA)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,we propose a variational quantum domain adaptation method inspired by the quantum convolutional neural network,named variational quantum domain adaptation(VQDA).The data are first uploaded by a‘quantum coding module',then the feature information is extracted by several‘quantum convolution layers'and‘quantum pooling layers',which is named‘Feature Extractor'.Subsequently,the labels and the domains of the samples are obtained by the‘quantum fully connected layer'.With a gradient reversal module,the trained‘Feature Extractor'can extract the features that cannot be distinguished from the source and target domains.The simulations on the local computer and IBM Quantum Experience(IBM Q)platform by Qiskit show the effectiveness of the proposed method.The results show that VQDA(with 8 quantum bits)has 91.46%average classification accuracy for DA task between MNIST→USPS(USPS→MNIST),achieves 91.16%average classification accuracy for gray-scale and color images(with 10 quantum bits),and has 69.25%average classification accuracy on the DA task for color images(also with 10 quantum bits).VQDA achieves a 9.14%improvement in average classification accuracy compared to its corresponding classical domain adaptation method with the same parameter scale for different DA tasks.Simultaneously,the parameters scale is reduced to 43%by using VQDA when both quantum and classical DA methods have similar classification accuracies.展开更多
In the field of Internet, an image is of great significance to information transmission. Meanwhile, how to ensure and improve its security has become the focus of international research. We combine DNA codec with quan...In the field of Internet, an image is of great significance to information transmission. Meanwhile, how to ensure and improve its security has become the focus of international research. We combine DNA codec with quantum Arnold transform(QAr T) to propose a new double encryption algorithm for quantum color images to improve the security and robustness of image encryption. First, we utilize the biological characteristics of DNA codecs to perform encoding and decoding operations on pixel color information in quantum color images, and achieve pixel-level diffusion. Second, we use QAr T to scramble the position information of quantum images and use the operated image as the key matrix for quantum XOR operations. All quantum operations in this paper are reversible, so the decryption operation of the ciphertext image can be realized by the reverse operation of the encryption process. We conduct simulation experiments on encryption and decryption using three color images of “Monkey”, “Flower”, and “House”. The experimental results show that the peak value and correlation of the encrypted images on the histogram have good similarity, and the average normalized pixel change rate(NPCR) of RGB three-channel is 99.61%, the average uniform average change intensity(UACI) is 33.41%,and the average information entropy is about 7.9992. In addition, the robustness of the proposed algorithm is verified by the simulation of noise interference in the actual scenario.展开更多
As a branch of quantum image processing,quantum image scaling has been widely studied.However,most of the existing quantum image scaling algorithms are based on nearest-neighbor interpolation and bilinear interpolatio...As a branch of quantum image processing,quantum image scaling has been widely studied.However,most of the existing quantum image scaling algorithms are based on nearest-neighbor interpolation and bilinear interpolation,the quantum version of bicubic interpolation has not yet been studied.In this work,we present the first quantum image scaling scheme for bicubic interpolation based on the novel enhanced quantum representation(NEQR).Our scheme can realize synchronous enlargement and reduction of the image with the size of 2^(n)×2^(n) by integral multiple.Firstly,the image is represented by NEQR and the original image coordinates are obtained through multiple CNOT modules.Then,16 neighborhood pixels are obtained by quantum operation circuits,and the corresponding weights of these pixels are calculated by quantum arithmetic modules.Finally,a quantum matrix operation,instead of a classical convolution operation,is used to realize the sum of convolution of these pixels.Through simulation experiments and complexity analysis,we demonstrate that our scheme achieves exponential speedup over the classical bicubic interpolation algorithm,and has better effect than the quantum version of bilinear interpolation.展开更多
We redesign the parameterized quantum circuit in the quantum deep neural network, construct a three-layer structure as the hidden layer, and then use classical optimization algorithms to train the parameterized quantu...We redesign the parameterized quantum circuit in the quantum deep neural network, construct a three-layer structure as the hidden layer, and then use classical optimization algorithms to train the parameterized quantum circuit, thereby propose a novel hybrid quantum deep neural network(HQDNN) used for image classification. After bilinear interpolation reduces the original image to a suitable size, an improved novel enhanced quantum representation(INEQR) is used to encode it into quantum states as the input of the HQDNN. Multi-layer parameterized quantum circuits are used as the main structure to implement feature extraction and classification. The output results of parameterized quantum circuits are converted into classical data through quantum measurements and then optimized on a classical computer. To verify the performance of the HQDNN, we conduct binary classification and three classification experiments on the MNIST(Modified National Institute of Standards and Technology) data set. In the first binary classification, the accuracy of 0 and 4 exceeds98%. Then we compare the performance of three classification with other algorithms, the results on two datasets show that the classification accuracy is higher than that of quantum deep neural network and general quantum convolutional neural network.展开更多
This paper explores a double quantum images representation(DNEQR)model that allows for simultaneous storage of two digital images in a quantum superposition state.Additionally,a new type of two-dimensional hyperchaoti...This paper explores a double quantum images representation(DNEQR)model that allows for simultaneous storage of two digital images in a quantum superposition state.Additionally,a new type of two-dimensional hyperchaotic system based on sine and logistic maps is investigated,offering a wider parameter space and better chaotic behavior compared to the sine and logistic maps.Based on the DNEQR model and the hyperchaotic system,a double quantum images encryption algorithm is proposed.Firstly,two classical plaintext images are transformed into quantum states using the DNEQR model.Then,the proposed hyperchaotic system is employed to iteratively generate pseudo-random sequences.These chaotic sequences are utilized to perform pixel value and position operations on the quantum image,resulting in changes to both pixel values and positions.Finally,the ciphertext image can be obtained by qubit-level diffusion using two XOR operations between the position-permutated image and the pseudo-random sequences.The corresponding quantum circuits are also given.Experimental results demonstrate that the proposed scheme ensures the security of the images during transmission,improves the encryption efficiency,and enhances anti-interference and anti-attack capabilities.展开更多
As a part of quantum image processing,quantum image filtering is a crucial technology in the development of quantum computing.Low-pass filtering can effectively achieve anti-aliasing effects on images.Currently,most q...As a part of quantum image processing,quantum image filtering is a crucial technology in the development of quantum computing.Low-pass filtering can effectively achieve anti-aliasing effects on images.Currently,most quantum image filterings are based on classical domains and grayscale images,and there are relatively fewer studies on anti-aliasing in the quantum domain.This paper proposes a scheme for anti-aliasing filtering based on quantum grayscale and color image scaling in the spatial domain.It achieves the effect of anti-aliasing filtering on quantum images during the scaling process.First,we use the novel enhanced quantum representation(NEQR)and the improved quantum representation of color images(INCQI)to represent classical images.Since aliasing phenomena are more pronounced when images are scaled down,this paper focuses only on the anti-aliasing effects in the case of reduction.Subsequently,we perform anti-aliasing filtering on the quantum representation of the original image and then use bilinear interpolation to scale down the image,achieving the anti-aliasing effect.The constructed pyramid model is then used to select an appropriate image for upscaling to the original image size.Finally,the complexity of the circuit is analyzed.Compared to the images experiencing aliasing effects solely due to scaling,applying anti-aliasing filtering to the images results in smoother and clearer outputs.Additionally,the anti-aliasing filtering allows for manual intervention to select the desired level of image smoothness.展开更多
The statistical error is ineluctable in any measurement. Quantum techniques, especially with the development of quantum information, can help us squeeze the statistical error and enhance the precision of measurement. ...The statistical error is ineluctable in any measurement. Quantum techniques, especially with the development of quantum information, can help us squeeze the statistical error and enhance the precision of measurement. In a quantum system, there are some quantum parameters, such as the quantum state, quantum operator, and quantum dimension, which have no classical counterparts. So quantum metrology deals with not only the traditional parameters, but also the quantum parameters. Quantum metrology includes two important parts： measuring the physical parameters with a precision beating the classical physics limit and measuring the quantum parameters precisely. In this review, we will introduce how quantum characters （e.g., squeezed state and quantum entanglement） yield a higher precision, what the research areas are scientists most interesting in, and what the development status of quantum metrology and its perspectives are.展开更多
Quantum correlation imaging plays an important role in quantum information processing.The existing quantum correlation imaging schemes mostly use the Gaussian beam as the pump source,resulting in the entangled two pho...Quantum correlation imaging plays an important role in quantum information processing.The existing quantum correlation imaging schemes mostly use the Gaussian beam as the pump source,resulting in the entangled two photons exhibiting a Gaussian distribution.In this Letter,we report the experimental demonstration of quantum correlation imaging using a flattop beam as the pump source,which can effectively solve the problem of imaging distortion.The sampling time for each point is 5 s,and the imaging similarity is 93.4%.The principle of this scheme is reliable,the device is simple,and it can achieve high-similarity quantum correlation imaging at room temperature.展开更多
As a part of quantum image processing, quantum image scaling is a significant technology for the development of quantum computation. At present, most of the quantum image scaling schemes are based on grayscale images,...As a part of quantum image processing, quantum image scaling is a significant technology for the development of quantum computation. At present, most of the quantum image scaling schemes are based on grayscale images, with relatively little processing for color images. This paper proposes a quantum color image scaling scheme based on bilinear interpolation, which realizes the 2^(n_(1)) × 2^(n_(2)) quantum color image scaling. Firstly, the improved novel quantum representation of color digital images(INCQI) is employed to represent a 2^(n_(1)) × 2^(n_(2)) quantum color image, and the bilinear interpolation method for calculating pixel values of the interpolated image is presented. Then the quantum color image scaling-up and scaling-down circuits are designed by utilizing a series of quantum modules, and the complexity of the circuits is analyzed.Finally, the experimental simulation results of MATLAB based on the classical computer are given. The ultimate results demonstrate that the complexities of the scaling-up and scaling-down schemes are quadratic and linear, respectively, which are much lower than the cubic function and exponential function of other bilinear interpolation schemes.展开更多
We propose a new quantum watermarking scheme based on threshold selection using informational entropy of quantum image.The core idea of this scheme is to embed information into object and background of cover image in ...We propose a new quantum watermarking scheme based on threshold selection using informational entropy of quantum image.The core idea of this scheme is to embed information into object and background of cover image in different ways.First,a threshold method adopting the quantum informational entropy is employed to determine a threshold value.The threshold value can then be further used for segmenting the cover image to a binary image,which is an authentication key for embedding and extraction information.By a careful analysis of the quantum circuits of the scheme,that is,translating into the basic gate sequences which show the low complexity of the scheme.One of the simulation-based experimental results is entropy difference which measures the similarity of two images by calculating the difference in quantum image informational entropy between watermarked image and cover image.Furthermore,the analyses of peak signal-to-noise ratio,histogram and capacity of the scheme are also provided.展开更多
In this paper, a new quantum images encoding scheme is proposed. The proposed scheme mainly consists of four different encoding algorithms. The idea behind of the scheme is a binary key generated randomly for each pix...In this paper, a new quantum images encoding scheme is proposed. The proposed scheme mainly consists of four different encoding algorithms. The idea behind of the scheme is a binary key generated randomly for each pixel of the original image. Afterwards, the employed encoding algorithm is selected corresponding to the qubit pair of the generated randomized binary key. The security analysis of the proposed scheme proved its enhancement through both randomization of the generated binary image key and altering the gray-scale value of the image pixels using the qubits of randomized binary key. The simulation of the proposed scheme assures that the final encoded image could not be recognized visually. Moreover, the histogram diagram of encoded image is flatter than the originM one. The Shannon entropies of the final encoded images are significantly higher than the original one, which indicates that the attacker can not gain any information about the encoded images.展开更多
This paper presents a spatial domain quantum watermarking scheme. For a quantum watermarking scheme,a feasible quantum circuit is a key to achieve it. This paper gives a feasible quantum circuit for the presented sche...This paper presents a spatial domain quantum watermarking scheme. For a quantum watermarking scheme,a feasible quantum circuit is a key to achieve it. This paper gives a feasible quantum circuit for the presented scheme. In order to give the quantum circuit, a new quantum multi-control rotation gate, which can be achieved with quantum basic gates, is designed. With this quantum circuit, our scheme can arbitrarily control the embedding position of watermark images on carrier images with the aid of auxiliary qubits. Besides reversely acting the given quantum circuit, the paper gives another watermark extracting algorithm based on quantum measurements. Moreover, this paper also gives a new quantum image scrambling method and its quantum circuit. Differ from other quantum watermarking schemes, all given quantum circuits can be implemented with basic quantum gates. Moreover, the scheme is a spatial domain watermarking scheme, and is not based on any transform algorithm on quantum images. Meanwhile, it can make sure the watermark be secure even though the watermark has been found. With the given quantum circuit, this paper implements simulation experiments for the presented scheme. The experimental result shows that the scheme does well in the visual quality and the embedding capacity.展开更多
With the development of Globe Energy Internet,quantum steganography has been used for information hiding to improve copyright protection.Based on secure quantum communication protocol,and flexible steganography,secret...With the development of Globe Energy Internet,quantum steganography has been used for information hiding to improve copyright protection.Based on secure quantum communication protocol,and flexible steganography,secret information is embedded in quantum images in covert communication.Under the premise of guaranteeing the quality of the quantum image,the secret information is transmitted safely with virtue of good imperceptibility.A novel quantum watermark algorithm is proposed in the paper,based on the shared group key value of the communication parties and the transmission of the selected carrier map pixel gray higher than 8 bits.According to the shared group key value of the communication parties,the two effective Bell state qubits of the carried quantum streak image are replaced with secret information.Compared with the existing algorithms,the new algorithm improves the robustness of the secret information itself and the execution efficiency of its embedding and extraction.Experimental simulation and performance analysis also show that the novel algorithm has an excellent performance in transparency,robustness and embedded capacity.展开更多
We demonstrate that the combination of digital spiral imaging with high-dimensional orbital angular momentum(OAM)entanglement can be used for efficiently probing and identifying pure phase objects,where the probing li...We demonstrate that the combination of digital spiral imaging with high-dimensional orbital angular momentum(OAM)entanglement can be used for efficiently probing and identifying pure phase objects,where the probing light does not necessarily touch the object,via the experimental,non-local decomposition of non-integer pure phase vortices in OAM-entangled photon pairs.The entangled photons are generated by parametric downconversion and then measured with spatial light modulators and single-mode fibers.The fractional phase vortices are defined in the idler photons,while their corresponding spiral spectra are obtained non-locally by scanning the measured OAM states in the signal photons.We conceptually illustrate our results with the biphoton Klyshko picture and the effective dimensionality to demonstrate the high-dimensional nature of the associated quantum OAM channels.Our result is a proof of concept that quantum imaging techniques exploiting high-dimensional entanglement can potentially be used for remote sensing.展开更多
As an emerging microscopic detection tool,quantum microscopes based on the principle of quantum precision measurement have attracted widespread attention in recent years.Compared with the imaging of classical light,qu...As an emerging microscopic detection tool,quantum microscopes based on the principle of quantum precision measurement have attracted widespread attention in recent years.Compared with the imaging of classical light,quantum-enhanced imaging can achieve ultra-high resolution,ultra-sensitive detection,and anti-interference imaging.Here,we introduce a quantum-enhanced scanning microscope under illumination of an entangled NOON state in polarization.For the phase imager with NOON states,we propose a simple four-basis projection method to replace the four-step phase-shifting method.We have achieved the phase imaging of micrometer-sized birefringent samples and biological cell specimens,with sensitivity close to the Heisenberg limit.The visibility of transmittance-based imaging shows a great enhancement for NOON states.Besides,we also demonstrate that the scanning imaging with NOON states enables the spatial resolution enhancement of√N compared with classical measurement.Our imaging method may provide some reference for the practical application of quantum imaging and is expected to promote the development of microscopic detection.展开更多
Simultaneously optimizing the estimation of the centroid and separation of two incoherent optical point sources is constrained by a tradeoff relation determined by an incompatibility coefficient.At the Rayleigh distan...Simultaneously optimizing the estimation of the centroid and separation of two incoherent optical point sources is constrained by a tradeoff relation determined by an incompatibility coefficient.At the Rayleigh distance,the incompatibility coefficient vanishes and thus the tradeoff relation no longer restricts the simultaneous optimization of measurement for a joint estimation.We construct such a joint optimal measurement by an elaborated analysis on the operator algebra of the symmetric logarithmic derivative.Our work not only confirms the existence of a joint optimal measurement for this specific imaging model,but also gives a promising method to characterize the condition on measurement compatibility for general multiparameter estimation problems.展开更多
基金support by the National Research Foundation of Korea(NRF)(2022R1A2C301189812,2022M3H4A1A04096465).
文摘Nonlinear optical metasurfaces,which relax the phase-matching constraints of bulk nonlinear crystals and allow for precise engineering,are opening new possibilities in the field of quantum photonics.Recent advancements have experimentally demonstrated high-resolution 2D imaging using a 1D detector array by combining quantum ghost imaging and all-optical scanning with spatially entangled photon pairs generated from a nonlinear metasurface.These findings establish metasurfaces as a promising platform for quantum imaging,communications,and sensing applications.
文摘Background:Quantum-enhanced medical imaging algorithms–quantum entanglement reconstruction,quantum noise suppression,and quantum beamforming–propose possible remedies for significant constraints in traditional diagnostic imaging,such as resolution,radiation efficiency,and real-time processing.Methods:This work used a mixed-methods strategy,including controlled phantom experiments,retrospective multi-center clinical data analysis,and quantum-classical hybrid processing to assess enhancements in resolution,dosage efficiency,and diagnostic confidence.Statistical validation included analysis of variance(ANOVA)and receiver-operating characteristic curve analysis,juxtaposing quantum-enhanced methodologies with conventional and deep learning approaches.Results:Quantum entanglement reconstruction enhanced magnetic resonance imaging spatial resolution by 33.2%(P<0.01),quantum noise suppression facilitated computed tomography scans with a 60%reduction in radiation,and quantum beamforming improved ultrasound contrast by 27%while preserving real-time processing(<2 ms delay).Inter-reader variability(12%in Diagnostic Confidence Scores)showed that systematic training is needed,even if the performance was better.The research presented(1)a reusable clinical quantum imaging framework,(2)enhanced hardware processes(field-programmable gate array/graphics processing unit acceleration),and(3)cost-benefit analyses demonstrating a 22-month return on investment breakeven point.Conclusion:Quantum-enhanced imaging has a lot of promise for use in medicine,especially in neurology and cancer.Future research should focus on multi-modal integration(e.g.,positron emission tomography–magnetic resonance imaging),cloud-based quantum simulations for enhanced accessibility,and extensive trials to confirm long-term diagnostic accuracy.This breakthrough gives healthcare systems a technology roadmap and a reason to spend money on quantum-enhanced diagnostics.
基金supported by the National Natural Science Foundation of China (Nos.12275062,62201165,11935012,and 61871162)。
文摘Performance assessment of an imaging system is important for the optimization design with various technologies.The information-theoretic viewpoint based on communication theory or statistical inference theory can provide objective and operational measures on imaging performance. These approaches can be further developed by combining with the quantum statistical inference theory for optimizing imaging performance over measurements and analyze its quantum limits, which is demanded in order to improve an imaging system when the photon shot noise in the measurement is the dominant noise source. The aim of this review is to discuss and analyze the recent developments in this branch of quantum imaging.
基金funded by Deanship of Research and Graduate Studies at King Khalid University.The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Group Project under grant number(RGP.2/556/45).
文摘Ensuring information security in the quantum era is a growing challenge due to advancements in cryptographic attacks and the emergence of quantum computing.To address these concerns,this paper presents the mathematical and computer modeling of a novel two-dimensional(2D)chaotic system for secure key generation in quantum image encryption(QIE).The proposed map employs trigonometric perturbations in conjunction with rational-saturation functions and hence,named as Trigonometric-Rational-Saturation(TRS)map.Through rigorous mathematical analysis and computational simulations,the map is extensively evaluated for bifurcation behaviour,chaotic trajectories,and Lyapunov exponents.The security evaluation validates the map’s non-linearity,unpredictability,and sensitive dependence on initial conditions.In addition,the proposed TRS map has further been tested by integrating it in a QIE scheme.The QIE scheme first quantum-encodes the classic image using the Novel Enhanced Quantum Representation(NEQR)technique,the TRS map is used for the generation of secure diffusion key,which is XOR-ed with the quantum-ready image to obtain the encrypted images.The security evaluation of the QIE scheme demonstrates superior security of the encrypted images in terms of statistical security attacks and also against Differential attacks.The encrypted images exhibit zero correlation and maximum entropy with demonstrating strong resilience due to 99.62%and 33.47%results for Number of Pixels Change Rate(NPCR)and Unified Average Changing Intensity(UACI).The results validate the effectiveness of TRS-based quantum encryption scheme in securing digital images against emerging quantum threats,making it suitable for secure image encryption in IoT and edge-based applications.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.62375140 and 61871234)。
文摘Quantum machine learning is an important application of quantum computing in the era of noisy intermediate-scale quantum devices.Domain adaptation(DA)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,we propose a variational quantum domain adaptation method inspired by the quantum convolutional neural network,named variational quantum domain adaptation(VQDA).The data are first uploaded by a‘quantum coding module',then the feature information is extracted by several‘quantum convolution layers'and‘quantum pooling layers',which is named‘Feature Extractor'.Subsequently,the labels and the domains of the samples are obtained by the‘quantum fully connected layer'.With a gradient reversal module,the trained‘Feature Extractor'can extract the features that cannot be distinguished from the source and target domains.The simulations on the local computer and IBM Quantum Experience(IBM Q)platform by Qiskit show the effectiveness of the proposed method.The results show that VQDA(with 8 quantum bits)has 91.46%average classification accuracy for DA task between MNIST→USPS(USPS→MNIST),achieves 91.16%average classification accuracy for gray-scale and color images(with 10 quantum bits),and has 69.25%average classification accuracy on the DA task for color images(also with 10 quantum bits).VQDA achieves a 9.14%improvement in average classification accuracy compared to its corresponding classical domain adaptation method with the same parameter scale for different DA tasks.Simultaneously,the parameters scale is reduced to 43%by using VQDA when both quantum and classical DA methods have similar classification accuracies.
基金Project supported by the Natural Science Foundation of Shandong Province, China (Grant No. ZR2021MF049)Joint Fund of Natural Science Foundation of Shandong Province (Grant Nos. ZR2022LLZ012 and ZR2021LLZ001)the Key R&D Program of Shandong Province, China (Grant No. 2023CXGC010901)。
文摘In the field of Internet, an image is of great significance to information transmission. Meanwhile, how to ensure and improve its security has become the focus of international research. We combine DNA codec with quantum Arnold transform(QAr T) to propose a new double encryption algorithm for quantum color images to improve the security and robustness of image encryption. First, we utilize the biological characteristics of DNA codecs to perform encoding and decoding operations on pixel color information in quantum color images, and achieve pixel-level diffusion. Second, we use QAr T to scramble the position information of quantum images and use the operated image as the key matrix for quantum XOR operations. All quantum operations in this paper are reversible, so the decryption operation of the ciphertext image can be realized by the reverse operation of the encryption process. We conduct simulation experiments on encryption and decryption using three color images of “Monkey”, “Flower”, and “House”. The experimental results show that the peak value and correlation of the encrypted images on the histogram have good similarity, and the average normalized pixel change rate(NPCR) of RGB three-channel is 99.61%, the average uniform average change intensity(UACI) is 33.41%,and the average information entropy is about 7.9992. In addition, the robustness of the proposed algorithm is verified by the simulation of noise interference in the actual scenario.
基金Project supported by the Scientific Research Fund of Hunan Provincial Education Department,China (Grant No.21A0470)the Natural Science Foundation of Hunan Province,China (Grant No.2023JJ50268)+1 种基金the National Natural Science Foundation of China (Grant Nos.62172268 and 62302289)the Shanghai Science and Technology Project,China (Grant Nos.21JC1402800 and 23YF1416200)。
文摘As a branch of quantum image processing,quantum image scaling has been widely studied.However,most of the existing quantum image scaling algorithms are based on nearest-neighbor interpolation and bilinear interpolation,the quantum version of bicubic interpolation has not yet been studied.In this work,we present the first quantum image scaling scheme for bicubic interpolation based on the novel enhanced quantum representation(NEQR).Our scheme can realize synchronous enlargement and reduction of the image with the size of 2^(n)×2^(n) by integral multiple.Firstly,the image is represented by NEQR and the original image coordinates are obtained through multiple CNOT modules.Then,16 neighborhood pixels are obtained by quantum operation circuits,and the corresponding weights of these pixels are calculated by quantum arithmetic modules.Finally,a quantum matrix operation,instead of a classical convolution operation,is used to realize the sum of convolution of these pixels.Through simulation experiments and complexity analysis,we demonstrate that our scheme achieves exponential speedup over the classical bicubic interpolation algorithm,and has better effect than the quantum version of bilinear interpolation.
基金Project supported by the Natural Science Foundation of Shandong Province,China (Grant No. ZR2021MF049)the Joint Fund of Natural Science Foundation of Shandong Province (Grant Nos. ZR2022LLZ012 and ZR2021LLZ001)。
文摘We redesign the parameterized quantum circuit in the quantum deep neural network, construct a three-layer structure as the hidden layer, and then use classical optimization algorithms to train the parameterized quantum circuit, thereby propose a novel hybrid quantum deep neural network(HQDNN) used for image classification. After bilinear interpolation reduces the original image to a suitable size, an improved novel enhanced quantum representation(INEQR) is used to encode it into quantum states as the input of the HQDNN. Multi-layer parameterized quantum circuits are used as the main structure to implement feature extraction and classification. The output results of parameterized quantum circuits are converted into classical data through quantum measurements and then optimized on a classical computer. To verify the performance of the HQDNN, we conduct binary classification and three classification experiments on the MNIST(Modified National Institute of Standards and Technology) data set. In the first binary classification, the accuracy of 0 and 4 exceeds98%. Then we compare the performance of three classification with other algorithms, the results on two datasets show that the classification accuracy is higher than that of quantum deep neural network and general quantum convolutional neural network.
基金Project supported by the Open Fund of Anhui Key Laboratory of Mine Intelligent Equipment and Technology (Grant No.ZKSYS202204)the Talent Introduction Fund of Anhui University of Science and Technology (Grant No.2021yjrc34)the Scientific Research Fund of Anhui Provincial Education Department (Grant No.KJ2020A0301)。
文摘This paper explores a double quantum images representation(DNEQR)model that allows for simultaneous storage of two digital images in a quantum superposition state.Additionally,a new type of two-dimensional hyperchaotic system based on sine and logistic maps is investigated,offering a wider parameter space and better chaotic behavior compared to the sine and logistic maps.Based on the DNEQR model and the hyperchaotic system,a double quantum images encryption algorithm is proposed.Firstly,two classical plaintext images are transformed into quantum states using the DNEQR model.Then,the proposed hyperchaotic system is employed to iteratively generate pseudo-random sequences.These chaotic sequences are utilized to perform pixel value and position operations on the quantum image,resulting in changes to both pixel values and positions.Finally,the ciphertext image can be obtained by qubit-level diffusion using two XOR operations between the position-permutated image and the pseudo-random sequences.The corresponding quantum circuits are also given.Experimental results demonstrate that the proposed scheme ensures the security of the images during transmission,improves the encryption efficiency,and enhances anti-interference and anti-attack capabilities.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.62172268 and 62302289)the Shanghai Science and Technology Project(Grant Nos.21JC1402800 and 23YF1416200)。
文摘As a part of quantum image processing,quantum image filtering is a crucial technology in the development of quantum computing.Low-pass filtering can effectively achieve anti-aliasing effects on images.Currently,most quantum image filterings are based on classical domains and grayscale images,and there are relatively fewer studies on anti-aliasing in the quantum domain.This paper proposes a scheme for anti-aliasing filtering based on quantum grayscale and color image scaling in the spatial domain.It achieves the effect of anti-aliasing filtering on quantum images during the scaling process.First,we use the novel enhanced quantum representation(NEQR)and the improved quantum representation of color images(INCQI)to represent classical images.Since aliasing phenomena are more pronounced when images are scaled down,this paper focuses only on the anti-aliasing effects in the case of reduction.Subsequently,we perform anti-aliasing filtering on the quantum representation of the original image and then use bilinear interpolation to scale down the image,achieving the anti-aliasing effect.The constructed pyramid model is then used to select an appropriate image for upscaling to the original image size.Finally,the complexity of the circuit is analyzed.Compared to the images experiencing aliasing effects solely due to scaling,applying anti-aliasing filtering to the images results in smoother and clearer outputs.Additionally,the anti-aliasing filtering allows for manual intervention to select the desired level of image smoothness.
基金Project supported by the National Basic Research Program of China(Grant Nos.2011CBA00200 and 2011CB9211200)the National Natural Science Foun-dation of China(Grant Nos.61108009 and 61222504)+1 种基金the Anhui Provincial Natural Science Foundation,China(Grant No.1208085QA08)the Ph.D.Program Foundation of Ministry of Education of China(Grant No.20113402120017)
文摘The statistical error is ineluctable in any measurement. Quantum techniques, especially with the development of quantum information, can help us squeeze the statistical error and enhance the precision of measurement. In a quantum system, there are some quantum parameters, such as the quantum state, quantum operator, and quantum dimension, which have no classical counterparts. So quantum metrology deals with not only the traditional parameters, but also the quantum parameters. Quantum metrology includes two important parts： measuring the physical parameters with a precision beating the classical physics limit and measuring the quantum parameters precisely. In this review, we will introduce how quantum characters （e.g., squeezed state and quantum entanglement） yield a higher precision, what the research areas are scientists most interesting in, and what the development status of quantum metrology and its perspectives are.
基金supported by the National Natural Science Foundation of China(Nos.12104506,62205372,and62201597)the Scientific Research Project of National University of Defense Technology(Nos.22-ZZCX-07,23-ZZCX-JDZ-46,24-ZZCX-JDZ-43,and ZK22-35)+2 种基金the Youth Independent Innovation Science Foundation Project of National University of Defense Technology(No.ZK23-45)the Hefei Comprehensive National Science Center Project(No.KY23C502)the Director Fund Project of Advanced Laser Technology Laboratory Foundation of Anhui Province(No.KY22C608)。
文摘Quantum correlation imaging plays an important role in quantum information processing.The existing quantum correlation imaging schemes mostly use the Gaussian beam as the pump source,resulting in the entangled two photons exhibiting a Gaussian distribution.In this Letter,we report the experimental demonstration of quantum correlation imaging using a flattop beam as the pump source,which can effectively solve the problem of imaging distortion.The sampling time for each point is 5 s,and the imaging similarity is 93.4%.The principle of this scheme is reliable,the device is simple,and it can achieve high-similarity quantum correlation imaging at room temperature.
基金the National Natural Science Foundation of China (Grant No. 6217070290)Shanghai Science and Technology Project (Grant Nos. 21JC1402800 and 20040501500)。
文摘As a part of quantum image processing, quantum image scaling is a significant technology for the development of quantum computation. At present, most of the quantum image scaling schemes are based on grayscale images, with relatively little processing for color images. This paper proposes a quantum color image scaling scheme based on bilinear interpolation, which realizes the 2^(n_(1)) × 2^(n_(2)) quantum color image scaling. Firstly, the improved novel quantum representation of color digital images(INCQI) is employed to represent a 2^(n_(1)) × 2^(n_(2)) quantum color image, and the bilinear interpolation method for calculating pixel values of the interpolated image is presented. Then the quantum color image scaling-up and scaling-down circuits are designed by utilizing a series of quantum modules, and the complexity of the circuits is analyzed.Finally, the experimental simulation results of MATLAB based on the classical computer are given. The ultimate results demonstrate that the complexities of the scaling-up and scaling-down schemes are quadratic and linear, respectively, which are much lower than the cubic function and exponential function of other bilinear interpolation schemes.
基金supported by the National Natural Science Foundation of China(Grant No.6217070290)the Shanghai Science and Technology Project(Grant Nos.21JC1402800 and 20040501500)+2 种基金the Scientific Research Fund of Hunan Provincial Education Department(Grant No.21A0470)the Hunan Provincial Natural Science Foundation of China(Grant No.2020JJ4557)Top-Notch Innovative Talent Program for Postgraduate Students of Shanghai Maritime University(Grant No.2021YBR009)。
文摘We propose a new quantum watermarking scheme based on threshold selection using informational entropy of quantum image.The core idea of this scheme is to embed information into object and background of cover image in different ways.First,a threshold method adopting the quantum informational entropy is employed to determine a threshold value.The threshold value can then be further used for segmenting the cover image to a binary image,which is an authentication key for embedding and extraction information.By a careful analysis of the quantum circuits of the scheme,that is,translating into the basic gate sequences which show the low complexity of the scheme.One of the simulation-based experimental results is entropy difference which measures the similarity of two images by calculating the difference in quantum image informational entropy between watermarked image and cover image.Furthermore,the analyses of peak signal-to-noise ratio,histogram and capacity of the scheme are also provided.
基金Supported by Kermanshah Branch,Islamic Azad University,Kermanshah,IRAN
文摘In this paper, a new quantum images encoding scheme is proposed. The proposed scheme mainly consists of four different encoding algorithms. The idea behind of the scheme is a binary key generated randomly for each pixel of the original image. Afterwards, the employed encoding algorithm is selected corresponding to the qubit pair of the generated randomized binary key. The security analysis of the proposed scheme proved its enhancement through both randomization of the generated binary image key and altering the gray-scale value of the image pixels using the qubits of randomized binary key. The simulation of the proposed scheme assures that the final encoded image could not be recognized visually. Moreover, the histogram diagram of encoded image is flatter than the originM one. The Shannon entropies of the final encoded images are significantly higher than the original one, which indicates that the attacker can not gain any information about the encoded images.
基金Supported by the National Natural Science Foundation of China under Grant Nos.61272514,61170272,61373131,61121061,61411146001the program for New Century Excellent Talents under Grant No.NCET-13-0681+2 种基金the National Development Foundation for Cryptological Research(Grant No.MMJJ201401012)the Fok Ying Tung Education Foundation under Grant No.131067the Shandong Provincial Natural Science Foundation of China under Grant No.ZR2013FM025
文摘This paper presents a spatial domain quantum watermarking scheme. For a quantum watermarking scheme,a feasible quantum circuit is a key to achieve it. This paper gives a feasible quantum circuit for the presented scheme. In order to give the quantum circuit, a new quantum multi-control rotation gate, which can be achieved with quantum basic gates, is designed. With this quantum circuit, our scheme can arbitrarily control the embedding position of watermark images on carrier images with the aid of auxiliary qubits. Besides reversely acting the given quantum circuit, the paper gives another watermark extracting algorithm based on quantum measurements. Moreover, this paper also gives a new quantum image scrambling method and its quantum circuit. Differ from other quantum watermarking schemes, all given quantum circuits can be implemented with basic quantum gates. Moreover, the scheme is a spatial domain watermarking scheme, and is not based on any transform algorithm on quantum images. Meanwhile, it can make sure the watermark be secure even though the watermark has been found. With the given quantum circuit, this paper implements simulation experiments for the presented scheme. The experimental result shows that the scheme does well in the visual quality and the embedding capacity.
基金This project is funded by the State Grid Key Project“Key Technology of Scale Engineering Application of Power Battery for Echelon Utilization”,the Project No.52010119002F.
文摘With the development of Globe Energy Internet,quantum steganography has been used for information hiding to improve copyright protection.Based on secure quantum communication protocol,and flexible steganography,secret information is embedded in quantum images in covert communication.Under the premise of guaranteeing the quality of the quantum image,the secret information is transmitted safely with virtue of good imperceptibility.A novel quantum watermark algorithm is proposed in the paper,based on the shared group key value of the communication parties and the transmission of the selected carrier map pixel gray higher than 8 bits.According to the shared group key value of the communication parties,the two effective Bell state qubits of the carried quantum streak image are replaced with secret information.Compared with the existing algorithms,the new algorithm improves the robustness of the secret information itself and the execution efficiency of its embedding and extraction.Experimental simulation and performance analysis also show that the novel algorithm has an excellent performance in transparency,robustness and embedded capacity.
基金LC thanks Jonathan Leach for previous illuminating discussions about the OAM spreading effect and the National Natural Science Foundation of China(Grant No.11104233)the Fundamental Research Funds for the Central Universities(Grants Nos.2011121043,2012121015)+1 种基金the Natural Science Foundation of Fujian Province of China(2011J05010)and the Program for New Century Excellent Talents in University of China(Grant No.NCET-13-0495).JR thanks Hamamatsu and Miles Padgett for their kind support of this work.
文摘We demonstrate that the combination of digital spiral imaging with high-dimensional orbital angular momentum(OAM)entanglement can be used for efficiently probing and identifying pure phase objects,where the probing light does not necessarily touch the object,via the experimental,non-local decomposition of non-integer pure phase vortices in OAM-entangled photon pairs.The entangled photons are generated by parametric downconversion and then measured with spatial light modulators and single-mode fibers.The fractional phase vortices are defined in the idler photons,while their corresponding spiral spectra are obtained non-locally by scanning the measured OAM states in the signal photons.We conceptually illustrate our results with the biphoton Klyshko picture and the effective dimensionality to demonstrate the high-dimensional nature of the associated quantum OAM channels.Our result is a proof of concept that quantum imaging techniques exploiting high-dimensional entanglement can potentially be used for remote sensing.
基金supported by he National Natural Science Foundation of China(Grant Nos.12304359,12304398,12404382,12234009,12274215,and 12427808)the China Postdoctoral Science Foundation(Grant No.2023M731611)+4 种基金the Jiangsu Funding Program for Excellent Postdoctoral Talent(Grant No.2023ZB717)Innovation Program for Quantum Science and Technology(Grant No.2021ZD0301400)Key R&D Program of Jiangsu Province(Grant No.BE2023002)Natural Science Foundation of Jiangsu Province(Grant Nos.BK20220759 and BK20233001)Program for Innovative Talents and Entrepreneurs in Jiangsu,and Key R&D Program of Guangdong Province(Grant No.2020B0303010001).
文摘As an emerging microscopic detection tool,quantum microscopes based on the principle of quantum precision measurement have attracted widespread attention in recent years.Compared with the imaging of classical light,quantum-enhanced imaging can achieve ultra-high resolution,ultra-sensitive detection,and anti-interference imaging.Here,we introduce a quantum-enhanced scanning microscope under illumination of an entangled NOON state in polarization.For the phase imager with NOON states,we propose a simple four-basis projection method to replace the four-step phase-shifting method.We have achieved the phase imaging of micrometer-sized birefringent samples and biological cell specimens,with sensitivity close to the Heisenberg limit.The visibility of transmittance-based imaging shows a great enhancement for NOON states.Besides,we also demonstrate that the scanning imaging with NOON states enables the spatial resolution enhancement of√N compared with classical measurement.Our imaging method may provide some reference for the practical application of quantum imaging and is expected to promote the development of microscopic detection.
基金supported by the National Natural Science Foundation of China (Grants No.12275062,No.11935012,and No.61871162)。
文摘Simultaneously optimizing the estimation of the centroid and separation of two incoherent optical point sources is constrained by a tradeoff relation determined by an incompatibility coefficient.At the Rayleigh distance,the incompatibility coefficient vanishes and thus the tradeoff relation no longer restricts the simultaneous optimization of measurement for a joint estimation.We construct such a joint optimal measurement by an elaborated analysis on the operator algebra of the symmetric logarithmic derivative.Our work not only confirms the existence of a joint optimal measurement for this specific imaging model,but also gives a promising method to characterize the condition on measurement compatibility for general multiparameter estimation problems.
