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Research on image classification using quantum convolutional neural networks based on multiple approaches

PHYSICA SCRIPTA 2025年第4期100卷 045116-045116页

作者： Dong, Yumin Ni, Xiaofeng Sun, Tonglei Wu, Gaojie Lin, Changjiang Chongqing Normal Univ Coll Comp & Informat Sci Chongqing 401331 Peoples R China

With the significant enhancement of quantum computing capabilities and their expanding applications in various fields, quantum image processing combined with quantum computing has become a key area of research in quantum computing, holding important theoretical value. In the face of the challenges posed by the digital information era, image classification technology demands higher standards from machine learning algorithms in terms of accuracy, computational speed, generalization capability, and complexity. This paper studies a series of quantum data encoding methods and parametric quantum circuit architectures, and proposes the application of Hybrid Hierarchical Encoding (HHE) and Hybrid quantum Convolutional Neural Network (HQCNN). The new encoding method HHE integrates the benefits of angle encoding and enhances the hybrid amplitude encoding design to achieve optimal classification performance without compromising the depth of quantum *** demonstrates outstanding classification performance and remarkable control over model complexity by leveraging the data processing capabilities of classical convolution and the complex computational power of quantum convolution. Experimental results show that HHE and HQCNN achieve better classification accuracy on the MNIST and Fashion-MNIST datasets compared to traditional classical CNN models, particularly when the number of parameters is significantly reduced.

关键词： quantum computing image classification image classification quantum data encoding parametric quantum circuit architectures hybrid hierarchical encoding hybrid quantum convolutional neural network

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Multicommodity information flow through quantum annealer

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quantum information processing 2024年第9期23卷 1-20页

作者： Ali, Munawar Ahmed, Hasnat Malik, Madiha Hussain Khalique, Aeysha Natl Univ Sci & Technol Sch Nat Sci Islamabad Pakistan CESAT Islamabad Pakistan Natl Ctr Phys NCP Shahdra Valley Rd Islamabad 44000 Pakistan

quantum computing offers a novel perspective for solving classically intractable problems. The computational heuristic non-binary nature of quantum computers, based on quantum mechanical properties, associates several advantages and disadvantages. We explore quantum annealing (QA), a metaheuristic algorithm with the primary objective of solving NP-hard optimization problems intractable to classical algorithms. Here we solve a particular family of NP problems, called origin-destination integer multi-commodity flow problem (ODIMCF), using QA. This includes the quadratic unconstrained binary optimization (QUBO) formulation and the practical implementation of this problem on the D-Wave QA. Additionally, quantum annealers are benchmarked against other classical solvers to assess the ODIMCF problem's solution quality and runtime performance.

关键词： quantum computing quantum annealing algorithm Combinatorial optimization Origin-destination integer multi-commodity flow problem

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Demonstration of hypergraph-state quantum information processing

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NATURE COMMUNICATIONS 2024年第1期15卷 2601页

作者： Huang, Jieshan Li, Xudong Chen, Xiaojiong Zhai, Chonghao Zheng, Yun Chi, Yulin Li, Yan He, Qiongyi Gong, Qihuang Wang, Jianwei Peking Univ Sch Phys State Key Lab Mesoscop Phys Beijing 100871 Peoples R China Peking Univ Frontiers Sci Ctr Nanooptoelectron Beijing 100871 Peoples R China Peking Univ Collaborat Innovat Ctr Quantum Matter Beijing 100871 Peoples R China Shanxi Univ Collaborat Innovat Ctr Extreme Opt Taiyuan 030006 Shanxi Peoples R China Peking Univ Yangtze Delta Inst Optoelect Nantong 226010 Jiangsu Peoples R China Hefei Natl Lab Hefei 230088 Peoples R China Harvard Univ John A Paulson Sch Engn & Appl Sci Cambridge MA 02138 USA

Complex entangled states are the key resources for measurement-based quantum computations, which is realised by performing a sequence of measurements on initially entangled qubits. Executable quantum algorithms in the graph-state quantum computing model are determined by the entanglement structure and the connectivity of entangled qubits. By generalisation from graph-type entanglement in which only the nearest qubits interact to a new type of hypergraph entanglement in which any subset of qubits can be arbitrarily entangled via hyperedges, hypergraph states represent more general resource states that allow arbitrary quantum computation with Pauli universality. Here we report experimental preparation, certification and processing of complete categories of four-qubit hypergraph states under the principle of local unitary equivalence, on a fully reprogrammable silicon-photonic quantum chip. Genuine multipartite entanglement for hypergraph states is certificated by the characterisation of entanglement witness, and the observation of violations of Mermin inequalities without any closure of distance or detection loopholes. A basic measurement-based protocol and an efficient resource state verification by color-encoding stabilizers are implemented with local Pauli measurement to benchmark the building blocks for hypergraph-state quantum computation. Our work prototypes hypergraph entanglement as a general resource for quantum information processing. Usual multiqubit entangled states can be described using the graph formalism, where each edge connects only two qubits. Here, instead, the authors use a reprogrammable silicon photonics chip to showcase preparation, verification and processing of arbitrary four-qubit hypergraph states, where hyperedges describe entanglement within a subset of many qubits.

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Transforming future technology with quantum-based IoT

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JOURNAL OF SUPERCOMPUTING 2024年第15期80卷 22362-22396页

作者： Khan, Habib Ullah Ali, Nasir Ali, Farhad Nazir, Shah Qatar Univ Coll Business & Econ Dept Accounting & Informat Syst Doha Qatar Beihang Univ Sch Aeronaut & Astronaut Beijing 100191 Peoples R China Quaid I Azam Univ Dept Elect Islamabad 45320 Pakistan Univ Swabi Dept Comp Sci Swabi 23430 Pakistan

With the advent of internet-enabled and hybrid technologies, information is becoming increasingly accessible to the general public. Smartphones and other gadgets are used extensively by people to share and promote ideas, in a variety of ways. Human interaction and communication has become more reliable and effective through advanced computing technologies. quantum computing is an emerging paradigm that will change the lives of individuals and the operations of organizations. quantum computers solve problems at high speed by operating in a superposition state in which the state can be either zero or one at the same instant. quantum sensors can be used efficiently in technological research to make accurate measurements and collect data that provide new insights into the behavior of nanomaterials. The use of quantum computing could also speed up the manufacturing process of devices with remarkable properties such as superconductivity, high strength or improved signal performance. quantum computing has the ability to dramatically speed up the development process of various organizations and increase their efficiency and effectiveness. The security and reliability of data and communication is improved by quantum computing techniques such as key generation and entanglement dispersion. Companies use cryptographic algorithms to protect their data. However, with the advent of quantum computing, cryptographic methods that rely on numerical aspects are no longer sufficient to protect data. quantum computing is an emerging field that is being applied to various problems that previously could not be solved using conventional methods. quantum computing plays an important role in the field of information processing, where information is precisely analyzed. Various quantum technologies and algorithms are used to secure company data. This paper provides a systematic review of the literature on the principles of quantum computing. The SLR focuses on achieving four aims "identifying a

关键词： quantum computing Cryptography quantum devices Security Q-IoT quantum information

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Restricting to the chip architecture maintains the quantum neural network accuracy

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quantum information processing 2024年第4期23卷 131-131页

作者： Friedrich, Lucas Maziero, Jonas Univ Fed Santa Maria Ctr Nat & Exact Sci Phys Dept Roraima Ave 1000 BR-97105900 Santa Maria RS Brazil

In the era of noisy intermediate-scale quantum devices, variational quantum algorithms (VQAs) stand as a prominent strategy for constructing quantum machine learning models. These models comprise both a quantum and a classical component. The quantum facet is characterized by a parametrization U, typically derived from the composition of various quantum gates. On the other hand, the classical component involves an optimizer that adjusts the parameters of U to minimize a cost function C. Despite the extensive applications of VQAs, several critical questions persist, such as determining the optimal gate sequence, devising efficient parameter optimization strategies, selecting appropriate cost functions, and understanding the influence of quantum chip architectures on the final results. This article aims to address the last question, emphasizing that, in general, the cost function tends to converge toward an average value as the utilized parameterization approaches a 2-design. Consequently, when the parameterization closely aligns with a 2-design, the quantum neural network model's outcome becomes less dependent on the specific parametrization. This insight leads to the possibility of leveraging the inherent architecture of quantum chips to define the parametrization for VQAs. By doing so, the need for additional swap gates is mitigated, consequently reducing the depth of VQAs and minimizing associated errors.

关键词： quantum neural networks Variational quantum algorithms quantum chip architecture

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NISQ-friendly measurement-based quantum clustering algorithms

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quantum information processing 2024年第10期23卷 1-19页

作者： Patil, Srushti Banerjee, Shreya Panigrahi, Prasanta K. Univ Copenhagen Niels Bohr Inst NNF Quantum Comp Programme Jagtvej 155 A DK-2200 Copenhagen N Denmark Indian Inst Sci Educ & Res Tirupati Dept Phys Tirupati 517619 Andhra Pradesh India Siksha O Anusandhan Univ Ctr Quantum Sci & Technol Bhubaneswar 751030 India Univ Sherbrooke Inst Quant Quebec City PQ J1K 2R1 Canada Indian Inst Sci Educ & Res Kolkata Mohanpur 741246 West Bengal India

Two novel measurement-based, quantum clustering algorithms are proposed based on quantum parallelism and entanglement. The first algorithm follows a divisive approach. The second algorithm is based on unsharp measurements, where we construct an effect operator with a Gaussian probability distribution to cluster similar data points. A major advantage of both algorithms is that they are simplistic in nature, easy to implement, and well suited for noisy intermediate scale quantum computers. We have successfully applied the first algorithm on a concentric circle data set, where the classical clustering approach fails, as well as on the Churritz data set of 130 cities, where we show that the algorithm succeeds with very low quantum resources. We applied the second algorithm on the labeled Wisconsin breast cancer dataset, and found that it is able to classify the dataset with high accuracy using only O(log(D)) qubits and polynomial measurements, where D is the maximal distance within any two points in the dataset. We also show that this algorithm works better with an assumed measurement error in the quantum system, making it extremely well suited for NISQ devices.

关键词： quantum clustering Unsharp measurements quantum algorithms

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Performance analysis and modeling for quantum computing simulation on distributed GPU platforms

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quantum information processing 2024年第11期23卷 1-40页

作者： Ahmadzadeh, Armin Sarbazi-Azad, Hamid Sharif Univ Technol Int Campus Kish Isl Iran Sharif Univ Technol Dept Comp Engn Tehran Iran

quantum computing holds great promise for accelerating computational tasks, but they are still not accessible. To fill this gap, quantum computing simulators have been widely used for the developing of quantum circuits and algorithms. Simulating quantum algorithms on classical computers also poses challenges due to the need for exponential memory and computational requirements. Many researchers attempted to address such challenges on different single-core, multi-core, and many-core systems, especially graphics processing units (GPUs). The diversity of CPU and GPU simulation of quantum circuits, including various CPU-GPU combinations and multiple parameters, including qubit size, memory capacity, circuit depth, GPU performance, resource heterogeneity, and load imbalance, makes it even more challenging. Finding the best configuration requires an exhaustive search in the design space, which is not possible in an acceptable time frame. Therefore, given the multitude of parameters and the analysis of influential factors, having an analytical model for selecting the proper configuration is desirable and even essential for large systems. This paper proposes a novel analytical performance model for quantum circuit simulation on a hybrid CPU-GPU platform of various sizes and parameters such as number of CPUs/GPUs, qubit size, memory capacity, quantum circuit depth, CPU/GPU performance, resource heterogeneity, and processing load. To do so, we focus on evaluating a scalable and adaptive hybrid quantum simulator in a hybrid platform with some CPUs and GPUs across multiple hosts. The model analyzes the execution time of individual GPU kernels and the impact of major micro-architecture features on performance. By employing dynamic load partitioning (DLP) and the heterogeneous multi-GPU kernel, performance bottlenecks are accurately identified, and execution time is estimated. The proposed model shows high accuracy, with a 94% accuracy compared to the experimental results on a hy

关键词： Many-core systems GPU Multi-GPU systems Hybrid parallel architectures quantum computing quantum circuits Simulation

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quantum computing software solutions, technologies, evaluation and limitations: a systematic mapping study

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COMPUTING 2025年第5期107卷 1-60页

作者： Desdentado, Elena Calero, Coral Moraga, M. angeles Garcia, Felix Univ Castilla La Mancha Inst Technol & Informat Syst Camino Moledores Ciudad Real 13005 Spain

quantum computing has emerged as a promising field with the potential to revolutionize information processing and storage. Understanding its current state and research trajectory is crucial. This study aims to map the current literature on quantum computing, to identify how quantum computing is being used in solving quantum software problems and improving quantum algorithms. Moreover, it examines evaluation parameters and the challenges faced in this field. A systematic mapping study was conducted using the SCOPUS database, including all papers up to December 2024. Relevant articles were selected based on inclusion criteria, and a content analysis was performed to categorize and synthesize the findings. information was gathered from 33 primary studies. Findings show that quantum computing is mainly applied in machine learning and optimization, though classical methods still outperform it. IBM quantum is the most used platform. Research focuses on algorithm efficiency, verification over validation, and resource optimization, but lacks standardized evaluation methods. Key limitations include hardware constraints, noise, and scalability, while challenges involve integration, error correction, and problem formulation. quantum computing continues to face significant technological challenges, but current research lays the groundwork for future advances. More practical studies on real hardware and strategies to improve the implementation and performance of quantum algorithms are needed. Effective evaluation, verification, and validation of quantum solutions must be further investigated.

关键词： quantum computing quantum software quantum technology Systematic mapping study SMS

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Experimental demonstration of deterministic quantum search algorithms on a programmable silicon photonic chip

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Science China(Physics,Mechanics & Astronomy) 2023年第9期66卷 1-7页

作者： Zhi-Hao Li Gui-Fang Yu Ya-Xin Wang Ze-Yu Xing Ling-Wen Kong Xiao-Qi Zhou State Key Laboratory of Optoelectronic Materials and Technologies School of PhysicsSun Yat-sen UniversityGuangzhou 510000China Hefei National Laboratory Hefei 230088China

The Grover quantum search algorithm is a landmark quantum computing application, which has a speed advantage over classical algorithms for searching an unsorted database. For an√ unsorted database of N items, the classical algorithm needs to search O(N) times, while the Grover algorithm only needs O(√N) times. However, except for the special case of N = 4, the traditional Grover algorithm always has some probability of failure. To solve this problem, several schemes for deterministically performing quantum search have been proposed, but they all impose additional requirements on the query Oracle and cannot be implemented in many practical scenarios. Recently, Roy et al. [Phys. Rev. Res. 4, L022013(2022)] proposed a new deterministic quantum search scheme with no additional requirements on the query Oracle, which has the potential to perfectly replace the traditional Grover algorithm. In this study, we experimentally implement on a programmable silicon quantum photonic chip four deterministic quantum search algorithms, including the Roy algorithm, all of which obtained an average search success rate of over0.93, exceeding the theoretical maximum of 0.9074 that the traditional Grover algorithm can achieve. Our results demonstrate the feasibility and superiority of the deterministic quantum search algorithms and are expected to facilitate the wider application of these algorithms in future quantum information processing.

关键词： integrated photonics quantum information technology deterministic quantum search

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When are quantum algorithms Applicable for Signal Decoding in Wireless Communication?

IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY

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IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY 2024年 5卷 24714-24728页

作者： Alsaui, Abdulmohsen Al-Nahhal, Ibrahim Dobre, Octavia A. Mem Univ Newfoundland Fac Engn & Appl Sci St John NF A1B 3X5 Canada

Multiple-input multiple-output (MIMO) technology utilizes multiple antennas at the transmitter and receiver to enhance data transmission speeds and reliability. Traditional MIMO decoding methods, however, can become increasingly complex as the number of antennas and modulation order rises. quantum computing brings forth a new realm of information processing with significant potential. This study investigates the applicability of quantum algorithms for decoding information in MIMO wireless communication systems. Specifically, the Durr-Hoyer quantum search, based on Grover's algorithm, and optimal quantum sorting algorithms are leveraged to reduce the query complexity with an analysis of the complexity and achievable bit error rate performance of the quantum-assisted decoders. The study considers cases of MIMO diversity, spatial modulation, and multiplexing transmission using both maximum-likelihood and fixed-complexity sphere decoders. By examining a variety of communication scenarios, this work aims to assess the applicability of quantum algorithms across different operational regimes and aids in extending the methodology to other communication systems.

关键词： Durr-Hoyer (DH) algorithm fixed-complexity sphere decoder (FCSD) Grover's algorithm maximum-likelihood (ML) decoder multiple-input multiple-output (MIMO) communication quantum algorithm quantum computing wireless communication

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