Pub Date : 2025-12-09DOI: 10.1109/TQE.2025.3642110
Purin Pongpanich;Tanasanee Phienthrakul
This study presents an investigation of the dual-discriminator hybrid quantum generative adversarial network (DDHQ-GAN), a framework designed to enhance the performance of conventional generative adversarial networks (GANs) through the incorporation of a hybrid quantum discriminator. The proposed DDHQ-GAN architecture comprises three primary components: a generator and two discriminators. The research evaluates the efficacy of the DDHQ-GAN in comparison with existing GAN variants, employing the Fréchet inception distance (FID) as a quantitative metric to assess image generation quality. The study further examines the interplay between the structural configurations of parameterized quantum circuits, classical neural network architectures, and model hyperparameters, using the Modified National Institute of Standards and Technology (MNIST) dataset as the experimental benchmark. Empirical results demonstrate that the DDHQ-GAN achieves superior performance, reflected by lower FID scores, while incurring only a marginal increase in the number of parameters and quantum computational resources.
{"title":"Dual-Discriminator Hybrid Quantum Generative Adversarial Networks for Improved GAN Performance","authors":"Purin Pongpanich;Tanasanee Phienthrakul","doi":"10.1109/TQE.2025.3642110","DOIUrl":"https://doi.org/10.1109/TQE.2025.3642110","url":null,"abstract":"This study presents an investigation of the dual-discriminator hybrid quantum generative adversarial network (DDHQ-GAN), a framework designed to enhance the performance of conventional generative adversarial networks (GANs) through the incorporation of a hybrid quantum discriminator. The proposed DDHQ-GAN architecture comprises three primary components: a generator and two discriminators. The research evaluates the efficacy of the DDHQ-GAN in comparison with existing GAN variants, employing the Fréchet inception distance (FID) as a quantitative metric to assess image generation quality. The study further examines the interplay between the structural configurations of parameterized quantum circuits, classical neural network architectures, and model hyperparameters, using the Modified National Institute of Standards and Technology (MNIST) dataset as the experimental benchmark. Empirical results demonstrate that the DDHQ-GAN achieves superior performance, reflected by lower FID scores, while incurring only a marginal increase in the number of parameters and quantum computational resources.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"7 ","pages":"1-14"},"PeriodicalIF":4.6,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11288093","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145982290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-08DOI: 10.1109/TQE.2025.3641027
Kai Zhang;Sen Kuang
Traditional many-body teleportation relies on the strong interaction property of a quantum many-body system, which usually requires numerous qubits and entanglement resources, making it difficult to realize experimentally. A natural scheme is to use a 1-D spin chain with simple structure to realize many-body teleportation. In this article, we analyze the conditions for general quantum many-body teleportation and construct an effective control Hamiltonian, realizing quantum many-body teleportation on the controlled 1-D spin chain. Our scheme, which only requires forward evolution and local measurements, can be used to perform quantum state transfer without the special presetting and modulation of coupling parameters of the chain and without strict control over the evolution time, thereby enhancing the experimental realizability. Furthermore, we improve the efficiency and accuracy of quantum state transfer by introducing quantum optimal control technique to optimize the control pulse sequences.
{"title":"Optimal Control-Assisted Rapid Quantum State Transfer on 1-D Spin Chain","authors":"Kai Zhang;Sen Kuang","doi":"10.1109/TQE.2025.3641027","DOIUrl":"https://doi.org/10.1109/TQE.2025.3641027","url":null,"abstract":"Traditional many-body teleportation relies on the strong interaction property of a quantum many-body system, which usually requires numerous qubits and entanglement resources, making it difficult to realize experimentally. A natural scheme is to use a 1-D spin chain with simple structure to realize many-body teleportation. In this article, we analyze the conditions for general quantum many-body teleportation and construct an effective control Hamiltonian, realizing quantum many-body teleportation on the controlled 1-D spin chain. Our scheme, which only requires forward evolution and local measurements, can be used to perform quantum state transfer without the special presetting and modulation of coupling parameters of the chain and without strict control over the evolution time, thereby enhancing the experimental realizability. Furthermore, we improve the efficiency and accuracy of quantum state transfer by introducing quantum optimal control technique to optimize the control pulse sequences.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"7 ","pages":"1-14"},"PeriodicalIF":4.6,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11283091","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-04DOI: 10.1109/TQE.2025.3640361
Sana Javed;Sergio Colet;Francisco Garcia-Herrero;Óscar Ruano;Juan Antonio Maestro;Bane Vasić;Mark F. Flanagan
This article proposes a novel low-complexity syndrome-based linear programming (SB-LP) decoding algorithm for decoding quantum low-density parity-check codes. Under the code-capacity model, the SB-LP decoder can be used as a standalone decoder; however, it is particularly powerful when used as a postprocessing step following SB min-sum (SB-MS) decoding. In the latter case, the proposed decoder is shown to be capable of significantly reducing the error floor of the SB-MS decoder for both flooded and layered SB-MS scheduling. Also, an early stopping criterion is introduced to decide when to activate the SB-LP algorithm, avoiding executing a predefined maximum number of iterations for the SB-MS decoder. Simulation results show, for some example hypergraph and generalized bicycle (GB) codes, that the proposed decoder can lower the error floor by one to three orders of magnitude compared to SB-MS for the same total number of decoding iterations. Furthermore, for the class of GB codes, it is shown that as the minimum distance of the code increases, the logical error rate provided by the proposed decoder also improves, indicating that the solution is scalable. Under the circuit-level noise model, it is shown that while the SB-LP decoder does not fully replace the need for ordered statistics decoding (OSD) when flooded SB-MS is used as a preliminary step, it reduces the number of calls to the OSD postprocessor, which directly impacts the overall latency. In addition, the method offers a syndrome-matching decoder and improves the accuracy of the logical error rate for bivariate bicycle codes of distances 6 to 18, particularly at low error rates, when compared to the belief propagation+OSD benchmark.
{"title":"Low-Complexity Syndrome-Based Linear Programming Decoding of Quantum LDPC Codes","authors":"Sana Javed;Sergio Colet;Francisco Garcia-Herrero;Óscar Ruano;Juan Antonio Maestro;Bane Vasić;Mark F. Flanagan","doi":"10.1109/TQE.2025.3640361","DOIUrl":"https://doi.org/10.1109/TQE.2025.3640361","url":null,"abstract":"This article proposes a novel low-complexity syndrome-based linear programming (SB-LP) decoding algorithm for decoding quantum low-density parity-check codes. Under the code-capacity model, the SB-LP decoder can be used as a standalone decoder; however, it is particularly powerful when used as a postprocessing step following SB min-sum (SB-MS) decoding. In the latter case, the proposed decoder is shown to be capable of significantly reducing the error floor of the SB-MS decoder for both flooded and layered SB-MS scheduling. Also, an early stopping criterion is introduced to decide when to activate the SB-LP algorithm, avoiding executing a predefined maximum number of iterations for the SB-MS decoder. Simulation results show, for some example hypergraph and generalized bicycle (GB) codes, that the proposed decoder can lower the error floor by one to three orders of magnitude compared to SB-MS for the same total number of decoding iterations. Furthermore, for the class of GB codes, it is shown that as the minimum distance of the code increases, the logical error rate provided by the proposed decoder also improves, indicating that the solution is scalable. Under the circuit-level noise model, it is shown that while the SB-LP decoder does not fully replace the need for ordered statistics decoding (OSD) when flooded SB-MS is used as a preliminary step, it reduces the number of calls to the OSD postprocessor, which directly impacts the overall latency. In addition, the method offers a syndrome-matching decoder and improves the accuracy of the logical error rate for bivariate bicycle codes of distances 6 to 18, particularly at low error rates, when compared to the belief propagation+OSD benchmark.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"7 ","pages":"1-19"},"PeriodicalIF":4.6,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11278092","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145982312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01DOI: 10.1109/TQE.2025.3638878
Subhadeep Mondal;Amit Kumar Dutta
Quantum neural networks (QNNs) are gaining attention as versatile models for quantum machine learning, but training them effectively remains a challenge. Most existing approaches, such as quantum multilayer perceptrons, use fidelity-based cost functions. While well-suited for pure states, these measures are less reliable when inputs and outputs are mixed states—a situation common in learning quantum channels. In this work, we introduce a training framework built on a relative entropy-inspired cost function. By quantifying the directional divergence between learned and target states, relative entropy provides a more informative and principled measure than linear fidelity, naturally capturing both spectral and eigenvector differences in mixed states. This approach preserves the completely positive structure of the network, supports efficient backpropagation in layered QNN configurations, and achieves improved accuracy and convergence over fidelity-based training. These results highlight entropy-based optimization as a promising path toward scalable, robust, and noise-resilient quantum learning.
{"title":"Relative Entropy-Based Training of Quantum Neural Networks","authors":"Subhadeep Mondal;Amit Kumar Dutta","doi":"10.1109/TQE.2025.3638878","DOIUrl":"https://doi.org/10.1109/TQE.2025.3638878","url":null,"abstract":"Quantum neural networks (QNNs) are gaining attention as versatile models for quantum machine learning, but training them effectively remains a challenge. Most existing approaches, such as quantum multilayer perceptrons, use fidelity-based cost functions. While well-suited for pure states, these measures are less reliable when inputs and outputs are mixed states—a situation common in learning quantum channels. In this work, we introduce a training framework built on a relative entropy-inspired cost function. By quantifying the directional divergence between learned and target states, relative entropy provides a more informative and principled measure than linear fidelity, naturally capturing both spectral and eigenvector differences in mixed states. This approach preserves the completely positive structure of the network, supports efficient backpropagation in layered QNN configurations, and achieves improved accuracy and convergence over fidelity-based training. These results highlight entropy-based optimization as a promising path toward scalable, robust, and noise-resilient quantum learning.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"7 ","pages":"1-14"},"PeriodicalIF":4.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11271543","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-24DOI: 10.1109/TQE.2025.3636049
Yannik N. Boeck;Holger Boche;Frank H.P. Fitzek
We consider exact quantum circuit synthesis, quantum gate efficiency, and the spectral gap conjecture from the perspective of computable analysis. Circuit synthesis, in both its exact and its approximate variant, is fundamental to the circuit model of quantum computing. As an engineering problem, however, the practical and theoretical aspects of quantum circuit synthesis are far from being fully understood. Particularly, this concerns explicit methods for gate-agnostic circuit synthesis and questions of gate efficiency. More than 20 years ago, Harrow et al. published their famous spectral gap theorem: given a suitable family of quantum gates, it is possible to approximate any unitary transformation by means of a quantum circuit whose length is proportional to the required accuracy’s logarithm. Moreover, Harrow et al. suspected that all universal gate families allow for this type of approximation, a hypothesis that became known as the spectral gap conjecture and remains unproven until today. Being an entirely classical task, quantum circuit synthesis must be considered in the context of digital computing, that is, in the context of Turing computability and computable analysis. Using the relevant mathematical framework, we establish no-go results concerning exact quantum circuit synthesis and quantum big-O analysis. Our findings relate to the theory of approximate t-designs, which has recently received notable attention through the literature. Moreover, as follows from our findings, the existence of an algorithm that computes leading big-O coefficients would prove the spectral gap conjecture true within the computable special unitary group.
{"title":"Feynman Meets Turing: Computability Aspects of Exact Circuit Synthesis, Gate Efficiency, and the Spectral Gap Conjecture","authors":"Yannik N. Boeck;Holger Boche;Frank H.P. Fitzek","doi":"10.1109/TQE.2025.3636049","DOIUrl":"https://doi.org/10.1109/TQE.2025.3636049","url":null,"abstract":"We consider exact quantum circuit synthesis, quantum gate efficiency, and the spectral gap conjecture from the perspective of computable analysis. Circuit synthesis, in both its exact and its approximate variant, is fundamental to the circuit model of quantum computing. As an engineering problem, however, the practical and theoretical aspects of quantum circuit synthesis are far from being fully understood. Particularly, this concerns explicit methods for gate-agnostic circuit synthesis and questions of gate efficiency. More than 20 years ago, Harrow et al. published their famous spectral gap theorem: given a suitable family of quantum gates, it is possible to approximate any unitary transformation by means of a quantum circuit whose length is proportional to the required accuracy’s logarithm. Moreover, Harrow et al. suspected that all universal gate families allow for this type of approximation, a hypothesis that became known as the spectral gap conjecture and remains unproven until today. Being an entirely classical task, quantum circuit synthesis must be considered in the context of digital computing, that is, in the context of Turing computability and computable analysis. Using the relevant mathematical framework, we establish no-go results concerning exact quantum circuit synthesis and quantum big-O analysis. Our findings relate to the theory of approximate t-designs, which has recently received notable attention through the literature. Moreover, as follows from our findings, the existence of an algorithm that computes leading big-O coefficients would prove the spectral gap conjecture true within the computable special unitary group.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"7 ","pages":"1-31"},"PeriodicalIF":4.6,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11266935","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145982306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study presents the design, simulation, and experimental characterization of a superconducting transmon qubit circuit prototype for potential applications in dark matter detection experiments. We describe a planar circuit design featuring two noninteracting transmon qubits, one with fixed frequency and the other flux tunable. Finite-element simulations were employed to extract key Hamiltonian parameters and optimize component geometries. The qubit was fabricated and then characterized at 20 mK, allowing for a comparison between simulated and measured qubit parameters. Good agreement was found for transition frequencies and anharmonicities (within 1% and 10%, respectively) while coupling strengths exhibited larger discrepancies (30%). We discuss potential causes for measured coherence times falling below expectations ($T_{1}sim ,$1–2 μs) and propose strategies for future design improvements. Notably, we demonstrate the application of a hybrid 3D–2D simulation approach for energy participation ratio evaluation, yielding a more accurate estimation of dielectric losses. This work represents an important first step in developing planar quantum nondemolition single-photon counters for dark matter searches, particularly for axion and dark photon detection schemes.
{"title":"Transmon Qubit Modeling and Characterization for Dark Matter Search","authors":"Roberto Moretti;Danilo Labranca;Pietro Campana;Rodolfo Carobene;Marco Gobbo;Manuel A. Castellanos-Beltran;David Olaya;Peter F. Hopkins;Leonardo Banchi;Matteo Borghesi;Alessandro Candido;Stefano Carrazza;Hervè Atsè Corti;Alessandro D’Elia;Marco Faverzani;Elena Ferri;Angelo Nucciotti;Luca Origo;Andrea Pasquale;Alex Stephane Piedjou Komnang;Alessio Rettaroli;Simone Tocci;Claudio Gatti;Andrea Giachero","doi":"10.1109/TQE.2025.3633176","DOIUrl":"https://doi.org/10.1109/TQE.2025.3633176","url":null,"abstract":"This study presents the design, simulation, and experimental characterization of a superconducting transmon qubit circuit prototype for potential applications in dark matter detection experiments. We describe a planar circuit design featuring two noninteracting transmon qubits, one with fixed frequency and the other flux tunable. Finite-element simulations were employed to extract key Hamiltonian parameters and optimize component geometries. The qubit was fabricated and then characterized at 20 mK, allowing for a comparison between simulated and measured qubit parameters. Good agreement was found for transition frequencies and anharmonicities (within 1% and 10%, respectively) while coupling strengths exhibited larger discrepancies (30%). We discuss potential causes for measured coherence times falling below expectations (<inline-formula><tex-math>$T_{1}sim ,$</tex-math></inline-formula>1–2 <italic>μ</i>s) and propose strategies for future design improvements. Notably, we demonstrate the application of a hybrid 3D–2D simulation approach for energy participation ratio evaluation, yielding a more accurate estimation of dielectric losses. This work represents an important first step in developing planar quantum nondemolition single-photon counters for dark matter searches, particularly for axion and dark photon detection schemes.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"7 ","pages":"1-8"},"PeriodicalIF":4.6,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11249713","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145729280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-14DOI: 10.1109/TQE.2025.3632540
Miguel Palma;Shuwen Kan;Wenqi Wei;Juntao Chen;Kaixun Hua;Sara Mouradian;Ying Mao
The rapid expansion of quantum cloud services has led to long job queues due to single-tenant execution models that underutilize hardware resources. Quantum multiprogramming (QMP) mitigates this by executing multiple circuits in parallel on a single device, but existing methods target superconducting systems with limited connectivity, high crosstalk, and lower gate fidelity. Trapped-ion architecture, with all-to-all connectivity, long coherence times, and high-fidelity mid-circuit measurement properties, presents itself as a more suitable platform for scalable QMP. We present CircPack, a hardware-aware circuit packing framework designed for modular trapped-ion devices based on the quantum charge-coupled device (QCCD) architecture. CircPack formulates static circuit scheduling as a 2-D packing problem with hardware-specific shuttling constraints. Compared to superconducting-based QMP approaches, CircPack achieves up to 70.72% better fidelity, 62.67% higher utilization, and 32.80% improved layer reduction. This framework is also capable of scalable balanced scheduling across a cluster of independent QCCD modules, highlighting trapped-ion systems’ potential in improving the throughput of quantum cloud computing in the near future.
{"title":"Hardware-Aware and Resource-Efficient Circuit Packing and Scheduling on Trapped-Ion Quantum Computers","authors":"Miguel Palma;Shuwen Kan;Wenqi Wei;Juntao Chen;Kaixun Hua;Sara Mouradian;Ying Mao","doi":"10.1109/TQE.2025.3632540","DOIUrl":"https://doi.org/10.1109/TQE.2025.3632540","url":null,"abstract":"The rapid expansion of quantum cloud services has led to long job queues due to single-tenant execution models that underutilize hardware resources. Quantum multiprogramming (QMP) mitigates this by executing multiple circuits in parallel on a single device, but existing methods target superconducting systems with limited connectivity, high crosstalk, and lower gate fidelity. Trapped-ion architecture, with all-to-all connectivity, long coherence times, and high-fidelity mid-circuit measurement properties, presents itself as a more suitable platform for scalable QMP. We present CircPack, a hardware-aware circuit packing framework designed for modular trapped-ion devices based on the quantum charge-coupled device (QCCD) architecture. CircPack formulates static circuit scheduling as a 2-D packing problem with hardware-specific shuttling constraints. Compared to superconducting-based QMP approaches, CircPack achieves up to 70.72% better fidelity, 62.67% higher utilization, and 32.80% improved layer reduction. This framework is also capable of scalable balanced scheduling across a cluster of independent QCCD modules, highlighting trapped-ion systems’ potential in improving the throughput of quantum cloud computing in the near future.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"7 ","pages":"1-15"},"PeriodicalIF":4.6,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11249463","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145778454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Future communication systems are expected to integrate quantum networks to enable highly secure communication and enhance computational capabilities. In quantum networks, communication is accomplished by sharing entanglement between remote locations, which is the basis for most known quantum protocols. Entanglement is a correlation between qubits that is not reproducible with classical means. However, as entanglement is susceptible to noise limiting its range, quantum repeaters can enable entanglement over more considerable distances. Using the entanglement swapping protocol, quantum repeaters can be placed between remote locations to establish entanglement. This requires each repeater to first generate entanglement with its neighboring nodes, named entanglement generation. However, as the size of current quantum networks is limited, the development and evaluation of quantum networks and quantum protocols are based on simulations. To simulate quantum networks accurately, accurate and high-performance models of the entanglement generation process must be employed. This article proposes two new models for generating entanglement in simulations and develops quantum protocols for generating and purifying entanglement. The protocols are evaluated in thorough simulations under perfect and realistic conditions regarding delay and fidelity. Furthermore, the accuracy and runtime of the models are evaluated. The results show that the models are accurate, with delay primarily influenced by the source duration, while longer coherence times significantly enhance fidelity. The model runtimes are consistently shorter than the simulation runtimes across all protocols, averaging about 2% of the total simulation time.
{"title":"Combined Physical- and Link-Layer Protocols for Quantum Networks","authors":"Benedikt Baier;Ria Rosenauer;Vili Li;Christian Deppe;Wolfgang Kellerer","doi":"10.1109/TQE.2025.3630201","DOIUrl":"https://doi.org/10.1109/TQE.2025.3630201","url":null,"abstract":"Future communication systems are expected to integrate quantum networks to enable highly secure communication and enhance computational capabilities. In quantum networks, communication is accomplished by sharing entanglement between remote locations, which is the basis for most known quantum protocols. Entanglement is a correlation between qubits that is not reproducible with classical means. However, as entanglement is susceptible to noise limiting its range, quantum repeaters can enable entanglement over more considerable distances. Using the entanglement swapping protocol, quantum repeaters can be placed between remote locations to establish entanglement. This requires each repeater to first generate entanglement with its neighboring nodes, named entanglement generation. However, as the size of current quantum networks is limited, the development and evaluation of quantum networks and quantum protocols are based on simulations. To simulate quantum networks accurately, accurate and high-performance models of the entanglement generation process must be employed. This article proposes two new models for generating entanglement in simulations and develops quantum protocols for generating and purifying entanglement. The protocols are evaluated in thorough simulations under perfect and realistic conditions regarding delay and fidelity. Furthermore, the accuracy and runtime of the models are evaluated. The results show that the models are accurate, with delay primarily influenced by the source duration, while longer coherence times significantly enhance fidelity. The model runtimes are consistently shorter than the simulation runtimes across all protocols, averaging about 2% of the total simulation time.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"7 ","pages":"1-15"},"PeriodicalIF":4.6,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11231333","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145674778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-31DOI: 10.1109/TQE.2025.3626745
Linzhi Huang;Hanyu Pei;Yuechen Li;Beibei Yin;Kai-Yuan Cai
Quantum computing has emerged as an innovative computational paradigm with great potential in various domains. As quantum computing advances, the development of high-quality quantum programs has become crucial, making it essential to ensure their reliability. Software testing plays a vital role in achieving the reliability and quality of software systems. Various testing strategies and tools have been proposed for traditional programs; however, research on testing methodologies for quantum programs is still in the early stages. Traditional testing techniques, while effective for classical programs, struggle to address the unique challenges posed by quantum programs, including inherent characteristics of quantum systems (such as superposition and entanglement), and the exponentially expanding input space as the number of qubits increases. Moreover, traditional testing strategies typically do not account for the hidden and nondeterministic failure patterns associated with input quantum bits (qubits), which, if recognized, could potentially lead to more efficient fault detection. Therefore, in this article, we introduce a novel approach—Quantum Dynamic Testing with Incremental Learning (QDT-IL)—which aims to effectively capture and adapt to the failure patterns in quantum programs. QDT-IL employs an incremental learning model to learn from executed test cases and continuously updates its predictions on the failure tendencies for new test cases. By utilizing distance-based diversity metrics, QDT-IL strategically increases the variety of test cases, enabling targeted exploration of failure-prone regions in the input space. This combination of adaptive learning and diverse test case selection noticeably enhances the effectiveness and efficiency of quantum program testing. Experimental studies show that QDT-IL outperforms the baseline strategies, providing a more effective testing process for quantum programs.
{"title":"A Dynamic Testing Strategy With Incremental Learning Model for Quantum Programs","authors":"Linzhi Huang;Hanyu Pei;Yuechen Li;Beibei Yin;Kai-Yuan Cai","doi":"10.1109/TQE.2025.3626745","DOIUrl":"https://doi.org/10.1109/TQE.2025.3626745","url":null,"abstract":"Quantum computing has emerged as an innovative computational paradigm with great potential in various domains. As quantum computing advances, the development of high-quality quantum programs has become crucial, making it essential to ensure their reliability. Software testing plays a vital role in achieving the reliability and quality of software systems. Various testing strategies and tools have been proposed for traditional programs; however, research on testing methodologies for quantum programs is still in the early stages. Traditional testing techniques, while effective for classical programs, struggle to address the unique challenges posed by quantum programs, including inherent characteristics of quantum systems (such as superposition and entanglement), and the exponentially expanding input space as the number of qubits increases. Moreover, traditional testing strategies typically do not account for the hidden and nondeterministic failure patterns associated with input quantum bits (qubits), which, if recognized, could potentially lead to more efficient fault detection. Therefore, in this article, we introduce a novel approach—Quantum Dynamic Testing with Incremental Learning (QDT-IL)—which aims to effectively capture and adapt to the failure patterns in quantum programs. QDT-IL employs an incremental learning model to learn from executed test cases and continuously updates its predictions on the failure tendencies for new test cases. By utilizing distance-based diversity metrics, QDT-IL strategically increases the variety of test cases, enabling targeted exploration of failure-prone regions in the input space. This combination of adaptive learning and diverse test case selection noticeably enhances the effectiveness and efficiency of quantum program testing. Experimental studies show that QDT-IL outperforms the baseline strategies, providing a more effective testing process for quantum programs.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"7 ","pages":"1-27"},"PeriodicalIF":4.6,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11223239","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145674815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：