Pub Date : 2025-03-06DOI: 10.1109/TQE.2025.3567322
Claudio Cicconetti
While quantum computing technologies are evolving toward achieving full maturity, hybrid algorithms, such as variational quantum computing, are already emerging as valid candidates to solve practical problems in fields, such as chemistry and operations research. This situation calls for a tighter and better integration of classical and quantum computing infrastructures to improve efficiency and users' quality of service. Inspired by recent developments in cloud technologies, serverless computing has recently been considered a promising solution for this purpose by both industry and research. In this work, we define a system model for a hybrid classical–quantum serverless system, with an associated open-source numerical simulator that can be driven by production traces and stochastic workload models. We therefore describe how we produced a public dataset using IBM Qiskit in a local and remote infrastructure, with a sample application on optimization. The simulation results show initial insights on some distinguishing features of the platform simulated, measured in terms of user and system metrics, for jobs with heterogeneous problem sizes and priorities. We also report a few lessons we learned from developing the application with IBM Qiskit serverless and running it on IBM Quantum backends.
{"title":"Modeling and Performance Evaluation of Hybrid Classical–Quantum Serverless Computing Platforms","authors":"Claudio Cicconetti","doi":"10.1109/TQE.2025.3567322","DOIUrl":"https://doi.org/10.1109/TQE.2025.3567322","url":null,"abstract":"While quantum computing technologies are evolving toward achieving full maturity, hybrid algorithms, such as variational quantum computing, are already emerging as valid candidates to solve practical problems in fields, such as chemistry and operations research. This situation calls for a tighter and better integration of classical and quantum computing infrastructures to improve efficiency and users' quality of service. Inspired by recent developments in cloud technologies, serverless computing has recently been considered a promising solution for this purpose by both industry and research. In this work, we define a system model for a hybrid classical–quantum serverless system, with an associated open-source numerical simulator that can be driven by production traces and stochastic workload models. We therefore describe how we produced a public dataset using IBM Qiskit in a local and remote infrastructure, with a sample application on optimization. The simulation results show initial insights on some distinguishing features of the platform simulated, measured in terms of user and system metrics, for jobs with heterogeneous problem sizes and priorities. We also report a few lessons we learned from developing the application with IBM Qiskit serverless and running it on IBM Quantum backends.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"6 ","pages":"1-13"},"PeriodicalIF":0.0,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10989577","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144179118","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 : 2025-03-06DOI: 10.1109/TQE.2025.3548423
Che-Ming Chang;Jie-Hong Roland Jiang;Dah-Wei Chiou;Ting Hsu;Guin-Dar Lin
Trapped-ion technologies stand out as leading contenders in the pursuit of quantum computing, due to their capacity for highly entangled qubits. Among many proposed trapped-ion architectures, the “drive-through” architecture has drawn increasing attention, notably for its remarkable ability to minimize heat generation, which is crucial for low-temperature operation and thermal noise reduction, thus reliable quantum computation. We present the first compilation system tailored for the drive-through architecture to achieve high-fidelity computation for intended quantum programs. Our approach accommodates the unique features of the new architecture that utilize transport gates to facilitate direct entanglement between static qubits and communication qubits. We optimize the qubit placement that changes over time for each trap, considering the cost of qubit swapping. Our method strategically balances the gate and swap distances, significantly improving the overall fidelity across various benchmarks.
{"title":"Quantum Circuit Compilation for Trapped-Ion Processors With the Drive-Through Architecture","authors":"Che-Ming Chang;Jie-Hong Roland Jiang;Dah-Wei Chiou;Ting Hsu;Guin-Dar Lin","doi":"10.1109/TQE.2025.3548423","DOIUrl":"https://doi.org/10.1109/TQE.2025.3548423","url":null,"abstract":"Trapped-ion technologies stand out as leading contenders in the pursuit of quantum computing, due to their capacity for highly entangled qubits. Among many proposed trapped-ion architectures, the “drive-through” architecture has drawn increasing attention, notably for its remarkable ability to minimize heat generation, which is crucial for low-temperature operation and thermal noise reduction, thus reliable quantum computation. We present the first compilation system tailored for the drive-through architecture to achieve high-fidelity computation for intended quantum programs. Our approach accommodates the unique features of the new architecture that utilize transport gates to facilitate direct entanglement between static qubits and communication qubits. We optimize the qubit placement that changes over time for each trap, considering the cost of qubit swapping. Our method strategically balances the gate and swap distances, significantly improving the overall fidelity across various benchmarks.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"6 ","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10915697","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896233","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 : 2025-02-21DOI: 10.1109/TQE.2025.3544839
Claudio Sanavio;Enea Mauri;Sauro Succi
We assess the convergence of the Carleman linearization of advection–diffusion–reaction (ADR) equations with a logistic nonlinearity. It is shown that five Carleman iterates provide a satisfactory approximation of the original ADR across a broad range of parameters and strength of nonlinearity. To assess the feasibility of a quantum algorithm based on this linearization, we analyze the projection of the Carleman ADR matrix onto the tensor Pauli basis. It is found that the Carleman ADR matrix requires an exponential number of Pauli gates as a function of the number of qubits. This prevents the practical implementation of the Carleman approach to the quantum simulation of ADR problems on current hardware. We propose to address this limitation by resorting to block-encoding techniques for sparse matrix employing oracles. Such quantum ADR oracles are presented in explicit form and shown to turn the exponential complexity into a polynomial one. However, due to the low probability of successfully implementing the nonunitary Carleman operator, further research is needed to implement the multitimestep version of the present circuit.
{"title":"Explicit Quantum Circuit for Simulating the Advection–Diffusion–Reaction Dynamics","authors":"Claudio Sanavio;Enea Mauri;Sauro Succi","doi":"10.1109/TQE.2025.3544839","DOIUrl":"https://doi.org/10.1109/TQE.2025.3544839","url":null,"abstract":"We assess the convergence of the Carleman linearization of advection–diffusion–reaction (ADR) equations with a logistic nonlinearity. It is shown that five Carleman iterates provide a satisfactory approximation of the original ADR across a broad range of parameters and strength of nonlinearity. To assess the feasibility of a quantum algorithm based on this linearization, we analyze the projection of the Carleman ADR matrix onto the tensor Pauli basis. It is found that the Carleman ADR matrix requires an exponential number of Pauli gates as a function of the number of qubits. This prevents the practical implementation of the Carleman approach to the quantum simulation of ADR problems on current hardware. We propose to address this limitation by resorting to block-encoding techniques for sparse matrix employing oracles. Such quantum ADR oracles are presented in explicit form and shown to turn the exponential complexity into a polynomial one. However, due to the low probability of successfully implementing the nonunitary Carleman operator, further research is needed to implement the multitimestep version of the present circuit.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"6 ","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10899872","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143706764","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 : 2025-02-17DOI: 10.1109/TQE.2025.3542484
Marc Jofre
The combination of quantum and telecommunication networks enables to revolutionize the way information is used, offering unparalleled capabilities and making it an ideal choice for many critical applications. In this sense, quantum protocols generally have a unique requirement to have strict time synchronization in order to operate, which generally consume quantum resources of part of the exchanged qubits. Accordingly, work demonstrates and characterizes a temporal alignment mechanism for quantum networks based on frequency testing, allowing to preserve the quantum state of qubits. The time synchronization correction achieved is within 100 ns working at 5 MHz with temporal and relative frequency offsets commonly acquired in quantum links using conventional hardware clocks with temporal stability in the range of $10^{-8}$ and 200-ns jitter.
{"title":"Qubit Rate Modulation-Based Time Synchronization Mechanism for Multinode Quantum Networks","authors":"Marc Jofre","doi":"10.1109/TQE.2025.3542484","DOIUrl":"https://doi.org/10.1109/TQE.2025.3542484","url":null,"abstract":"The combination of quantum and telecommunication networks enables to revolutionize the way information is used, offering unparalleled capabilities and making it an ideal choice for many critical applications. In this sense, quantum protocols generally have a unique requirement to have strict time synchronization in order to operate, which generally consume quantum resources of part of the exchanged qubits. Accordingly, work demonstrates and characterizes a temporal alignment mechanism for quantum networks based on frequency testing, allowing to preserve the quantum state of qubits. The time synchronization correction achieved is within 100 ns working at 5 MHz with temporal and relative frequency offsets commonly acquired in quantum links using conventional hardware clocks with temporal stability in the range of <inline-formula> <tex-math>$10^{-8}$</tex-math></inline-formula> and 200-ns jitter.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"6 ","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10891179","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611832","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}
In silicon quantum computers, a single electron is trapped in a microstructure called a quantum dot, and its spin is used as a qubit. For large-scale integration of qubits, we previously proposed an approach of sharing a control gate in the row or column of a 2-D quantum dot array. In our array, the shuttling of electrons is a useful technique to operate the target qubit independently and avoid crosstalk. However, since the shuttling is also conducted using shared control gates, the movement of qubits is complexly constrained. We, therefore, propose a formal model based on state transition systems to describe those constraints and operation procedures on the array. We also present an approach to generate operation procedures under the constraints. Utilizing this approach, we present a concrete method for our 16 × 8 quantum dot array. By implementing the proposed method as a quantum compiler, we confirmed that it is possible to generate operation procedures in a practical amount of time for arbitrary quantum circuits. We also demonstrated that crosstalk can be avoided by shuttling and that the fidelity in that case is higher than when crosstalk is not avoided.
{"title":"Generating Shuttling Procedures for Constrained Silicon Quantum Dot Array","authors":"Naoto Sato;Tomonori Sekiguchi;Takeru Utsugi;Hiroyuki Mizuno","doi":"10.1109/TQE.2025.3542462","DOIUrl":"https://doi.org/10.1109/TQE.2025.3542462","url":null,"abstract":"In silicon quantum computers, a single electron is trapped in a microstructure called a quantum dot, and its spin is used as a qubit. For large-scale integration of qubits, we previously proposed an approach of sharing a control gate in the row or column of a 2-D quantum dot array. In our array, the shuttling of electrons is a useful technique to operate the target qubit independently and avoid crosstalk. However, since the shuttling is also conducted using shared control gates, the movement of qubits is complexly constrained. We, therefore, propose a formal model based on state transition systems to describe those constraints and operation procedures on the array. We also present an approach to generate operation procedures under the constraints. Utilizing this approach, we present a concrete method for our 16 × 8 quantum dot array. By implementing the proposed method as a quantum compiler, we confirmed that it is possible to generate operation procedures in a practical amount of time for arbitrary quantum circuits. We also demonstrated that crosstalk can be avoided by shuttling and that the fidelity in that case is higher than when crosstalk is not avoided.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"6 ","pages":"1-38"},"PeriodicalIF":0.0,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10890998","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621676","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 : 2025-02-13DOI: 10.1109/TQE.2025.3541882
Diego Alvarez-Estevez
Quantum-enhanced machine learning is a rapidly evolving field that aims to leverage the unique properties of quantum mechanics to enhance classical machine learning. However, the practical applicability of these methods remains an open question, particularly beyond the context of specifically crafted toy problems, and given the current limitations of quantum hardware. This study focuses on quantum kernel methods in the context of classification tasks. In particular, it examines the performance of quantum kernel estimation and quantum kernel training (QKT) in connection with two quantum feature mappings, namely, ZZFeatureMap and CovariantFeatureMap. Remarkably, these feature maps have been proposed in the literature under the conjecture of possible near-term quantum advantage and have shown promising performance in ad hoc datasets. This study aims to evaluate their versatility and generalization capabilities in a more general benchmark, encompassing both artificial and established reference datasets. Classical machine learning methods, specifically support vector machines and logistic regression, are also incorporated as baseline comparisons. Experimental results indicate that quantum methods exhibit varying performance across different datasets. Despite outperforming classical methods in ad hoc datasets, mixed results are obtained for the general case among standard classical benchmarks. The experimental data call into question a general added value of applying QKT optimization, for which the additional computational cost does not necessarily translate into improved classification performance. Instead, it is suggested that a careful choice of the quantum feature map in connection with proper hyperparameterization may prove more effective.
{"title":"Benchmarking Quantum Machine Learning Kernel Training for Classification Tasks","authors":"Diego Alvarez-Estevez","doi":"10.1109/TQE.2025.3541882","DOIUrl":"https://doi.org/10.1109/TQE.2025.3541882","url":null,"abstract":"Quantum-enhanced machine learning is a rapidly evolving field that aims to leverage the unique properties of quantum mechanics to enhance classical machine learning. However, the practical applicability of these methods remains an open question, particularly beyond the context of specifically crafted toy problems, and given the current limitations of quantum hardware. This study focuses on quantum kernel methods in the context of classification tasks. In particular, it examines the performance of quantum kernel estimation and quantum kernel training (QKT) in connection with two quantum feature mappings, namely, ZZFeatureMap and CovariantFeatureMap. Remarkably, these feature maps have been proposed in the literature under the conjecture of possible near-term quantum advantage and have shown promising performance in ad hoc datasets. This study aims to evaluate their versatility and generalization capabilities in a more general benchmark, encompassing both artificial and established reference datasets. Classical machine learning methods, specifically support vector machines and logistic regression, are also incorporated as baseline comparisons. Experimental results indicate that quantum methods exhibit varying performance across different datasets. Despite outperforming classical methods in ad hoc datasets, mixed results are obtained for the general case among standard classical benchmarks. The experimental data call into question a general added value of applying QKT optimization, for which the additional computational cost does not necessarily translate into improved classification performance. Instead, it is suggested that a careful choice of the quantum feature map in connection with proper hyperparameterization may prove more effective.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"6 ","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10884820","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716524","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 : 2025-02-11DOI: 10.1109/TQE.2025.3541123
Amar Abane;Michael Cubeddu;Van Sy Mai;Abdella Battou
Entanglement routing in near-term quantum networks consists of choosing the optimal sequence of short-range entanglements to combine through swapping operations to establish end-to-end entanglement between two distant nodes. Similar to traditional routing technologies, a quantum routing protocol uses network information to choose the best paths to satisfy a set of end-to-end entanglement requests. However, in addition to network state information, a quantum routing protocol must also take into account the requested entanglement fidelity, the probabilistic nature of swapping operations, and the short lifetime of entangled states. In this work, we formulate a practical entanglement routing problem and analyze and categorize the main approaches to address it, drawing comparisons to, and inspiration from, classical network routing strategies where applicable. We classify and discuss the studied quantum routing schemes into reactive, proactive, and hybrid routing.
{"title":"Entanglement Routing in Quantum Networks: A Comprehensive Survey","authors":"Amar Abane;Michael Cubeddu;Van Sy Mai;Abdella Battou","doi":"10.1109/TQE.2025.3541123","DOIUrl":"https://doi.org/10.1109/TQE.2025.3541123","url":null,"abstract":"Entanglement routing in near-term quantum networks consists of choosing the optimal sequence of short-range entanglements to combine through swapping operations to establish end-to-end entanglement between two distant nodes. Similar to traditional routing technologies, a quantum routing protocol uses network information to choose the best paths to satisfy a set of end-to-end entanglement requests. However, in addition to network state information, a quantum routing protocol must also take into account the requested entanglement fidelity, the probabilistic nature of swapping operations, and the short lifetime of entangled states. In this work, we formulate a practical entanglement routing problem and analyze and categorize the main approaches to address it, drawing comparisons to, and inspiration from, classical network routing strategies where applicable. We classify and discuss the studied quantum routing schemes into reactive, proactive, and hybrid routing.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"6 ","pages":"1-39"},"PeriodicalIF":0.0,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10882978","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143570564","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 : 2025-02-05DOI: 10.1109/TQE.2025.3538934
Mark A. Webster;Dan E. Browne
Quantum error correction and the use of quantum error correction codes are likely to be essential for the realization of practical quantum computing. Because the error models of quantum devices vary widely, quantum codes that are tailored for a particular error model may have much better performance. In this work, we present a novel evolutionary algorithm that searches for an optimal stabilizer code for a given error model, number of physical qubits, and number of encoded qubits. We demonstrate an efficient representation of stabilizer codes as binary strings, which allows for random generation of valid stabilizer codes as well as mutation and crossing of codes. Our algorithm finds stabilizer codes whose distance closely matches the best-known-distance codes of Grassl (2007) for $n leq 20$ physical qubits. We perform a search for optimal distance Calderbank–Steane–Shor codes and compare their distance to the best known codes. Finally, we show that the algorithm can be used to optimize stabilizer codes for biased error models, demonstrating a significant improvement in the undetectable error rate for $[[12,1]]_{2}$ codes versus the best-known-distance code with the same parameters. As part of this work, we also introduce an evolutionary algorithm QDistEvol for finding the distance of quantum error correction codes.
{"title":"Engineering Quantum Error Correction Codes Using Evolutionary Algorithms","authors":"Mark A. Webster;Dan E. Browne","doi":"10.1109/TQE.2025.3538934","DOIUrl":"https://doi.org/10.1109/TQE.2025.3538934","url":null,"abstract":"Quantum error correction and the use of quantum error correction codes are likely to be essential for the realization of practical quantum computing. Because the error models of quantum devices vary widely, quantum codes that are tailored for a particular error model may have much better performance. In this work, we present a novel evolutionary algorithm that searches for an optimal stabilizer code for a given error model, number of physical qubits, and number of encoded qubits. We demonstrate an efficient representation of stabilizer codes as binary strings, which allows for random generation of valid stabilizer codes as well as mutation and crossing of codes. Our algorithm finds stabilizer codes whose distance closely matches the best-known-distance codes of Grassl (2007) for <inline-formula><tex-math>$n leq 20$</tex-math></inline-formula> physical qubits. We perform a search for optimal distance Calderbank–Steane–Shor codes and compare their distance to the best known codes. Finally, we show that the algorithm can be used to optimize stabilizer codes for biased error models, demonstrating a significant improvement in the undetectable error rate for <inline-formula><tex-math>$[[12,1]]_{2}$</tex-math></inline-formula> codes versus the best-known-distance code with the same parameters. As part of this work, we also introduce an evolutionary algorithm QDistEvol for finding the distance of quantum error correction codes.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"6 ","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10874169","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143564005","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 : 2025-01-29DOI: 10.1109/TQE.2025.3535823
Alessio Di Santo;Walter Tiberti;Dajana Cassioli
Quantum secret sharing (QSS) is a cryptographic protocol that leverages quantum mechanics to distribute a secret among multiple parties. With respect to the classical counterpart, in QSS, the secret is encoded into quantum states and shared by a dealer such that only an authorized subsets of participants, i.e., the players, can reconstruct it. Several state-of-the-art studies aim to transpose classical secret sharing into the quantum realm, while maintaining their reliance on traditional network topologies (e.g., star, ring, and fully connected), and require that all the $n$ players calculate the secret. These studies exploit the Greenberger–Horne–Zeilinger state, which is a type of maximally entangled quantum state involving three or more qubits. However, none of these works account for redundancy, enhanced security/privacy features, or authentication mechanisms able to fingerprint players. To address these gaps, in this article, we introduce a new concept of QSS, which leans on a generic distributed quantum network, based on a threshold scheme, where all the players collaborate also to the routing of quantum information among them. The dealer, by exploiting a custom flexible weighting system, takes advantage of a newly defined quantum Dijkstra algorithm to select the most suitable subset of $t$ players, out of the entire set on $n$ players, to involve in the computation. To fingerprint and authenticate users, CRYSTAL-Kyber primitives are adopted, while also protecting each player’s privacy by hiding their identities. We show the effectiveness and performance of the proposed protocol by testing it against the main classical and quantum attacks, thereby improving the state-of-the-art security measures.
{"title":"Security and Fairness in Multiparty Quantum Secret Sharing Protocol","authors":"Alessio Di Santo;Walter Tiberti;Dajana Cassioli","doi":"10.1109/TQE.2025.3535823","DOIUrl":"https://doi.org/10.1109/TQE.2025.3535823","url":null,"abstract":"Quantum secret sharing (QSS) is a cryptographic protocol that leverages quantum mechanics to distribute a secret among multiple parties. With respect to the classical counterpart, in QSS, the secret is encoded into quantum states and shared by a dealer such that only an authorized subsets of participants, i.e., the players, can reconstruct it. Several state-of-the-art studies aim to transpose classical secret sharing into the quantum realm, while maintaining their reliance on traditional network topologies (e.g., star, ring, and fully connected), and require that all the <inline-formula><tex-math>$n$</tex-math></inline-formula> players calculate the secret. These studies exploit the Greenberger–Horne–Zeilinger state, which is a type of maximally entangled quantum state involving three or more qubits. However, none of these works account for redundancy, enhanced security/privacy features, or authentication mechanisms able to fingerprint players. To address these gaps, in this article, we introduce a new concept of QSS, which leans on a generic distributed quantum network, based on a threshold scheme, where all the players collaborate also to the routing of quantum information among them. The dealer, by exploiting a custom flexible weighting system, takes advantage of a newly defined quantum Dijkstra algorithm to select the most suitable subset of <inline-formula><tex-math>$t$</tex-math></inline-formula> players, out of the entire set on <inline-formula><tex-math>$n$</tex-math></inline-formula> players, to involve in the computation. To fingerprint and authenticate users, CRYSTAL-Kyber primitives are adopted, while also protecting each player’s privacy by hiding their identities. We show the effectiveness and performance of the proposed protocol by testing it against the main classical and quantum attacks, thereby improving the state-of-the-art security measures.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"6 ","pages":"1-18"},"PeriodicalIF":0.0,"publicationDate":"2025-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10857623","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143521454","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 : 2025-01-28DOI: 10.1109/TQE.2025.3535319
{"title":"2024 Index IEEE Transactions on Quantum Engineering Vol. 5","authors":"","doi":"10.1109/TQE.2025.3535319","DOIUrl":"https://doi.org/10.1109/TQE.2025.3535319","url":null,"abstract":"","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2025-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10856694","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106065","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}
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