Pub Date : 2024-11-27DOI: 10.1109/TQE.2024.3507155
Nishanth Chandra;Pradeep Kumar Krishnamurthy
In this article, we propose and experimentally demonstrate a novel synchronization method for quantum key distribution (QKD) systems. The method consists of maximizing the visibility of frequency-domain interference of optical sidebands about an optical carrier at the receiver node. The sidebands are generated by phase modulation of the optical carrier by an radio-frequency (RF) signal whose phase can be dynamically varied. The phase-variable RF signal is generated by the field-programmable gate array (FPGA) at the transmitter and the receiver using GTX transceivers. In order to facilitate this, we use square waveforms for RF signal instead of the conventional sinusoidal signals. We derive mathematical expressions for sideband power as a function of the phase difference between RF signals at transmitter and receiver. The phase is adjusted using dynamic phase shifter module, implemented by the FPGA. We propose a complete workflow that allows transmitter and receiver synchronization to within 12.6 ps directly over the quantum channel of QKD systems. Once synchronized, the same system can be switched over to quantum transmission by user-defined time delay. The workflow was implemented on a Xilinx Kintex-7 KC705 FPGA board. We studied the robustness of our technique by evaluating the stability of the interferometer over an operation of 10 min with standard deviation of interference to be less than 9% of the mean detection amplitude.
{"title":"FPGA-Based Synchronization of Frequency-Domain Interferometer for QKD","authors":"Nishanth Chandra;Pradeep Kumar Krishnamurthy","doi":"10.1109/TQE.2024.3507155","DOIUrl":"https://doi.org/10.1109/TQE.2024.3507155","url":null,"abstract":"In this article, we propose and experimentally demonstrate a novel synchronization method for quantum key distribution (QKD) systems. The method consists of maximizing the visibility of frequency-domain interference of optical sidebands about an optical carrier at the receiver node. The sidebands are generated by phase modulation of the optical carrier by an radio-frequency (RF) signal whose phase can be dynamically varied. The phase-variable RF signal is generated by the field-programmable gate array (FPGA) at the transmitter and the receiver using GTX transceivers. In order to facilitate this, we use square waveforms for RF signal instead of the conventional sinusoidal signals. We derive mathematical expressions for sideband power as a function of the phase difference between RF signals at transmitter and receiver. The phase is adjusted using dynamic phase shifter module, implemented by the FPGA. We propose a complete workflow that allows transmitter and receiver synchronization to within 12.6 ps directly over the quantum channel of QKD systems. Once synchronized, the same system can be switched over to quantum transmission by user-defined time delay. The workflow was implemented on a Xilinx Kintex-7 KC705 FPGA board. We studied the robustness of our technique by evaluating the stability of the interferometer over an operation of 10 min with standard deviation of interference to be less than 9% of the mean detection amplitude.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"6 ","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10769019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825841","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 : 2024-11-18DOI: 10.1109/TQE.2024.3501683
Miloš Prokop;Petros Wallden;David Joseph
Finding the shortest vector in a lattice is a problem that is believed to be hard both for classical and quantum computers. Many major postquantum secure cryptosystems base their security on the hardness of the shortest vector problem (SVP) (Moody, 2023). Finding the best classical, quantum, or hybrid classical–quantum algorithms for the SVP is necessary to select cryptosystem parameters that offer a sufficient level of security. Grover's search quantum algorithm provides a generic quadratic speedup, given access to an oracle implementing some function, which describes when a solution is found. In this article, we provide concrete implementation of such an oracle for the SVP. We define the circuit and evaluate costs in terms of the number of qubits, the number of gates, depth, and T-quantum cost. We then analyze how to combine Grover's quantum search for small SVP instances with state-of-the-art classical solvers that use well-known algorithms, such as the block Korkine Zolotorev (Schnorr and Euchner, 1994), where the former is used as a subroutine. This could enable solving larger instances of SVP with higher probability than classical state-of-the-art records, but still very far from posing any threat to cryptosystems being considered for standardization. Depending on the technology available, there is a spectrum of tradeoffs in creating this combination.
{"title":"Grover's Oracle for the Shortest Vector Problem and Its Application in Hybrid Classical–Quantum Solvers","authors":"Miloš Prokop;Petros Wallden;David Joseph","doi":"10.1109/TQE.2024.3501683","DOIUrl":"https://doi.org/10.1109/TQE.2024.3501683","url":null,"abstract":"Finding the shortest vector in a lattice is a problem that is believed to be hard both for classical and quantum computers. Many major postquantum secure cryptosystems base their security on the hardness of the shortest vector problem (SVP) (Moody, 2023). Finding the best classical, quantum, or hybrid classical–quantum algorithms for the SVP is necessary to select cryptosystem parameters that offer a sufficient level of security. Grover's search quantum algorithm provides a generic quadratic speedup, given access to an oracle implementing some function, which describes when a solution is found. In this article, we provide concrete implementation of such an oracle for the SVP. We define the circuit and evaluate costs in terms of the number of qubits, the number of gates, depth, and T-quantum cost. We then analyze how to combine Grover's quantum search for small SVP instances with state-of-the-art classical solvers that use well-known algorithms, such as the block Korkine Zolotorev (Schnorr and Euchner, 1994), where the former is used as a subroutine. This could enable solving larger instances of SVP with higher probability than classical state-of-the-art records, but still very far from posing any threat to cryptosystems being considered for standardization. Depending on the technology available, there is a spectrum of tradeoffs in creating this combination.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"6 ","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10756628","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825840","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 : 2024-10-30DOI: 10.1109/TQE.2024.3488518
Jorge M. Ramirez;Elaine Wong;Caio Alves;Sarah Chehade;Ryan Bennink
This study investigates the frame potential and expressiveness of commutative quantum circuits. Based on the Fourier series representation of these circuits, we express quantum expectation and pairwise fidelity as characteristic functions of random variables, and we characterize expressiveness as the recurrence probability of a random walk on a lattice. A central outcome of our work includes formulas to approximate the frame potential and expressiveness for any commutative quantum circuit, underpinned by convergence theorems in the probability theory. We identify the lattice volume of the random walk as means to approximate expressiveness based on circuit architecture. In the specific case of commutative circuits involving Pauli- $Z$ rotations, we provide theoretical results relating expressiveness and circuit structure. Our probabilistic representation also provides means for bounding and approximately calculating the frame potential of a circuit through sampling methods.
{"title":"Expressiveness of Commutative Quantum Circuits: A Probabilistic Approach","authors":"Jorge M. Ramirez;Elaine Wong;Caio Alves;Sarah Chehade;Ryan Bennink","doi":"10.1109/TQE.2024.3488518","DOIUrl":"https://doi.org/10.1109/TQE.2024.3488518","url":null,"abstract":"This study investigates the frame potential and expressiveness of commutative quantum circuits. Based on the Fourier series representation of these circuits, we express quantum expectation and pairwise fidelity as characteristic functions of random variables, and we characterize expressiveness as the recurrence probability of a random walk on a lattice. A central outcome of our work includes formulas to approximate the frame potential and expressiveness for any commutative quantum circuit, underpinned by convergence theorems in the probability theory. We identify the lattice volume of the random walk as means to approximate expressiveness based on circuit architecture. In the specific case of commutative circuits involving Pauli-\u0000<inline-formula><tex-math>$Z$</tex-math></inline-formula>\u0000 rotations, we provide theoretical results relating expressiveness and circuit structure. Our probabilistic representation also provides means for bounding and approximately calculating the frame potential of a circuit through sampling methods.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10738429","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142736338","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 : 2024-10-25DOI: 10.1109/TQE.2024.3486546
Benjamin Gys;Lander Burgelman;Kristiaan De Greve;Georges Gielen;Francky Catthoor
The development of future full-scale quantum computers (QCs) not only comprises the design of good quality qubits, but also entails the design of classical complementary metal–oxide semiconductor (CMOS) control circuitry and optimized operation protocols. The construction and implementation of quantum error correction (QEC) protocols, necessary for correcting the errors that inevitably occur in the physical qubit layer, form a crucial step in this design process. The steadily rising numbers of qubits in a single system make the development of small-scale quantum architectures that are able to execute such protocols a pressing challenge. Similar to classical systems, optimized simulation tools can greatly improve the efficiency of the design process. We propose an automated simulation framework for the development of qubit microarchitectures, in which the effects of design choices in the physical qubit layer on the performance of QEC protocols can be evaluated, whereas the focus in the current state-of-the-art design tools only lies on the simulation of the individual quantum gates. The hybrid Hamiltonian framework introduces the innovative combination of a hybrid nature that allows to incorporate several levels throughout the QC stack, with optimized embedded solvers. This provides the level of detail required for an in-depth analysis of the QEC protocol's stability.
{"title":"Hybrid Hamiltonian Simulation Approach for the Analysis of Quantum Error Correction Protocol Robustness","authors":"Benjamin Gys;Lander Burgelman;Kristiaan De Greve;Georges Gielen;Francky Catthoor","doi":"10.1109/TQE.2024.3486546","DOIUrl":"https://doi.org/10.1109/TQE.2024.3486546","url":null,"abstract":"The development of future full-scale quantum computers (QCs) not only comprises the design of good quality qubits, but also entails the design of classical complementary metal–oxide semiconductor (CMOS) control circuitry and optimized operation protocols. The construction and implementation of quantum error correction (QEC) protocols, necessary for correcting the errors that inevitably occur in the physical qubit layer, form a crucial step in this design process. The steadily rising numbers of qubits in a single system make the development of small-scale quantum architectures that are able to execute such protocols a pressing challenge. Similar to classical systems, optimized simulation tools can greatly improve the efficiency of the design process. We propose an automated simulation framework for the development of qubit microarchitectures, in which the effects of design choices in the physical qubit layer on the performance of QEC protocols can be evaluated, whereas the focus in the current state-of-the-art design tools only lies on the simulation of the individual quantum gates. The hybrid Hamiltonian framework introduces the innovative combination of a hybrid nature that allows to incorporate several levels throughout the QC stack, with optimized embedded solvers. This provides the level of detail required for an in-depth analysis of the QEC protocol's stability.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10735416","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142691744","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 this article, we study a Grover-type method for quadratic unconstrained binary optimization (QUBO) problems. For an $n$ -dimensional QUBO problem with $m$ nonzero terms, we construct a marker oracle for such problems with a tunable parameter, $Lambda in [ 1, m ] cap mathbb {Z}$ . At $d in mathbb {Z}_+$ precision, the oracle uses $O (n + Lambda d)$ qubits and has total depth of $O (frac{m}{Lambda } log _{2} (n) + log _{2} (d))$ and a non-Clifford depth of $O (frac{m}{Lambda })$ . Moreover, each qubit is required to be connected to at most $O (log _{2} (Lambda + d))$ other qubits. In the case of a maximum graph cuts, as $d = 2 leftlceil log _{2} (n) rightrceil$ always suffices, the depth of the marker oracle can be made as shallow as $O (log _{2} (n))$ . For all values of $Lambda$ , the non-Clifford gate count of these oracles is strictly lower (at least by a factor of $sim 2$ ) than previous constructions. Furthermore, we introduce a novel fixed-point Grover adaptive search for QUBO problems, using our oracle design and a hybrid fixed-point Grover search, motivated by the works of Boyer et al. (1988) and Li et al. (2019). This method has better performance guarantees than previous Grover adaptive search methods. Some of our results are novel and useful for any method based on the fixed-point Grover search. Finally, we give a heuristic argument that, with high probability and in $O (frac{log _{2} (n)}{sqrt{epsilon }})$ time, this adaptive method finds a configuration that is among the best $epsilon 2^{n}$ ones.
{"title":"Fixed-Point Grover Adaptive Search for Quadratic Binary Optimization Problems","authors":"Ákos Nagy;Jaime Park;Cindy Zhang;Atithi Acharya;Alex Khan","doi":"10.1109/TQE.2024.3484650","DOIUrl":"https://doi.org/10.1109/TQE.2024.3484650","url":null,"abstract":"In this article, we study a Grover-type method for quadratic unconstrained binary optimization (QUBO) problems. For an \u0000<inline-formula><tex-math>$n$</tex-math></inline-formula>\u0000-dimensional QUBO problem with \u0000<inline-formula><tex-math>$m$</tex-math></inline-formula>\u0000 nonzero terms, we construct a marker oracle for such problems with a tunable parameter, \u0000<inline-formula><tex-math>$Lambda in [ 1, m ] cap mathbb {Z}$</tex-math></inline-formula>\u0000. At \u0000<inline-formula><tex-math>$d in mathbb {Z}_+$</tex-math></inline-formula>\u0000 precision, the oracle uses \u0000<inline-formula><tex-math>$O (n + Lambda d)$</tex-math></inline-formula>\u0000 qubits and has total depth of \u0000<inline-formula><tex-math>$O (frac{m}{Lambda } log _{2} (n) + log _{2} (d))$</tex-math></inline-formula>\u0000 and a non-Clifford depth of \u0000<inline-formula><tex-math>$O (frac{m}{Lambda })$</tex-math></inline-formula>\u0000. Moreover, each qubit is required to be connected to at most \u0000<inline-formula><tex-math>$O (log _{2} (Lambda + d))$</tex-math></inline-formula>\u0000 other qubits. In the case of a maximum graph cuts, as \u0000<inline-formula><tex-math>$d = 2 leftlceil log _{2} (n) rightrceil$</tex-math></inline-formula>\u0000 always suffices, the depth of the marker oracle can be made as shallow as \u0000<inline-formula><tex-math>$O (log _{2} (n))$</tex-math></inline-formula>\u0000. For all values of \u0000<inline-formula><tex-math>$Lambda$</tex-math></inline-formula>\u0000, the non-Clifford gate count of these oracles is strictly lower (at least by a factor of \u0000<inline-formula><tex-math>$sim 2$</tex-math></inline-formula>\u0000) than previous constructions. Furthermore, we introduce a novel fixed-point Grover adaptive search for QUBO problems, using our oracle design and a hybrid fixed-point Grover search, motivated by the works of Boyer et al. (1988) and Li et al. (2019). This method has better performance guarantees than previous Grover adaptive search methods. Some of our results are novel and useful for any method based on the fixed-point Grover search. Finally, we give a heuristic argument that, with high probability and in \u0000<inline-formula><tex-math>$O (frac{log _{2} (n)}{sqrt{epsilon }})$</tex-math></inline-formula>\u0000 time, this adaptive method finds a configuration that is among the best \u0000<inline-formula><tex-math>$epsilon 2^{n}$</tex-math></inline-formula>\u0000 ones.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10726869","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142679411","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 : 2024-10-16DOI: 10.1109/TQE.2024.3476009
Mohadeseh Azari;Paul Polakos;Kaushik P. Seshadreesan
The Gottesman–Kitaev–Preskill (GKP) code, being information theoretically near optimal for quantum communication over Gaussian thermal-loss optical channels, is likely to be the encoding of choice for advanced quantum networks of the future. Quantum repeaters based on GKP-encoded light have been shown to support high end-to-end entanglement rates across large distances despite realistic finite squeezing in GKP code preparation and homodyne detection inefficiencies. Here, we introduce a quantum switch for GKP qubit-based quantum networks. Its architecture involves multiplexed GKP qubit-based entanglement link generation with clients and their all-photonic storage, enabled by GKP qubit graph state resources. The switch uses a multiclient generalization of a recently introduced entanglement-ranking-based link matching heuristic for bipartite entanglement distribution between clients via entanglement swapping. Since generating the GKP qubit graph state resource is hardware intensive, given a total resource budget and an arbitrary layout of clients, we address the question of their optimal allocation to the different client–pair connections served by the switch such that the switch's sum throughput is maximized while also being fair in terms of the individual entanglement rates. We illustrate our results for an exemplary data center network, where the data center is a client of a switch, and all of its other clients aim to connect to the data center alone—a scenario that also captures the general case of a gateway router connecting a local area network to a global network. Together with compatible quantum repeaters, our quantum switch provides a way to realize quantum networks of arbitrary topology.
{"title":"Quantum Switches for Gottesman–Kitaev–Preskill Qubit-Based All-Photonic Quantum Networks","authors":"Mohadeseh Azari;Paul Polakos;Kaushik P. Seshadreesan","doi":"10.1109/TQE.2024.3476009","DOIUrl":"https://doi.org/10.1109/TQE.2024.3476009","url":null,"abstract":"The Gottesman–Kitaev–Preskill (GKP) code, being information theoretically near optimal for quantum communication over Gaussian thermal-loss optical channels, is likely to be the encoding of choice for advanced quantum networks of the future. Quantum repeaters based on GKP-encoded light have been shown to support high end-to-end entanglement rates across large distances despite realistic finite squeezing in GKP code preparation and homodyne detection inefficiencies. Here, we introduce a quantum switch for GKP qubit-based quantum networks. Its architecture involves multiplexed GKP qubit-based entanglement link generation with clients and their all-photonic storage, enabled by GKP qubit graph state resources. The switch uses a multiclient generalization of a recently introduced entanglement-ranking-based link matching heuristic for bipartite entanglement distribution between clients via entanglement swapping. Since generating the GKP qubit graph state resource is hardware intensive, given a total resource budget and an arbitrary layout of clients, we address the question of their optimal allocation to the different client–pair connections served by the switch such that the switch's sum throughput is maximized while also being fair in terms of the individual entanglement rates. We illustrate our results for an exemplary data center network, where the data center is a client of a switch, and all of its other clients aim to connect to the data center alone—a scenario that also captures the general case of a gateway router connecting a local area network to a global network. Together with compatible quantum repeaters, our quantum switch provides a way to realize quantum networks of arbitrary topology.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10720623","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672018","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 : 2024-10-15DOI: 10.1109/TQE.2024.3481280
Yifeng Peng;Xinyi Li;Zhiding Liang;Ying Wang
As fifth-generation (5G) and next-generation communication systems advance and find widespread application in critical infrastructures, the importance of vulnerability detection becomes increasingly critical. The growing complexity of these systems necessitates rigorous testing and analysis, with stringent requirements for both accuracy and speed. In this article, we present a state-of-the-art supervised hybrid quantum neural network named HyQ2 for vulnerability detection in next-generation wireless communication systems. The proposed HyQ2 is integrated with graph-embedded and quantum variational circuits to validate and detect vulnerabilities from the 5G system's state transitions based on graphs extracted from log files. We address the limitations of classical machine learning models in processing the intrinsic linkage relationships of high-dimensional data. These models often suffer from dead neurons and excessively large outputs caused by the unbounded range of the rectified linear unit (ReLU) activation function. We propose the HyQ2 method to overcome these challenges, which constructs quantum neurons by selecting random neurons' outputs from a classical neural network. These quantum neurons are then utilized to capture more complex relationships, effectively limiting the ReLU output. Using only two qubits, our validation results demonstrate that HyQ2 outperforms traditional classical machine learning models in vulnerability detection. The small and compact variational circuit of HyQ2 minimizes the noise and errors in the measurement. Our results demonstrate that HyQ2 achieves a high area under the curve (AUC) value of 0.9708 and an accuracy of 95.91%. To test the model's performance in quantum noise environments, we simulate quantum noise by adding bit flipping, phase flipping, amplitude damping, and depolarizing noise. The results show that the prediction accuracy and receiver operating characteristic AUC value fluctuate around 0.2%, indicating HyQ2’s robustness in noisy quantum environments. In addition, the noise resilience and robustness of the HyQ2 algorithm were substantiated through experiments on the IBM quantum machine with only a 0.2% decrease compared to the simulation results.
{"title":"HyQ2: A Hybrid Quantum Neural Network for NextG Vulnerability Detection","authors":"Yifeng Peng;Xinyi Li;Zhiding Liang;Ying Wang","doi":"10.1109/TQE.2024.3481280","DOIUrl":"https://doi.org/10.1109/TQE.2024.3481280","url":null,"abstract":"As fifth-generation (5G) and next-generation communication systems advance and find widespread application in critical infrastructures, the importance of vulnerability detection becomes increasingly critical. The growing complexity of these systems necessitates rigorous testing and analysis, with stringent requirements for both accuracy and speed. In this article, we present a state-of-the-art supervised hybrid quantum neural network named HyQ2 for vulnerability detection in next-generation wireless communication systems. The proposed HyQ2 is integrated with graph-embedded and quantum variational circuits to validate and detect vulnerabilities from the 5G system's state transitions based on graphs extracted from log files. We address the limitations of classical machine learning models in processing the intrinsic linkage relationships of high-dimensional data. These models often suffer from dead neurons and excessively large outputs caused by the unbounded range of the rectified linear unit (ReLU) activation function. We propose the HyQ2 method to overcome these challenges, which constructs quantum neurons by selecting random neurons' outputs from a classical neural network. These quantum neurons are then utilized to capture more complex relationships, effectively limiting the ReLU output. Using only two qubits, our validation results demonstrate that HyQ2 outperforms traditional classical machine learning models in vulnerability detection. The small and compact variational circuit of HyQ2 minimizes the noise and errors in the measurement. Our results demonstrate that HyQ2 achieves a high area under the curve (AUC) value of 0.9708 and an accuracy of 95.91%. To test the model's performance in quantum noise environments, we simulate quantum noise by adding bit flipping, phase flipping, amplitude damping, and depolarizing noise. The results show that the prediction accuracy and receiver operating characteristic AUC value fluctuate around 0.2%, indicating HyQ2’s robustness in noisy quantum environments. In addition, the noise resilience and robustness of the HyQ2 algorithm were substantiated through experiments on the IBM quantum machine with only a 0.2% decrease compared to the simulation results.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-19"},"PeriodicalIF":0.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10716796","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142636455","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 : 2024-10-09DOI: 10.1109/TQE.2024.3476929
Steven Herbert;Ifan Williams;Roland Guichard;Darren Ng
In this article, based on some simple and reasonable assumptions, we derive a Gaussian noise model for quantum amplitude estimation. We provide results from quantum amplitude estimation run on various IBM superconducting quantum computers and on Quantinuum's H1 trapped-ion quantum computer to show that the proposed model is a good fit for real-world experimental data. We also show that the proposed Gaussian noise model can be easily composed with other noise models in order to capture effects that are not well described by Gaussian noise. We give a generalized procedure for how to embed this noise model into any quantum-phase-estimation-free quantum amplitude estimation algorithm, such that the amplitude estimation is “noise aware.” We then provide experimental results from running an implementation of noise-aware quantum amplitude estimation using data from an IBM superconducting quantum computer, demonstrating that the addition of “noise awareness” serves as an effective means of quantum error mitigation.
在本文中，基于一些简单合理的假设，我们推导出了量子振幅估计的高斯噪声模型。我们提供了在各种 IBM 超导量子计算机和 Quantinuum 的 H1 捕获离子量子计算机上运行的量子振幅估计结果，表明所提出的模型与真实世界的实验数据非常吻合。我们还表明，所提出的高斯噪声模型可以很容易地与其他噪声模型组成，以捕捉高斯噪声无法很好描述的效应。我们给出了如何将该噪声模型嵌入任何无量子相位估计的量子振幅估计算法的通用程序，从而使振幅估计具有 "噪声意识"。然后，我们提供了利用 IBM 超导量子计算机的数据运行噪声感知量子振幅估算实现的实验结果，证明增加 "噪声感知 "可作为量子误差缓解的有效手段。
{"title":"Noise-Aware Quantum Amplitude Estimation","authors":"Steven Herbert;Ifan Williams;Roland Guichard;Darren Ng","doi":"10.1109/TQE.2024.3476929","DOIUrl":"https://doi.org/10.1109/TQE.2024.3476929","url":null,"abstract":"In this article, based on some simple and reasonable assumptions, we derive a Gaussian noise model for quantum amplitude estimation. We provide results from quantum amplitude estimation run on various IBM superconducting quantum computers and on Quantinuum's H1 trapped-ion quantum computer to show that the proposed model is a good fit for real-world experimental data. We also show that the proposed Gaussian noise model can be easily composed with other noise models in order to capture effects that are not well described by Gaussian noise. We give a generalized procedure for how to embed this noise model into any quantum-phase-estimation-free quantum amplitude estimation algorithm, such that the amplitude estimation is “noise aware.” We then provide experimental results from running an implementation of noise-aware quantum amplitude estimation using data from an IBM superconducting quantum computer, demonstrating that the addition of “noise awareness” serves as an effective means of quantum error mitigation.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-23"},"PeriodicalIF":0.0,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10711252","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555072","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}
Support vector machines (SVMs) are widely used machine learning models, with formulations for both classification and regression tasks. In the last years, with the advent of working quantum annealers, hybrid SVM models characterized by quantum training and classical execution have been introduced. These models have demonstrated comparable performance to their classical counterparts. However, they are limited in the training set size due to the restricted connectivity of the current quantum annealers. Hence, to take advantage of large datasets, a strategy is required. In the classical domain, local SVMs, namely, SVMs trained on the data samples selected by a $k$ -nearest neighbors model, have already proven successful. Here, the local application of quantum-trained SVM models is proposed and empirically assessed. In particular, this approach allows overcoming the constraints on the training set size of the quantum-trained models while enhancing their performance. In practice, the fast local kernel support vector machine (FaLK-SVM) method, designed for efficient local SVMs, has been combined with quantum-trained SVM models for binary and multiclass classification. In addition, for comparison, FaLK-SVM has been interfaced for the first time with a classical single-step multiclass SVM model. Concerning the empirical evaluation, D-Wave's quantum annealers and real-world datasets taken from the remote sensing domain have been employed. The results have shown the effectiveness and scalability of the proposed approach, but also its practical applicability in a real-world large-scale scenario.
{"title":"Local Binary and Multiclass SVMs Trained on a Quantum Annealer","authors":"Enrico Zardini;Amer Delilbasic;Enrico Blanzieri;Gabriele Cavallaro;Davide Pastorello","doi":"10.1109/TQE.2024.3475875","DOIUrl":"https://doi.org/10.1109/TQE.2024.3475875","url":null,"abstract":"Support vector machines (SVMs) are widely used machine learning models, with formulations for both classification and regression tasks. In the last years, with the advent of working quantum annealers, hybrid SVM models characterized by quantum training and classical execution have been introduced. These models have demonstrated comparable performance to their classical counterparts. However, they are limited in the training set size due to the restricted connectivity of the current quantum annealers. Hence, to take advantage of large datasets, a strategy is required. In the classical domain, local SVMs, namely, SVMs trained on the data samples selected by a \u0000<inline-formula><tex-math>$k$</tex-math></inline-formula>\u0000-nearest neighbors model, have already proven successful. Here, the local application of quantum-trained SVM models is proposed and empirically assessed. In particular, this approach allows overcoming the constraints on the training set size of the quantum-trained models while enhancing their performance. In practice, the fast local kernel support vector machine (FaLK-SVM) method, designed for efficient local SVMs, has been combined with quantum-trained SVM models for binary and multiclass classification. In addition, for comparison, FaLK-SVM has been interfaced for the first time with a classical single-step multiclass SVM model. Concerning the empirical evaluation, D-Wave's quantum annealers and real-world datasets taken from the remote sensing domain have been employed. The results have shown the effectiveness and scalability of the proposed approach, but also its practical applicability in a real-world large-scale scenario.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10706813","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142573633","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 : 2024-09-25DOI: 10.1109/TQE.2024.3467271
Namitha Liyanage;Yue Wu;Siona Tagare;Lin Zhong
A fault-tolerant quantum computer must decode and correct errors faster than they appear to prevent exponential slowdown due to error correction. The Union-Find (UF) decoder is promising with an average time complexity slightly higher than $O(d^{3})$ . We report a distributed version of the UF decoder that exploits parallel computing resources for further speedup. Using a field-programmable gate array (FPGA)-based implementation, we empirically show that this distributed UF decoder has a sublinear average time complexity with regard to $d$ , given $O(d^{3})$ parallel computing resources. The decoding time per measurement round decreases as $d$ increases, the first time for a quantum error decoder. The implementation employs a scalable architecture called Helios that organizes parallel computing resources into a hybrid tree-grid structure. Using a Xilinx VCU129 FPGA, we successfully implement $d$ up to 21 with an average decoding time of 11.5 ns per measurement round under 0.1% phenomenological noise and 23.7 ns for $d=17$ under equivalent circuit-level noise. This performance is significantly faster than any existing decoder implementation. Furthermore, we show that Helios can optimize for resource efficiency by decoding $d=51$ on a Xilinx VCU129 FPGA with an average latency of 544 ns per measurement round.
{"title":"FPGA-Based Distributed Union-Find Decoder for Surface Codes","authors":"Namitha Liyanage;Yue Wu;Siona Tagare;Lin Zhong","doi":"10.1109/TQE.2024.3467271","DOIUrl":"https://doi.org/10.1109/TQE.2024.3467271","url":null,"abstract":"A fault-tolerant quantum computer must decode and correct errors faster than they appear to prevent exponential slowdown due to error correction. The Union-Find (UF) decoder is promising with an average time complexity slightly higher than \u0000<inline-formula><tex-math>$O(d^{3})$</tex-math></inline-formula>\u0000. We report a distributed version of the UF decoder that exploits parallel computing resources for further speedup. Using a field-programmable gate array (FPGA)-based implementation, we empirically show that this distributed UF decoder has a sublinear average time complexity with regard to \u0000<inline-formula><tex-math>$d$</tex-math></inline-formula>\u0000, given \u0000<inline-formula><tex-math>$O(d^{3})$</tex-math></inline-formula>\u0000 parallel computing resources. The decoding time per measurement round decreases as \u0000<inline-formula><tex-math>$d$</tex-math></inline-formula>\u0000 increases, the first time for a quantum error decoder. The implementation employs a scalable architecture called Helios that organizes parallel computing resources into a hybrid tree-grid structure. Using a Xilinx VCU129 FPGA, we successfully implement \u0000<inline-formula><tex-math>$d$</tex-math></inline-formula>\u0000 up to 21 with an average decoding time of 11.5 ns per measurement round under 0.1% phenomenological noise and 23.7 ns for \u0000<inline-formula><tex-math>$d=17$</tex-math></inline-formula>\u0000 under equivalent circuit-level noise. This performance is significantly faster than any existing decoder implementation. Furthermore, we show that Helios can optimize for resource efficiency by decoding \u0000<inline-formula><tex-math>$d=51$</tex-math></inline-formula>\u0000 on a Xilinx VCU129 FPGA with an average latency of 544 ns per measurement round.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-18"},"PeriodicalIF":0.0,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10693533","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142516853","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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