Pub Date : 2023-11-28DOI: 10.1109/TQE.2023.3337328
Ginés Carrascal;Paula Hernamperez;Guillermo Botella;Alberto del Barrio
In portfolio theory, the investment portfolio optimization problem is one of those problems whose complexity grows exponentially with the number of assets. By backtesting classical and quantum computing algorithms, we can get a sense of how these algorithms might perform in the real world. This work establishes a methodology for backtesting classical and quantum algorithms in equivalent conditions, and uses it to explore four quantum and three classical computing algorithms for portfolio optimization and compares the results. Running 10 000 experiments on equivalent conditions we find that quantum can match or slightly outperform classical results, showing a better escalability trend. To the best of our knowledge, this is the first work that performs a systematic backtesting comparison of classical and quantum portfolio optimization algorithms. In this work, we also analyze in more detail the variational quantum eigensolver algorithm, applied to solve the portfolio optimization problem, running on simulators and real quantum computers from IBM. The benefits and drawbacks of backtesting are discussed, as well as some of the challenges involved in using real quantum computers of more than 100 qubits. Results show quantum algorithms can be competitive with classical ones, with the advantage of being able to handle a large number of assets in a reasonable time on a future larger quantum computer.
{"title":"Backtesting Quantum Computing Algorithms for Portfolio Optimization","authors":"Ginés Carrascal;Paula Hernamperez;Guillermo Botella;Alberto del Barrio","doi":"10.1109/TQE.2023.3337328","DOIUrl":"https://doi.org/10.1109/TQE.2023.3337328","url":null,"abstract":"In portfolio theory, the investment portfolio optimization problem is one of those problems whose complexity grows exponentially with the number of assets. By backtesting classical and quantum computing algorithms, we can get a sense of how these algorithms might perform in the real world. This work establishes a methodology for backtesting classical and quantum algorithms in equivalent conditions, and uses it to explore four quantum and three classical computing algorithms for portfolio optimization and compares the results. Running 10 000 experiments on equivalent conditions we find that quantum can match or slightly outperform classical results, showing a better escalability trend. To the best of our knowledge, this is the first work that performs a systematic backtesting comparison of classical and quantum portfolio optimization algorithms. In this work, we also analyze in more detail the variational quantum eigensolver algorithm, applied to solve the portfolio optimization problem, running on simulators and real quantum computers from IBM. The benefits and drawbacks of backtesting are discussed, as well as some of the challenges involved in using real quantum computers of more than 100 qubits. Results show quantum algorithms can be competitive with classical ones, with the advantage of being able to handle a large number of assets in a reasonable time on a future larger quantum computer.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-20"},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10329473","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139494285","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 : 2023-11-24DOI: 10.1109/TQE.2023.3336514
Mohammad Rezai;Jawad A. Salehi
The light's image is the primary source of information carrier in nature. Indeed, a single photon's image possesses a vast information capacity that can be harnessed for quantum information processing. Our scheme for implementing quantum information processing on a discretized photon wavefront via universal multiport processors employs a class of quantum Fourier optical systems composed of spatial phase modulators and 4f-processors with phase-only pupils having a characteristic periodicity that reduces the number of optical resources quadratically as compared to other conventional path-encoding techniques. In particular, this article employs quantum Fourier optics to implement some key quantum logical gates that can be instrumental in optical quantum computations. For instance, we demonstrate the principle by implementing the single-qubit Hadamard and the two-qubit controlled- not gates via simulation and optimization techniques. Due to various advantages of the proposed scheme, including the large information capacity of the photon wavefront, a quadratically reduced number of optical resources compared with other conventional path-encoding techniques, and dynamic programmability, the proposed scheme has the potential to be an essential contribution to linear optical quantum computing and optical quantum signal processing.
{"title":"Quantum Computation via Multiport Discretized Quantum Fourier Optical Processors","authors":"Mohammad Rezai;Jawad A. Salehi","doi":"10.1109/TQE.2023.3336514","DOIUrl":"https://doi.org/10.1109/TQE.2023.3336514","url":null,"abstract":"The light's image is the primary source of information carrier in nature. Indeed, a single photon's image possesses a vast information capacity that can be harnessed for quantum information processing. Our scheme for implementing quantum information processing on a discretized photon wavefront via universal multiport processors employs a class of quantum Fourier optical systems composed of spatial phase modulators and 4f-processors with phase-only pupils having a characteristic periodicity that reduces the number of optical resources quadratically as compared to other conventional path-encoding techniques. In particular, this article employs quantum Fourier optics to implement some key quantum logical gates that can be instrumental in optical quantum computations. For instance, we demonstrate the principle by implementing the single-qubit Hadamard and the two-qubit controlled-\u0000<sc>not</small>\u0000 gates via simulation and optimization techniques. Due to various advantages of the proposed scheme, including the large information capacity of the photon wavefront, a quadratically reduced number of optical resources compared with other conventional path-encoding techniques, and dynamic programmability, the proposed scheme has the potential to be an essential contribution to linear optical quantum computing and optical quantum signal processing.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10328681","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139109603","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 : 2023-11-17DOI: 10.1109/TQE.2023.3333224
Sangwoo Park;Osvaldo Simeone
Quantum machine learning is a promising programming paradigm for the optimization of quantum algorithms in the current era of noisy intermediate-scale quantum computers. A fundamental challenge in quantum machine learning is generalization, as the designer targets performance under testing conditions while having access only to limited training data. Existing generalization analyses, while identifying important general trends and scaling laws, cannot be used to assign reliable and informative “error bars” to the decisions made by quantum models. In this article, we propose a general methodology that can reliably quantify the uncertainty of quantum models, irrespective of the amount of training data, the number of shots, the ansatz, the training algorithm, and the presence of quantum hardware noise. The approach, which builds on probabilistic conformal prediction (CP), turns an arbitrary, possibly small, number of shots from a pretrained quantum model into a set prediction, e.g., an interval, that provably contains the true target with any desired coverage level. Experimental results confirm the theoretical calibration guarantees of the proposed framework, referred to as quantum CP.
{"title":"Quantum Conformal Prediction for Reliable Uncertainty Quantification in Quantum Machine Learning","authors":"Sangwoo Park;Osvaldo Simeone","doi":"10.1109/TQE.2023.3333224","DOIUrl":"https://doi.org/10.1109/TQE.2023.3333224","url":null,"abstract":"Quantum machine learning is a promising programming paradigm for the optimization of quantum algorithms in the current era of noisy intermediate-scale quantum computers. A fundamental challenge in quantum machine learning is generalization, as the designer targets performance under testing conditions while having access only to limited training data. Existing generalization analyses, while identifying important general trends and scaling laws, cannot be used to assign reliable and informative “error bars” to the decisions made by quantum models. In this article, we propose a general methodology that can reliably quantify the uncertainty of quantum models, irrespective of the amount of training data, the number of shots, the ansatz, the training algorithm, and the presence of quantum hardware noise. The approach, which builds on probabilistic conformal prediction (CP), turns an arbitrary, possibly small, number of shots from a pretrained quantum model into a set prediction, e.g., an interval, that \u0000<italic>provably</i>\u0000 contains the true target with any desired coverage level. Experimental results confirm the theoretical calibration guarantees of the proposed framework, referred to as quantum CP.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"5 ","pages":"1-24"},"PeriodicalIF":0.0,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10321713","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139908602","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}
Very recently, the BERT graph convolutional network (BertGCN) model has attracted much attention from researchers due to its good text classification performance. However, just using original documents in the corpus to construct the topology of graphs for GCN-based models may lose some effective information. In this paper, we focus on sentiment classification, an important branch of text classification, and propose the multistream BERT graph convolutional network (MS-BertGCN) for sentiment classification based on cross-document learning. In the proposed method, we first combine the documents in the training set based on within-class similarity. Then, each heterogeneous graph is constructed using a group of combinations of documents for the single-stream BertGCN model. Finally, we construct multistream-BertGCN (MS-BertGCN) based on multiple heterogeneous graphs constructed from different groups of combined documents. The experimental results show that our MS-BertGCN model outperforms state-of-the-art methods on sentiment classification tasks.
{"title":"Multistream BertGCN for Sentiment Classification Based on Cross-Document Learning","authors":"Meng Li, Yujin Xie, Weifeng Yang, Shenyu Chen","doi":"10.1155/2023/3668960","DOIUrl":"https://doi.org/10.1155/2023/3668960","url":null,"abstract":"Very recently, the BERT graph convolutional network (BertGCN) model has attracted much attention from researchers due to its good text classification performance. However, just using original documents in the corpus to construct the topology of graphs for GCN-based models may lose some effective information. In this paper, we focus on sentiment classification, an important branch of text classification, and propose the multistream BERT graph convolutional network (MS-BertGCN) for sentiment classification based on cross-document learning. In the proposed method, we first combine the documents in the training set based on within-class similarity. Then, each heterogeneous graph is constructed using a group of combinations of documents for the single-stream BertGCN model. Finally, we construct multistream-BertGCN (MS-BertGCN) based on multiple heterogeneous graphs constructed from different groups of combined documents. The experimental results show that our MS-BertGCN model outperforms state-of-the-art methods on sentiment classification tasks.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"22 17","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136281983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-02DOI: 10.1109/TQE.2023.3329714
Evan Sutcliffe;Alejandra Beghelli
Quantum networks facilitate numerous applications including secure communication and distributed quantum computation by performing entanglement distribution. For some multiuser quantum applications, access to a shared multipartite state is required. We consider the problem of designing protocols for distributing such states, at an increased rate. For this, we propose three protocols that leverage multipath routing to increase the distribution rate for multiuser applications. The protocols are evaluated on quantum networks with noisy intermediate scale quantum (NISQ) constraints, including limited quantum memories and probabilistic entanglement generation. Simulation results show that the developed protocols achieve an exponential increase in the distribution rate of multipartite states compared to single-path routing techniques, with a maximum increase of four orders of magnitude for the cases studied. Furthermore, the relative increase in the distribution rate was also found to improve for larger sets of users. When the protocols were tested in scaled-down real-world topologies, it was found that a topology had a significant effect on the multipartite state distribution rates achieved by the protocols. Finally, we found that the benefits of multipath routing are maximum for short quantum memory decoherence times and intermediate values of entanglement generation probability. Hence, the protocols developed can benefit NISQ quantum network control and design.
{"title":"Multiuser Entanglement Distribution in Quantum Networks Using Multipath Routing","authors":"Evan Sutcliffe;Alejandra Beghelli","doi":"10.1109/TQE.2023.3329714","DOIUrl":"10.1109/TQE.2023.3329714","url":null,"abstract":"Quantum networks facilitate numerous applications including secure communication and distributed quantum computation by performing entanglement distribution. For some multiuser quantum applications, access to a shared multipartite state is required. We consider the problem of designing protocols for distributing such states, at an increased rate. For this, we propose three protocols that leverage multipath routing to increase the distribution rate for multiuser applications. The protocols are evaluated on quantum networks with noisy intermediate scale quantum (NISQ) constraints, including limited quantum memories and probabilistic entanglement generation. Simulation results show that the developed protocols achieve an exponential increase in the distribution rate of multipartite states compared to single-path routing techniques, with a maximum increase of four orders of magnitude for the cases studied. Furthermore, the relative increase in the distribution rate was also found to improve for larger sets of users. When the protocols were tested in scaled-down real-world topologies, it was found that a topology had a significant effect on the multipartite state distribution rates achieved by the protocols. Finally, we found that the benefits of multipath routing are maximum for short quantum memory decoherence times and intermediate values of entanglement generation probability. Hence, the protocols developed can benefit NISQ quantum network control and design.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"4 ","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10305417","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134891543","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 : 2023-11-01DOI: 10.1109/TQE.2023.3329213
Mostafizur Rahaman Laskar;Amit Kumar Dutta
The structured matrix completion problem (SMCP) is ubiquitous in several signal processing applications. In this article, we consider a fixed pattern, namely, the Hankel-structure for the SMCP under quantum formalism. By exploiting its structure, a lower-gate-complexity quantum circuit realization of a Hankel system is demonstrated. Further, we propose a quantum simulation algorithm for the Hankel-structured Hamiltonian with an advantage in quantum gate-operation complexity in comparison with the standard quantum Hamiltonian simulation technique. We show its application in eigenvalue spectrum estimation for signal processing applications. An error bound associated with this proposed quantum evolution is proposed with the consideration of spectrum estimation and measurement uncertainty. Numerical results are reported adopting random matrix theory in its fold to evaluate the efficacy of the proposed architecture and algorithm for large-dimensional systems, including an example application in delay estimation for ranging operations in a wireless communication system.
{"title":"A Proposed Quantum Framework for Low-Complexity Quantum Simulation and Spectrum Estimation of Hankel-Patterned Systems","authors":"Mostafizur Rahaman Laskar;Amit Kumar Dutta","doi":"10.1109/TQE.2023.3329213","DOIUrl":"10.1109/TQE.2023.3329213","url":null,"abstract":"The structured matrix completion problem (SMCP) is ubiquitous in several signal processing applications. In this article, we consider a fixed pattern, namely, the Hankel-structure for the SMCP under quantum formalism. By exploiting its structure, a lower-gate-complexity quantum circuit realization of a Hankel system is demonstrated. Further, we propose a quantum simulation algorithm for the Hankel-structured Hamiltonian with an advantage in quantum gate-operation complexity in comparison with the standard quantum Hamiltonian simulation technique. We show its application in eigenvalue spectrum estimation for signal processing applications. An error bound associated with this proposed quantum evolution is proposed with the consideration of spectrum estimation and measurement uncertainty. Numerical results are reported adopting random matrix theory in its fold to evaluate the efficacy of the proposed architecture and algorithm for large-dimensional systems, including an example application in delay estimation for ranging operations in a wireless communication system.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"4 ","pages":"1-18"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10304328","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135363112","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}
We show how to generate stationary continuous-variable pairwise entanglement between microwave modes in a hybrid optoelectromechanical system, which consists of a single Fabry–Pérot cavity, a parallel-plate capacitor with a moving element as the mechanical resonator, and several pairs of microwave cavities. The optical mode and mechanical resonator are coupled via radiation pressure; meanwhile, several pairs of the microwave mode and mechanical resonator are capacitively coupled. Under an experimentally reachable parameter regime, we show the influence of different key parameters on pairwise entanglement and find that it is also robust against temperature. Our model and results are expected to provide a new perspective on quantum networks with increasingly large scales, quantum internet with multiple local users, and multiport microwave quantum illumination radar.
{"title":"Continuous-Variable Pairwise Entanglement Based on Optoelectromechanical System","authors":"Qizhi Cai, Jinkun Liao, Qiang Zhou","doi":"10.1155/2023/8993363","DOIUrl":"https://doi.org/10.1155/2023/8993363","url":null,"abstract":"We show how to generate stationary continuous-variable pairwise entanglement between microwave modes in a hybrid optoelectromechanical system, which consists of a single Fabry–Pérot cavity, a parallel-plate capacitor with a moving element as the mechanical resonator, and several pairs of microwave cavities. The optical mode and mechanical resonator are coupled via radiation pressure; meanwhile, several pairs of the microwave mode and mechanical resonator are capacitively coupled. Under an experimentally reachable parameter regime, we show the influence of different key parameters on pairwise entanglement and find that it is also robust against temperature. Our model and results are expected to provide a new perspective on quantum networks with increasingly large scales, quantum internet with multiple local users, and multiport microwave quantum illumination radar.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135871111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-25DOI: 10.1109/TQE.2023.3327055
Jungin E. Kim;Yan Wang
The searching efficiency of the quantum approximate optimization algorithm is dependent on both the classical and quantum sides of the algorithm. Recently, a quantum approximate Bayesian optimization algorithm (QABOA) that includes two mixers was developed, where surrogate-based Bayesian optimization is applied to improve the sampling efficiency of the classical optimizer. A continuous-time quantum walk mixer is used to enhance exploration, and the generalized Grover mixer is also applied to improve exploitation. In this article, an extension of the QABOA is proposed to further improve its searching efficiency. The searching efficiency is enhanced through two aspects. First, two mixers, including one for exploration and the other for exploitation, are applied in an alternating fashion. Second, uncertainty of the quantum circuit is quantified with a new quantum Matérn kernel based on the kurtosis of the basis state distribution, which increases the chance of obtaining the optimum. The proposed new two-mixer QABOA's with and without uncertainty quantification are compared with three single-mixer QABOA's on five discrete and four mixed-integer problems. The results show that the proposed two-mixer QABOA with uncertainty quantification has the best performance in efficiency and consistency for five out of the nine tested problems. The results also show that QABOA with the generalized Grover mixer performs the best among the single-mixer algorithms, thereby demonstrating the benefit of exploitation and the importance of dynamic exploration–exploitation balance in improving searching efficiency.
{"title":"Quantum Approximate Bayesian Optimization Algorithms With Two Mixers and Uncertainty Quantification","authors":"Jungin E. Kim;Yan Wang","doi":"10.1109/TQE.2023.3327055","DOIUrl":"10.1109/TQE.2023.3327055","url":null,"abstract":"The searching efficiency of the quantum approximate optimization algorithm is dependent on both the classical and quantum sides of the algorithm. Recently, a quantum approximate Bayesian optimization algorithm (QABOA) that includes two mixers was developed, where surrogate-based Bayesian optimization is applied to improve the sampling efficiency of the classical optimizer. A continuous-time quantum walk mixer is used to enhance exploration, and the generalized Grover mixer is also applied to improve exploitation. In this article, an extension of the QABOA is proposed to further improve its searching efficiency. The searching efficiency is enhanced through two aspects. First, two mixers, including one for exploration and the other for exploitation, are applied in an alternating fashion. Second, uncertainty of the quantum circuit is quantified with a new quantum Matérn kernel based on the kurtosis of the basis state distribution, which increases the chance of obtaining the optimum. The proposed new two-mixer QABOA's with and without uncertainty quantification are compared with three single-mixer QABOA's on five discrete and four mixed-integer problems. The results show that the proposed two-mixer QABOA with uncertainty quantification has the best performance in efficiency and consistency for five out of the nine tested problems. The results also show that QABOA with the generalized Grover mixer performs the best among the single-mixer algorithms, thereby demonstrating the benefit of exploitation and the importance of dynamic exploration–exploitation balance in improving searching efficiency.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"4 ","pages":"1-17"},"PeriodicalIF":0.0,"publicationDate":"2023-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10296859","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134980312","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 order to meet mobile cellular users' ever-increasing data demands, today's 4G and 5G wireless networks are designed mainly with the goal of maximizing spectral efficiency. While they have made progress in this regard, controlling the carbon footprint and operational costs of such networks remains a long-standing problem among network designers. This article takes a long view on this problem, envisioning a NextG scenario where the network leverages quantum annealing for cellular baseband processing. We gather and synthesize insights on power consumption, computational throughput and latency, spectral efficiency, operational cost, and feasibility timelines surrounding quantum annealing technology. Armed with these data, we project the quantitative performance targets future quantum annealing hardware must meet in order to provide a computational and power advantage over complementary metal–oxide semiconductor (CMOS) hardware, while matching its whole-network spectral efficiency. Our quantitative analysis predicts, that with 82.32 $mu$ s problem latency and 2.68 M qubits, quantum annealing will achieve a spectral efficiency equal to CMOS while reducing power consumption by 41 kW (45% lower) in a large MIMO base station with 400-MHz bandwidth and 64 antennas, and a 160-kW power reduction (55% lower) using 8.04 M qubits in a centralized radio access network setting with three large MIMO base stations.
{"title":"A Cost and Power Feasibility Analysis of Quantum Annealing for NextG Cellular Wireless Networks","authors":"Srikar Kasi;Paul Warburton;John Kaewell;Kyle Jamieson","doi":"10.1109/TQE.2023.3326469","DOIUrl":"10.1109/TQE.2023.3326469","url":null,"abstract":"In order to meet mobile cellular users' ever-increasing data demands, today's 4G and 5G wireless networks are designed mainly with the goal of maximizing spectral efficiency. While they have made progress in this regard, controlling the carbon footprint and operational costs of such networks remains a long-standing problem among network designers. This article takes a long view on this problem, envisioning a NextG scenario where the network leverages quantum annealing for cellular baseband processing. We gather and synthesize insights on power consumption, computational throughput and latency, spectral efficiency, operational cost, and feasibility timelines surrounding quantum annealing technology. Armed with these data, we project the quantitative performance targets future quantum annealing hardware must meet in order to provide a computational and power advantage over complementary metal–oxide semiconductor (CMOS) hardware, while matching its whole-network spectral efficiency. Our quantitative analysis predicts, that with 82.32 \u0000<inline-formula><tex-math>$mu$</tex-math></inline-formula>\u0000s problem latency and 2.68 M qubits, quantum annealing will achieve a spectral efficiency equal to CMOS while reducing power consumption by 41 kW (45% lower) in a large MIMO base station with 400-MHz bandwidth and 64 antennas, and a 160-kW power reduction (55% lower) using 8.04 M qubits in a centralized radio access network setting with three large MIMO base stations.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"4 ","pages":"1-17"},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10290945","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135153015","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 : 2023-10-19DOI: 10.1109/TQE.2023.3326093
Natarajan Venkatachalam;Foram P. Shingala;Selvagangai C;Hema Priya S;Dillibabu S;Pooja Chandravanshi;Ravindra P. Singh
Key distillation is an essential component of every quantum key distribution (QKD) system because it compensates for the inherent transmission errors of a quantum channel. However, the interoperability and throughput aspects of the postprocessing components are often neglected. In this article, we propose a high-throughput key distillation framework that supports multiple QKD protocols, implemented in a field-programmable gate array (FPGA). The proposed design adapts a MapReduce programming model to efficiently process large chunks of raw data across the limited computing resources of an FPGA. We present a novel hardware-efficient integrated postprocessing architecture that offers dynamic error correction, mutual authentication with a physically unclonable function, and an inbuilt high-speed encryption application that utilizes the key for secure communication. In addition, we have developed a semiautomated high-level synthesis framework that is compatible with any discrete variable QKD system, showing promising speedup. Overall, the experimental results demonstrate a noteworthy enhancement in scalability achieved through the utilization of a single FPGA platform.
{"title":"Scalable QKD Postprocessing System With Reconfigurable Hardware Accelerator","authors":"Natarajan Venkatachalam;Foram P. Shingala;Selvagangai C;Hema Priya S;Dillibabu S;Pooja Chandravanshi;Ravindra P. Singh","doi":"10.1109/TQE.2023.3326093","DOIUrl":"10.1109/TQE.2023.3326093","url":null,"abstract":"Key distillation is an essential component of every quantum key distribution (QKD) system because it compensates for the inherent transmission errors of a quantum channel. However, the interoperability and throughput aspects of the postprocessing components are often neglected. In this article, we propose a high-throughput key distillation framework that supports multiple QKD protocols, implemented in a field-programmable gate array (FPGA). The proposed design adapts a MapReduce programming model to efficiently process large chunks of raw data across the limited computing resources of an FPGA. We present a novel hardware-efficient integrated postprocessing architecture that offers dynamic error correction, mutual authentication with a physically unclonable function, and an inbuilt high-speed encryption application that utilizes the key for secure communication. In addition, we have developed a semiautomated high-level synthesis framework that is compatible with any discrete variable QKD system, showing promising speedup. Overall, the experimental results demonstrate a noteworthy enhancement in scalability achieved through the utilization of a single FPGA platform.","PeriodicalId":100644,"journal":{"name":"IEEE Transactions on Quantum Engineering","volume":"4 ","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10288091","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135058587","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：