Pub Date : 2024-11-12DOI: 10.1140/epjqt/s40507-024-00289-z
Akash Kundu, Aritra Sarkar, Abhishek Sadhu
Quantum architecture Search (QAS) is a promising direction for optimization and automated design of quantum circuits towards quantum advantage. Recent techniques in QAS emphasize Multi-Layer Perceptron (MLP)-based deep Q-networks. However, their interpretability remains challenging due to the large number of learnable parameters and the complexities involved in selecting appropriate activation functions. In this work, to overcome these challenges, we utilize the Kolmogorov-Arnold Network (KAN) in the QAS algorithm, analyzing their efficiency in the task of quantum state preparation and quantum chemistry. In quantum state preparation, our results show that in a noiseless scenario, the probability of success is 2× to 5× higher than MLPs. In noisy environments, KAN outperforms MLPs in fidelity when approximating these states, showcasing its robustness against noise. In tackling quantum chemistry problems, we enhance the recently proposed QAS algorithm by integrating curriculum reinforcement learning with a KAN structure. This facilitates a more efficient design of parameterized quantum circuits by reducing the number of required 2-qubit gates and circuit depth. Further investigation reveals that KAN requires a significantly smaller number of learnable parameters compared to MLPs; however, the average time of executing each episode for KAN is higher.
{"title":"KANQAS: Kolmogorov-Arnold Network for Quantum Architecture Search","authors":"Akash Kundu, Aritra Sarkar, Abhishek Sadhu","doi":"10.1140/epjqt/s40507-024-00289-z","DOIUrl":"10.1140/epjqt/s40507-024-00289-z","url":null,"abstract":"<div><p>Quantum architecture Search (QAS) is a promising direction for optimization and automated design of quantum circuits towards quantum advantage. Recent techniques in QAS emphasize Multi-Layer Perceptron (MLP)-based deep Q-networks. However, their interpretability remains challenging due to the large number of learnable parameters and the complexities involved in selecting appropriate activation functions. In this work, to overcome these challenges, we utilize the Kolmogorov-Arnold Network (KAN) in the QAS algorithm, analyzing their efficiency in the task of quantum state preparation and quantum chemistry. In quantum state preparation, our results show that in a noiseless scenario, the probability of success is 2× to 5× higher than MLPs. In noisy environments, KAN outperforms MLPs in fidelity when approximating these states, showcasing its robustness against noise. In tackling quantum chemistry problems, we enhance the recently proposed QAS algorithm by integrating curriculum reinforcement learning with a KAN structure. This facilitates a more efficient design of parameterized quantum circuits by reducing the number of required 2-qubit gates and circuit depth. Further investigation reveals that KAN requires a significantly smaller number of learnable parameters compared to MLPs; however, the average time of executing each episode for KAN is higher.</p></div>","PeriodicalId":547,"journal":{"name":"EPJ Quantum Technology","volume":"11 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://epjquantumtechnology.springeropen.com/counter/pdf/10.1140/epjqt/s40507-024-00289-z","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-05DOI: 10.1140/epjqt/s40507-024-00287-1
Giacomo Zuccarini, Claudio Sutrini, Maria Bondani, Chiara Macchiavello, Massimiliano Malgieri
Research and curriculum development on quantum information science is a novel but technologically and socially significant challenge for physics education. While the debate is open on the core content, the approaches, and the strategies for addressing the need of effective instruction on the subject-matter, some indications have begun to emerge. Among them, the importance of an earlier start of education and of helping students develop not only a theoretical knowledge, but also high-level experimental skills including ideal design and conduction of experiments. Such skills are challenging to attain in existing traditional programs and may be considered inaccessible at introductory level because of the difficulties connected with qubit implementations. Here we present the design process, the structure, and a preliminary evaluation of a course for secondary school that is aimed to promote the building of a basic but integrated understanding of quantum information science, including experimental design and lab activities. The course was developed within the model of educational reconstruction, and embedded into a conceptual change framework in physics and computation. The encoding of polarization and which-path information of a photon is used to engage students in the development of a global model of logical encoding and processing, in ideal experimental design of gates and circuits, and in their implementation on the optical bench. Data show the effectiveness of the course in promoting student engagement in the modelling of gates in different encodings, in fostering an understanding of the computational role of physical setups, and a positive attitude and interest towards quantum computation and innovative teaching methods.
{"title":"Teaching quantum information science to secondary school students with photon polarization and which-path encoding","authors":"Giacomo Zuccarini, Claudio Sutrini, Maria Bondani, Chiara Macchiavello, Massimiliano Malgieri","doi":"10.1140/epjqt/s40507-024-00287-1","DOIUrl":"10.1140/epjqt/s40507-024-00287-1","url":null,"abstract":"<div><p>Research and curriculum development on quantum information science is a novel but technologically and socially significant challenge for physics education. While the debate is open on the core content, the approaches, and the strategies for addressing the need of effective instruction on the subject-matter, some indications have begun to emerge. Among them, the importance of an earlier start of education and of helping students develop not only a theoretical knowledge, but also high-level experimental skills including ideal design and conduction of experiments. Such skills are challenging to attain in existing traditional programs and may be considered inaccessible at introductory level because of the difficulties connected with qubit implementations. Here we present the design process, the structure, and a preliminary evaluation of a course for secondary school that is aimed to promote the building of a basic but integrated understanding of quantum information science, including experimental design and lab activities. The course was developed within the model of educational reconstruction, and embedded into a conceptual change framework in physics and computation. The encoding of polarization and which-path information of a photon is used to engage students in the development of a global model of logical encoding and processing, in ideal experimental design of gates and circuits, and in their implementation on the optical bench. Data show the effectiveness of the course in promoting student engagement in the modelling of gates in different encodings, in fostering an understanding of the computational role of physical setups, and a positive attitude and interest towards quantum computation and innovative teaching methods.</p></div>","PeriodicalId":547,"journal":{"name":"EPJ Quantum Technology","volume":"11 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://epjquantumtechnology.springeropen.com/counter/pdf/10.1140/epjqt/s40507-024-00287-1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-05DOI: 10.1140/epjqt/s40507-024-00286-2
Hugo Molinares, Fernanda Pinilla, Enrique Muñoz, Francisco Muñoz, Vitalie Eremeev
Hexagonal boron nitride exhibits two types of defects with great potential for quantum information technologies: single-photon emitters (SPEs) and one-dimensional grain boundaries hosting topologically-protected phonons, termed as topologically-protected phonon lines (TPL). Here, by means of a simple effective model and density functional theory calculations, we show that it is possible to use these phonons for the transmission of information. Particularly, a single SPE can be used to induce single-, two- and qubit-phonon states in the one-dimensional channel, and (ii) two distant SPEs can be coupled by the TPL that acts as a waveguide, thus exhibiting strong quantum correlations. We highlight the possibilities offered by this material-built-in nano-architecture as a phononic device for quantum information technologies.
{"title":"Generation of phonon quantum states and quantum correlations among single photon emitters in hexagonal boron nitride","authors":"Hugo Molinares, Fernanda Pinilla, Enrique Muñoz, Francisco Muñoz, Vitalie Eremeev","doi":"10.1140/epjqt/s40507-024-00286-2","DOIUrl":"10.1140/epjqt/s40507-024-00286-2","url":null,"abstract":"<div><p>Hexagonal boron nitride exhibits two types of defects with great potential for quantum information technologies: single-photon emitters (SPEs) and one-dimensional grain boundaries hosting topologically-protected phonons, termed as <i>topologically-protected phonon lines</i> (TPL). Here, by means of a simple effective model and density functional theory calculations, we show that it is possible to use these phonons for the transmission of information. Particularly, a single SPE can be used to induce single-, two- and qubit-phonon states in the one-dimensional channel, and <i>(ii)</i> two distant SPEs can be coupled by the TPL that acts as a waveguide, thus exhibiting strong quantum correlations. We highlight the possibilities offered by this material-built-in nano-architecture as a phononic device for quantum information technologies.</p></div>","PeriodicalId":547,"journal":{"name":"EPJ Quantum Technology","volume":"11 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://epjquantumtechnology.springeropen.com/counter/pdf/10.1140/epjqt/s40507-024-00286-2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-28DOI: 10.1140/epjqt/s40507-024-00280-8
Ashwin Sivakumar, Harishankar K Nair, Aurum Joshi, Kenson Wesley R, Akash P Videsh, Reena Monica P
Material discovery is a phenomenon practiced since the evolution of the world. The discovery of materials has led to significant development in varied fields such as Science, Engineering and Technology. Computationally simulating molecules has been an area of interest in the industry as well as academia. However, simulating large molecules can be computationally expensive in terms of computing power and complexity. Quantum computing is a recent development that can improve the efficiency in predicting properties of atoms and molecules which will be useful for material design. The Variational Quantum Eigensolver (VQE) is one such quantum algorithm used to calculate the ground state energy of molecules or ions. In this study, we have done a comparative analysis of the parameters that constitute the VQE algorithm. This includes components such as basis, qubit mapping, ansatz, and optimizers used. We have also developed a database consisting of 79 single atoms and their variations of oxidation states and 33 molecules with the data of their Hamiltonian and ground state energy and dipole moment.
{"title":"A computational study and analysis of Variational Quantum Eigensolver over multiple parameters for molecules and ions","authors":"Ashwin Sivakumar, Harishankar K Nair, Aurum Joshi, Kenson Wesley R, Akash P Videsh, Reena Monica P","doi":"10.1140/epjqt/s40507-024-00280-8","DOIUrl":"10.1140/epjqt/s40507-024-00280-8","url":null,"abstract":"<div><p>Material discovery is a phenomenon practiced since the evolution of the world. The discovery of materials has led to significant development in varied fields such as Science, Engineering and Technology. Computationally simulating molecules has been an area of interest in the industry as well as academia. However, simulating large molecules can be computationally expensive in terms of computing power and complexity. Quantum computing is a recent development that can improve the efficiency in predicting properties of atoms and molecules which will be useful for material design. The Variational Quantum Eigensolver (VQE) is one such quantum algorithm used to calculate the ground state energy of molecules or ions. In this study, we have done a comparative analysis of the parameters that constitute the VQE algorithm. This includes components such as basis, qubit mapping, ansatz, and optimizers used. We have also developed a database consisting of 79 single atoms and their variations of oxidation states and 33 molecules with the data of their Hamiltonian and ground state energy and dipole moment.</p></div>","PeriodicalId":547,"journal":{"name":"EPJ Quantum Technology","volume":"11 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://epjquantumtechnology.springeropen.com/counter/pdf/10.1140/epjqt/s40507-024-00280-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142524502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-25DOI: 10.1140/epjqt/s40507-024-00285-3
Minati Rath, Hema Date
This study explores the integration of quantum data embedding techniques into classical machine learning (ML) algorithms; to assess performance enhancements and computational implications across a spectrum of models. We explored various classical-to-quantum mapping methods; ranging from basis encoding and angle encoding to amplitude encoding; for encoding classical data. We conducted an extensive empirical study encompassing popular ML algorithms, including Logistic Regression, K-Nearest Neighbors, Support Vector Machines, and ensemble methods like Random Forest, LightGBM, AdaBoost, and CatBoost. Our findings reveal that quantum data embedding contributes to improved classification accuracy and F1 scores, particularly notable in models that inherently benefit from enhanced feature representation. We observed nuanced effects on running time, with low-complexity models exhibiting moderate increases and more computationally intensive models experiencing discernible changes. Notably, ensemble methods demonstrated a favorable balance between performance gains and computational overhead.
This study underscores the potential of quantum data embedding to enhance classical ML models and emphasizes the importance of weighing performance improvements against computational costs. Future research may involve refining quantum encoding processes to optimize computational efficiency and explore scalability for real-world applications. Our work contributes to the growing body of knowledge on the intersection of quantum computing and classical machine learning, offering insights for researchers and practitioners seeking to harness the advantages of quantum-inspired techniques in practical scenarios.
本研究探索将量子数据嵌入技术整合到经典机器学习(ML)算法中,以评估各种模型的性能提升和计算影响。我们探索了各种经典到量子的映射方法,从基础编码、角度编码到振幅编码,用于编码经典数据。我们进行了广泛的实证研究,涵盖了流行的 ML 算法,包括 Logistic 回归、K-Nearest Neighbors、支持向量机,以及随机森林、LightGBM、AdaBoost 和 CatBoost 等集合方法。我们的研究结果表明,量子数据嵌入有助于提高分类准确率和 F1 分数,这在本质上得益于增强特征表示的模型中尤为明显。我们观察到了量子数据嵌入对运行时间的细微影响,低复杂度模型表现出适度的增长,而计算密集型模型则经历了明显的变化。这项研究强调了量子数据嵌入增强经典 ML 模型的潜力,并强调了权衡性能提升与计算成本的重要性。未来的研究可能涉及改进量子编码过程,以优化计算效率,并探索实际应用的可扩展性。我们的工作为量子计算与经典机器学习交叉领域不断增长的知识库做出了贡献,为研究人员和从业人员在实际应用场景中利用量子启发技术的优势提供了启示。
{"title":"Quantum data encoding: a comparative analysis of classical-to-quantum mapping techniques and their impact on machine learning accuracy","authors":"Minati Rath, Hema Date","doi":"10.1140/epjqt/s40507-024-00285-3","DOIUrl":"10.1140/epjqt/s40507-024-00285-3","url":null,"abstract":"<div><p>This study explores the integration of quantum data embedding techniques into classical machine learning (ML) algorithms; to assess performance enhancements and computational implications across a spectrum of models. We explored various classical-to-quantum mapping methods; ranging from basis encoding and angle encoding to amplitude encoding; for encoding classical data. We conducted an extensive empirical study encompassing popular ML algorithms, including Logistic Regression, K-Nearest Neighbors, Support Vector Machines, and ensemble methods like Random Forest, LightGBM, AdaBoost, and CatBoost. Our findings reveal that quantum data embedding contributes to improved classification accuracy and F1 scores, particularly notable in models that inherently benefit from enhanced feature representation. We observed nuanced effects on running time, with low-complexity models exhibiting moderate increases and more computationally intensive models experiencing discernible changes. Notably, ensemble methods demonstrated a favorable balance between performance gains and computational overhead.</p><p>This study underscores the potential of quantum data embedding to enhance classical ML models and emphasizes the importance of weighing performance improvements against computational costs. Future research may involve refining quantum encoding processes to optimize computational efficiency and explore scalability for real-world applications. Our work contributes to the growing body of knowledge on the intersection of quantum computing and classical machine learning, offering insights for researchers and practitioners seeking to harness the advantages of quantum-inspired techniques in practical scenarios.</p></div>","PeriodicalId":547,"journal":{"name":"EPJ Quantum Technology","volume":"11 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://epjquantumtechnology.springeropen.com/counter/pdf/10.1140/epjqt/s40507-024-00285-3","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142518802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Quantum algorithms have demonstrated extraordinary potential across numerous fields, offering significant advantages in solving practical problems. Power Quality Disturbances (PQDs) have always been a critical factor affecting the stability and safety of electrical power systems, and accurately detecting and identifying PQDs is crucial for ensuring reliable system operation. This paper explores the application of quantum algorithms in the field of power quality and proposes a novel method using Quantum Support Vector Machines (QSVM) to detect and identify PQDs, which marks the first application of QSVM in PQD analysis. The QSVM model employed involves three main stages: quantum feature mapping, quantum kernel computation, and model training. Quantum feature mapping uses quantum circuits to map classical data into a high-dimensional Hilbert space, enhancing feature separability. Quantum kernel computation calculates the inner products between features for model training. Rigorous theoretical and experimental analyses validate our approach. This method achieves a time complexity of (O(N^{2} log (N))), superior to classical SVM algorithms. Simulation results show high accuracy in PQDs detection, achieving a 100% detection rate and a 96.25% accuracy rate in single PQD identification. Experimental outcomes demonstrate robustness, maintaining over 87% accuracy even with increased noise levels, confirming its effectiveness in PQDs detection and identification.
{"title":"An advanced quantum support vector machine for power quality disturbance detection and identification","authors":"Qing-Le Wang, Yu Jin, Xin-Hao Li, Yue Li, Yuan-Cheng Li, Ke-Jia Zhang, Hao Liu, Long Cheng","doi":"10.1140/epjqt/s40507-024-00283-5","DOIUrl":"10.1140/epjqt/s40507-024-00283-5","url":null,"abstract":"<div><p>Quantum algorithms have demonstrated extraordinary potential across numerous fields, offering significant advantages in solving practical problems. Power Quality Disturbances (PQDs) have always been a critical factor affecting the stability and safety of electrical power systems, and accurately detecting and identifying PQDs is crucial for ensuring reliable system operation. This paper explores the application of quantum algorithms in the field of power quality and proposes a novel method using Quantum Support Vector Machines (QSVM) to detect and identify PQDs, which marks the first application of QSVM in PQD analysis. The QSVM model employed involves three main stages: quantum feature mapping, quantum kernel computation, and model training. Quantum feature mapping uses quantum circuits to map classical data into a high-dimensional Hilbert space, enhancing feature separability. Quantum kernel computation calculates the inner products between features for model training. Rigorous theoretical and experimental analyses validate our approach. This method achieves a time complexity of <span>(O(N^{2} log (N)))</span>, superior to classical SVM algorithms. Simulation results show high accuracy in PQDs detection, achieving a 100% detection rate and a 96.25% accuracy rate in single PQD identification. Experimental outcomes demonstrate robustness, maintaining over 87% accuracy even with increased noise levels, confirming its effectiveness in PQDs detection and identification.</p></div>","PeriodicalId":547,"journal":{"name":"EPJ Quantum Technology","volume":"11 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://epjquantumtechnology.springeropen.com/counter/pdf/10.1140/epjqt/s40507-024-00283-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142453129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-22DOI: 10.1140/epjqt/s40507-024-00284-4
J. A. Bravo-Montes, Miriam Bastante, Guillermo Botella, Alberto del Barrio, F. García-Herrero
Currently, access to quantum processors is costly in terms of time, and power. There are quantum simulators and emulators on the market that offer alternatives for evaluating the behavior of a real quantum processor. However, these emulation environments present accuracy deviations from real devices, mainly because of difficult-to-model error sources. In this study, a methodology is proposed that allows the selection of noise models and adjustment of their parameters, considering the nature of the backends (technology, topology, vendor, model, etc.). The proposed methodology is illustrated using a small superconducting example based on the ibm_perth backend (seven qubits) and a comparison between the quantum emulators Qaptiva and Qiskit, where six different noise models are applied, achieving a fidelity deviation of 0.686% at best with respect to the real device.
{"title":"A methodology to select and adjust quantum noise models through emulators: benchmarking against real backends","authors":"J. A. Bravo-Montes, Miriam Bastante, Guillermo Botella, Alberto del Barrio, F. García-Herrero","doi":"10.1140/epjqt/s40507-024-00284-4","DOIUrl":"10.1140/epjqt/s40507-024-00284-4","url":null,"abstract":"<div><p>Currently, access to quantum processors is costly in terms of time, and power. There are quantum simulators and emulators on the market that offer alternatives for evaluating the behavior of a real quantum processor. However, these emulation environments present accuracy deviations from real devices, mainly because of difficult-to-model error sources. In this study, a methodology is proposed that allows the selection of noise models and adjustment of their parameters, considering the nature of the backends (technology, topology, vendor, model, etc.). The proposed methodology is illustrated using a small superconducting example based on the <i>ibm_perth</i> backend (seven qubits) and a comparison between the quantum emulators <i>Qaptiva</i> and <i>Qiskit</i>, where six different noise models are applied, achieving a fidelity deviation of 0.686% at best with respect to the real device.</p></div>","PeriodicalId":547,"journal":{"name":"EPJ Quantum Technology","volume":"11 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://epjquantumtechnology.springeropen.com/counter/pdf/10.1140/epjqt/s40507-024-00284-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142453128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-18DOI: 10.1140/epjqt/s40507-024-00282-6
Vicente P. Soloviev, Vedran Dunjko, Concha Bielza, Pedro Larrañaga, Hao Wang
Quantum architecture search (QAS) involves optimizing both the quantum parametric circuit configuration but also its parameters for a variational quantum algorithm. Thus, the problem is known to be multi-level as the performance of a given architecture is unknown until its parameters are tuned using classical routines. Moreover, the task becomes even more complicated since well-known trainability issues, e.g., barren plateaus (BPs), can occur. In this paper, we aim to achieve two improvements in QAS: (1) to reduce the number of measurements by an online surrogate model of the evaluation process that aggressively discards architectures of poor performance; (2) to avoid training the circuits when BPs are present. To detect the presence of the BPs, we employed a recently developed metric, information content, which only requires measuring the energy values of a small set of parameters to estimate the magnitude of cost function’s gradient. The main idea of this proposal is to leverage a recently developed metric which can be used to detect the onset of vanishing gradients to ensure the overall search avoids such unfavorable regions. We experimentally validate our proposal for the variational quantum eigensolver and showcase that our algorithm is able to find solutions that have been previously proposed in the literature for the Hamiltonians; but also to outperform the state of the art when initializing the method from the set of architectures proposed in the literature. The results suggest that the proposed methodology could be used in environments where it is desired to improve the trainability of known architectures while maintaining good performance.
量子架构搜索(QAS)不仅涉及优化量子参数电路配置,还涉及优化变量子算法的参数。因此,这个问题是多层次的,因为在使用经典程序调整参数之前,给定架构的性能是未知的。此外,由于可能出现众所周知的可训练性问题,如贫瘠高原(BP),因此任务变得更加复杂。在本文中,我们的目标是实现 QAS 的两项改进:(1) 通过评估过程的在线代理模型减少测量次数,该模型会主动放弃性能较差的架构;(2) 避免在出现 BP 时对电路进行训练。为了检测 BPs 的存在,我们采用了最近开发的一种指标--信息含量,它只需要测量一小部分参数的能量值,就能估算出成本函数梯度的大小。这项建议的主要思路是利用最近开发的指标来检测梯度消失的起始点,以确保整体搜索避开此类不利区域。我们通过实验验证了我们针对变分量子等差数列求解器提出的建议,并表明我们的算法不仅能找到以前文献中提出的哈密尔顿解,而且在从文献中提出的架构集初始化方法时,其性能也优于目前的技术水平。结果表明,所提出的方法可用于希望提高已知架构的可训练性,同时保持良好性能的环境中。
{"title":"Trainability maximization using estimation of distribution algorithms assisted by surrogate modelling for quantum architecture search","authors":"Vicente P. Soloviev, Vedran Dunjko, Concha Bielza, Pedro Larrañaga, Hao Wang","doi":"10.1140/epjqt/s40507-024-00282-6","DOIUrl":"10.1140/epjqt/s40507-024-00282-6","url":null,"abstract":"<div><p>Quantum architecture search (QAS) involves optimizing both the quantum parametric circuit configuration but also its parameters for a variational quantum algorithm. Thus, the problem is known to be multi-level as the performance of a given architecture is unknown until its parameters are tuned using classical routines. Moreover, the task becomes even more complicated since well-known trainability issues, e.g., barren plateaus (BPs), can occur. In this paper, we aim to achieve two improvements in QAS: (1) to reduce the number of measurements by an online surrogate model of the evaluation process that aggressively discards architectures of poor performance; (2) to avoid training the circuits when BPs are present. To detect the presence of the BPs, we employed a recently developed metric, information content, which only requires measuring the energy values of a small set of parameters to estimate the magnitude of cost function’s gradient. The main idea of this proposal is to leverage a recently developed metric which can be used to detect the onset of vanishing gradients to ensure the overall search avoids such unfavorable regions. We experimentally validate our proposal for the variational quantum eigensolver and showcase that our algorithm is able to find solutions that have been previously proposed in the literature for the Hamiltonians; but also to outperform the state of the art when initializing the method from the set of architectures proposed in the literature. The results suggest that the proposed methodology could be used in environments where it is desired to improve the trainability of known architectures while maintaining good performance.</p></div>","PeriodicalId":547,"journal":{"name":"EPJ Quantum Technology","volume":"11 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://epjquantumtechnology.springeropen.com/counter/pdf/10.1140/epjqt/s40507-024-00282-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142451134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-18DOI: 10.1140/epjqt/s40507-024-00281-7
Efraim Yehuda Weissman, Avraham Merzel, Nadav Katz, Igal Galili
{"title":"Correction: Keep it secret, keep it safe: teaching quantum key distribution in high school","authors":"Efraim Yehuda Weissman, Avraham Merzel, Nadav Katz, Igal Galili","doi":"10.1140/epjqt/s40507-024-00281-7","DOIUrl":"10.1140/epjqt/s40507-024-00281-7","url":null,"abstract":"","PeriodicalId":547,"journal":{"name":"EPJ Quantum Technology","volume":"11 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://epjquantumtechnology.springeropen.com/counter/pdf/10.1140/epjqt/s40507-024-00281-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142447395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-17DOI: 10.1140/epjqt/s40507-024-00278-2
Chao Du, Zhi Ma, Yiting Liu, Hong Wang, Yangyang Fei
Recently, the circular connectivity pattern has been presented for a class of stabilizer quantum error correction codes. The circular connectivity pattern for such a class of stabilizer codes can be implemented in a resource-efficient manner using a single ancilla and native two-qubit Controlled-Not-Swap gates (CNS) gates, which may be interesting for demonstrating error-correction codes with superconducting quantum processors. However, one concern is that this scheme is not fault-tolerant. And it might not apply to the Calderbank-Shor-Steane (CSS) codes. In this paper, we present a fault-tolerant version of the circular connectivity pattern, named the double-circular connectivity pattern. This pattern is an implementation for syndrome-measurement circuits with a flagged error correction scheme for stabilizer codes. We illustrate that this pattern is available for Steane code (a CSS code), Laflamme’s five-qubit code, and Shor’s nine-qubit code. For Laflamme’s five-qubit code and Shor’s nine-qubit code, the pattern has the property that it uses only native two-qubit CNS gates, which are more efficient in the superconducting quantum platform.
{"title":"Fault-tolerant double-circular connectivity pattern for quantum stabilizer codes","authors":"Chao Du, Zhi Ma, Yiting Liu, Hong Wang, Yangyang Fei","doi":"10.1140/epjqt/s40507-024-00278-2","DOIUrl":"10.1140/epjqt/s40507-024-00278-2","url":null,"abstract":"<div><p>Recently, the circular connectivity pattern has been presented for a class of stabilizer quantum error correction codes. The circular connectivity pattern for such a class of stabilizer codes can be implemented in a resource-efficient manner using a single ancilla and native two-qubit Controlled-Not-Swap gates (CNS) gates, which may be interesting for demonstrating error-correction codes with superconducting quantum processors. However, one concern is that this scheme is not fault-tolerant. And it might not apply to the Calderbank-Shor-Steane (CSS) codes. In this paper, we present a fault-tolerant version of the circular connectivity pattern, named the double-circular connectivity pattern. This pattern is an implementation for syndrome-measurement circuits with a flagged error correction scheme for stabilizer codes. We illustrate that this pattern is available for Steane code (a CSS code), Laflamme’s five-qubit code, and Shor’s nine-qubit code. For Laflamme’s five-qubit code and Shor’s nine-qubit code, the pattern has the property that it uses only native two-qubit CNS gates, which are more efficient in the superconducting quantum platform.</p></div>","PeriodicalId":547,"journal":{"name":"EPJ Quantum Technology","volume":"11 1","pages":""},"PeriodicalIF":5.8,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://epjquantumtechnology.springeropen.com/counter/pdf/10.1140/epjqt/s40507-024-00278-2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}