2022 IEEE International Conference on Quantum Computing and Engineering (QCE)最新文献

Modular software for real-time quantum control systems 模块化软件用于实时量子控制系统

2022 IEEE International Conference on Quantum Computing and Engineering (QCE) Pub Date : 2022-09-01 DOI: 10.1109/QCE53715.2022.00077

L. Riesebos, Brad Bondurant, Jacob Whitlow, Junki Kim, M. Kuzyk, Tianyi Chen, Samuel Phiri, Ye Wang, Chao Fang, Andrew Van Horn, Jungsang Kim, K. Brown

引用次数: 6

Power dependent dynamics of the 2nd excited state of a Transmon qubit Transmon量子比特第二激发态的功率依赖动力学

2022 IEEE International Conference on Quantum Computing and Engineering (QCE) Pub Date : 2022-09-01 DOI: 10.1109/QCE53715.2022.00136

Jeakyung Choi, Heyok Hwang, Eunseong Kim

引用次数: 0

Efficient Data Encoding and Decoding for Quantum Computing 量子计算的高效数据编码与解码

2022 IEEE International Conference on Quantum Computing and Engineering (QCE) Pub Date : 2022-09-01 DOI: 10.1109/QCE53715.2022.00110

Naveed Mahmud, M. Jeng, Md. Alvir Islam Nobel, Manu Chaudhary, S. Islam, David Levy, E. El-Araby

{"title":"Efficient Data Encoding and Decoding for Quantum Computing","authors":"Naveed Mahmud, M. Jeng, Md. Alvir Islam Nobel, Manu Chaudhary, S. Islam, David Levy, E. El-Araby","doi":"10.1109/QCE53715.2022.00110","DOIUrl":"https://doi.org/10.1109/QCE53715.2022.00110","url":null,"abstract":"Noisy Intermediate-Scale Quantum (NISQ) devices face many critical challenges that limit their usefulness for practical applications. A primary challenge is classical-to-quantum (C2Q) data encoding, which requires specific circuits for quantum state initialization, particularly for I/O intensive applications. The required state initialization circuits are often complex, and violate decoherence constraints. Another critical challenge for quantum computers is quantum state readout or quantum-to-classical (Q2C) data decoding. The general approach for Q2C involves repeated sampling of the quantum circuit, which often incurs significant overhead in the overall execution time. In this paper, we propose time-efficient methods for C2Q data encoding and Q2C data decoding for quantum algorithms. Decoherence optimized circuits for C2Q data encoding are presented along with analysis of their circuit depths. For Q2C, a novel approach based on more efficient sampling of the output state using the Quantum Wavelet Transform is proposed. The proposed methods are experimentally evaluated on a state-of-the-art quantum computing device from IBM Quantum using realistic multi-spectral data. Experimental results are consistent with our theoretical expectations and confirm the efficiency of our proposed methods compared to existing techniques. More specifically, our proposed C2Q method demonstrates a theoretical 2x reduction in circuit depth which resulted in improving the experimental execution time compared to the state-of-the-art, while our Q2C method achieved a maximum of 89% reduction in circuit sampling time.","PeriodicalId":263626,"journal":{"name":"2022 IEEE International Conference on Quantum Computing and Engineering (QCE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125738616","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}

引用次数: 0

Unraveling the Effect of COVID-19 on the Selection of Optimal Portfolio Using Hybrid Quantum-Classical Algorithms 利用混合量子经典算法揭示COVID-19对最优投资组合选择的影响

2022 IEEE International Conference on Quantum Computing and Engineering (QCE) Pub Date : 2022-09-01 DOI: 10.1109/QCE53715.2022.00154

Shreyes Upadhyay, Vaidehi Dhande, Ishan NH Mankodi, Rupayan Bhatacharjee, Aaryav Mishra, Anindita Banerjee, R. Venkatraman

{"title":"Unraveling the Effect of COVID-19 on the Selection of Optimal Portfolio Using Hybrid Quantum-Classical Algorithms","authors":"Shreyes Upadhyay, Vaidehi Dhande, Ishan NH Mankodi, Rupayan Bhatacharjee, Aaryav Mishra, Anindita Banerjee, R. Venkatraman","doi":"10.1109/QCE53715.2022.00154","DOIUrl":"https://doi.org/10.1109/QCE53715.2022.00154","url":null,"abstract":"Portfolio optimization is one of the important problem classes in finance sector. As the world economy recovered and reaching the pre-COVID levels and is still continuing to grow, it is imperative to understand what kind of impact COVID-19 had on portfolio optimization and how quantum computers can be used in doing so. Hybrid quantum algorithms like variational quantum eigen solver (VQE), quantum approximate optimization algorithm (QAOA) have been tried for identifying optimal portfolios. In the present work, we employ these algorithms to carry out portfolio optimization for different time intervals (which includes pre and during COVID-19 periods) and unravel the impact of COVID-19 on the same, across different industries.Our results show that the companies’ stocks were growing steadily more on a sideways movement from 2016-2017. The stocks start to pick momentum from 2018-2019 and in 2020 early months as dip can be observed, however all the stocks recover to normal levels and even reaching lifetime highs from second half of 2020. Keywords—Quantum Algorithms, Portfolio Optimization, Covid-19, Markowitz model, QAOA, VQE","PeriodicalId":263626,"journal":{"name":"2022 IEEE International Conference on Quantum Computing and Engineering (QCE)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126655943","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}

引用次数: 0

Quantum Computing for the Faint of Heart 心脏微弱的量子计算

2022 IEEE International Conference on Quantum Computing and Engineering (QCE) Pub Date : 2022-09-01 DOI: 10.1109/QCE53715.2022.00089

Noah Davis, B. Cour

引用次数: 1

A Continuous Variable Quantum Switch 连续可变量子开关

2022 IEEE International Conference on Quantum Computing and Engineering (QCE) Pub Date : 2022-09-01 DOI: 10.1109/QCE53715.2022.00057

I. Tillman, Thirupathaiah Vasantam, K. Seshadreesan

引用次数: 1

Enhanced entangling gates and scalable multizone operations in surface traps with integrated photonics 集成光子学表面陷阱中增强的纠缠门和可扩展的多区域操作

2022 IEEE International Conference on Quantum Computing and Engineering (QCE) Pub Date : 2022-09-01 DOI: 10.1109/qce53715.2022.00111

C. Mordini, Alfredo Ricci Vásquez, Chi Zhang, M. Malinowski, D. Kienzler, K. Mehta, J. Home

{"title":"Enhanced entangling gates and scalable multizone operations in surface traps with integrated photonics","authors":"C. Mordini, Alfredo Ricci Vásquez, Chi Zhang, M. Malinowski, D. Kienzler, K. Mehta, J. Home","doi":"10.1109/qce53715.2022.00111","DOIUrl":"https://doi.org/10.1109/qce53715.2022.00111","url":null,"abstract":"We present a surface-electrode Paul trap featuring integrated photonics elements, where ions are illuminated with two interfering beams at 729 nm forming a standing wave along the trap axis. In this field configuration, it is possible to excite the motional sidebands of a trapped ion while suppressing the off- resonant coupling to the corresponding carrier transition. This is of particular interest for quantum information processing, as it would allow implementing faster and lower error Mølmer-Sørensen entangling gates.We characterize the optical properties of the chip by scanning with sub-wavelength resolution the position of a single ion through the standing wave and observing Rabi oscillations for carrier and first motional sideband of different quadrupole transitions. We characterize both the strength of resonant couplings and the AC Stark shift induced by off-resonant couplings. We measure noise and drifts in the ion position and observe high stability in the standing wave profile without the need for active phase stabilization.Integrated optics allow to reliably reproduce the same field configuration in different regions of the chip, opening the way for implementing distributed, parallel quantum operations. We show the ability to control ions in different regions of the trap at the same time. We implemented real-time control of the DC voltages controlling the axial configuration of the trapping potential which enables us to load multiple ion crystals, merge, split, and shuttle them across the device.","PeriodicalId":263626,"journal":{"name":"2022 IEEE International Conference on Quantum Computing and Engineering (QCE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125731338","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}

引用次数: 0

Quantum Annealing Error Mitigation Using Mirror Symmetries on Different Generations of Quantum Annealers 利用不同代量子退加工机的镜像对称性降低量子退火误差

2022 IEEE International Conference on Quantum Computing and Engineering (QCE) Pub Date : 2022-09-01 DOI: 10.1109/QCE53715.2022.00140

Bhavika Bhalgamiya, Dilina Perera, M. Novotny

引用次数: 0

Smart Agriculture Decision Making Scheme Using Quantum Annealing 基于量子退火的智能农业决策方案

2022 IEEE International Conference on Quantum Computing and Engineering (QCE) Pub Date : 2022-09-01 DOI: 10.1109/QCE53715.2022.00145

Chia-Ho Ou, Dong-Jie Jiang, Chih-Yu Chen, Lien-Po Yu, Ching-Ray Chang

{"title":"Smart Agriculture Decision Making Scheme Using Quantum Annealing","authors":"Chia-Ho Ou, Dong-Jie Jiang, Chih-Yu Chen, Lien-Po Yu, Ching-Ray Chang","doi":"10.1109/QCE53715.2022.00145","DOIUrl":"https://doi.org/10.1109/QCE53715.2022.00145","url":null,"abstract":"Smart agriculture is introduced with the latest technologies to improve the overall agricultural production capacity and efficiency. This paper proposes a quantum-inspired decision making scheme for crop cultivation in smart agriculture. The goal of the scheme is to increase the farmers’ welfare by planting different types of crop on adjacent farmlands to achieve optimal balance of crop demand and production. The proposed scheme is modeled as a graph coloring problem, which is computationally hard to solve for large and complex graphs in general. By taking advantage of quantum-inspired metaheuristic approach, the graph coloring problem is formulated as Quadratic Unconstrained Binary Optimization (QUBO) model and solved by a quantum annealer. The experimental realization of the proposed method is investigated on D-Wave quantum annealing devices and its performance is compared with those of the brute-force and greedy algorithms. The experimental results show that the proposed decision making scheme achieves a higher success probability than the greedy algorithm and a much lower run time than the brute-force approach.","PeriodicalId":263626,"journal":{"name":"2022 IEEE International Conference on Quantum Computing and Engineering (QCE)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122245017","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}

引用次数: 0

Feature Selection for Classification with QAOA QAOA分类的特征选择

2022 IEEE International Conference on Quantum Computing and Engineering (QCE) Pub Date : 2022-09-01 DOI: 10.1109/QCE53715.2022.00117

Gloria Turati, Maurizio Ferrari Dacrema, P. Cremonesi

{"title":"Feature Selection for Classification with QAOA","authors":"Gloria Turati, Maurizio Ferrari Dacrema, P. Cremonesi","doi":"10.1109/QCE53715.2022.00117","DOIUrl":"https://doi.org/10.1109/QCE53715.2022.00117","url":null,"abstract":"Feature selection is of great importance in Machine Learning, where it can be used to reduce the dimensionality of classification, ranking and prediction problems. The removal of redundant and noisy features can improve both the accuracy and scalability of the trained models. However, feature selection is a computationally expensive task with a solution space that grows combinatorically. In this work, we consider in particular a quadratic feature selection problem that can be tackled with the Quantum Approximate Optimization Algorithm (QAOA), already employed in combinatorial optimization. First we represent the feature selection problem with the QUBO formulation, which is then mapped to an Ising spin Hamiltonian. Then we apply QAOA with the goal of finding the ground state of this Hamiltonian, which corresponds to the optimal selection of features. In our experiments, we consider seven different real–world datasets with dimensionality up to 21 and run QAOA on both a quantum simulator and, for small datasets, the 7–qubit IBM (ibm–perth) quantum computer. We use the set of selected features to train a classification model and evaluate its accuracy. Our analysis shows that it is possible to tackle the feature selection problem with QAOA and that currently available quantum devices can be used effectively. Future studies could test a wider range of classification models as well as improve the effectiveness of QAOA by exploring better performing optimizers for its classical step.","PeriodicalId":263626,"journal":{"name":"2022 IEEE International Conference on Quantum Computing and Engineering (QCE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127991265","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}

引用次数: 3