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Resource-efficient quantum-classical hybrid algorithm for energy gap evaluation

Physical Review A 2024年第5期109卷 052416-052416页

作者： Yongdan Yang Ying Li Xiaosi Xu Xiao Yuan Graduate School of China Academy of Engineering Physics Beijing 100193 China Center on Frontiers of Computing Studies Peking University Beijing 100871 China School of Computer Science Peking University Beijing 100871 China

Estimating the eigenvalue or energy gap of a Hamiltonian H is vital for studying quantum many-body systems. Particularly, many of the problems in quantum chemistry, condensed-matter physics, and nuclear physics investigate the energy gap between two eigenstates. Hence, how to efficiently solve the energy gap becomes an important motive for researching new quantum algorithms. In this work, we propose a hybrid nonvariational quantum algorithm that uses the Monte Carlo method and real-time Hamiltonian simulation to evaluate the energy gap of a general quantum many-body system. Compared to conventional approaches, our algorithm does not require controlled real-time evolution, thus making its implementation much more experimental friendly for near-term quantum devices and early fault-tolerant quantum computers. To verify the efficiency of our algorithm, we conduct numerical simulations for the Heisenberg model and molecule systems on a classical emulator.

关键词： Quantum algorithms Quantum computation

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Numerical Verification of Generation of Ultrasound-Driven Bent Flow by Centripetal and Tangential Body Force Field

Numerical Verification of Generation of Ultrasound-Driven Be...

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IEEE Symposium (IUS) Ultrasonics

作者： Kenta Matsuuchi Keisuke Hasegawa Department of Information Physics and Computing Graduate School of Information Science and Technology The University of Tokyo Tokyo Japan Department of Mechanical Science Graduate School of Science and Engineering Saitama University Saitama Japan

We propose a method of generating midair acoustic streaming traveling along a curve by combining a central acceleration field with a tangential one by ultrasound emissions from multiple phased arrays of ultrasound transducers. Via numerical experiments, we confirmed, using a hypothetical acceleration field, that a centripetal force contributed to the steady formation of a narrow curved flow. We also demonstrated that a curved flow (0.4 m radius semicircle) could be generated by the phased arrays emitting both centripetal and tangential acceleration field in their possible arrangements, both numerically and experimentally. Half of the arrays generated tangential force field parallel to the given beam trajectory and the others generated centripetal force field that penetrated the center of the array. Although currently generated flows being short in spatial range, such curved flows can potentially increase the spatial flexibility of applications, by circumventing obstacles in the environment, for example.

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Temperature-Dependent Hydrogen Modulations of Ultra-Scaled a-IGZO Thin Film Transistor Under Gate Bias Stress

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2024年 5卷 9-16页

作者： Aslam, Muhammad Chang, Shu-Wei Chuang, Min-Hui Chen, Yi-Ho Lee, Yao-Jen Li, Yiming Parallel and Scientific Computing Laboratory National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electrical Engineering National Cheng Kung University Tainan701401 Taiwan Institute of Communications Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Graduate Degree Program of College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Biomedical Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan

Recently, a-IGZO has advanced toward the next-generation electronics system because of its compatibility with complementary metal oxide semiconductor (CMOS) and back-end-of-line (BOEL) based systems. A systematic electrical characterization of a-IGZO TFT related to reliability issues, such as positive bias temperature stress (PBTS) and negative bias temperature stress (NBTS), would entitle its integration into novel electronics systems. Unexpectedly, PBTS is characterized by the transition of positive Vth shift to negative Vth shift (ΔVth, the positive shift followed by the stress and temperature activated negative shift). This transition is attributed to charge trapping/trap-site generations and hydrogen migration to the active layer. The ΔVth shift mechanism depends on the temperature and voltage stress. On the other hand, a negative ΔVth shift has been observed during the NBTS operation and could be attributed to the hole trapping at the interface of GI/IGZO. An effective suppression of the gate leakage current has also been observed during reliability tests. Simulation results reveal a pronounced potential at the edges of source and drain regions, and considered the origin of hydrogen migration into the IGZO layer. Thermal image results also reveal the strong temperature/potential distribution at the edges of the source/drain regions, indorsing the simulation results. © 2020 IEEE.

关键词： Oxide semiconductors

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Transcriptomic analysis of Andrias davidianus meat and experimental validation for exploring its bioactive components as functional foods

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Food science and Human Wellness 2024年第1期13卷 166-172页

作者： Changge Guan Zhenglin Tan Shucheng Li Yi Wang Naoyuki Yamamoto Chong Zhang Songjun Wang Junjie Chen Xinhui Xing Key Laboratory for Industrial Biocatalysis Ministry of Education of ChinaDepartment of Chemical EngineeringTsinghua UniversityBeijing 100084China School of Life Science and Technology Tokyo Institute of TechnologyYokohama 226-0026Japan Sensing System Research Center National Institute of Advanced Industrial Science and TechnologyTsukuba 305-8565Japan Center for Synthetic and Systems Biology Tsinghua UniversityBeijing 100084China Henan Giant Salamander Protection and Development Association Luoyang 471000China Intelligent Computing Research Center Harbin Institute of TechnologyShenzhen 518071China Institute of Biopharmaceutical and Health Engineering Tsinghua Shenzhen International Graduate SchoolShenzhen 518055China Institute of Biomedical Health Technology and Engineering Shenzhen Bay LaboratoryShenzhen 518067China

Andrias davidianus(Chinese giant salamander,CGS)is the largest and oldest extant amphibian species in the world and is a source of prospective functional food in ***,the progress of functional peptides mining was slow due to lack of reference genome and protein sequence *** this study,we illustrated full-length transcriptome sequencing to interpret the proteome of CGS meat and obtain 10703 coding DNA *** functional annotation and amino acid composition analysis,we have discovered various genes related to signal transduction,and 16 genes related to *** have also found vast variety of functional peptides through protein coding sequence(CDS)analysis by comparing the data obtained with the functional peptide ***-Pro-Ile predicted by the CDS analysis was released from the CGS meat through enzymatic hydrolysis,suggesting that our approach is *** study suggested that transcriptomic analysis can be used as a reference to guide polypeptide mining in CGS meat,thereby providing a powerful mining strategy for the bioresources with unknown genomic and proteomic sequences.

关键词： Chinese giant salamander Transcriptomic analysis Bioactive components Functional peptides mining

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Structured multi-track accompaniment arrangement via style prior modelling 24

Structured multi-track accompaniment arrangement via style p...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Jingwei Zhao Gus Xia Ziyu Wang Ye Wang Institute of Data Science NUS and Integrative Sciences and Engineering Programme NUS Graduate School Machine Learning Department MBZUAI and Computer Science Department NYU Shanghai Computer Science Department NYU Shanghai and Machine Learning Department MBZUAI School of Computing NUS and Institute of Data Science NUS and Integrative Sciences and Engineering Programme NUS Graduate School

ISBN: (纸本)9798331314385

In the realm of music AI, arranging rich and structured multi-track accompaniments from a simple lead sheet presents significant challenges. Such challenges include maintaining track cohesion, ensuring long-term coherence, and optimizing computational efficiency. In this paper, we introduce a novel system that leverages prior modelling over disentangled style factors to address these challenges. Our method presents a two-stage process: initially, a piano arrangement is derived from the lead sheet by retrieving piano texture styles; subsequently, a multi-track orchestration is generated by infusing orchestral function styles into the piano arrangement. Our key design is the use of vector quantization and a unique multi-stream Transformer to model the long-term flow of the orchestration style, which enables flexible, controllable, and structured music generation. Experiments show that by factorizing the arrangement task into interpretable sub-stages, our approach enhances generative capacity while improving efficiency. Additionally, our system supports a variety of music genres and provides style control at different composition hierarchies. We further show that our system achieves superior coherence, structure, and overall arrangement quality compared to existing baselines.

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FLUID-IoT : Flexible and Fine-Grained Access Control in Shared IoT Environments via Multi-user UI Distribution 24

FLUID-IoT : Flexible and Fine-Grained Access Control in Shar...

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Proceedings of the CHI Conference on Human Factors in computing Systems

作者： Sunjae Lee Minwoo Jeong Daye Song Junyoung Choi Seoyun Son Jean Y Song Insik Shin School of Computing KAIST Korea Republic of Graduate School of Information Security KAIST Korea Republic of Electrical Engineering and Computer Science DGIST Korea Republic of

ISBN: (纸本)9798400703300

The rapid growth of the Internet of Things (IoT) in shared spaces has led to an increasing demand for sharing IoT devices among multiple users. Yet, existing IoT platforms often fall short by offering an all-or-nothing approach to access control, not only posing security risks but also inhibiting the growth of the shared IoT ecosystem. This paper introduces FLUID-IoT, a framework that enables flexible and granular multi-user access control, even down to the User Interface (UI) component level. Leveraging a multi-user UI distribution technique, FLUID-IoT transforms existing IoT apps into centralized hubs that selectively distribute UI components to users based on their permission levels. Our performance evaluation, encompassing coverage, latency, and memory consumption, affirm that FLUID-IoT can be seamlessly integrated with existing IoT platforms and offers adequate performance for daily IoT scenarios. An in-lab user study further supports that the framework is intuitive and user-friendly, requiring minimal training for efficient utilization.

关键词： Access Control IoT-Security Multi-User IoT UI distribution

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Parkinson's Disease Detection Based on Vocal Biomarkers and Machine Learning Approach

Parkinson's Disease Detection Based on Vocal Biomarkers and ...

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2024 International Telecommunications Conference, ITC-Egypt 2024

作者： Alrosan, Ayat Abdel-Aty, M. Hafez, Mohamed Alkhazaleh, Shawkat Deif, Mohanad A. Elgohary, Rania Skyline University College School of Computing Sharjah United Arab Emirates Ahlia University Deanship of Research and Graduate Studies Bahrain FEQS INTI-IU-University Faculty of Engineering Nilai Malaysia Jadara University Faculty of Science and Information Technology Department of Mathematics Jordan Department of Artificial intelligence 12566 Egypt

ISBN: (纸本)9798350351408

Parkinson's disease (PD) must be identified early to provide prompt treatment and better patient outcomes. This study looks into using machine learning methods in conjunction with vocal biomarkers to identify Parkinson's disease early. Vocal data was analyzed using four techniques: Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Random Forest, and Logistic Regression algorithms. The third strategy, which used the Synthetic Minority Over-sampling Technique (SMOTE) for data balance, performed exceptionally well and stood out among the others. Utilizing SMOTE for dataset balancing, the Random Forest algorithm produced an exceptional 98.3 % accuracy. The study highlights the effectiveness of voice biomarkers, examines the various approaches used, and draws comparisons between them. © 2024 IEEE.

关键词： Random forests

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Performance Upper Bound of the Grover-Mixer Quantum Alternating Operator Ansatz

arXiv

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arXiv 2024年

作者： Xie, Ningyi Xu, Jiahua Chen, Tiejin Saito, Yoshiyuki Asai, Nobuyoshi Cai, Dongsheng Graduate School of Science and Technology University of Tsukuba Japan School of Computing and Augmented Intelligence Arizona State University United States Graduate School of Computer Science and Engineering University of Aizu Japan School of Computer Science and Engineering University of Aizu University of Aizu Japan Faculty of Engineering Information and Systems University of Tsukuba Japan

The Quantum Alternating Operator Ansatz (QAOA) represents a branch of quantum algorithms designed for solving combinatorial optimization problems. A specific variant, the Grover-Mixer Quantum Alternating Operator Ansatz (GM-QAOA), ensures uniform amplitude across states that share equivalent objective values. This property makes the algorithm independent of the problem structure, focusing instead on the distribution of objective values within the problem. In this work, we prove the probability upper bound for measuring a computational basis state from a GM-QAOA circuit with a given depth, which is a critical factor in QAOA cost. From this, we derive the upper bounds for the probability of sampling an optimal solution and for the approximation ratio of maximum optimization problems, based on the objective value distribution. Using numerical analysis, we link the distribution to the problem size and build the regression models that relate the problem size, QAOA depth, and performance upper bound. Our results suggest that the GM-QAOA provides a quadratic enhancement in sampling probability and requires circuit depth that scales exponentially with problem size to maintain consistent performance. © 2024, CC BY.

关键词： Mixers (machinery)

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Multilingual Sentiment Analysis using Deep-Learning Architectures 5

Multilingual Sentiment Analysis using Deep-Learning Architec...

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5th International Conference on Smart Systems and Inventive Technology, ICSSIT 2023

作者： Dominic, Praveen Purushothaman, Niranjan Kumar, Anish Skanda Anil Prabagaran, A. Blessy, J. Angelin John, A. School of Graduate Studies MSc in Big Data Analytics Trent University Ontario Canada Visa Consolidated Support Services India Pvt. Ltd Bengaluru India School of Computing Science and Engineering Galgotias University Uttar Pradesh Greater Noida India

ISBN: (纸本)9781665474672

Machine learning techniques such as NLP (Natural language processing) play a key role in a context where mining social media data could add great value to governments of the world countries. The posts and tweets shared by the people on social media can be mined to infer the valuable 'mindset' of the people which is much required for any ruling government in the world. The objective of this study is to conduct sentiment analysis to mine the sentiment of the people regarding the ongoing war between Russia and Ukraine, using machine learning techniques. The idea is to analyze and infer if the countries have reacted in some way, considering the sentiment of their citizens, in the context of economic effects. The pipeline of the implementation associated starts with the data collection from social media such as Twitter and Reddit using Snscraper and the PRAW (Python Reddit API Wrapper). The larger posts from Reddit are handled by implementing suitable text summarization techniques. Sentiment analysis is performed for the social media data using the BERT transformer model. The non-English posts are translated to English using neural machine translation. Also, sentiment analysis is performed at various granularities such as the location and the people that are tagged using Named Entity Recognition techniques. Finally, a comparative analysis of the world countries' sentiment and their corresponding reliance on Russian oil is performed. © 2023 IEEE.

关键词： Sentiment analysis

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Entanglement-assisted phase-estimation algorithm for calculating dynamical response functions

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Physical Review A 2024年第2期110卷 022618页

作者： Rei Sakuma Shu Kanno Kenji Sugisaki Takashi Abe Naoki Yamamoto Materials Informatics Initiative RD Technology & Digital Transformation Center Quantum Computing Center Science & Innovation Center Yokohama 227-8502 Japan Graduate School of Science and Technology Centre for Quantum Engineering Research and Education Department of Applied Physics and Physico-Informatics

Dynamical response functions are fundamental quantities to describe the excited-state properties in quantum many-body systems. Quantum algorithms have been proposed to evaluate these quantities by means of quantum phase estimation (QPE), where the energy spectra are directly extracted from the QPE measurement outcomes in the frequency domain. Accurate estimation of excitation energies and transition probabilities with these QPE-based approaches is, however, challenging because of the problem of spectral leakage (or peak broadening) which is inherent in the QPE algorithm. To overcome this issue, in this work we consider an extension of the QPE-based approach adopting the optimal entangled input states, which is known to achieve the Heisenberg-limited scaling for the estimation precision. We show that with this method the peaks in the calculated energy spectra are more localized than those calculated by the original QPE-based approaches, suggesting the mitigation of the spectral leakage problem. By analyzing the probability distribution with the entangled phase estimation, we propose a simple scheme to better estimate both the transition energies and the corresponding transition probabilities of the peaks of interest in the spectra. The validity of our prescription is demonstrated by numerical simulations in various quantum many-body problems: the spectral function of a simple electron-plasmon model in condensed-matter physics, the dipole transitions of the H2O molecule in quantum chemistry, and the electromagnetic transitions of the Li6 nucleus in nuclear physics.

关键词： Electronic transitions Nuclear transition rates Quantum computation Green's function methods

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