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arXiv 2023年

作者： Zhao, Jingwei Xia, Gus Wang, Ye School of Computing NUS Singapore Institute of Data Science NUS Singapore Integrative Sciences and Engineering Programme NUS Graduate School Singapore Music X Lab NYU Shanghai China MBZUAI United Arab Emirates

Music rearrangement is a common music practice of reconstructing and reconceptualizing a piece using new composition or instrumentation styles, which is also an important task of automatic music generation. Existing studies typically model the mapping from a source piece to a target piece via supervised learning. In this paper, we tackle rearrangement problems via self-supervised learning, in which the mapping styles can be regarded as conditions and controlled in a flexible way. Specifically, we are inspired by the representation disentanglement idea and propose Q&A, a query-based algorithm for multi-track music rearrangement under an encoder-decoder framework. Q&A learns both a content representation from the mixture and function (style) representations from each individual track, while the latter queries the former in order to rearrange a new piece. Our current model focuses on popular music and provides a controllable pathway to four scenarios: 1) re-instrumentation, 2) piano cover generation, 3) orchestration, and 4) voice separation. Experiments show that our query system achieves high-quality rearrangement results with delicate multi-track structures, significantly outperforming the baselines. © 2023, CC BY.

关键词： Music

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Scalable circuit depth reduction in feedback-based quantum optimization with a quadratic approximation

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Physical Review Research 2025年第1期7卷 013035-013035页

作者： Don Arai Ken N. Okada Yuichiro Nakano Kosuke Mitarai Keisuke Fujii Graduate School of Engineering Science Osaka University 1-3 Machikaneyama Toyonaka Osaka 560-8531 Japan Center for Quantum Information and Quantum Biology Osaka University 1-2 Machikaneyama Toyonaka 560-0043 Japan RIKEN Center for Quantum Computing (RQC) Hirosawa 2-1 Wako Saitama 351-0198 Japan

Combinatorial optimization problems are one of the areas where near-term noisy quantum computers may have practical advantage against classical computers. Recently, a feedback-based quantum optimization algorithm has been proposed by Magann et al., Phys. Rev. Lett. 129, 250502 (2022). The method explicitly determines quantum circuit parameters by feeding back measurement results thus avoids classical parameter optimization that is known to cause significant trouble in quantum approximate optimization algorithm, the well-studied near-term algorithm. Meanwhile, a significant drawback of the feedback-based quantum optimization is that it requires deep circuits, rendering the method unsuitable to noisy quantum devices. In this study we propose a feedback law for parameter determination by introducing the second-order approximation with respect to time interval, a hyperparameter in the feedback-based quantum optimization. This allows one to take larger time interval, leading to acceleration of convergence to solutions. In numerical simulations on the maximum cut problem we demonstrate that our proposal significantly reduces circuit depth, with its linear scaling with the problem size smaller by more than an order of magnitude. We expect that the feedback law proposed in this work may pave the way for feedback-based quantum optimization with near-term noisy quantum computers.

关键词： Quantum computers

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Coherent transfer of the higher-order polarization state of photons to the spin structure state of electrons in a semiconductor

Optica Quantum

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Optica Quantum 2024年第4期2卷 245-253页

作者： Toshiki Matsumoto Sota Sato Shota Akei Yuichiro Nakano Satoshi Iba Jun Ishihara Katsuhiko Miyamoto Nobuhiko Yokoshi Takashige Omatsu Ken Morita Graduate School of Engineering Chiba Universityhttps://***/01hjzeq58 Chiba 263-8522 Japan Research Center for Emerging Computing Technologies National Institute of Advanced Industrial Science and Technology Tsukuba Ibaraki 305-8568 Japan Graduate School of Engineering Tohoku University Sendai 980-8577 Japan Molecular Chirality Research Center Chiba Universityhttps://***/01hjzeq58 Chiba 263-8522 Japan Department of Physics and Electronics Osaka Metropolitan University Osaka 599-8531 Japan

Quantum state conversion from the higher-order polarization states of photons on a higher-order Poincaré sphere (HOPS) with spin angular momentum (SAM) and orbital angular momentum (OAM) to an electron system in a semiconductor host is an interesting topic for high-density quantum media conversion with high degrees of freedom (DoFs). In this paper, we present the spatial spin structure states of electrons on a higher-order Bloch sphere, corresponding to HOPS states, using the similarity between the electron states on the Bloch sphere and the polarization states on the Poincaré sphere. Furthermore, the coherent transfer of the spatial structure of photon polarization to the spin structure state of electrons was demonstrated for the first time in GaAs/AlGaAs quantum wells using a V-shaped three-level system. The results provide insights into the simultaneous coherent transfer of SAM and OAM from the extended states of photon-to-electron systems, leading to the realization of the quantum state transfer of the high-dimensional entangled states of photons to electron spins with different DoFs.

关键词： Circular polarization Photonic entanglement Quantum information Quantum teleportation Quantum wells Spatial light modulators

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TCM Tongue Segmentation and Analysis with a Mobile Device

TCM Tongue Segmentation and Analysis with a Mobile Device

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International Conference on Electrical, Electronics and System engineering (ICEESE)

作者： Alex Grant James Ferrarelli Maximilian Rozano QingQing Liu Jiaming Su Chen-Hsiang Yu School of Computing and Data Science Wentworth Institute of Technology Boston MA U.S.A. Dongzhimen Hospital Beijing University of Chinese Medicine Beijing China Multidisciplinary Graduate Engineering College of Engineering Northeastern University Boston MA U.S.A.

Mobile devices and applications provide increased accessibility to things like Traditional Chinese Medicine (TCM). Ideally, one would be able to seek out a diagnosis to the tongue using advanced machine learning models in a mobile device. However, such kind of models are still not yet available for the public. In this research, we investigated a way of combining machine learning with a mobile application to support tongue diagnosis for the public. For tongue segmentation, we experimented with an unsupervised approach (K-means), a supervised method and a deep learning model. There are two outcomes presented in this research. Firstly, the user can seamlessly take a picture from a mobile phone and send it over to the server for a segmentation process. Secondly, the image processed by the server would have at least some levels of autonomous analysis preformed on it with acceptable results using machine learning methods. Our current results indicate that we were able to finish some key steps in this process.

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Clifford gates with logical transversality for self-dual CSS codes

arXiv

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arXiv 2025年

作者： Tansuwannont, Theerapat Takada, Yugo Fujii, Keisuke Center for Quantum Information and Quantum Biology The University of Osaka Osaka Toyonaka560-0043 Japan Graduate School of Engineering Science The University of Osaka Osaka Toyonaka560-8531 Japan RIKEN Center for Quantum Computing Hirosawa 2-1 Saitama Wako351-0198 Japan

Quantum error-correcting codes with high encoding rate are good candidates for large-scale quantum computers as they use physical qubits more efficiently than codes of the same distance that encode only a few logical qubits. Some logical gate of a high-rate code can be fault-tolerantly implemented using transversal physical gates, but its logical operation may depend on the choice of a symplectic basis that defines logical Pauli operators of the code. In this work, we focus on [[n, k, d]] self-dual Calderbank-Shor-Steane (CSS) codes with k ≥ 1 and prove necessary and sufficient conditions for the code to have a symplectic basis such that (1) transversal logical Hadamard gates Nkj=1 H¯j can be implemented by transversal physical Hadamard gates Nni=1 Hi, and (2) for any (a1, . . ., ak) ∈ {−1, 1}k, transversal logical phase gates Nkj=1 S¯jaj can be implemented by transversal physical phase gates Nni=1 Sibi for some (b1, . . ., bn) ∈ {−1, 1}n. Self-dual CSS codes satisfying the conditions include any codes with odd n. We also generalize the idea to concatenated self-dual CSS codes and show that certain logical Clifford gates have multiple transversal implementations, each by logical gates at a different level of concatenation. Several applications of our results for fault-tolerant quantum computation with low overhead are also provided. Copyright © 2025, The Authors. All rights reserved.

关键词： Qubits

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Unsupervised Localization Toward Crowdsourced Trajectory Data: A Deep Reinforcement Learning Approach

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IEEE Transactions on Wireless Communications 2025年

作者： Si, Haonan Hou, Xiangwang Wang, Jingjing Boateng, Gordon Owusu Zhang, Zekai Guo, Xiansheng Niyato, Dusit University of Electronic Science and Technology of China Department of Electronic Engineering Chengdu611731 China Tsinghua University Department of Electronic Engineering Beijing100084 China Beihang University School of Cyber Science and Technology Beijing100191 China Tsinghua University Tsinghua Shenzhen International Graduate School Shenzhen518055 China Nanyang Technological University College of Computing and Data Science 117583 Singapore

Crowdsourcing is an effective method to alleviate the burden of conducting a site-survey procedure for localization tasks. However, crowdsourced data is typically inaccurately and scarcely annotated, rendering accurate localization a rather challenging problem. To alleviate this problem, we propose VRLoc, a deep reinforcement learning (DRL)-based unsupervised wireless localization framework using crowdsourced trajectory data. The proposed VRLoc primarily encompasses three components, i.e., a robust K-means (RKM) clustering method for generating a series of virtual reference points (VRPs), DRL for determining the physical layout for VRPs, and online localization based on VRPs. Specifically, the proposed RKM method employs a density-based approach for the initialization of cluster centers, rather than the commonly used random solution, yielding repeatable and reliable VRP generation results. To accurately determine the physical locations for VRPs, we develop a modified soft actor-critic (SAC)- based VRP layout method with multiple objectives, i.e., the connection topology among VRPs, the floor-plan information, and the near-field condition. Then, we effectively predict locations of target users by utilizing classification models to match the online collected samples with the VRPs annotated by physical locations. The proposed framework is advantageous in achieving high-accuracy unsupervised localization, with the VRPs bridging the unlabeled crowdsourced data and physical location space. Both experimental and simulation results demonstrate the effectiveness and superiority of the proposed VRLoc framework as an accurate and practical solution for unsupervised localization. © 2002-2012 IEEE.

关键词： Deep reinforcement learning

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Optimal and nearly optimal simulation of multiperiodic time-dependent Hamiltonians

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Physical Review Research 2023年第3期5卷 033067-033067页

作者： Kaoru Mizuta RIKEN Center for Quantum Computing (RQC) Hirosawa 2-1 Wako Saitama 351-0198 Japan Department of Applied Physics Graduate School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656 Japan Photon Science Center Graduate School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656 Japan

Simulating Hamiltonian dynamics is one of the most fundamental and significant tasks for characterizing quantum materials. Recently, a series of quantum algorithms employing block encoding of Hamiltonians have succeeded in providing efficient simulation of time-evolution operators on quantum computers. While time-independent Hamiltonians can be simulated by the quantum eigenvalue transformation (QET) or quantum singular value transformation with the optimal query complexity in time t and desirable accuracy ɛ, generic time-dependent Hamiltonians face at larger query complexity and more complicated oracles due to the difficulty of handling time-dependency. In this paper, we establish a QET-based approach for simulating time-dependent Hamiltonians with multiple time periodicity. Such time-dependent Hamiltonians involve a variety of nonequilibrium systems such as time-periodic systems (Floquet systems) and time-quasiperiodic systems. Overcoming the difficulty of time dependency, our protocol can simulate the dynamics under multiperiodic time-dependent Hamiltonians with optimal and nearly optimal query complexity both in time t and desirable accuracy ɛ, and simple oracles as well as the optimal algorithm for time-independent cases.

关键词： Quantum simulation Nonequilibrium systems

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Analysis of temporal structure of laser chaos by Allan variance

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Physical Review E 2023年第1期107卷 014211-014211页

作者： Naoki Asuke Nicolas Chauvet André Röhm Kazutaka Kanno Atsushi Uchida Tomoaki Niiyama Satoshi Sunada Ryoichi Horisaki Makoto Naruse Department of Information Physics and Computing Graduate School of Information Science and Technology The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656 Japan Department of Information and Computer Sciences Saitama University 255 Shimo-Okubo Sakura-ku Saitama city Saitama 338-8570 Japan Faculty of Mechanical Engineering Institute of Science and Engineering Kanazawa University Kakuma Kanazawa city Ishikawa 920-1192 Japan

Allan variance has been widely utilized for evaluating the stability of the time series generated by atomic clocks and lasers, in time regimes ranging from short to extremely long. This multiscale examination capability of the Allan variance may also be beneficial in evaluating the chaotic oscillating dynamics of semiconductor lasers— not just for conventional phase stability analysis. In the present study, we demonstrated Allan variance analysis of the complex time series generated by a semiconductor laser with delayed feedback, including low-frequency fluctuations (LFFs), which exhibit both fast and slow dynamics. While the detection of LFFs is difficult with the conventional power spectrum analysis method in the low-frequency regime, the Allan variance approach clearly captured the appearance of multiple time-scale dynamics, such as LFFs. This study demonstrates that Allan variance can help in understanding and characterizing diverse laser dynamics, including LFFs, spanning a wide range of timescales.

关键词： Chaos

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New Approach to Multi-Modal Multi-View Video Coding

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Chinese Journal of Electronics 2023年第2期18卷 338-342页

作者： Yun Zhang Mei Yu Gangyi Jiang Institute of Computing Technology Chinese Academic of Sciences Beijing China Graduate School of Chinese Academic of Sciences Beijing China Faculty of Information Science and Engineering Ningbo University Ningbo China National Key Laboratory of Software New Technology Nanjing University Nanjing China

The correlation characteristics of Multi-view video (MVV) are influenced by the content of the video, illumination change, speed of moving objects and cameras, camera distance, frame rate, etc. In this paper, a framework of Multi-modal multi-view video coding (MMVC) is proposed on the basis of correlation analysis to achieve optimal performances among high compression efficiency, low complexity, low memory cost, view scalability and fast random access. Different prediction modes are designed to fit MVV with different correlations and meet different requirements of the Multi-view video coding (MVC). An optimal prediction mode is adaptively selected from the candidate modes according to the correlation characteristics of MVV. Experimental results have proved that MMVC not only has best random accessibility, but also has outstanding performance in compression efficiency, low memory requirement, low complexity and view scalability. MMVC is regarded as the most efficient and balanced MVC scheme among the compared schemes.

关键词： Video coding Correlation Costs Scalability Memory management Video sequences Lighting

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An Artificial Intelligence Approach for Solving Stochastic Transportation Problems

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Computers, Materials & Continua 2022年第1期70卷 817-829页

作者： Prachi Agrawal Khalid Alnowibet Talari Ganesh Adel F.Alrasheedi Hijaz Ahmad Ali Wagdy Mohamed Department of Mathematics and Scientific Computing National Institute of Technology HamirpurHimachal Pradesh177005India Statistics and Operations Research Department College of ScienceKing Saud UniversityRiyadh11451Kingdom of Saudi Arabia Section of Mathematics International Telematic University UninettunoRoma00186Italy Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGizaEgypt

Recent years witness a great deal of interest in artificial intelligence(AI)tools in the area of *** has developed a large number of tools to solve themost difficult search-and-optimization problems in computer science and operations ***,metaheuristic-based algorithms are a sub-field of *** study presents the use of themetaheuristic algorithm,that is,water cycle algorithm(WCA),in the transportation problem.A stochastic transportation problem is considered in which the parameters supply and demand are considered as random variables that follow the Weibull *** the parameters are stochastic,the corresponding constraints are *** are converted into deterministic constraints using the stochastic programming *** this study,we propose evolutionary algorithms to handle the difficulties of the complex high-dimensional optimization *** is influenced by the water cycle process of how streams and rivers flow toward the sea(optimal solution).WCA is applied to the stochastic transportation problem,and obtained results are compared with that of the new metaheuristic optimization algorithm,namely the neural network algorithm which is inspired by the biological nervous *** is concluded that WCA presents better results when compared with the neural network algorithm.

关键词： Artificial intelligence metaheuristic algorithm stochastic programming transportation problem water cycle algorithm weibull distribution

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