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arXiv 2024年

作者： Liu, Yang Lu, Jincheng Xiong, Zhongfei Wu, Fan O. Christodoulides, Demetrios Chen, Yuntian Jiang, Jian-Hua School of Physical Science and Technology Collaborative Innovation Center of Suzhou Nano Science and Technology Soochow University 1 Shizi Street Suzhou215006 China Jiangsu Key Laboratory of Micro and Nano Heat Fluid Flow Technology and Energy Application School of Physical Science and Technology Suzhou University of Science and Technology Suzhou215009 China School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan430074 China CREOL College of Optics and Photonics University of Central Florida OrlandoFL32816-2700 United States Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States School of Biomedical Engineering Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou215123 China School of Physics University of Science and Technology of China Hefei230026 China

Nonlinear multimode optical systems have attracted substantial attention due to their rich physical properties. Complex interplay between the nonlinear effects and mode couplings makes it difficult to understand the collective dynamics of photons. Recent studies show that such collective phenomena can be effectively described by a Rayleigh–Jeans thermodynamics theory which is a powerful tool for the study of nonlinear multimode photonic systems. These systems, in turn, offer a compelling platform for investigating fundamental issues in statistical physics, attributed to their tunability and the ability to access negative temperature regimes. However, to date, a theory for the nonequilibrium transport and fluctuations is yet to be established. Here, we employ the full counting statistics theory to study the nonequilibrium transport of particle and energy in nonlinear multimode photonic systems in both positive and negative temperature regimes. Furthermore, we discover that in situations involving two reservoirs of opposite temperatures and chemical potentials, an intriguing phenomenon known as the loop current effect can arise, wherein the current in the positive energy sector runs counter to that in the negative energy sector. In addition, we numerically confirm that the fluctuation theorem remains applicable in optical thermodynamics systems across all regimes, from positive temperature to negative ones. Our findings closely align with numerical simulations based on first-principles nonlinear wave equations. Our work seeks to deepen the understanding of irreversible non-equilibrium processes and statistical fluctuations in nonlinear many-body photonic systems which will enhance our grasp of collective phenomena of photons and foster a fruitful intersection between optics and statistical physics. © 2024, CC BY-NC-ND.

关键词： Temperature

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Nonlinear Feedforward enabling Nonlinear Quadrature Measurement toward Fault-tolerant Universal Quantum Computation

Nonlinear Feedforward enabling Nonlinear Quadrature Measurem...

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Frontiers in Optics + Laser Science 2021, FiO+LS 2021 - Part of Frontiers in Optics, FiO 2021

作者： Sakguchi, Atsushi Konno, Shunya Hanamura, Fumiya Ogawa, Hisashi Takase, Kan Asavanant, Warit Marek, Petr Filip, Radim Yoshikawa, Jun-Ichi Yonezawa, Hidehiro Huntington, Elanor Furusawa, Akira Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Saitama Wako351-0198 Japan Department of Optics Palacký University 17. listopadu 1192/12 Olomouc77146 Czech Republic Centre for Quantum Computation and Communication Technology School of Engineering and Information Technology University of New South Wales CanberraACT2600 Australia Centre for Quantum Computation and Communication Technology Research School of Electrical Energy and Materials Engineering College of Engineering and Computer Science Australian National University CanberraACT2600 Australia

We demonstrate nonlinear feedforward combined with non-Gaussian ancillae localized in time, which realizes nonlinear quadrature measurement. Our technology in principle enables fault-tolerant universal quantum computa... 详细信息

ISBN: (纸本)9781557528209

关键词： Quantum computers

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Exploiting NOMA and RIS in Integrated Sensing and Communication

arXiv

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arXiv 2022年

作者： Zuo, Jiakuo Liu, Yuanwei Zhu, Chenming Zou, Yixuan Zhang, Dengyin Al-Dhahir, Naofal The Institute of Communications and Information Technology China Information Consulting and Designing Institute Company Ltd. Nanjing210003 China School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing China The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom The Department of Electrical and Computer Engineering The University of Texas at Dallas RichardsonTX75080 United States

A novel integrated sensing and communication (ISAC) system is proposed, where a dual-functional base station is utilized to transmit the superimposed non-orthogonal multiple access (NOMA) communication signal for serving communication users and sensing targets simultaneously. Furthermore, a new reconfigurable intelligent surface (RIS)-aided-sensing structure, where a dedicated RIS is deployed to provide virtual line-of-sight (LoS) links for radar targets, is also proposed to address the significant path loss or blockage of LoS links for the sensing task. Based on this setup, the beampattern gain at the RIS for the radar target is derived and adopted as a sensing metric. The objective of this paper is to maximize the minimum beampattern gain by jointly optimizing active beamforming at the base station (BS), power allocation coefficients among NOMA users and passive beamforming at the RIS. To tackle the non-convexity of the formulated optimization problem, the beampattern gain and constraints are first transformed into more tractable forms. Then, an iterative block coordinate descent (IBCD) algorithm is proposed by employing successive convex approximation (SCA), Schur complement, semidefinite relaxation (SDR) and sequential rank-one constraint relaxation (SRCR) methods. To reduce the complexity of the proposed IBCD algorithm, a low-complexity iterative alternating optimization (IAO) algorithm is proposed. Particularly, the active beamforming is optimized by solving a semidefinite programming (SDP) problem and the closed-form solutions of the power allocation coefficients are derived. Numerical results show that: i) the proposed RIS-NOMA-ISAC system always outperforms the RIS-ISAC system © 2022, CC BY.

关键词： Beamforming

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Jseun: Joint Semantic-Instance Segmentation of Point Cloud Via Neighbor Features for Indoor Scenes

SSRN

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SSRN 2023年

作者： Chen, Hui Jiang, Jinlong Chen, Wanlou Liu, Wanquan Liu, Peter Xiaoping College of Automation Engineering Shanghai University of Electric Power Shanghai200090 China Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Nanovision Medical Technology Co. Ltd Shanghai200000 China School of Intelligent Systems Engineering Sun Yat-sen University Guangzhou510275 China Department of Systems and Computer Engineering Carleton University OttawaONK1S 5B6 Canada

Efficient and accurate segmentation of the point cloud for indoor scenes is an important task for 3D scene understanding. Due to the complexity of indoor environments. It is difficult to fully extract the details of point cloud, resulting in poor recognizability in existing models. In this paper, a novel framework called joint semantic-instance segmentation via enhancedutilization of neighbor features is proposed to achieve semantic and instance segmentation of indoor scenes. This framework mines point cloud information from a local scale, but it is different from other models in that it focuses on the full mining of point cloud neighbor information. In this regard, a new neighbor feature extraction module is developed to enrich the expression of neighborhood information and enlarge the construction of the neighborhood neighbor scope. Besides, semantic and instance segmentations take advantages of each other by constructing a mutual promotion model of semantic and instance, which can obtain more accurate semantic and instance predictions for indoor scenes. The proposed scheme is evaluated on the S3DIS dataset and compared with existing methods. Experimental results demonstrate that this method is more effective and efficient than previous approaches in joint 3D semantic and instance segmentation. © 2023, The Authors. All rights reserved.

关键词： Semantics

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Facial age estimation by group-centric feature learning

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Expert Systems with Applications 2025年 285卷

作者： Zhao, Qilu Li, Yante College of Computer Science and Technology Qingdao University 308 Ningxia Road Qingdao266000 China Department of Information Technology and Electronic Engineering University of Oulu Pentti Kaiteran katu 1 Oulu90570 Finland

Predicting age from facial images presents a significant challenge due to the intricate nature of the facial aging process. Human faces undergo gradual changes as they age, causing faces to appear very similar at adjacent ages. However, notable age differences result in significant appearance changes, as the human face matures in different ways at different ages, e.g., bone growth in childhood and skin wrinkles in adulthood. In a word, the process of facial aging is continuous but also non-stationary. To address these challenges, our approach is grounded in the insight that the non-stationary aging process can be decomposed into a series of stationary subprocesses. Using a divide-and-conquer strategy, we divide ages into several overlapping groups to facilitate group-centric feature learning. Within each age group, where the aging dynamics are relatively stable, we employ a specialized deep neural network, termed an "expert", to extract group-centric ordinal features. The overlapping of age groups allows each expert to capture the continuity between adjacent groups. The group-centric features are then fused into universal representations, with an attention layer employed to selectively emphasize the most salient feature pertinent to the final age estimation task. For the age estimator, we leverage a hybrid method involving expectation regression to alleviate the inconsistency between training and evaluation stages found in traditional label distribution learning estimators. Extensive experiments involving several famous datasets (MORPH2, CACD, and AFAD) for age estimation have demonstrated the superior performance of our proposed model over several existing state-of-the-art methods. © 2025 Elsevier Ltd

关键词： Self-supervised learning

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Quasi-Phase-Matching Enabled by van der Waals Stacking

arXiv

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arXiv 2024年

作者： Tang, Yilin Sripathy, Kabilan Qin, Hao Lu, Zhuoyuan Guccione, Giovanni Janousek, Jiri Zhu, Yi Hasan, Md Mehedi Iwasa, Yoshihiro Lam, Ping Koy Lu, Yuerui School of Engineering College of Engineering Computing and Cybernetics The Australian National University CanberraACT2601 Australia ARC Centre for Quantum Computation and Communication Technology The Australian National University CanberraACT2601 Australia Research School of Physics College of Science The Australian National University CanberraACT2601 Australia Department of Computer Engineering TUM School of Computation Information and Technology Technical University of Munich Munich80333 Germany Clarendon Laboratory University of Oxford OxfordOX1 3PU United Kingdom RIKEN Center for Emergent Matter Science Hirosawa 2-1 Wako Saitama351-0198 Japan 2 Fusionopolis Way Innovis #08-03 Singapore138634 Singapore

Quasi-phase matching (QPM) is a technique extensively utilized in nonlinear optics for enhancing the efficiency and stability of frequency conversion processes. However, the conventional QPM relies on periodically poled ferroelectric crystals, which are limited in availability. The 3R phase of molybdenum disulfide (3R-MoS2), a transition metal dichalcogenide (TMDc) with the broken inversion symmetry, stands out as a promising candidate for QPM, enabling efficient nonlinear process. Here, we experimentally demonstrate the QPM at nanoscale, utilizing van der Waals stacking of 3R-MoS2 layers with specific orientation to realize second harmonic generation (SHG) enhancement beyond the non QPM limit. We have also demonstrated enhanced spontaneous parametric down-conversion (SPDC) via QPM of 3R-MoS2 homo-structure, enabling more efficient generation of entangled photon pairs. The tunable capacity of 3R-MoS2 van der Waals stacking provides a platform for tuning phase-matching condition. This technique opens interesting possibilities for potential applications in nonlinear process and quantum technology. Copyright © 2024, The Authors. All rights reserved.

关键词： Van der Waals forces

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Immersive Virtual Reality Enhanced Reinforcement Induced Physical Therapy(Everest)

SSRN

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SSRN 2024年

作者： Altukhaim, Samirah Sakabe, Naoko Nagaratnam, Kirubananthan Mannava, Neelima Kondo, Toshiyuki Hayashi, Yoshikatsu Biomedical Science and Biomedical Engineering School of Biological Sciences University of Reading Whiteknights ReadingRG6 6AY United Kingdom Physiotherapy Group in Stroke Unit Alamiri Hospital Kuwait Department of Computer and Information Sciences Graduate School of Engineering Tokyo University of Agriculture and Technology 2-24-16 Naka-cho Koganei Tokyo Japan Stroke Unit Royal Berkshire Hospital London Road ReadingRG1 5AN United Kingdom

Background: Motor impairment of the upper limb (UL) post-stroke is prevalent, adversely affecting patients' quality of life. Previous research has shown that constraint-induced movement therapy (CIMT) is effective in UL rehabilitation. However, CIMT's rigorous regimen may hinder patient adherence, potentially affecting treatment efficacy. Immersive virtual reality (IVR) is an innovative approach for stroke rehabilitation. It utilizes VR technology to create dynamic environments and modify avatars efficiently, offering a less exhausting alternative to CIMT. We propose an IVR-based therapeutic approach that integrates positive reinforcement components to enhance motor coordination, offering an alternative to CIMT. This study aimed to evaluate the effect of incorporating positive reinforcement components into IVR-enhanced physical therapy (PT) on motor ***: Eighteen stroke patients were randomly allocated to two groups: the intervention group (n=10) received 30 ± 10 minutes/day of IVR therapy with PT, while the control group (n=8) received PT alone. PT sessions, lasting 40 ± 10 minutes/day, were conducted on the ward in accordance with national guidelines. Session frequency was tailored to individual hospital stays, adjusted due to pandemic-related early discharge protocols. For participants with stroke who received IVR (intervention group), the task involved reaching for 35 targets randomly distributed across seven different locations in the VR environment. The number of movement repetitions varied depending on their ability to repeat the task. The movement of the virtual image of the UL was reinforced by visual feedback to the participants, that is, the participants perceived their motor coordination as if their UL was moving to a greater degree than what was occurring in everyday life. The primary outcome measure investigated was the Fugl-Meyer assessment (FMA) scale for the affected UL, with secondary measures including a kinematic dataset (e.g., ti

关键词： Virtual reality

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Hybrid data mining based breast prediction of COVID-19

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AIP Conference Proceedings 2023年第1期2523卷

作者： D. Geetha T. Sathiya H. Azath M. Ramkumar T. R. Ganesh Babu 1Department of Information Science and Engineering BNM Institute of Technology Bengaluru Karnataka India. 1Department of Computer Science and Engineering Sona College of Technology Salem Tamil Nadu 636005 India. 3School of Computing Science and Engineering VIT Bhopal University India. 4Department of Electronics and Communication Engineering HKBK College of Engineering Nagavara Bengaluru Karnataka 560045 India 5Department of Electronics and Communication Engineering Muthayammal EngineeringCollege Rasipuram-637408 Namakkal District Tamil Nadu India

Coronavirus, Corona Virus Disease-2019, brought about by an original Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2). A compelling screening of this infection can empower speedy and proficient finding of COVID-19 can diminish the weight on the medical care framework. A nitty gritty examination gave dataset can assemble unique and different kinds of AI calculations, which their exhibition could be processed and further assessed. This paper proposed a mixture information mining method that coordinated Random Forest with SVM (Support Vector Machines). The accompanying case proposed model is to beat the wide range of various Machine Learning models like SVM, Decision Tree, KNN and Logistic Regression.

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Model-Driven Deep Learning for Non-Coherent Massive Machine-Type Communications

arXiv

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arXiv 2023年

作者： Ma, Zhe Wu, Wen Gao, Feifei Shen, Xuemin The Institute for Artificial Intelligence Tsinghua University State Key Lab of Intelligent Technologies and Systems Beijing National Research Center for Information Science and Technology Department of Automation Tsinghua University Beijing100084 China The Frontier Research Center Peng Cheng Laboratory Guangdong Shenzhen518055 China The Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

In this paper, we investigate the joint device activity and data detection in massive machine-type communications (mMTC) with a one-phase non-coherent scheme, where data bits are embedded in the pilot sequences and the base station simultaneously detects active devices and their embedded data bits without explicit channel estimation. Due to the correlated sparsity pattern introduced by the noncoherent transmission scheme, the traditional approximate message passing (AMP) algorithm cannot achieve satisfactory performance. Therefore, we propose a deep learning (DL) modified AMP network (DL-mAMPnet) that enhances the detection performance by effectively exploiting the pilot activity correlation. The DL-mAMPnet is constructed by unfolding the AMP algorithm into a feedforward neural network, which combines the principled mathematical model of the AMP algorithm with the powerful learning capability, thereby benefiting from the advantages of both techniques. Trainable parameters are introduced in the DL-mAMPnet to approximate the correlated sparsity pattern and the large-scale fading coefficient. Moreover, a refinement module is designed to further advance the performance by utilizing the spatial feature caused by the correlated sparsity pattern. Simulation results demonstrate that the proposed DL-mAMPnet can significantly outperform traditional algorithms in terms of the symbol error rate performance. © 2023, CC BY-NC-SA.

关键词： Message passing

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Breakdown of the static dielectric screening approximation of Coulomb interactions in atomically thin semiconductors

arXiv

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arXiv 2024年

作者： Mhenni, Amine Ben Van Tuan, Dinh Geilen, Leonard Petrić, Marko M. Erdi, Melike Watanabe, Kenji Taniguchi, Takashi Tongay, Sefaattin Müller, Kai Wilson, Nathan P. Finley, Jonathan J. Dery, Hanan Barbone, Matteo Walter Schottky Institute TUM School of Natural Sciences MCQST Technical University of Munich Munich Germany Department of Electrical and Computer Engineering University of Rochester RochesterNY United States Walter Schottky Institute TUM School of Computation Information and Technology MCQST Technical University of Munich Munich Germany School for Engineering of Matter Transport and Energy Arizona State University TempeAZ United States Research Center for Electronic and Optical Materials National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan Research Center for Materials Nanoarchitectonics National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan Department of Physics and Astronomy University of Rochester RochesterNY United States

Coulomb interactions in atomically thin materials are uniquely sensitive to variations in the dielectric screening of the environment, which can be used to control exotic quantum many-body phases and engineer exciton potential landscapes. A static approximation of the dielectric response, where increased dielectric screening is predicted to cause an energy redshift of the exciton resonance, has been until now sufficient. Here, we use charge-tunable exciton resonances to study screening effects in transition metal dichalcogenide monolayers embedded in materials with dielectric constants ranging from 4 to more than 1000, a range two orders of magnitude larger than previous studies. In contrast to the redshift predicted by static models employed until now, we observe a blueshift of the exciton resonance exceeding 30 meV for larger dielectric constant environments. By introducing a dynamical screening model based on a new solution to the Bethe-Salpeter equation, we find that while the exciton binding energy remains mostly controlled by the static dielectric response, the exciton self-energy is dominated by the high-frequency one. Our results supplant the understanding of screening in layered materials and their heterostructures, introduce a knob to tune selected many-body effects, and open new routes to detect and control correlated quantum many-body states and to design optoelectronic and quantum devices. © 2024, CC BY-NC-ND.

关键词： Nanocrystals

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