829 research outputs found

    Genetic algorithms and simulated annealing for robustness analysis

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    Genetic algorithms (GAs) and simulated annealing (SA) have been promoted as useful, general tools for nonlinear optimization. This paper explores their use in robustness analysis with real parameter variations, a known NP hard problem which would appear to be ideally suited to demonstrate the power of GAs and SA. Numerical experiment results show convincingly that they turn out to be poorer than existing branch and bound (B&B) approaches. While this may appear to shed doubt on some of the hype surrounding these stochastic optimization techniques, we find that they do have attractive features, which are also demonstrated in this study. For example, both GAs and SA are almost trivial to understand and program, so they require essentially no expertise, in sharp contrast to the B&B methods. They may be suitable for problems where programming effort is much more important than running time or the quality of the answer. Robustness analysis for engineering problems is not the best candidate in this respect, but it does provide an interesting test case for the evaluation of GAs and SA. A simple hill climbing algorithm is also studied for comparison

    Stochastic Controlled Averaging for Federated Learning with Communication Compression

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    Communication compression, a technique aiming to reduce the information volume to be transmitted over the air, has gained great interests in Federated Learning (FL) for the potential of alleviating its communication overhead. However, communication compression brings forth new challenges in FL due to the interplay of compression-incurred information distortion and inherent characteristics of FL such as partial participation and data heterogeneity. Despite the recent development, the performance of compressed FL approaches has not been fully exploited. The existing approaches either cannot accommodate arbitrary data heterogeneity or partial participation, or require stringent conditions on compression. In this paper, we revisit the seminal stochastic controlled averaging method by proposing an equivalent but more efficient/simplified formulation with halved uplink communication costs. Building upon this implementation, we propose two compressed FL algorithms, SCALLION and SCAFCOM, to support unbiased and biased compression, respectively. Both the proposed methods outperform the existing compressed FL methods in terms of communication and computation complexities. Moreover, SCALLION and SCAFCOM accommodates arbitrary data heterogeneity and do not make any additional assumptions on compression errors. Experiments show that SCALLION and SCAFCOM can match the performance of corresponding full-precision FL approaches with substantially reduced uplink communication, and outperform recent compressed FL methods under the same communication budget.Comment: 45 pages, 4 figure

    Data Arrangement With Rotation Transformation for Fully Polarimetric Synthetic Aperture Radar

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    This letter proposes a data arrangement for fully polarimetric synthetic aperture radar (PolSAR). It is an essential novel method in the use of the rotation transformation in data interpretation. The key point of the proposal is employing a single pixel-based and selective rotation transformation for each pixel before the speckle filtering. The experimental results with ALOS2-PALSAR2 data show that the proposed data arrangement has much higher performance in recognizing double-bounce scattering in the man-made target area. At the same time, it is effective in avoiding the overestimation of double-bounce and/or surface scattering in natural target areas

    Wireless Network Digital Twin for 6G: Generative AI as A Key Enabler

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    Digital twin, which enables emulation, evaluation, and optimization of physical entities through synchronized digital replicas, has gained increasingly attention as a promising technology for intricate wireless networks. For 6G, numerous innovative wireless technologies and network architectures have posed new challenges in establishing wireless network digital twins. To tackle these challenges, artificial intelligence (AI), particularly the flourishing generative AI, emerges as a potential solution. In this article, we discuss emerging prerequisites for wireless network digital twins considering the complicated network architecture, tremendous network scale, extensive coverage, and diversified application scenarios in the 6G era. We further explore the applications of generative AI, such as transformer and diffusion model, to empower the 6G digital twin from multiple perspectives including implementation, physical-digital synchronization, and slicing capability. Subsequently, we propose a hierarchical generative AI-enabled wireless network digital twin at both the message-level and policy-level, and provide a typical use case with numerical results to validate the effectiveness and efficiency. Finally, open research issues for wireless network digital twins in the 6G era are discussed

    Dynamical study of Dβˆ—DKD^{*}DK and Dβˆ—DDΛ‰D^{*}D \bar{D} systems at quark level

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    Inspired by that Belle\uppercase\expandafter{\romannumeral2} Collaboration recently reported TccT_{cc}, which can be interpreted as a molecular DDβˆ—DD^{*}, we investigated the trihadron system of TccT_{cc} partner with IJPIJ^{P}=01βˆ’01^{-} in the framework of a chiral quark model. It's widely accepted that the main component of X(3872)X(3872) contains the molecular DΛ‰Dβˆ—\bar{D}D^{*}, while the main component of Ds0βˆ—(2317)D_{s0}^{*}(2317) is molecular DKDK. Based on these three well-known exotic states, Tcc(DDβˆ—)T_{cc} (DD^{*}), X(3872)(DΛ‰Dβˆ—)X(3872) (\bar{D}D^{*}) and Ds0βˆ—(2317)(DK)D_{s0}^{*}(2317) (DK), we dynamically investigate Dβˆ—DKD^{*}DK and DDβˆ—DΛ‰DD^{*}\bar{D} systems at quark level to search for possible bound states. The results show that both of them are bound states, in which the binding energy of the molecular state DDβˆ—KDD^*K is relatively small, only 0.8 MeV, while the binding energy of DDβˆ—DΛ‰DD^*\bar{D} is up to 1.9 MeV. According to the calculation results of the Root-square-mean distances, the spatial structure of the two systems shows obvious (DDβˆ—DD^*)-(DΛ‰\bar{D}/KK) structure, in which DD is close to Dβˆ—D^* while DDβˆ—DD^* as a whole is relatively distant from the third hadron (DΛ‰\bar{D}/KK), which are similar to the nucleon-electron structure. As a result, we strongly recommend that these bound states DDβˆ—DΛ‰DD^*\bar{D} and DDβˆ—KDD^*K are searched for experimentally

    Investigation of the analog of the PcP_{c} states-the doubly charmed molecular pentaquarks

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    Motivated by the LHCb Collaboration's observation of a doubly charmed tetraquark state Tcc(3875)T_{cc}(3875), we systematically investigate the existence of doubly charmed pentaquark states using the resonating group method based on the QDCSM framework. The effective potential of the two involved hadrons and the bound state dynamics are included in the present work. Moreover, we have also calculated the scattering phase shifts of open channels by channel coupling to look for possible resonance states. Our estimations indicate that there is a bound state in I(JP)=32(52βˆ’)I(J^{P})=\frac{3}{2}(\frac{5}{2}^{-}), with a mass of 4461.74461.7 MeV. Additionally, five resonance states can be obtained by coupling the open channel, which are Ξccρ\Xi_{cc}\rho and Ξ£cDβˆ—\Sigma_{c}D^{\ast} with I(JP)=12(12βˆ’)I(J^{P})=\frac{1}{2}(\frac{1}{2}^{-}), Ξ›cDβˆ—\Lambda_{c}D^{\ast} and Ξ£cDβˆ—\Sigma_{c}D^{\ast} with I(JP)=12(32βˆ’)I(J^{P})=\frac{1}{2}(\frac{3}{2}^{-}) and Ξ£cDβˆ—\Sigma_{c}D^{\ast} with I(JP)=32(12βˆ’)I(J^{P})=\frac{3}{2}(\frac{1}{2}^{-})respectively. The existence of these predicted doubly charmed pentaquark states needs to be supported by experimental measurements and discoveries. We hope that some experiments can find evidence of these states.Comment: arXiv admin note: text overlap with arXiv:2211.0943
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