机器联觉:通信与多模态感知的智能融合

通信感知一体化技术局限于雷达感知与通信在频谱和硬件层面上的共享,不足以提升新兴应用场景中通信与感知的性能.在涵盖海量多模态感知和通信数据的场景中,通信感知一体化技术应向考虑多模态感知的方向进行范式演进,即通信与多模态感知的智能融合.受人类联觉现象启发,文中系统化建立并论述通信和多模态感知智能融合的范式——机器联觉.首先,总结机器联觉3种典型工作模式:唤起模式、增强模式、合作模式,系统全面给出通信和多模态感知之间相互辅助增强的目的与方式.然后,介绍机器联觉研究的数据基础(通信与多模态感知智能融合仿真数据集)和理论基础(通信与多模态感知联觉机理).最后,综述当前机器联觉的研究现状,并展望未来的研究方向. Integrated sensing and communications(ISAC) technique is limited to the sharing of radar sensing and communications at the spectrum and hardware levels, and it fails to enhance the performance of communication and sensing in future emerging application scenarios. In scenarios involving massive multi-modal sensing and communication data, ISAC should evolve towards the incorporation of multi-modal sensing, specifically intelligent multi-modal sensing-communication integration. Inspired by human synesthesia, a paradigm for intelligent multi-modal sensing-communication integration, synesthesia of machines (SoM), is systematically established and discussed in this paper. Firstly, three typical operational modes of SoM, SoM-evoke, SoM-enhance and SoM-concert, are systematically summarized, and thus the purposes and methods of the mutual assistance and enhancement between communications and multi-modal sensing are given comprehensively. Then, the data foundation of SoM research, mixed multi-modal sensing and communication(M3 SC) simulation dataset, and the theoretical foundation of SoM research, SoM mechanism, are also discussed. Finally, the current research status of SoM is reviewed and future research directions are prospected. © 2023 Journal of Pattern Recognition and Artificial Intelligence. All rights reserved

Prediction of Energy Resolution in the JUNO Experiment

International audienceThis paper presents the energy resolution study in the JUNO experiment, incorporating the latest knowledge acquired during the detector construction phase. The determination of neutrino mass ordering in JUNO requires an exceptional energy resolution better than 3% at 1 MeV. To achieve this ambitious goal, significant efforts have been undertaken in the design and production of the key components of the JUNO detector. Various factors affecting the detection of inverse beta decay signals have an impact on the energy resolution, extending beyond the statistical fluctuations of the detected number of photons, such as the properties of liquid scintillator, performance of photomultiplier tubes, and the energy reconstruction algorithm. To account for these effects, a full JUNO simulation and reconstruction approach is employed. This enables the modeling of all relevant effects and the evaluation of associated inputs to accurately estimate the energy resolution. The study reveals an energy resolution of 2.95% at 1 MeV. Furthermore, the study assesses the contribution of major effects to the overall energy resolution budget. This analysis serves as a reference for interpreting future measurements of energy resolution during JUNO data taking. Moreover, it provides a guideline in comprehending the energy resolution characteristics of liquid scintillator-based detectors

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel

Determination of the number of ψ(3686) events taken at BESIII

The number of ψ(3686) events collected by the BESIII detector during the 2021 run period is determined to be (2259.3±11.1)×106 by counting inclusive ψ(3686) hadronic events. The uncertainty is systematic and the statistical uncertainty is negligible. Meanwhile, the numbers of ψ(3686) events collected during the 2009 and 2012 run periods are updated to be (107.7±0.6)×106 and (345.4±2.6)×106, respectively. Both numbers are consistent with the previous measurements within one standard deviation. The total number of ψ(3686) events in the three data samples is (2712.4±14.3)×10^

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies