Subjects: Astronomy submitted time 2024-03-26 Cooperative journals: 《天文学进展》
Abstract： Time series reconstruction is a crucial data processing step in time domain astronomy and serves as the foundation for fitting light curves and conducting time domain analysis. For many large-field time domain surveys, it is necessary to complete this computational process within a single exposure cycle. With the rapid increase in astronomical data, existing methods for astronomical data processing struggle to simultaneously meet the accuracy and efficiency requirements of time-series reconstruction. The memory-based computing general-purpose distributed framework, Spark, holds the potential to improve the efficiency of this process. However, applying Spark directly often encounters issues. MapReduce distributed models like Hadoop and Spark require relatively independent tasks among distributed cluster nodes and minimal data transfer across nodes during execution. Otherwise, frequent communication becomes an efficiency bottleneck for the application of the model. However, due to the presence of boundary problems in cross-matching, it is inevitable to transmit newly added data at the boundaries, severely restricting the concurrency of the model and reducing the acceleration ratio in practical parallel model applications. Therefore, we propose a non-blocking asynchronous execution flow, where each distributed process handles continuous processing exclusively for independent sky regions. The delayed batch appending of additional identification tasks from block-edge newly added celestial bodies in other nodes is determined based on the progress of each process. This ensures that identification calculations are not omitted, thereby improving concurrent efficiency while maintaining algorithm accuracy. Additionally, a research study was conducted on different join strategies between two tables, examining them from both theoretical and experimental perspectives. Furthermore, a join-free strategy was proposed. Finally, the design of an efficient time-series reconstruction system based on the Spark distributed framework validates the aforementioned research. Experimental results demonstrate a significant improvement in the efficiency of the proposed time-series reconstruction algorithm compared to previous research, laying a solid foundation for the analysis of astronomical time-series data in time-domain astronomy.
Subjects: Astronomy submitted time 2024-03-22 Cooperative journals: 《天文学进展》
Abstract： Time series reconstruction is a crucial data processing step in time domain astronomy and serves as the foundation for fitting light curves and conducting time domain analysis. For many large-field time domain surveys, it is necessary to complete this computational process within a single exposure cycle. With the rapid increase in astronomical data, existing methods for astronomical data processing struggle to simultaneously meet the accuracy and efficiency requirements of time-series reconstruction. The memory-based computing general-purpose distributed framework, Spark, holds the potential to improve the efficiency of this process. However, applying Spark directly often encounters issues. MapReduce distributed models like Hadoop and Spark require relatively independent tasks among distributed cluster nodes and minimal data transfer across nodes during execution. Otherwise, frequent communication becomes an efficiency bottleneck for the application of the model. However, due to the presence of boundary problems in cross-matching, it is inevitable to transmit newly added data at the boundaries, severely restricting the concurrency of the model and reducing the acceleration ratio in practical parallel model applications. Therefore, we propose a non-blocking asynchronous execution flow, where each distributed process handles continuous processing exclusively for independent sky regions. The delayed batch appending of additional identification tasks from block-edge newly added celestial bodies in other nodes is determined based on the progress of each process. This ensures that identification calculations are not omitted, thereby improving concurrent efficiency while maintaining algorithm accuracy. Additionally, a research study was conducted on different join strategies between two tables, examining them from both theoretical and experimental perspectives. Furthermore, a join-free strategy was proposed. Finally, the design of an efficient time-series reconstruction system based on the Spark distributed framework validates the aforementioned research. Experimental results demonstrate a significant improvement in the efficiency of the proposed time-series reconstruction algorithm compared to previous research, laying a solid foundation for the analysis of astronomical time-series data in time-domain astronomy.
Subjects: Astronomy >> Astrophysical processes submitted time 2019-07-30 Cooperative journals: 《天文研究与技术》
Abstract：经过十余年的不断建设和发展，中国虚拟天文台（China-VO）已成为支撑天文学观测、研究、教学的重要技术和资源平台。随着多信使天文学和时域天文学时代的到来，虚拟天文台也需要升级自身的核心能力，以给天文工作者提供更精准的服务和技术支撑。为此，中国虚拟天文台团队结合天文学的发展方向和信息技术发展趋势梳理了一份核心技术需求清单，并以问卷的形式针对领域内专家和用户开展了调研。通过对调研结果的统计和分析，中国虚拟天文台明确了未来一段时期的主要努力方向和目标，计划采用平台化的开发模式，并开放第三方开发接口，以吸引更多感兴趣的开发者基于虚拟天文台资源做出实用的工具，更好地实现资源与技术向服务的快速转换。
Subjects: Astronomy >> Astrophysical processes submitted time 2019-07-09 Cooperative journals: 《天文研究与技术》
Abstract： 随着多波段时域天文学的快速发展，远程天文台逐渐显露出优势，成为时域天文学研究的重要工具。然而，国内还没有自主、成熟、稳定的系统可以应用到远程天文台的建设当中，为此中国虚拟天文台提出并设计了一套硬件集成系统以便于集成控制和扩展移植。电源模块是其中重要的组成部分，实现电源的集成控制将极大提升整个系统的稳定性。本文设计了一个闭环的电源集成控制模块，通过嵌入式技术实现了天文台各设备电源的集成控制、平顶的开关控制以及各个设备状态的监测，并提供多种控制模式。通过发送随机网络指令对该模块进行了24小时的连续测试，并测试了网络中断情况下短消息的控制。通过发送与监测数据的对比，结果表明系统具有良好的稳定性。
Subjects: Astronomy >> Astrophysical processes submitted time 2017-09-26 Cooperative journals: 《天文研究与技术》
Abstract：海量观测数据及次生数据的高效存储与检索，天文大数据的快速及时处理，加速天文学研究的科学产出等问题，已成为天文观测和天文研究迫切需要解决的难题。以信息技术为支撑的天文大数据的高效分析和处理，帮助天文学家重新审视和了解宇宙。虚拟天文台的出现为全球范围内研究资源的无缝透明连接提供了协议、标准，以协议为基拙规范了天文数据的发布与检索方式。以国内外现有的观测设备为基拙，综述目前主流天文机构的数据发布与检索相关情况。
Subjects: Astronomy >> Astrophysical processes submitted time 2017-09-26 Cooperative journals: 《天文研究与技术》
Abstract：传统光学天象厅因为节目制作难度大，成本高昂，功能扩展困难等缺点逐渐被功能强大的数字天象厅取代。随着天文教育和科普的深入推广，国内对数字天象厅的需求越来越大。数字天象厅的核心是球幕投影技术。针对球幕投影技术存在的一些技术问题，如自动化程度不高，需要人工干预等，提出了面向中小型球幕天象厅易于实现的多投影自动拼接方案。对方案中的几何校正、亮度校正、颜色校正等核心功能进行了详细的论述。该方案便于操作，易于实现，对中小型球幕有良好表现，对大型球幕也有借鉴意义。
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