Machine Learning for Astrophysics: Proceedings of the Ml4astro International Conference 30 May - 1 Jun 2022

本書回顧了機器學習技術在天體物理學社群中的應用現狀，並為讀者提供了該領域的完整概述。各章節的貢獻使讀者能夠通過平衡的理論與數值方法及工具，輕鬆消化材料，並應用於不同的理論與觀測天文學領域。本書幫助讀者真正理解並量化在多個天體物理學領域中使用機器學習的機會與限制。

Filomena Bufano (Ph.D. in Astronomy) has been a research staff scientist at Istituto Nazionale di Astrofisica (INAF) since 2016. Her scientific interests have been mainly focused on the study of massive stars evolution, in particular on their final stages. Promoting a multi-wavelength approach in her studies, she worked using data from different telescopes/surveys from UV to radio frequencies and has been a member of numerous international collaborations and projects. In view of the approaching era of a deluge of data expected from new ground and space-based facilities, she acquired deep skills in the use of machine learning algorithms: since 2017 she has been engaged in two important European projects, i.e. ViaLactea and the ongoing NEANIAS project (sponsor of the conference, too). Nowadays, she is involved in the preliminary activities of the Square Kilometre Array focussed on the Galactic Plane and in the Early Science Data Analysis phase of two important pathfinder/precursor of SKA: ASKAP and MeerKAT.

Eva Sciacca (Ph.D. in Mathematics for Technology) is a Computer Scientist and Information Technology researcher with over a decade of experience, working at the Istituto Nazionale di Astrofisica (INAF) since 2012. She has been extensively involved in cutting-edge research activities in the field of big-data, visual analytics, and machine learning. She has been instrumental in facilitating astrophysical data processing on distributed computing infrastructures, with a special focus on High-Performance Computing (HPC) and Cloud Computing. Over the past five years, Eva has played a pivotal role in several European-funded projects, including VIALACTEA, INDIGO-DataCloud, AENEAS, EOSC-Pilot, NEANIAS, and SPACE. She has been at the forefront of harnessing the potential of the European Open Science Cloud (EOSC) and the European High-Performance Computing Joint Undertaking (EuroHPC JU) to advance scientific research, and she isactively involved in the IT activities of the Square Kilometre Array (SKA) Regional Centres.

Francesco Schilliro is a signal processing engineer skilled in algorithm and instrumentation for radio astronomy, working at the Istituto Nazionale di Astrofisica (INAF) since 2000. He started working at the Noto VLBI Antenna, where he was also involved in the design of radio astronomy antenna control system software and devices. Both experiences were important for his activity as digital engineer and designer for SKA post-processing equipment, in particular for the design and prototyping of Tile Processor Module of Low-Frequency Aperture Array component of SKA. His experience as software architect for radio astronomy control system was improved by working as software Architect for the SKA Dish Consortium and in particular for control and monitoring the SKA antennas.
Currently he is involved in AI research involving the application of Machine Learning and Deep Learningalgorithms to heterogeneous hardware, processing data coming from SKA precursors (Meerkat, ASKAP). Recent activity involves quantum computing algorithms and application to astrophysical items.

Simone Riggi (Ph.D. Physics) has been a Research Data Scientist at the Istituto Nazionale di Astrofisica (INAF) since 2012. His work has primarily focused on scientific data analysis and visualization, machine learning, distributed computing, instrumentation simulation, monitoring and control, and system engineering. He has contributed to large research and technological projects in the fields of radio astronomy, high-energy cosmic rays, and applied physics, such as the Pierre Auger Observatory experiment, the Muon Portal project, and various European H2020 projects (AENEAS, NEANIAS). Currently, he is involved in the design and construction phase of the Square Kilometer Array (SKA) telescope and in the Galactic science programs carried out within the ASKAP-EMU and MeerKAT-GPS surveys. In these contexts, he is responsible for the monitoring and control system of SKA-Mid antennas and for developing radio source analysis tools using machine learning techniques and multi-wavelength data.

Filomena Bufano（天文學博士）自2016年以來一直擔任意大利國家天文物理研究所（INAF）的研究科學家。她的科學興趣主要集中在大質量恆星的演化研究，特別是它們的最終階段。她在研究中推廣多波長的方法，使用來自不同望遠鏡/調查的數據，涵蓋從紫外線到無線電頻率，並參與了多個國際合作和項目。考慮到即將到來的來自新地面和太空設施的數據洪流，她在機器學習算法的使用上獲得了深厚的技能：自2017年以來，她參與了兩個重要的歐洲項目，即ViaLactea和正在進行的NEANIAS項目（也是本次會議的贊助商）。如今，她參與了聚焦於銀河平面的平方公里陣列（SKA）的初步活動，以及SKA的兩個重要先導/前驅項目ASKAP和MeerKAT的早期科學數據分析階段。

Eva Sciacca（技術數學博士）是一位計算機科學家和信息技術研究員，擁有超過十年的經驗，自2012年以來在意大利國家天文物理研究所（INAF）工作。她在大數據、視覺分析和機器學習領域的前沿研究活動中積極參與。她在分佈式計算基礎設施上促進天文物理數據處理方面發揮了重要作用，特別專注於高性能計算（HPC）和雲計算。在過去五年中，Eva在多個歐洲資助的項目中發揮了關鍵作用，包括VIALACTEA、INDIGO-DataCloud、AENEAS、EOSC-Pilot、NEANIAS和SPACE。她在利用歐洲開放科學雲（EOSC）和歐洲高性能計算聯合企業（EuroHPC JU）推進科學研究方面走在前沿，並積極參與平方公里陣列（SKA）區域中心的IT活動。

Francesco Schilliro是一位信號處理工程師，專精於無線電天文學的算法和儀器，自2000年以來在意大利國家天文物理研究所（INAF）工作。他最初在Noto VLBI天線工作，並參與了無線電天文學天線控制系統軟體和設備的設計。這兩段經歷對他作為SKA後處理設備的數位工程師和設計師的工作至關重要，特別是在SKA的低頻孔徑陣列組件的Tile Processor Module的設計和原型製作方面。他作為無線電天文學控制系統的軟體架構師的經驗，通過擔任SKA Dish Consortium的軟體架構師得到了提升，特別是在控制和監控SKA天線方面。目前，他參與了涉及機器學習和深度學習算法應用於異構硬體的AI研究，處理來自SKA前驅項目（Meerkat、ASKAP）的數據。最近的活動涉及量子計算算法及其在天文物理項目中的應用。

Simone Riggi（物理學博士）自2012年以來一直是意大利國家天文物理研究所（INAF）的研究數據科學家。他的工作主要集中在科學數據分析和可視化、機器學習、分佈式計算、儀器模擬、監控和控制以及系統工程。他參與了多個大型研究和技術項目，涵蓋無線電天文學、高能宇宙射線和應用物理等領域，如Pierre Auger Observatory實驗、Muon Portal項目以及各種歐洲H2020項目（AENEAS、NEANIAS）。目前，他參與平方公里陣列（SKA）望遠鏡的設計和建設階段，以及在ASKAP-EMU和MeerKAT-GPS調查中進行的銀河科學計劃。在這些背景下，他的工作...