相關主題
商品描述
The dark universe contains matter and energy unidentifiable with current physical models, accounting for 95% of all the matter and energetic equivalent in the universe. The enormous surplus brings up daunting enigmas, such as the cosmological constant problem and the apparent distortions in the dynamics of deep space, and so coming to grips with the invisible universe has become a scientific imperative.
This book addresses this need, reckoning that no cogent physical model of the dark universe can be implemented without first addressing the metaphysical hurdles along the way. The foremost problem is identifying the topology of the universe which, as argued in the book, is highly relevant to unveil the secrets of the dark universe.
Artificial Intelligence (AI) is a valuable tool in this effort since it can reconcile conflicting data from deep space with the extant laws of physics by building models to decipher the dark universe. This book explores the applications of AI and how it can be used to embark on a metaphysical quest to identify the topology of the universe as a prerequisite to implement a physical model of the dark sector that enables a meaningful extrapolation into the visibile sector.
The book is intended for a broad readership, but a background in college-level physics and computer science is essential. The book will be a valuable guide for graduate students as well as researchers in physics, astrophysics, and computer science focusing on AI applications to elucidate the nature of the dark universe.
Key Features:
- Provides readers with an intellectual toolbox to understand physical arguments on dark matter and energy.
- Up to date with the latest cutting-edge research.
- Authored by an expert on artificial intelligence and mathematical physics.
商品描述(中文翻譯)
黑暗宇宙包含了目前物理模型無法識別的物質和能量，佔據了宇宙中所有物質和能量等價的95%。這巨大的盈餘帶來了令人畏懼的謎題，例如宇宙常數問題和深空動力學中的明顯扭曲，因此，理解這個看不見的宇宙已成為科學上的迫切需求。
本書針對這一需求，認為在實施黑暗宇宙的合理物理模型之前，必須首先解決沿途的形而上學障礙。首要問題是識別宇宙的拓撲結構，正如本書所論述的，這對揭示黑暗宇宙的秘密具有高度相關性。
人工智慧（AI）在這一努力中是一個寶貴的工具，因為它可以通過建立模型來解讀黑暗宇宙，從而調和來自深空的矛盾數據與現有的物理定律。本書探討了AI的應用，以及如何利用它展開一場形而上學的探索，以識別宇宙的拓撲結構，這是實施黑暗領域物理模型的前提，並使得對可見領域的有意義外推成為可能。
本書旨在面向廣泛的讀者群，但具備大學水平的物理學和計算機科學背景是必須的。本書將成為研究生以及專注於AI應用以闡明黑暗宇宙本質的物理學、天體物理學和計算機科學研究者的寶貴指南。
主要特點：
- 為讀者提供理解有關暗物質和能量的物理論點的智力工具箱。
- 緊跟最新的前沿研究。
- 由人工智慧和數學物理專家撰寫。
作者簡介
Ariel Fernández (born Ariel Fernández Stigliano, April 8, 1957) is an Argentine-American physical chemist and mathematician. He obtained a Ph.D. in Chemical Physics from Yale University in record time and held the Karl F. Hasselmann Endowed Chair Professorship in Engineering at Rice University until his retirement. He was also an adjunct professor of computer science at the University of Chicago. To date, he has published over 500 scientific papers in professional journals and has also authored nine books on physical chemistry, molecular medicine, artificial intelligence, mathematical cosmology, and mathematical physics. Additionally, he holds several patents on technological innovation. Fernández is a member of the National Research Council of Argentina (CONICET) and, since 2018, heads the Daruma Institute for Applied Intelligence, the research arm of AF Innovation, a consultancy based in Argentina and the United States.
作者簡介(中文翻譯)
阿里爾·費爾南德茲（Ariel Fernández，原名阿里爾·費爾南德茲·斯蒂格利亞諾，1957年4月8日出生）是一位阿根廷裔美國物理化學家和數學家。他以創紀錄的速度獲得耶魯大學化學物理學博士學位，並在萊斯大學擔任卡爾·F·哈塞爾曼工程學講座教授，直到退休。他同時也是芝加哥大學的計算機科學兼任教授。迄今為止，他已在專業期刊上發表超過500篇科學論文，並著有九本關於物理化學、分子醫學、人工智慧、數學宇宙學和數學物理學的書籍。此外，他還擁有多項技術創新專利。費爾南德茲是阿根廷國家研究委員會（CONICET）的成員，自2018年以來，他擔任達魯瑪應用智慧研究所的負責人，該研究所是AF Innovation的研究部門，該顧問公司在阿根廷和美國均有業務。
