Artificial Intelligence on Dark Matter and Dark Energy: Reverse Engineering of the Big Bang

As we prod the cosmos at very large scales, basic tenets of physics seem to crumble under the weight of contradicting evidence. This book helps mitigate the crisis. It resorts to artificial intelligence (AI) for answers and describes the outcome of this quest in terms of an ur-universe, a quintessential compact multiply connected space that incorporates a fifth dimension to encode space-time as a latent manifold.

In some ways, AI is bolder than humans because the huge corpus of knowledge, starting with the prodigious Standard Model (SM) of particle physics, poses almost no burden to its conjecture-framing processes. Why not feed AI with the SM enriched by the troubling cosmological phenomenology on dark matter and dark energy and see where AI takes us vis-à-vis reconciling the conflicting data with the laws of physics? This is precisely the intellectual adventure described in this book and - to the best of our knowledge - in no other book on the shelf. As the reader will discover, many AI conjectures and validations ultimately make a lot of sense, even if their boldness does not feel altogether "human" yet.

This book is written for a broad readership. Prerequisites are minimal, but a background in college math/physics/computer science is desirable. This book does not merely describe what is known about dark matter and dark energy but also provides readers with intellectual tools to engage in a quest for the deepest cosmological mystery.

當我們在宇宙的大尺度上進行探索時，物理學的基本原理似乎在相互矛盾的證據下崩潰。這本書有助於緩解這一危機。它借助人工智能（AI）來尋找答案，並以「原始宇宙」的形式描述了這一探索的結果，即一個包含第五維度的基本緊湊多連接空間，將時空編碼為潛在流形。

在某些方面，人工智能比人類更大膽，因為從粒子物理學的巨大知識庫開始，幾乎不會對其猜測框架過程造成負擔。為什麼不將人工智能與關於暗物質和暗能量的困擾宇宙現象學相結合，看看人工智能如何將矛盾的數據與物理定律調和起來？這正是本書描述的智力冒險，據我們所知，這是唯一一本這樣的書。正如讀者將會發現的，許多人工智能的猜測和驗證最終都是有道理的，即使它們的大膽性還不完全「人類化」。

這本書面向廣泛的讀者。先備知識要求很少，但具備大學數學/物理/計算機科學背景更好。這本書不僅描述了關於暗物質和暗能量的已知知識，還為讀者提供了參與尋找最深層宇宙之謎的智力工具。

Ariel Fernández, PhD, (born Ariel Fernández Stigliano) is an Argentine-American physical chemist and mathematician. He earned a PhD in chemical physics at Yale University in record time and held the Hasselmann Endowed Chair Professorship in Bioengineering at Rice University until his retirement. To date, he has published approximately 500 scientific papers in professional journals, including PNAS, Nature, Nature Biotechnology, Physical Review Letters, Genome Research, and Genome Biology. Dr. Fernández has also authored seven books on biophysics, molecular medicine, AI, and mathematical physics, and holds several patents on technological innovation. Since 2018, Dr. Fernández has headed the Daruma Institute for Applied Intelligence, the research arm of AF Innovation, a consultancy currently based in Argentina and the United States.

Ariel Fernández博士（原名Ariel Fernández Stigliano）是一位阿根廷裔美國物理化學家和數學家。他在耶魯大學以最短時間獲得化學物理學博士學位，並在萊斯大學擔任Hasselmann Endowed Chair生物工程教授直到退休。迄今為止，他在專業期刊上發表了約500篇科學論文，包括《PNAS》、《Nature》、《Nature Biotechnology》、《Physical Review Letters》、《Genome Research》和《Genome Biology》。Fernández博士還撰寫了七本關於生物物理學、分子醫學、人工智能和數學物理學的書籍，並擁有幾項技術創新的專利。自2018年以來，Fernández博士一直領導Daruma Institute for Applied Intelligence，該研究機構是AF Innovation的研究部門，該顧問公司目前位於阿根廷和美國。