Название: Artificial Intelligence on Dark Matter and Dark Energy: Reverse Engineering of the Big BangАвтор: Ariel Fernandez
Издательство: CRC Press
Серия: Chapman & Hall/CRC Artificial Intelligence and Robotics Series
Год: 2024
Страниц: 173
Язык: английский
Формат: pdf (true)
Размер: 34.0 MB
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-a-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.
The AI approach resorts to the underlying science critically revisited in the light of the startling experimental anomalies that arise in deep-space cosmology. As shown in this book, AI is able to illustrate how science is best done: Not by prejudice but through analysis of big data in response to an intriguing hypothesis that humans, too loyal to their scientific cliques, are sometimes unable to formulate or accept.
As we prod the cosmos at very large scales, the pillars of physics seem feebler than ever, just about to crumble under the weight of contradicting evidence. This book helps miti-gate the current crisis. It resorts to artificial intelligence for answers and describes the outcome of this quest in terms of an ur-universe, a quintessential compact and multiply connected space that incorporates a fifth dimension to encode Einstein’s space-time as a latent manifold.
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.
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