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