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Querying Artificial Intelligence on the Dark Universe in a Quintessential Encoding of Space-time

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Title: Querying Artificial Intelligence on the Dark Universe in a Quintessential Encoding of Space-time
Description: This book explores the possibility of the use of artificial intelligence (AI) to solve one of the cosmos'biggest mysteries: the nature of undetectable forms of matter, namely dark matter and dark energy, which make up 95% of the universe. The book describes the outcome of this quest in terms of an entangled ur-universe that admits no observer, and incorporates an extra dimension to encode space-time as a latent manifold. A cosmic engine fueled by dark energy that maintains the topology of the universe during its expansion, involving autocatalytic vacuum creation, is identified.The physical picture of the cosmos presented in the book paves the way for a solution to the cosmological constant problem and provides a cogent explanation for the huge gap between the predicted and measured values that has troubled physicists for decades.
Authors: Ariel Fernández, Author
Resource Type: eBook.
Subjects: Artificial intelligence, Dark energy (Astronomy)--Data processing, Dark matter (Astronomy)--Data processing
Categories: COMPUTERS / Artificial Intelligence / General, SCIENCE / Space Science / Cosmology
Database: eBook Collection (EBSCOhost)
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  – Type: ebook-pdf
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  Availability: 0
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DbLabel: eBook Collection (EBSCOhost)
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RelevancyScore: 1116
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 1116.28857421875
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  Data: This book explores the possibility of the use of artificial intelligence (AI) to solve one of the cosmos'biggest mysteries: the nature of undetectable forms of matter, namely dark matter and dark energy, which make up 95% of the universe. The book describes the outcome of this quest in terms of an entangled ur-universe that admits no observer, and incorporates an extra dimension to encode space-time as a latent manifold. A cosmic engine fueled by dark energy that maintains the topology of the universe during its expansion, involving autocatalytic vacuum creation, is identified.The physical picture of the cosmos presented in the book paves the way for a solution to the cosmological constant problem and provides a cogent explanation for the huge gap between the predicted and measured values that has troubled physicists for decades.
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      – Code: 523.1126
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Artificial intelligence
        Type: general
      – SubjectFull: Dark energy (Astronomy)--Data processing
        Type: general
      – SubjectFull: Dark matter (Astronomy)--Data processing
        Type: general
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      – TitleFull: Querying Artificial Intelligence on the Dark Universe in a Quintessential Encoding of Space-time
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            NameFull: Ariel Fernández, Author
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2023
            – D: 24
              M: 10
              Type: profile
              Y: 2023
          Identifiers:
            – Type: isbn-print
              Value: 9781527531178
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              Value: 9781527531185
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            – TitleFull: Querying Artificial Intelligence on the Dark Universe in a Quintessential Encoding of Space-time
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