Quantum Deep Learning Triuniverse

Angus M. McCoss
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引用次数: 7

Abstract

An original quantum foundations concept of a deep learning computational Universe is introduced. The fundamental information of the Universe (or Triuniverse) is postulated to evolve about itself in a Red, Green and Blue (RGB) tricoloured stable self-mutuality in three information processing loops. The colour is a non-optical information label. The information processing loops form a feedback-reinforced deep learning macrocycle with trefoil knot topology. Fundamental information processing is driven by ψ-Epistemic Drive, the Natural appetite for information selected for advantageous knowledge. From its substrate of Mathematics, the knotted information processing loops determine emergent Physics and thence the evolution of super-emergent Life (biological and artificial intelligence). RGB-tricoloured information is processed in sequence in an Elemental feedback loop (R), then an Operational feedback loop (G), then a Structural feedback loop (B) and back to an Elemental feedback loop (R), and so on around the trefoil in deep learning macrocycles. It is postulated that hierarchical information correspondence from Mathematics through Physics to Life is mapped and conserved within each colour. The substrate of Mathematics has RGB-tricoloured feedback loops which are respectively Algebra (R), Algorithms (G) and Geometry (B). In Mathematics, the trefoil macrocycle is Algebraic Algorithmic Geometry and its correlation system is a Tensor Neural Knot Network enabling Qutrit Entanglement. Emergent Physics has corresponding RGB-tricoloured feedback loops of Quantum Mechanics (R), Quantum Deep Learning (G) and Quantum Geometrodynamics (B). In Physics, the trefoil macrocycle is Quantum Intelligent Geometrodynamics and its correlation system is Quantum Darwinism. Super-emergent Life has corresponding RGB-tricoloured loops of Variation (R), Selection (G) and Heredity (B). In the evolution of Life, the trefoil macrocycle is Variational Selective Heredity and its correlation ecosystem is Darwin’s ecologically “Entangled Bank”.
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量子深度学习三位一体
介绍了深度学习计算宇宙的原始量子基础概念。宇宙(或三宇宙)的基本信息被假设在三个信息处理循环中以红、绿、蓝(RGB)三色稳定的自互性发展。颜色是非光学信息标签。信息处理回路形成一个三叶结拓扑的反馈强化深度学习大环。基础信息处理是由一种对有利知识的信息的自然偏好所驱动的。在数学的基础上,错综复杂的信息处理回路决定了涌现的物理学,进而决定了超涌现生命(生物和人工智能)的进化。rgb -三色信息依次在元素反馈回路(R)、操作反馈回路(G)、结构反馈回路(B)和元素反馈回路(R)中进行处理,如此循环往复,形成深度学习大循环中的三叶草。假设从数学到物理到生活的层次信息对应被映射并保存在每种颜色中。数学的基础是rgb -三色反馈回路,分别是代数(R)、算法(G)和几何(B)。在数学中,三叶大环是代数算法几何,它的相关系统是一个支持Qutrit纠缠的张量神经结网络。涌现物理有对应的量子力学(R)、量子深度学习(G)和量子几何动力学(B)的rgb三色反馈环。在物理学中,三叶草大环是量子智能几何动力学,其相关系统是量子达尔文主义。超涌现生命具有相应的rgb -三色变异环(R)、选择环(G)和遗传环(B)。在生命进化中,三叶草大环是变分选择性遗传,其相关生态系统是达尔文的生态学“纠缠库”。
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来源期刊
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