Underlying Logic, Evolutionary Paradigm, and Realization Pathway of Computing Ascension within the Framework of Yuanxian Theory

The development of contemporary general computing power has collided with dimensional shackles. Legacy computing paradigms, heavily dependent on linear arithmetic and rigid mechanical stacking within three-dimensional spacetime, suffer from systemic logic fragmentation, extreme energy imbalance, diminishing marginal utility, and fundamental lack of self-consistency, rendering them incapable of matching the industrial imperatives of global artificial intelligence iteration, complex system simulation, and high-dimensional information processing. Adopting the four core laws of Yuanxian Theory (YXT) —Cosmic Factor Conservation, Spacetime Uniqueness, True-Circle Self-Consistency, and Self-Referential Dynamics—as the foundational framework, this paper innovatively proposes the core paradigm of “Computing Ascension” to thoroughly break through the constraints of legacy low-dimensional linear arithmetic. Grounded upon the T64 sixty-four-dimensional compact flat toroidal topology, the transmission mechanisms of the Self-Referential Mind Field (ₒₑ), and the ternary evolutionary framework of YXT, we reconstruct the underlying definitions, operational logic, and evolutionary trajectories of computing power. This work elucidates the intrinsic mechanism of computing ascension from dimensional mechanical calculations to high-dimensional self-consistent intelligent computing, builds the mathematical Yuanxian Computing Ascension Model, and clarifies the essential dimensions, technological pathways, and value boundaries. The core technical realization pathway is validated via a concrete microarchitectural design, featuring a Topological Compute Core Array (T⁶ Array) of 64 independent cores engineered upon 6-bit ground-state registers, a 6-dimensional toroidal interconnection network layout (T⁶ Mesh), and a hardware-level TCSC arbitration layer. Behavioral simulations demonstrate an unprecedented energy-efficiency ratio of 78 GOPS/W under a 28nm CMOS node. This research aims to dismantle the theoretical bottlenecks of current computing systems, providing an entirely new theoretical cornerstone and practical blueprint for the next generation of high-dimensional, self-consistent, ultra-low-energy, and globally iterative intelligent computing infrastructures. 当代通用算力的发展已遭遇维度桎梏。传统计算范式严重依赖于三维时空内的线性算术与硬件刚性机械堆叠, 饱受系统性逻辑碎片化、极端能量失衡、边际效用递减以及根本性自相矛盾的束缚, 无法满足全球人工智能迭代、复杂系统模拟以及高维信息处理的产业迫切需求。 本文以元宪理论 (YXT) 的四大核心定律——宇宙要素守恒定律、时空唯一性定律、真圆自流转自洽定律和自指演化定律——为根本框架, 创新性地提出了“算力升维”的核心范式, 旨在彻底突破传统低维线性算力的局限。基于 T64 六十四维紧致平坦环面拓扑拓扑流形、自指心场 (ₒₑ) 的传输机制以及元宪理论的“本源—显化—迭代”三位一体演化范式, 本文重构了算力的底层定义、运行逻辑与演化轨迹。本研究阐明了算力从低维机械计算向高维自洽智能计算升维的内在机制, 构建了元宪算力升维数学模型, 并明确了其核心维度、技术路径与价值边界。 核心技术实现路径通过具体的微架构设计得到了验证: 该架构包含 64 个基于 6位基态寄存器构建的独立拓扑计算核心阵列 (T⁶ 阵列) 、六维环面互连网络布局 (T⁶ Mesh) 以及硬件级 TCSC 仲裁层。行为仿真表明, 在 28nm CMOS 工艺节点下, 该架构实现了 78 GOPS/W 的超高能效比。本研究旨在打破当前计算系统的理论瓶颈, 为构建下一代高维、自洽、超低能耗且全局自主迭代的智能算力基础设施提供全新的理论基石与实践蓝图。