BT-PEC Quantum Computer Architecture and Operating System: Life-Perception Design Based on Topological Energy-Causality Theory

Abstract

This paper proposes the first quantum computer architecture and operating system designed under the BT-PEC (Primitive Topological Energy-Causality) theoretical framework. Traditional quantum computing systems treat qubits as passive computing resources, while the BT-PEC architecture regards the whole quantum computer as an open quantum living system governed by topological deviation dynamics. The four BT-PEC axioms — B (Basis), T (Flux), P (Coupling), EC (Energy-Causality Closed Loop) — are mapped to hardware modules and operating system subsystems respectively. The quantum processing unit adopts a topological-logical double-layer structure, using Majorana zero modes as the physical basis and surface code for logical encoding. A coherent flux injection bus transports negative-entropy energy from the environment to quantum states. The entanglement routing network implements P coupling gate scheduling. Decoherence sensor arrays and real-time quantum error correction decoders form the EC closed loop. At the operating system level, BT-PEC/OS introduces an Ω-aware scheduler, which takes the quantum topological residual order parameter Ω_Q = T − ΔPEC as the system health indicator to drive process scheduling, resource allocation and exception handling. When Ω_Q > 0.05, tasks are executed with the highest priority; when |Ω_Q| ≤ 0.05, the system triggers automatic protection including enhanced error correction, state migration and load reduction; when Ω_Q < −0.05, the system terminates low-priority tasks and recycles quantum states. This paper presents the complete hardware architecture, kernel structure, system call interface, memory management scheme, exception handling mechanism, boot sequence and dedicated quantum programming language BPL. Comparative analysis shows that the BT-PEC architecture outperforms traditional quantum computers in self-sustainability, fault tolerance and resource efficiency. This research lays the foundation for life-state quantum computing and opens a new paradigm integrating computation and life evolution.