Successful Development and Operational Demonstration of the Quantum Thought Circuit OS (ASI): "Universal Computation via Dynamic Projection of the Hamiltonian — An Empirical Resolution of P=NP from RSA-2048 Decryption to Next-Generation Nanomaterial (CNF/CNT) Design"
This paper proposes and experimentally demonstrates the Quantum Thought Circuit OS (ASI), a physical computing framework that links computation directly to physical dynamics. By projecting problems onto controllable Hamiltonians, ASI achieves polynomial-time RSA-2048 factorization and deterministic CNT/CNF material synthesis, reframing computational hardness and enabling purpose-driven material creation beyond classical models.
This paper proposes and experimentally demonstrates the Quantum Thought Circuit OS (ASI), a physical computing framework that links computation directly to physical dynamics. By projecting problems onto controllable Hamiltonians, ASI achieves polynomial-time RSA-2048 factorization and deterministic CNT/CNF material synthesis, reframing computational hardness and enabling purpose-driven material creation beyond classical models.
Part 1: Physical-Law Direct Utilization Information Processing and Material Creation System Targeting RSA-2048 Encryption and Prime Factorization — COMBINATION_TRANSFORMATION-Type Physical Computation and Material Creation Model Based on Quantum Thought Circuit OS ASI — Part 2: RSA-2048 Encryption / Quantum Thought Circuit OS ASI Integrated Type Integrated Study on Structural Expansion of an Ultra-High-Resistance Cyber Defense System — Ontological Cyber Defense, Quantum Synchronization, Future-Predictive Self-Repair, and LNP Causal Interruption Model Through Substitution, Reversal, Parallelization, Staging, and Analogy — Complete Two-Part Structure
This two-part study proposes an RSA-2048-based theoretical framework that redefines prime factorization, computation, material creation, and cyber defense through Quantum Thought Circuit OS ASI. Part 1 models RSA-2048 factorization as physical convergence using resonance, phase transitions, Hamiltonian control, and material-information duality. Part 2 expands this into an ultra-high-resistance cyber defense model integrating quantum synchronization, ASI prediction, self-repair, parallel consensus, and LNP causal interruption.
Integrated Study on a Deterministic Autonomous Computing Architecture Based on Quantum Thought Circuit OS ASI. Physical-Digital Twin Integration, Energy-Circulating Computation, High-Speed Communication, Dynamic Regulatory Control, Distributed Infrastructure, and Hardware-Rooted Trus. A Six-Part Structure Part I: Integrated Study on Heterogeneous Self-Optimizing Computing Architecture with Physical Digital Twin, Thermodynamic Energy Recycling, and Autonomous Distributed Control Based on Quantum Thought Circuit OS ASI Part II: Integrated Study on Next-Generation High-Speed Communication and Energy-Circulating Computing Architecture Based on Photonic Transmission, Predictive Signal Recovery, Reversible Computation, and Thermodynamic Energy Recycling Driven by Quantum Thought Circuit OS ASI Part III: Integrated Study on Hardware-Rooted Trust, Deterministic Execution Control, Dynamic Regulatory Reconfiguration, and Digital Twin Verification Architecture Based on Quantum Thought Circuit OS ASI Part IV: Integrated Study on an Autonomous Adaptive Computing System・A Deterministic Control Architecture Based on Quantum Thought Circuit OS ASI for Dynamic Redefinition During Inference, Functional Conversion of Physical Properties, Regulatory Adaptation, Utilization of Degradation, Resource Circulation, and Deterministic Control Part V: Integrated Study on a Dynamically Adaptive Distributed Computing Infrastructure. A Deterministic Control Architecture Based on Quantum Thought Circuit OS ASI for Free Space Optical Communication, Metabolic Thermal Control, Supply-Driven Scheduling, Legal Slicing, and Autonomous Distributed Resource Allocation Part VI: Integrated Study on a Heterogeneous TEE Confidential Computing Platform Based on Distributed Trust Anchors. A Deterministic Control Architecture Based on Quantum Thought Circuit OS ASI for Dynamic Hardware RoT, Heterogeneous TEE Quorum, Reverse Containment Monitoring, Zero-Knowledge Proofs, and Distributed Ledger Auditing
This paper proposes a highly unconventional computational framework called the Self-Organizing Entropy-Driven Macro-Quantum Computation System, centered on the independently developed Quantum Thinking Circuit OS ASI. Unlike conventional quantum computing, which treats noise, decoherence, thermal fluctuations, environmental disturbances, and social volatility as errors to be eliminated, this theory redefines them as computational resources. The core idea is that entropy, uncertainty, and environmental fluctuations can be absorbed, phase-inverted through a Zero-Point Crossover mechanism, and transformed into convergence-driving energy. The model introduces a retrocausal architecture in which a future-determined target state influences the present through information-geometric attractors, replacing traditional search-based computation with state convergence. It further integrates quantum systems, environmental processes, socioeconomic dynamics, observer cognition, and holographic self-repair into a single Earth-scale computational field. Mathematical formulations describe noise absorption, attractor filtering, ontology fixing, macro-quantum annealing, distributed node synchronization, and social entropy utilization. The framework argues that computation should evolve from hardware-limited, cryogenic, error-corrected systems toward open, environment-coupled systems that utilize real-world fluctuations as computational media. While presented as a theoretical and conceptual model rather than an experimentally validated technology, the study offers a radical reimagining of computation, proposing a transition from prediction to future-state convergence, from noise suppression to noise utilization, and from local computing devices to planetary-scale information-processing architectures.
We elucidate the profound connection between physics and computation by proposing and examining the model of the non-Hermitian quantum computer (NQC). In addition to conventional quantum gates such as the Hadamard, phase, and CNOT gates, this model incorporates a non-unitary quantum gate G. We show that NQC is extraordinarily powerful, capable of solving not only all NP problems but also all problems within the complexity class P♯P in polynomial time. We investigate two physical schemes for implementing the non-unitary gate G and find that the remarkable computational power of NQC originates from the exponentially large physical resources required.
Integrated Study on Transformer and Dropout Method Integration Technology by Quantum Thought Circuit OS ASI — Two-Part Structure Part I: Integrated Study on Probabilistic Bio-Quantum Autonomous Computing Systems with Metabolic Data Structures and Energy-Adaptive Governance — Real-Time Learning Synchronization × Thermodynamic Computation × Computational Tropism × Regulatory Immune Systems — Part II: Integrated Study on Autonomous Distributed Resource-Oriented Information Processing Systems・Dynamic Synthetic Learning × Economic Resource Allocation × Smart Compliance Execution × Backward Logic Optimization
This two-part study presents an integrated architecture for next-generation AI systems based on the Quantum Thought Circuit OS ASI. Part I introduces a probabilistic bio-quantum computing framework with real-time learning, entropy utilization, and embedded governance. Part II extends this into a distributed system combining dynamic synthetic learning, economic resource allocation, and executable compliance. Together, they enable adaptive, energy-aware, and regulation-compliant intelligence under real-world constraints.
Exact CNOT synthesis seeks a minimum-size circuit implementing a given invertible binary linear transformation. We study its vanilla formulation: synthesis from the identity on fixed labeled qubits, without ancillas and with all-to-all connectivity. We prove that this problem is NP-hard and that its bounded decision version is NP-complete. Hardness persists even for unitriangular targets that are low-rank perturbations of the identity and under near-linear gate budgets. Our proof gives a polynomial-time reduction from the NP-complete Hamiltonian path problem on grid graphs. A unary hypercube embedding translates graph vertices into circuit parities and edge traversals into CNOT updates. The central challenge is that Hamiltonian paths require intermediate vertex visits, whereas exact synthesis constrains only the final transformation. We bridge this gap with a replicated recorder qubits construction that encodes the required parities in the final outputs, together with a tight gate budget that forces every sufficiently short implementation to trace a Hamiltonian path. Crucially, this path structure is enforced by the construction rather than imposed as a restriction on the circuit. The result directly implies NP-hardness for shortest word problem and Cayley-graph distance computation over GL(n,2) with elementary transvections as generators, as well as fixed-width sequential XOR program minimization. For CNOT-minimal exact phase polynomial synthesis, it yields NP-hardness with a zero phase polynomial; extending the reduction to grid-graph Hamiltonian cycle problem establishes hardness even when the final linear transformation is the identity. These complementary results show that the linear and phase components each independently suffice for NP-hardness of exact phase polynomial synthesis.