I present a complete quantum computing architecture based on hexagonal spin-lattice shielding.Each COMPUTE cell is an entangled quantum register that explores an exponential statespace internally.The central insight: Quantum computation does not add—it multiplies.• Classical parallel (20 independent qubits): 40 states per cycle (linear scaling 2N)• Quantum entangled (20-qubit register): 220 = 1, 048, 576 states per cycle (exponentialscaling 2N )• Quantum advantage at N = 20: 26, 214×Key validated metrics:• T2 effective: 384(23) ms (conservative) to 492 ms (ideal)• Duty cycle: 88.8 ± 0.4%• Throughput: 250,000–410,000 quantum packets/s (network)• States processed: 2.6 × 1010 coherent states/s (4 entangled registers)• Quantum advantage over superconductor: 100× more states/s• 5-hop fidelity: 95.5–97.5%The architecture is not a network of qubits—it is a network of exponential quantumprocessors.
I present a complete quantum computing architecture based on hexagonal spin-lattice shielding.Each COMPUTE cell is an entangled quantum register that explores an exponential statespace internally.The central insight: Quantum computation does not add—it multiplies.• Classical parallel (20 independent qubits): 40 states per cycle (linear scaling 2N)• Quantum entangled (20-qubit register): 220 = 1, 048, 576 states per cycle (exponentialscaling 2N )• Quantum advantage at N = 20: 26, 214×Key validated metrics:• T2 effective: 384(23) ms (conservative) to 492 ms (ideal)• Duty cycle: 88.8 ± 0.4%• Throughput: 250,000–410,000 quantum packets/s (network)• States processed: 2.6 × 1010 coherent states/s (4 entangled registers)• Quantum advantage over superconductor: 100× more states/s• 5-hop fidelity: 95.5–97.5%The architecture is not a network of qubits—it is a network of exponential quantumprocessors.
Classical computing architectures encode information into discrete binary digits residing in isolated regions of phase space. Quantum computing replaces this paradigm by leveraging complex state vectors defined within continuous, multi-dimensional Hilbert spaces. This paper provides a unified mathematical framework examining finite-dimensional Hilbert spaces in quantum information processing. It traces the structural scaling of quantum state spaces from single-qubit systems up through composite tensor product structures and multi-qubit registers. By detailing computational basis representations, state transformations, probability amplitudes, and multipartite entanglement classes, such as Bell, GHZ, and W states, this paper demonstrates how exponential dimensional scaling enables quantum parallelism while presenting computational barriers to classical simulation.
I present a conceptual extension of the structured spin-environment framework previouslyintroduced in the Bubble architecture. Instead of an isolated spherical spin shell, I consider aperiodic hexagonal lattice of protective spins surrounding each qubit. I introduce a minimaltheoretical model for the qubit–lattice dipolar coupling and perform numerical simulationsthat suggest ordered geometries can suppress the variance of the local magnetic noise comparedto disordered arrangements. I further present a reproducible synthetic-dataset simulationof the complete experimental protocol, including Ramsey, Hahn echo, CPMG, and pulsedABAC sequences with alternating magnetic polarity. The simulation confirms the centralhierarchy Tordered+ABAC+pulses2 > T bare2 ≳ Tdisordered2, with the ordered nuclear cluster showingnear-perfect coherence and the disordered ensembles collapsing in microseconds.A key innovation of this revision is the recognition that protective spins need not bepassive spectators. I demonstrate—through order-of-magnitude estimates and numericalFloquet-cycle simulations—that proximal nuclear spins (13C) can simultaneously serve as (i)geometric noise suppressors via ordered dipolar cancellation, and (ii) individually addressablequantum memories via the hyperfine interaction. This dual-purpose architecture transformseach hexagonal cell from a passive shield into an active hybrid processing node, where thecentral NV electron spin performs fast logic while the surrounding nuclear register providesmemory, redundancy, and auxiliary computation. I quantify the trade-off between shieldingfidelity and memory operation duty cycle, showing that for memory fractions fmem ≲ 0.1, thecoherence degradation remains below the threshold of detectability in current NV experiments.Central to my proposal is a redefinition of the hybrid Aharonov–Bohm–Aharonov–Casher(ABAC) mechanism: rather than a tool for single-spin addressing, I treat it as a phase-synchronisation protocol that modulates the global phase relation between the qubit andthe collective spin lattice. This document is explicitly exploratory: no complete theory isdeveloped, but falsifiable predictions, order-of-magnitude estimates, and open questions areprovided to guide future investigation.
Quantum computing is emerging as a revolutionary paradigm in the field of computing, promising an exponential leap in computing power and problemsolving that challenges even the most advanced supercomputers of the classical era.At the heart of this revolution lies the peculiarity of the quantum world, where subatomic particles can exist in multiple states simultaneously, a phenomenon known as superposition, and entangle their states in a way that defies classical logic.It is this capacity for superposition and entanglement that gives quantum computing its disruptive power.One of the most intriguing properties of quantum computing is its ability to process information using Qubits, the quantum analogues of classical bits.While a classical bit can only be in a single 0 or 1 state, a Qubit can simultaneously represent a 0, a 1, or any superposition of these states, allowing multiple calculations to be performed in parallel.This massively parallel processing capability is the basis for the potential superiority of quantum computers over their classical counterparts in a wide range of applications.The architecture of quantum computers is inherently different from classical computers.While the latter use transistors to store and manipulate information in bits, quantum computers use Qubits, which can be implemented in a variety of physical systems, such as atoms, ion traps, photons, superconductors or nuclear magnetic resonance.The manipulation of the Qubits is carried out through quantum gates, fundamental operations that transform the quantum state of the Qubits and allow quantum calculations to be carried out.Furthermore, to maintain quantum coherence, the control and isolation of the quantum system from its environment is crucial, posing significant challenges in terms of designing and building scalable and robust quantum systems.
Abstract The generation of a register of highly coherent, but independent, qubits is a prerequisite to performing universal quantum computation. Here we introduce a qubit encoded in two nuclear spin states of a single87Sr atom and demonstrate coherence approaching the minute-scale within an assembled register of individually-controlled qubits. While other systems have shown impressive coherence times through some combination of shielding, careful trapping, global operations, and dynamical decoupling, we achieve comparable coherence times while individually driving multiple qubits in parallel. We highlight that even with simultaneous manipulation of multiple qubits within the register, we observe coherence in excess of 105times the current length of the operations, with T2echo=(40±7) T2echo=40±7 seconds. We anticipate that nuclear spin qubits will combine readily with the technical advances that have led to larger arrays of individually trapped neutral atoms and high-fidelity entangling operations, thus accelerating the realization of intermediate-scale quantum information processors.
Quantum computing is a revolutionary approach to computation that leverages the principles of quantum mechanics, enabling computers to process information in fundamentally different ways than classical computers. Unlike traditional bits, which represent data as either 0s or 1s, quantum bits, or qubits, can exist in multiple states simultaneously due to superposition. Additionally, qubits can be entangled, allowing them to be interconnected in ways that enhance computational power and efficiency. This unique behavior has the potential to run certain types of computation tasks much faster than classical computers can, marking a significant leap forward in technology. When building actual quantum computers to run practical quantum algorithms, one needs efficient ways to map the algorithms to the hardware components, similar to compiling classical algorithms onto CPU/GPU hardware. This thesis aims to tackle some of the important problems in the mapping process. First, can we address hardware errors and algorithm errors at the same time? Second, can we build a better circuit complexity metric to inspire better quantum architecture design, and can we design better quantum algorithms and compilation techniques using this improved metric? Lastly, can we use physics-level simulation results to inspire better circuit-level optimization techniques? We hope to provide positive answers to all three questions above through three separate architectural innovations.
This paper proposes a novel distributed computing architecture leveraging the principles of quantum entanglement for enhanced parallel computation. Traditional distributed computing relies heavily on classical communication, which introduces latency and bandwidth limitations. This architecture aims to overcome these challenges by exploiting the inherent correlations within entangled quantum states. We introduce a framework where multiple computational nodes are interconnected via entangled qubits, forming a quantum entanglement network. This network facilitates direct, correlated computation between nodes, theoretically enabling a significant speedup compared to conventional parallel processing. The core claim of this work is the realization of ultra-efficient parallel computation through entanglement-based distributed computing. The presented model details the architecture, the entanglement management strategy, and the theoretical computational advantages. We focus on the conceptual design and the underlying mathematical framework, providing a foundation for future research and development in this area. The key mathematical concept driving this architecture is the manipulation of entangled states to perform computations without the need for direct data transfer between nodes. This approach presents a fundamentally different paradigm for distributed computing, with the potential to revolutionize fields reliant on computationally intensive tasks.