Explore the mysteries of quantum entanglement and enable long-distance information transmission
Harness quantum superposition states to achieve breakthroughs in parallel computing
Research the stability of quantum states and overcome computational bottlenecks
TECHNICAL WHITE PAPER
The road to quantum computing as a trinity of qubits, error correction, and integration processes (Version 2.0, revised and expanded)
The classical scaling roadmap is hitting two ceilings at once: under exponential extrapolation, per-chip transistor counts approach feature sizes smaller than the interatomic spacing of silicon, while the per-switch energy of today's CMOS devices remains three to four orders of magnitude above the Landauer thermodynamic limit—and with each order of magnitude of approach, device sensitivity to thermal fluctuations and noise rises nonlinearly. The report therefore returns to Feynman's proposal: rather than simulating quantum systems with ever-larger classical machines, build computing devices that themselves obey quantum mechanics—n qubits natively inhabit a 2^n-dimensional Hilbert space, whereas for classical storage, once n exceeds roughly 266, the number of required amplitudes rivals the total number of atoms in the observable universe.
The solution rests on three pillars—qubits, the control and measurement system, and the error correction architecture: starting from the first principles of superposition, entanglement, measurement, and decoherence, it establishes a complete theoretical chain from physical qubits to logical qubits. What actually determines computational capability is not the coherence time T2 itself but its ratio to gate time—trapped ions reach T2 on the order of seconds but gate speeds in the microsecond range, while superconducting qubits have T2 of tens to hundreds of microseconds yet gate speeds of tens of nanoseconds; competition among platforms is, at its core, each optimizing the same exponential decay law along a different axis. On the control side, the report systematically covers microwave control chains, cryogenic CMOS and room-temperature FPGA controllers, closed-loop calibration against parameter drift, and the noise-temperature budget of cascaded amplification.
The report dissects the physical mechanisms, process bottlenecks, and scaling prospects of the six mainstream routes: superconducting, trapped-ion, photonic, neutral-atom, semiconductor quantum dot, and topological qubits. The superconducting transmon exemplifies a classic quantitative trade-off: by increasing the ratio of Josephson energy to charging energy, the levels' sensitivity to charge noise falls approximately exponentially, at the cost of anharmonicity weakening only as the square root of that ratio—a polynomial price for an exponential gain. On fabrication, coverage spans the aluminum, niobium, and tantalum material systems and interface losses, double-angle evaporation junction fabrication, flip-chip bonding and through-silicon via (TSV) 3D integration, and batch-to-batch consistency and yield targets.
For the evolution path, the report maps the staged transition from the noisy intermediate-scale quantum (NISQ) era, through quantum advantage verification and logical-qubit engineering, to fault-tolerant universal quantum computing (FTQC), with resource estimates for each stage: roughly 20 million physical qubits running for about eight hours to factor RSA-2048, versus billions of years for the classical number field sieve—a gap of about fourteen orders of magnitude, which is a complexity-class separation rather than one that engineering optimization can close. At the industry level, it analyzes the urgency and priorities of post-quantum cryptography migration: Shor's algorithm is an exponential blow to public-key systems, whereas Grover's algorithm offers only a quadratic speedup against symmetric ciphers, so doubling key lengths restores the security margin.