Qubit Physics

Previous discussions covered composite superconducting qubits. Here, we briefly introduce other types of qubits. In applications, qubits must strike a balance between easy controllability and resistance to noise, extending decoherence time. However, these two demands often conflict; ease of control means greater susceptibility to noise, while higher stability implies difficulty in control. Developing hybrid systems that integrate different qubit types or composite qubits is a viable direction.
Ref: arxiv: 2303.04061

(a) Superconducting Quantum Processor
Composed of artificial atom arrays using Josephson Junctions and capacitors, controlled via microwave electronics.
Qubit Count: ~100
Quantum Gate Fidelity: Single Qubit Gate \(F_1 > 99\%\), Two Qubit Gate \(F_2 > 99\%\)
Pros: Fast operation, high controllability, excellent scalability
Cons: Crosstalk, low-temperature requirement, challenges in large-scale expansion

(b) Trapped Ion Quantum Computing
Utilizing laser-cooled atomic ions, trapped with RF electric fields and manipulated with lasers.
Qubit Count: 20–30
Quantum Gate Fidelity: Single Qubit Gate \(F_1 > 99.9\%\), Two Qubit Gate \(F_2 > 99\%\)
Pros: Long coherence time, high gate precision, reconfigurable qubit links
Cons: Difficult to scale up technically

(c) Semiconductor Spin-Based Quantum Computing
Utilizing the electron or hole spin within semiconductor quantum dots as qubits.
Qubit Count: 6
Quantum Gate Fidelity: Single Qubit Gate \(F_1 \approx 99.99\%\), Two Qubit Gate \(F_2 \approx 99.5\%\)
Pros: Mature technology, long coherence time, compact footprint
Cons: Requires nanoscale manufacturing precision

(d) NV Center Quantum Computing
Quantum operations using the long coherence time of electron and nuclear spins at point defects in diamonds (NV centers).
Qubit Count: 10
Quantum Gate Fidelity: Single Qubit Gate \(F_1 \approx 99.995\%\), Two Qubit Gate \(F_2 \approx 99.2\%\)
Pros: Room-temperature operation, high sensitivity, suitable for quantum networks
Cons: Difficult to scale up

(e) Neutral Atom Array Quantum Computing
Utilizing optical tweezers to trap neutral atoms and controlling interatomic interactions via Rydberg effects.
Qubit Count: Digital Processor: 24
Analog Simulator: 289
Pros: Supports both digital computation and analog simulation, highly scalable
Cons: Needs improvement in two-qubit gate fidelity

(f) NMR Quantum Computing
Using nuclear spins in molecules for quantum operations.
Qubit Count: 12
Quantum Gate Fidelity: Single Qubit Gate \(F_1 \approx 99.98\%\), Two Qubit Gate \(F_2 \approx 99.3\%\)
Pros: Room-temperature operation, long coherence time, suitable for digital simulations
Cons: Difficult to scale up to large systems

(g) Photonic Quantum Computing
Manipulating quantum information using single photons or conjugate variables of electromagnetic field modes.
Qubit Count: 18 (individual control), 255 (Jiuzhang 3.0)
Quantum Gate Fidelity: Single Qubit Gate \(F_1 \approx 99.84\%\), Two Qubit Gate \(F_2 \approx 99.69\%\)
Pros: Resistance to decoherence, room-temperature operation, suitable for distributed quantum computing
Cons: Photon-photon gates are challenging to implement

(h) Topological Quantum Computing
Based on topological encoding using non-Abelian anyons, performing operations through braiding.
Qubit Count: Experimental stage
Quantum Gate Fidelity: N/A
Pros: Intrinsic topological protection, potential for large-scale error correction
Cons: Still in development

Originally written in Chinese by the author, these articles are translated into English to invite cross-language resonance.