Rigetti Computing
Overview
Full-stack quantum computing company focused on hybrid quantum-classical algorithms. Integrates quantum processors with classical co-processors for low-latency workloads.
Key Milestones
- 2013: Rigetti Computing founded by Chad Rigetti (former IBM researcher)
- 2018: Rigetti Quantum Cloud Services launched
- 2020: 32-qubit Aspen-9 processor
- 2021: SPAC merger announced with Supernova Partners
- 2022: 80-qubit Aspen-M-2 processor
- 2023: 84-qubit Ankaa-2 processor with improved connectivity
- 2024: Focus on quantum-classical hybrid algorithms (QAOA, VQE)
Technology Approach
Rigetti uses superconducting transmon qubits with tunable coupling. Their processors emphasize low-latency classical-quantum integration via proprietary Quantum Processing Units (QPUs) tightly coupled to classical FPGAs.
Hybrid Architecture
Rigetti’s key differentiator: co-locating classical and quantum processors to minimize communication overhead. This enables:
- Sub-microsecond classical-quantum roundtrip (important for hybrid algorithms)
- Real-time feedback for error correction experiments
- Parametric circuits that adapt based on classical computation results
The company positions this as critical for near-term quantum advantage in optimization and chemistry, where iterative hybrid algorithms dominate.
Hardware Generations
Aspen Series (2018-2022)
- 8 → 32 → 80 qubits
- Heavy-hexagonal lattice topology (similar to IBM)
- Available on Amazon Braket and Rigetti Quantum Cloud Services
Ankaa Series (2023-present)
- 84 qubits (Ankaa-2)
- Improved gate fidelities (~99%)
- Reduced crosstalk via better qubit connectivity
Roadmap:
- 336-qubit processor by 2025
- Modular architecture with chip-to-chip connectivity
Quantum Cloud Services
Rigetti operates its own cloud platform (QCS) plus availability on:
- Amazon Braket — Pay-per-shot pricing
- Azure Quantum — Integrated with Microsoft’s platform
Pricing: ~$0.003 per gate operation (varies by system generation).
Competitive Position
Strengths:
- Vertical integration (designs chips, builds full systems)
- Strong hybrid algorithm focus (good for NISQ-era applications)
- Low-latency classical-quantum integration
Challenges:
- Smaller qubit counts than IBM (84 vs. 1,121)
- Lower gate fidelities than trapped ions (99% vs. 99.7%+)
- Public company with limited revenue (mostly research contracts)
vs. IBM:
Rigetti emphasizes hybrid algorithms and low-latency integration; IBM focuses on utility-scale systems with error mitigation.
vs. IonQ:
Superconducting qubits are faster but noisier; trapped ions have better coherence but slower gates.
Recent Developments
2024 Focus: Rigetti shifted strategy toward modular quantum computing. Instead of building monolithic 1,000+ qubit chips, they’re developing chip-to-chip interconnects to scale via networking.
Partnerships:
- NASA Ames Research Center (quantum algorithm development)
- DARPA (quantum networking research)
- UK National Quantum Computing Centre (collaborative research)
Revenue (2023): $11.4M (mostly government and research contracts, not yet profitable).
Applications
Rigetti targets:
- Optimization — QAOA for combinatorial problems
- Chemistry — VQE for molecular simulation
- Machine learning — Quantum kernel methods, variational classifiers
The company emphasizes near-term quantum advantage for problems where hybrid algorithms can outperform classical-only approaches before fault tolerance.
Long-Term Vision
Rigetti’s roadmap: reach 1,000+ logical qubits by late 2020s via modular architecture. The bet: interconnected smaller processors will scale better than monolithic chips.
Success depends on solving the chip-to-chip communication problem: Can networked quantum processors maintain coherence and gate fidelity across links? This remains unproven at scale.