| Rigetti | |
|---|---|
| Name | Rigetti Computing |
| Type | Private |
| Industry | Quantum computing |
| Founded | 2013 |
| Founder | Chad Rigetti |
| Headquarters | Berkeley, California |
| Key people | Chad Rigetti (CEO) |
| Products | Quantum processors, Forest (software), QPU cloud services |
Rigetti
Rigetti (formally Rigetti Computing) is an American quantum computing company that develops superconducting quantum processors and integrated hardware–software systems aimed at practical quantum acceleration for computational problems. Founded in 2013, Rigetti is notable for combining cryogenic quantum processor development, classical control electronics, and a cloud-hosted programming stack to enable cloud access to noisy intermediate-scale quantum (NISQ) devices, contributing to experimental benchmarks in the field of Quantum Physics and Quantum computing.
Rigetti was founded in 2013 by Chad Rigetti, a physicist who previously worked on superconducting qubits at Yale University and at IBM Research. The company initially raised venture capital and established a fabrication facility and cryogenic laboratory in the San Francisco Bay Area. Early milestones included demonstrations of small-scale superconducting circuits and the announcement of a cloud-accessible quantum computing platform. Rigetti has competed and collaborated with organizations such as Google's quantum team, IBM, Microsoft, and start-ups like D-Wave Systems and IonQ in the race to build practical quantum hardware. Over time, Rigetti expanded its workforce with engineers and researchers from institutions including UC Berkeley, Harvard University, and national laboratories such as Lawrence Berkeley National Laboratory.
Rigetti's work centers on superconducting circuit quantum electrodynamics (cQED), a platform grounded in principles of superconductivity and Josephson junctions. Superconducting transmon qubits used by Rigetti are non-linear oscillators that implement two-level quantum systems through fabricated aluminum or niobium circuits on a silicon or sapphire substrate. Control and readout employ microwave electronics, cryogenic refrigerators (dilution refrigerators), and room-temperature field-programmable gate arrays (FPGA) for pulse sequencing. Rigetti's engineering integrates concepts from quantum error correction research, quantum control theory, and cryogenic packaging to reduce decoherence and crosstalk in multi-qubit processors.
Rigetti has designed and fabricated a series of quantum processing units (QPUs) with increasing qubit counts and connectivity graphs. Architectures have used nearest-neighbor coupling on planar superconducting chips, tunable couplers, and custom resonator layouts to implement two-qubit gates such as cross-resonance and controlled-Z variants. Notable product families and prototypes include early 8–19 qubit devices, later devices scaling to dozens of qubits, and modular approaches intended to connect multiple QPUs. Rigetti has published performance metrics including single- and two-qubit gate fidelities, coherence times (T1, T2), and benchmarked primitives relevant to quantum algorithms like the variational quantum eigensolver and quantum approximate optimization algorithm (QAOA).
Rigetti developed an integrated software ecosystem to program QPUs, historically branded as Forest and later unified under cloud APIs. The stack exposes a quantum instruction language for pulse-level and gate-level control, compilers that map high-level circuits to native gate sets, and simulators for classical validation. Rigetti supports hybrid quantum–classical workflows and tooling for variational algorithms, using interfaces compatible with languages such as Python. The company contributed to open-source projects and interoperability efforts that connect with other frameworks such as Qiskit-style circuit representations and standards promoted by consortia including the Quantum Economic Development Consortium.
Rigetti researchers have authored peer-reviewed papers on superconducting qubit fabrication, error characterization, randomized benchmarking, quantum control, and scaling strategies. The firm has partnered with academic groups at Stanford University, MIT, and UC Berkeley, industrial partners including Amazon Web Services (for cloud integration), and government labs for applied research. Collaborative projects have included algorithm benchmarking for chemistry and optimization, studies of noise mitigation techniques, and demonstrations of cloud-accessible quantum experiments. Rigetti's data and methodology have been cited in comparative studies evaluating NISQ-era devices from Google Quantum AI and IBM Quantum.
Rigetti offers cloud access to QPUs and hybrid services targeting domains where quantum heuristics may provide advantage: quantum chemistry, combinatorial optimization, machine learning, and materials modeling. Commercial offerings combine QPU time with classical compute for hybrid solvers, professional services, and custom integrations for enterprise users. Partnerships with cloud providers and systems integrators aim to make quantum-assisted workflows available via APIs and managed platforms. Rigetti positions its technology for use cases such as portfolio optimization, logistics, and prototype quantum simulation for chemical reaction modeling.
Rigetti faces industry-wide challenges: increasing qubit count while maintaining gate fidelity and coherence, implementing scalable quantum error correction, and reducing crosstalk in dense layouts. Engineering hurdles include cryogenic control complexity, fabrication yield, and classical infrastructure for low-latency hybrid loops. The company's stated roadmap focuses on larger QPUs, modular connectivity, improvements in two-qubit gate fidelity, and software advances in compilation and error mitigation to enable useful quantum advantage on specific problem classes. Continued progress will depend on advances in quantum error correction, materials science, and system-level co-design across hardware and software.
Category:Quantum computing companies Category:Superconducting qubits