IonQ

IonQ is a quantum-computing company that builds gate-model quantum computers from trapped ions. It was founded in 2015 and grew out of academic work by Christopher Monroe and Jungsang Kim. Its systems are notable for all-to-all qubit connectivity and for being offered through major cloud platforms rather than sold as on-premises hardware.

#Trapped-ion approach

IonQ encodes qubits in the internal energy states of individual ytterbium ions held in an electromagnetic trap and manipulated with laser pulses. Because the ions share a common motional mode, any qubit can interact with any other qubit through that shared motion, giving all-to-all connectivity. This means a two-qubit gate can be applied between any pair without routing the interaction through intermediate qubits, which reduces the overhead that limits fixed-layout architectures. Trapped ions are also identical by nature, since every ion of a species is the same, and they tend to show long coherence times and high gate fidelities. The main tradeoffs are slower gate speeds than superconducting circuits and the engineering difficulty of scaling beyond a single trap (Wright et al. 2019). To grow past the limits of one trap, IonQ has described photonic interconnects that would link separate ion-trap modules by exchanging photons, a networking approach it presents as a scaling path rather than a completed system.

#Systems and the algorithmic-qubits metric

IonQ has released a sequence of processors, including the Aria and Forte systems, and reports capability using a company-defined metric it calls algorithmic qubits (written as #AQ). Rather than counting physical qubits, the metric is meant to reflect how large a useful circuit a machine can run given its error rates and connectivity. It is a vendor-defined measure, so figures quoted in algorithmic qubits are not directly comparable to physical qubit counts or to other companies' benchmarks. As with all single-number metrics, it captures some aspects of performance and omits others, and should be read alongside independent benchmarking.

#Cloud access

IonQ makes its hardware available primarily through cloud services, including Amazon Braket, Microsoft Azure Quantum, and Google Cloud (AWS Braket). This delivery model lets researchers run circuits without operating the cryogenic and laser infrastructure themselves. As of early 2026, IonQ's machines remain research and early-application tools, and the company has not reported a fault-tolerant system or a demonstrated Quantum advantage on a practical problem.

#Relation to cryptography

IonQ builds universal gate-model machines, so a sufficiently large and error-corrected trapped-ion computer could in principle run Shor's algorithm. Current systems are far too small and are not error-corrected at scale, so they pose no near-term threat to deployed cryptography. Trapped ions' high fidelities make the modality a serious long-run candidate, but the same scaling and error-correction obstacles that face every platform apply here.