System Model H2: Accelerating your path to fault-tolerant quantum computing
A quantum revolution is on the horizon
Entering a New Phase of Quantum Computing with our Second-generation System
The System Model H2, Powered by Honeywell, is our latest generation of quantum computers with a new racetrack-shaped trap. Featuring 32 fully-connected qubits and an all-new architecture, Quantinuum’s H2 provides a quantum volume of 65,536 (216) and the largest GHZ-state.
Quantinuum’s System Model H2 includes numerous hallmark features that set it apart from other types of quantum computers, including:
single-qubit gate fidelity
two-qubit gate fidelity
- Highest commercially available two-qubit gate fidelity
- All-to-all connectivity
- Qubit reuse
- Mid-circuit measurement with conditional logic
A Race Track Trapped-Ion Quantum Processor
Quantinuum’s benchmarking assessment of the System Model H2’s performance is considered one of the most thorough assessments of any quantum system to date. The benchmarking and characterization are representative of the levels of diligence and transparency Quantinuum puts into launching a commercial quantum computer. In the assessment, over 14 different benchmarks were performed, H2 achieved a quantum volume measurement of 65,636 (N=16), a 32-qubit GHZ-state measurement, and the industry’s best commercially available two-qubit gate fidelity.
Creation of Non-Abelian Topological Order and Anyons on a Trapped-Ion Processor
Researchers from Quantinuum and collaborators from Harvard University and Caltech have demonstrated a new state of matter, a non-Abelian topologically ordered state. Due to the differentiating features and precision control of the H2 processor, the topological state was created in a way where its properties could be precisely controlled in real-time. The precise control of non-Abelian anyons has been long held as the path to using topological qubits for a fault tolerant quantum computer.
Exploring the neighborhood of 1-layer QAOA with Instantaneous Quantum Polynomial Circuits
Quantinuum’s machine learning team demonstrated a new heuristic optimization routine that can solve optimization problems with minimal quantum resources. It solves more problem instances and ones of a larger size than the most used quantum algorithm (QAOA – Quantum Approximate Optimization Algorithm) under similar resources in Quantinuum’s trapped-ion H2 device. The results from this work motivate further study of quantum heuristic algorithms for optimization at the relevant scale for real-world optimization problems.
Alignment between Initial State and Mixer Improves QAOA Performance for Constrained Portfolio Optimization
Global Technology Applied Research at JPMorgan Chase demonstrated that the performance of the quantum alternating operator ansatz (QAOA), a promising quantum algorithm for combinatorial optimization problems, depends on the alignment between the initial state of QAOA and the ground state of the mixing Hamiltonian. The researchers used the findings to successfully optimize a portfolio of 32 assets using Quantinuum’s System Model H2.