• Quantum volume – Several quantum computing companies announced significant increases in their quantum volume metrics, indicating larger and more powerful quantum processors.

• Ion trap chips – IonQ and Honeywell announced new trapped ion quantum chip architectures with increased qubit counts and connectivity. IonQ’s new chip has more than 1 million ion traps.

• Quantum circuits – Researchers demonstrated new techniques for designing quantum circuits that achieve an exponential reduction in circuit depth requirements for certain algorithms.

• Quantum memories – Progress was made on developing quantum memories to store quantum information for extended periods, which is essential for scaling quantum computers.

• Quantum software stacks – Companies like QC Ware, Zapata, Xanadu and others expanded their software tooling for developing quantum algorithms and applications.

• Quantum simulation – Researchers used quantum computers to simulate quantum systems with more qubits and particles than ever before, indicating potential for unlocking new scientific discoveries.

• Quantum machine learning – Quantum algorithms for machine learning tasks like classification, recommendation and clustering showed promising results, though still outperformed by classical AI.

• Quantum networking – Techniques for establishing quantum networks between nodes made progress, though significant challenges remain for creating large-scale quantum internet.

While we are still years away from a universally useful quantum computer, 2022 saw meaningful advances in hardware scaling, algorithms, software, quantum memories and real-world applications. However, many challenges around qubit quality, error correction and control still exist, making significant quantum advantage likely still a decade off.

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