Samuel Jaques
University of Oxford | Department of Materials
Quantum Landscape 2022

Landscape of Quantum Computing in 2022

Last year I wrote a brief explainer of where quantum computing was and where it needs to go, specifically to break crypto. There's been some progress in quantum computing, so I've updated the chart below:

Check last year's post for the explaination of the chart. The key differences this year:

If you compare this to last year's chart it seems like there were big breakthroughs in qubit quality. I'm not sure, since my methods of producing a single number for "qubit error" weren't rigorous. There seems to be progress, but I wouldn't claim any precise trends.

Other news that doesn't fit on the chart:

Besides those, not much has changed. The main conclusions from last year still hold:

Chart methodology

(see last year's page)
  • Current chips:
    • Google 2022 came from here, where I used the CZ error for the box-and-whisker chart. I listed the number of qubits as 72 (the total on the device) even though the paper only uses 49 (so maybe other qubits are much worse or non-functional).
    • IBM 2022 came from live data, which I captured on Nov 10. I took the worst of all the types of error for each qubit/pair of qubits.
    • For Honewell, I used the worst error type (measurement) from their simulation parameters (which are based on experiment and worse than all experimental error types they list in that paper)