Google patents AI tool to clean up quantum computer calibration data
Google has filed a patent application for a method that uses a type of artificial intelligence called a de-corrupting autoencoder to clean up noisy data from quantum computers. The system learns to remove errors from calibration measurements by practicing on data that has been intentionally damaged, allowing it to recover accurate values for qubit parameters.
In the filing’s own words
Systems and methods for calibrating a qubit parameter for a qubit in a quantum computing system are provided. In one example, a method includes obtaining, by one or more computing devices, data associated with a set of one or more qubit parameters for a qubit in a quantum computing system. The method includes obtaining, by the one or more computing devices, calibration data associated with at least one qubit parameter in the set of one or more qubit parameters. The method includes determining, by the one or more computing devices, a value for the at least one qubit parameter based at least in part on the calibration data using a de-corrupting autoencoder.
What exactly they claim (claim 1)
1. A method for training an autoencoder for data de-corruption comprising: obtaining, by a computing system comprising one or more processors, input data, wherein the input data comprises good data from a calibration process for a quantum computing system; artificially corrupting, using the computing system, the input data at least in part; generating, using the computing system, a reconstructed training batch, wherein the reconstructed training batch is generated using the artificially corrupted data and the input data; performing, using the computing system, a loss function on the reconstructed training batch; updating, using the computing system, one or more parameters based on the loss function; and building, using the computing system, a de-corruption autoencoder based on the one or more updated parameters.
Facts
- Company
- Google (Google LLC)
- Official title
- Denoising Qubit Calibration Data with Deep Learning
- Publication number
- US20260289378A1
- Application number
- 19695955
- Filed
- Jun 2, 2026
- Published
- Sep 24, 2026
- Inventors
- 1
- Claims
- 20
Classified under
G06N 10/60 Physics & computingG06N 3/045 Physics & computingG06N 3/088 Physics & computingMore from Google in AI & software
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.