GPT-5.6 Sol is used in conjunction with Codex to manage quantum computing experiments. The system autonomously runs experiments, generating data based on researcher-defined parameters. Analysis of the results is performed by the model, identifying patterns and anomalies within the data. Qubit calibration is also automated, adjusting parameters to optimize experimental conditions.
This approach reduces the manual effort required for quantum computing research. Researchers can focus on designing experiments and interpreting results rather than managing the technical details of the process. The system’s ability to analyze data and calibrate qubits contributes to improved experimental accuracy and efficiency.
This integration represents a potential use case for large language models in scientific research. The system demonstrates the capability of models to manage complex, real-time processes and contribute to data-driven scientific discovery.
Source: https://openai.com/index/codex-quantum-computing-experiments