Nvidia releases quantum computing AI calibration model: achieving automatic tuning of quantum computers and promoting AI+quantum fusion BlockBeats News: On July 28th, NVIDIA released the open-source AI model NVIDIA Ising Calibration 1.5, which is used to automatically analyze diagnostic data of quantum processors (QPUs) and autonomously determine device calibration plans, achieving automation of the quantum computer calibration process. Nvidia stated that Ising Calibration 1.5 is a visual language model (VLM) designed specifically for quantum computing calibration scenarios, capable of understanding quantum chip experimental data and completing "zero sample" analysis in the absence of historical cases. At the same time, it can combine relevant experimental samples for contextual learning (ICL) to help quantum devices continuously optimize their operating status. In the QCalEval quantum calibration benchmark test, Ising Calibration 1.5 leads open source models of the same scale by an average of about 10% in zero sample inference ability. When using relevant experimental cases for context learning, the performance of the previous generation model is improved by about 86.5%, surpassing multiple open source models and approaching the level of top-level closed source large models. The model has 31 billion parameters and supports GPU operation in data centers such as NVIDIA Grace Blackwell and Vera Rubin. It also introduces a quantified version of NVFP4, which can be deployed on a single consumer GPU or NVIDIA DGX Spark, significantly reducing the threshold for quantum laboratory use. Nvidia claims that the training data for Ising Calibration 1.5 comes from various quantum bit architectures, including superconducting qubits, quantum dots, ions, neutral atoms, and helium surface electrons, providing calibration capabilities for different types of quantum computing devices. The industry believes that automated calibration is one of the key bottlenecks for the large-scale development of quantum computing. NVIDIA's launch of AI driven quantum calibration tools means that AI models are starting to extend from traditional computing to quantum hardware control layers, and may become an important component of the future infrastructure of the quantum computing industry. [Original link]