Title: NIST Discloses Ray-Based Classifier Apparatus and Machine Learning Tuning Device
Summary:
The National Institute of Standards and Technology (NIST) has disclosed a new apparatus and device for classifying and tuning quantum devices using machine learning. The apparatus includes a machine learning module that generates a device state, and an autotuning module that produces recognition data based on the device state and ray-based data.
The autotuning module contains several components, including a recognition module, measurement module, comparison module, prediction module, gate voltage controller, and another measurement module. The machine learning module also includes a training data generator module.
The apparatus produces various types of data, such as comparison data, prediction data for the device, controller data, and device control data. The gate voltage controller uses the device control data to control the device. The measurement module generates ray-based data, which the recognition module uses to perform recognition on the ray-based data using the device state.
The disclosed apparatus and device aim to improve the classification and tuning of quantum devices using machine learning techniques. By generating and analyzing ray-based data, the apparatus can recognize and predict device states, allowing for more accurate control and optimization of quantum devices.
Keywords: Classifier, Autotuning, Machine Learning, Recognition, Ray-based
